Strategic Value Innovation

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MICHAEL S. JORDAN

STRATEGIC

VALUE

INNOVATIONDevelop Highly Profitable Products and

Services In Less Time With Less Risk

Institute for Strategic Innovation





Strategic Value Innovation

Develop Highly Profitable Products and

Services In Less Time With Less Risk

A Guide to the AVID Methodology

Atlanta, Georgia, USA

www.innodyn.net

Version 1.5

June 2014

By Michael S. Jordan

INNODYNBusiness Growth Development

®



© Copyright 2014 INNODYN, LLCAtlanta, Georgia

www.innodyn.net

Version 1.5, June 2014

All rights to the text and illustrations reserved by INNODYN.



CONTENTS

Introduction

Complexity, Risk, and Innovation Success .......................................................... 1

An Overview of the AVID Methodology .............................................................. 9

Stage 1: Identify Growth Opportunity

Step 1 - Define Target Value Space ....................................................................... 25

Step 2 - Create Compelling Value Proposition ................................................... 32

Step 3 - Delineate Viable Business Model ........................................................... 40

Stage 2: Design Solution

Step 4 - Capture Customer Outcomes ................................................................. 57

Step 5 - Identify Customer Segments .................................................................. 67

Step 6 - Design Optimal Solution ......................................................................... 71

Stage 3: Test/Validate

Step 7 - Test/Validate Solution Utility .................................................................. 81

Step 8 - Test/Validate Critical Demand ................................................................ 86

Step 9 - Optimize Business Model ........................................................................ 98

Stage 4: Develop Execution Strategies

Step 10 - Resolve Ecosystem Constraints ............................................................ 109

Step 11 - Develop Operational Change Model .................................................. 117

Step 12 - Prepare Final Deliverables .................................................................... 125

AppendixAbout the Author ..................................................................................................... 135





StrategicGrowth Plan

ExecutionTeams

Identify GrowthOpportunity

Design Solution

Test/ValidateDevelop Execution

Strategy & Plan

1) Define Target Value Space

2) Create Compelling Value Proposition

3) Delineate Viable Business Model

4) Capture Customer Outcomes

5) Identify Customer Segments

6) Design Optimal Solution

7) Test/Validate Solution Utility

8) Test/Validate Critical Demand

9) Optimize Business Model

10) Resolve Key Ecosystem Contraints

11) Develop Operational Change Model

12) Develop Execution Strategy & Plan

Viable

BusinessModel

OptimalSolutionDesign

OptimizedBusiness

Model

Creation

Gate1

Gate2

Gate3

Leadership

Culture

KnowledgeCreation

GrowthTarget

ExecutionPhase


Design Solution


Strategies










10) Resolve Ecosystem Contraints


12) Prepare Final Deliverables

Viable

BusinessModel


OptimizedBusiness

Model

Creation

Gate1

Gate2

Gate3

Knowledge

Leadership

Culture/Teams

Creation

INTRODUCTION



Complexity, Risk, And Innovation Success

Complexity And Innovation Risk

Failure To Resolve Innovation Risk

Value Innovation Versus Value Extension

The Discovery Phase and Value Targets

Overview of the AVID Methodology

A Better Way To Manage The Discovery Phase

The Core Innovation Technologies

Why AVID is Called Agile

A Systems Perspective on Innovation

The Big Picture

The Growth Target

The Four Stages and 12 Action Steps

The Decision Gates

The Five Targeting Tools

Enabling Organizational Factors

INTRODUCTION



1INRODUCION

Complexity, Risk, and Innovation

Complexity and Innovation Risk

Business today is complex! Yet this did not happen overnight. Rather, complexity has beensteadily increasing over the years driven by globalization, the Internet, aster development

o technologies, more competitors entering the market, more diversity in what customers

want, multiple stakeholder demands, and other actors. What is not obvious, however, is

the effect that complexity has had on innovation risk.

Te relationship between complexity and innovation risk is an indirect one. Complexity

affects the business environment in two significant ways. First, complexity drives

business uncertainty — the extent to which business conditions and outcomes range

rom predictable to unpredictable. Second, complexity drives industry clockspeed, aconcept introduced by Charles Fine in 1998, which he described as the evolution rate o

an industry. Specifically, we define this evolution across two dimensions — how quickly

products/services mature, and how ofen business models change. Industry clockspeed

determines the extent that business conditions are stable or dynamic. In sum, complexity

affects innovation risk via the impact it has on business uncertainty and industry

clockspeed (see figure 1.1).

Industry Clockspeed

Stable Dynamic

Business Uncertainty

Predictable Unpredictable

Business Environment InnovationRisk

Complexity

+-

+-

Figure 1.1: Relationship between complexity and innovation risk.

Back in the day, the business environment was relatively stable and predictable. Industry

boundaries were well compartmentalized, and most industry clockspeeds were slow

and steady. Business uncertainty was relatively low because everyone ollowed the same

business rules, practices, and strategies. Companies knew who their competitors were and

where they stood in the pack. Back then, companies determined what products/services



2 STRATEGIC VALUE INNOVATION

customers would get and when they would get them — a supply side economy. Tis was

a wonderul world where companies had the luxury o efficiently planning and executing

profitable growth. A dramatic increase in complexity has changed all o this. Te business

environment is now dynamic and unpredictable (see figure 1.2). Companies live in aworld today where competitive response to new products/services is aster; disruptive

business models appear with little notice; and customer priorities can change on a dime.

Te upside o increased complexity is that there are more ways to create and deliver value.

Ironically, this also makes it is more difficult to identiy value creation opportunities

and how best to exploit these opportunities. Tus, increased complexity, coupled with

the act that industry clockspeeds are much aster, means that there are more growth

opportunities. Te bad news is that complexity obscures these growth opportunities,

making them difficult to identiy and riskier to implement. We call this the innovation

paradox.

IncreasingUncertainty

Timeline

C o m p l e x i t y

High

Low

Then Now

Dynamic &Unpredictable

Stable &Predictable

I n n o v a

t i o n

R i s k

FasterIndustryClockspeed

Figure 1.2: More complexity equals more innovation risk.

Back in the day, the primary growth strategy or most companies was to incrementally

extend the value o existing products/services or as long as it remained profitable to do

so. Tey had plenty o time to exploit their core products/services because the business

environment was relatively stable and predictable. In today’s business environment,

however, incremental value extension does not have the horsepower to propel growth like



3INRODUCION

it used to. Te window or exploiting existing products/service is much shorter because

product/service maturity happens aster — commoditization sets in much sooner. Te

bottom line is that the lie expectancy o core products and services is getting shorter in

most industries, and the only way to compensate or this is to build more growth engines.Companies that are not able to consistently build new growth engines will see their

earnings steadily decline.

Te most profitable and enduring growth engines attract customers with new value

propositions and open up new markets. o build these kinds o super growth engines,

companies must engage in product/service innovation. Te catch-22 is that innovation

risk is high today. Because o this, only one in seven new product/service innovations

succeed. We describe a successul innovation as one that produces an amount o profitable

revenue sufficient to carry its pro rata share o a company’s growth target relative tothe time and resources invested into the innovation. Tus, an innovation may produce

marginal profits and still be considered a ailure by our definition.

Perhaps the most obvious question to ask is — why do innovations ail?

Failure to Resolve Innovation Risks

We cannot say that risk is the ultimate cause o innovation ailure. Tat would be too bold

a statement. Although innovation risk kills many new product/service projects, the realreason or these ailures is that companies are not effectively resolving innovation risks

prior to execution. Te key to successul innovation is to first recognize risk actors, and

then pro-actively eliminate and/or manage them so that success is in your avor, not the

other way around.

What are these risk actors? In short, a risk actor is anything that gets in the way o:

1. Creating a product/service that will be valued by customers.

2. Converting this value into sufficient customer demand to generate revenue.

3. Developing a business model capable o converting the revenue into enough

net profit to drive growth.

We use the word “enough” because the success o an innovation is relative to the growth




target that the innovation project is aiming or.

Given these objectives, you can image the incredible number o innovation risk actors

working against success — selecting a poor innovation target, not understanding whatcustomers value, developing an innovation that can easily be imitated by competitors,

unexpected costs that permanently decrease the profitability o the innovation, poor

operational execution o an innovation project, conflicts and snags with partners in the

ecosystem — the list goes on.

All risk actors all into one o two categories:

Risk actors that are ignored or unrecognized.

Decisions, designs, strategies and/or activities that are inormed by flawedassumptions.

Value Innovation Versus Value Extension

Let’s dig even deeper. Te question now is: why do companies have a hard time recognizing

and then effectively resolving these risk actors during the innovation process? o answer this

question, we must first make the distinction between two very different types o product/

service development projects.

Companies tend to view new product/service projects as i they were the all same. In act,

they are not all the same. At this point, we clariy the difference between value extension

and value innovation. A new product/service that extends the value proposition o an

existing product/service line (value platorm) is a value extension. A value extension

targets existing customers o a value platorm in the same market. Value extensions are

relatively low risk projects because the path orward is well illuminated. Tere is relatively

little ambiguity as to what is needed, who it will be sold to, how it will work, how it will

be sold, and how it fits in with the current business model. Te success o an existing

value platorm validates these assumptions. Value extension is about exploiting existing

products/services by incrementally moving the value proposition up a sustaining value

trajectory. Because industry clockspeeds are getting aster, the window or exploiting core

products/services is much shorter today. Tis is due to the effects o complexity.



5INRODUCION

A value innovation, on the other hand, is a product/service that creates a completely new

value proposition. Specifically, the new product/service involves helping customers get an

important “job” done in a new way. A new value platorm is created that can be exploited

over time by moving the value proposition up a sustaining value trajectory.

You know you are dealing with a value innovation i the value proposition:

Requires a undamental change in the current business model or requires a

completely separate business model.

Involves a new market.

Sells to new customers.

Involves changes to the company’s ecosystem.

Unlike value extension, value innovation is high risk because the path orward is

ambiguous — there is no existing value platorm to inorm decisions about what

customers value, the business model, and product/service design. It is seldom the case that

a good value innovation opportunity alls at the ront door o a company. o find these

opportunities, companies must engage with customers, suppliers, partners, and others in

different ways to discover new ways to create, deliver, and capture value.

Value innovation opportunities and risk actors cannot be ascertained by conventionalbusiness analysis techniques. For instance, companies ofen use the SWO ramework

to access opportunities and risks. Tey use traditional “voice o the customer” methods

to capture customer requirements; they develop a business case that argues or a growth

opportunity; they quantiy the profit-generating potential o a new product/service; and

they assess the risk actors. I the business case passes the ROI test, management approves

the project, and off it goes to planning and execution. Te problem is that the entire

business case is premised on the notion that innovation opportunities and risk actors

are already “out there” and thereore can be captured and analyzed. Te business case is

assumed to be complete and accurate when, in act, it is replete with omissions and flawedassumptions. Even though the business case may look reasonable on paper, the ailure o

the project is already guaranteed, because the opportunity is at best marginal and at worst

fictional. Te innovation risk actors cannot be resolved because they are not known. Tis

is the strange case where the company doesn’t know what it doesn’t know.




Now we can better answer the question posed above — why do companies have a

hard time recognizing and then effectively resolving risk actors during the innovation

process? Te answer is that they are using conventional product/service development tools

and methodologies designed or low risk value extension projects to drive high-risk value

innovation projects. Tey ail to recognize that value innovation projects require a radically

different approach to identiying growth opportunities and resolving innovation risks.

From a project management perspective, a key difference between a value extension

project and a value innovation project is in the discovery phase (also reerred to as the

pre-development phase).

Beore an innovation project can move to the execution phase, certain critical outputs are

necessary or project success:

A new product/service capable o achieving the company’s growth target.

A business model that can create and deliver a compelling value proposition to

customers while generating the required net profit or the company.

An optimal product/service design that can ulfill the customer value

proposition.

All assumptions associated with these outputs must be valid, or the project is doomed to

ail. We reer to the outputs o the discovery phase that determine project success as value

targets.

Te Discovery Phase and Value argets

Te discovery phase o an innovation project is ofen called the “uzzy ront end” because

o the ambiguous nature o innovation under conditions o high uncertainty; i.e.,

value targets are not clear. Innovation risk increases to the extent that the assumptions

underlying value targets are flawed. Te ambiguity surrounding value innovation makes

it easy to generate fictional or weak value targets. Further, activities in the discovery

phase or a value innovation project are viewed as seemingly chaotic, unpredictable, and

unstructured. By contrast, the discovery phase o a value extension project is relatively

straightorward (more pre-development than discovery). Because the value targets in

a value extension project are in line o sight, activities are structured, predictable, and

ormal. Te purpose o a value extension project is to move an existing value proposition



7INRODUCION

up a sustaining value trajectory. As such, the path orward is relatively clear because the

value platorm that is being extended already exists. Tat is, the existing value platorm

provides a baseline rom which to identiy/define value targets and to validate the

accuracy o these targets beore moving to the development phase.

Because the value targets are known up ront, the risk actors or a value extension project

are conspicuous and can thereore be readily identified and described in the business case.

Uncertainty or a value extension project is relatively low. Most o the risk associated with

a value extension project has to do with execution variances, which are managed during

the development phase. A value innovation project, on the other hand, does not have an

existing value platorm which can be used as a baseline to identiy/define value targets.

Uncertainty obscures the value targets, which drives up innovation risk. Unlike execution

risk, which can be managed in the development phase, innovation risk must be resolvedin the discovery phase beore execution. Because o the extreme difference in the level o

uncertainty, the dynamics o the discovery phase or a value innovation project are much

different rom the dynamics o the discovery phase or a value extension project.

Te high level o uncertainty in the discovery phase partially explains why the success

rate or value extension projects is generally much higher than that o value innovation

projects. Conventional methods/tools effectively handle the discovery phase or value

extension projects because the value targets are in line o sight with an existing value

platorm. Due to higher uncertainty, however, these same methods/tools are less effectiveat handling the discovery phase or value innovation projects. Companies that use

conventional methods/tools or the discovery phase when uncertainty is high, ofen end

up with fictional or marginal value targets based on omissions and flawed assumptions. In

such cases, value innovation projects are literally designed to ail, regardless o how well

the project is executed because innovation risks have not been resolved. o increase the

success rate o value innovation projects, companies need to adopt an approach or the

discovery phase that involves a different mindset, different methods, and different tools

than those conventionally used or value extension projects.

Te discovery approach is premised on the idea that value targets are “discovered”

through exploratory activities that engage customers, employees, managers, partners, and

other stakeholders in the search or new ways to create, deliver, and capture value.




Tese exploratory activities involve:

Re-conceptualizing the market and the value that a company is capable o

creating. Interacting with customers and non-customers in different contexts to gain

insights into the important “jobs” that they need to get done.

Designing profitable business models that offer customers compelling new

value propositions.

Designing new product/services based on how customers perceive value rather

than how the company defines value.

Finding new ways to work with business suppliers and partners to create value

or customers and the business ecosystem.

In short, the discovery process is about collaborative learning. Discovery is not about

executing a plan or applying conventional analytical methods/tools coming rom the

mindset that value targets and risks can readily be identified because they are already

“out there”. Te outputs o the discovery phase are value targets that have been validated

through empirical procedures effectively resolving the innovation risks. Only with correct

value targets can a company move a value innovation project to the development phase

with a reasonable expectation that it will succeed.



9INRODUCION

An Overview o the AVID Methodology

A Better Way to Manage the Discovery Phase

Te Agile Value Innovation Discovery (AVID) methodology is a best practice orstructuring the discovery phase or value innovation projects. Te AVID methodology

is ast and flexible under conditions o uncertainty because it does not require that the

value targets be known up ront. It does not require a set o assumptions that can be fixed

throughout the innovation process, as is ofen the case or conventional development

methodologies. In act, just the opposite is true. Ideas and assumptions cycle through

the discovery process and may change requently as a result o ideation, collaboration,

and empirical testing. Assumptions that ail the reality test generate new learning

loops that are immediately cycled back into the next iteration o ideation and testing.

Failed assumptions are viewed as “off target”, which becomes the impetus or continueddiscovery learning. Te AVID methodology ensures that the value targets that come out

o the discovery phase define a profitable growth opportunity, and that the underlying

assumptions have been validated. When companies invest the time to do the discovery

phase well, execution moves quickly and efficiently and hits the right target.

Te traditional phase/stage gate methodology has come under fire or being inadequate

or use with value innovation projects. Many criticize this methodology as too rigid and

planning-oriented or innovation purposes. Specifically, the phase/stage gate methodology

is criticized or stifling creativity with too much structure, inhibiting learning, killingnascent innovation ideas that do not meet financial criteria, generally slowing things

down to a crawl during the innovation process, et cetera. We would suggest, however,

that the problem is not the phase/stage methodology per se. Rather, the problem is

that the phase/stage gate methodology does not work well in the discovery phase when

uncertainty is high.

Te phase/stage gate methodology emerged in the late 1980s as the best practice or

structuring the development o new products/services in a business environment

where uncertainty was low. Tat is, the phase/stage gate methodology was designed orincremental value extension projects where the value targets are in line o sight. Te

problem is that over the last ew decades, uncertainty has increased dramatically. Tis

uncertainty maniests itsel in the discovery phase which exploits the weakness o the

phase/stage gate methodology — its inability to generate value targets under conditions

o high uncertainty. Tat said, there is no need to discount the part o the phase/stage




gate methodology that is useul or innovation projects, which is the execution phase.

Once a lucrative growth opportunity has been identified, and the innovation risks have

been resolved in the discovery phase, the phase/stage methodology is the best practice or

managing the development phase o the project.

When it comes to value innovation projects (or radical value extension projects) where

the value targets are obscured by uncertainty, the best way to increase the odds o success

is to use a methodology better suited or the purpose. Te Agile Value Innovation

Discovery (AVID) methodology effectively structures the discovery phase or value

innovation projects where uncertainty obscures the value targets. Since the ocus o AVID

is solely on the discovery phase, AVID can be used on the ront-end o a phase/stage gate

methodology. AVID helps teams to identiy the best growth opportunities and to resolve

innovation risks prior to the development phase. Further, using the AVID methodologysignificantly decreases the time to market or a new product/service by compressing both

the discovery and execution phases.

Tis is possible or two reasons. First, the agility o the AVID methodology enables teams

to move through the discovery phase much aster. Second, the testing and validation step

o the phase/stage gate methodology can be eliminated because the AVID methodology

delivers empirically tested value targets. Removing this step significantly compresses the

execution phase (see figure 1.3). Tus, using AVID on the ront-end with a streamlined

phase/stage gate methodology or execution reduces total lead time in the productdevelopment process.

Traditional Phase/Stage Gate Methodology

Scoping Business Case DevelopmentFull

LaunchTesting &Validation

IdeaGeneration

Discovery Phase Execution Phase

AVID Methodology DevelopmentFull

Launch

Discovery Phase Execution Phase

AVID + Streamlined Phase/Stage Gate Methodology

Figure 1.3: Contemporary approach to the discovery phase.



11INRODUCION

Up until now, a contemporary and rigorous methodology or structuring the discovery

phase has not been proposed. What are generally used in lieu o the AVID methodology

are piecemeal methods and tools that ail to address all the critical aspects o the discovery

phase. Te result o such an ad hoc approach is the selection o fictitious or marginalgrowth opportunities where innovation risks go unresolved as the project moves into the

execution phase. Alternatively, the AVID methodology offers companies an orderly and

repeatable best practice or managing the discovery process. Te effective use o the AVID

methodology will dramatically increase the chances that a new product/service innovation

will succeed. Ultimately, AVID enables companies to systematically create profitable growth

engines in less time and with less risk.

AVID is ideal or companies o all sizes that want to develop innovative products and

services that will help the company achieve its strategic growth objective. Te input intothe AVID methodology is a growth target or a yet-to-be identified new product/service.

Te growth target specifies the desired amount o net profit that a new product/service

needs to generate over some time period to support the company’s strategic growth plan.

Te AVID methodology is the best practice or identiying a new product/service that is

capable o achieving this growth target.

Te AVID methodology delivers three value targets:

A new product/service capable o achieving a desired growth target. A business model that is capable o creating and delivering a compelling value

proposition to customers while generating the required net profit or the

company.

An optimal product/service design that is capable o ulfilling the customer

value proposition via the business model.

All assumptions associated with the value targets are validated via empirical testing. Te

validation o assumptions resolves all innovation risks prior to the execution phase. Te

final deliverable o the AVID methodology includes execution strategies or implementing

the value targets in the execution phase.





13INRODUCION

Te Customer Development Model and the Lean Startup methodologies are great or

startups, but are less useul or companies that are extending their current business

model. Open Services Innovation ocuses on the flexible sourcing o the raw ingredients

o innovation, but does not deal with other important aspects o the innovation process.Design Tinking offers a great creative process or innovating via rapid prototyping, but it

ignores many other aspects. Discovery-driven Innovation provides powerul innovation

management methods, but it has little to do with the actual innovation process itsel.

In short, every innovation technology has its strengths within a certain area/context o

innovation, but none o them address all the critical aspects o the discovery phase. Critical

aspects o the discovery phase that are not effectively dealt with will significantly increase

the risk o innovation ailure.

Te Agile Value Innovation Discovery (AVID) methodology is not a new innovationtechnology. Rather, AVID is a comprehensive methodology that provides the best practice

or moving through the discovery phase. AVID is a composite o all the core innovation

technologies. Tis enables companies to leverage any and all the innovation technologies

that are useul during the discovery phase. In act, the innovation technologies provide

the means o executing steps in the AVID methodology. Going orward, we reer to an

innovation technology as a “lens” and/or a tool. A lens provides a conceptual/theoretical

view o a particular aspect o innovation. A tool structures the activity associated with

executing steps.

Te AVID methodology resolves three important issues. First, it enables teams to more

effectively leverage more innovation technologies across a wide spectrum o innovation

contexts, circumstances, and conditions. Second, it addresses all critical aspects o the

discovery phase o innovation, significantly decreasing the risk o innovation ailure.

Tird, it provides a common language around which teams can ideate, collaborate, and

work to maximize knowledge creation and work flow productivity during the innovation

discovery process. We introduce a ew new lenses and tools required or successul

innovation that are not adequately addressed by the innovation technologies. Some o

these new lenses/tools include the Customers Value Model, the Operational ChangeModel, the Design Funnel, and Business Model Optimization.




Why AVID is Called “Agile”

Te AVID methodology is called “agile” because it incorporates some o the general

principles o Agile Methodology, an iterative (non-linear) approach to sofware

development that has been evolving since the 1980s. Te agile approach uses empiricalevidence captured throughout the discovery phase to generate customer value insights

rather than a fixed execution plan that assumes knowledge o customer needs. Because

o this, customer needs do not need to be known ahead o time. Assumptions regarding

value creation, delivery, and capture are tested along the way to determine their validity

beore they are accepted. Agile methodology is a more effective way to work when

the project requirements cannot be known in advance due to uncertainties. An Agile

approach provides opportunities to assess the direction o a value innovation project

throughout the discovery phase as new knowledge is acquired.

Te agile approach is “iterative” because teams are required to cycle back to previous

steps to challenge flawed assumptions when they ail the reality test. Te agile approach is

also “incremental” because stages and/or steps provide the structure that moves a project

steadily towards completion. By contrast, teams using a conventional linear-sequential

product development model have only one chance to get each aspect o a project

right. With a linear approach, the efficacy o the project is not known until the project

is complete. In the agile paradigm, every aspect o development — customer needs,

product/service design, business model, risks, and assumptions — is continually revisited

throughout development.

A Systems Perspective o Innovation

Many believe that the discovery phase or product/service innovation cannot be

structured because it is too amorphous and dynamic. Tey say that there are just too

many scenarios, approaches, contexts, and that no one methodology can take all o these

possibilities into account. Tey assert that structuring the discovery phase will stifle

creativity and will slow down the process with bureaucracy and controls; that innovation

is a serendipitous phenomenon that depends on having just the right people andconditions to make it happen. Te act is that innovation is a very complex phenomenon

— it is the ultimate multi-disciplinary sport. Innovation involves all aspects o business

— competitive strategy, operations, marketing, finance, supply chain, leadership, culture,

organizational capabilities, ecosystems, and other things. Who is comortable claiming

that they are competent in all o these business disciplines? Not many. Quite simply,



15INRODUCION

innovation is overwhelming or most o us mortals.

Ten there are the core innovation technologies like Blue Ocean Teory, Design Tinking,

etc. Although each o these technologies is very useul, none o them individuallyencompasses all the aspects and contexts o the discovery phase. It’s like having bits and

pieces o a large map with lots o chunks missing. Companies do their best with what

they have. Tey gather a ew pieces o the map and proceed through an ad hoc innovation

process. Sometimes they develop a winner.

However, all indications are that only one out o seven product/service innovations

succeed. Tese are terrible odds! What most people do not appreciate is just how many

ways a product/service innovation can ail. Te truth is that no amount o creativity,

bravado, or wishul thinking will surmount these pitalls. Te only way to increase theodds o success is to use a best practice or the discovery phase that enables a company

to consistently develop successul innovations via an orderly and repeatable process.

A best practice provides the oundation or continual learning and the development

o organizational capabilities. It is through a best practice that all employees rise to

the occasion to contribute to the innovation efforts, not just the ew gifed or the most

influential.

Te dynamics inside the discovery phase include interactions between various aspects

o the business, interactions with customers, interactions between people, interactionsbetween a company and its business ecosystem, and interactions with competitors and

the market. Te discovery phase is too complex to comprehend rom a linear perspective,

which conceptualizes a phenomenon as a collection o discrete causes and effects. Te

discovery phase is too complex to be reduced in this way.

However, the dynamics o the discovery phase can be understood rom a systems thinking

perspective. When viewed through the lens o systems thinking, it becomes clear that

certain patterns o interactions produce certain outcomes. Because the various aspects

o a system are interdependent, interactions are subject to trade-offs and constraints. Inthe world o systems, interactions produce eedbacks. Tese eedbacks then inorm more

interactions.

In the discovery phase, interaction and eedback iterate to produce knowledge which then

inorms decisions. Tese decisions determine the success or ailure o outcomes. Tis is




why conventional linear methods like phase/stage gate do not manage the discovery phase

well when uncertainty is high. As the name suggests, “discovery” is the result o multiple

iterations o interaction, eedback, and learning over the course o time. Te best growth

opportunities cannot be ascertained by conventional analysis methods like SWO, whichassumes everything there is to know is already out there. Instead, the best opportunities are

discovered through interactions. As these opportunities are developed into business models

and product/service designs, no assumption can be taken or granted. Te discovery phase

requires empirical validation rather than analytical verification.

Te Big Picture

Te AVID methodology is a systems approach or managing the discovery phase

o product/service innovation. Te structure o AVID acilitates rapid learning andknowledge creation through cycles o interactions and eedback which systematically

reveal value targets or lucrative growth opportunities. Te AVID methodology enables

teams to quickly refine value targets and resolve associated innovation risks through

empirical procedures. Te AVID methodology is a hybrid ramework that incorporates

certain structural eatures, unctions, and logic rom other development methodologies

— Agile Methodology, Phase/Stage Gate methodology, the Spiral Lie cycle Model,

Kline’s Chain-Linked Model, and the New Concept Development Model. Te AVID

methodology is both incremental and iterative. It incorporates theories, concepts,

strategies, principles, techniques, methods, and tools rom many o the core innovationtechnologies — Teory o Disruptive Innovation, Blue Ocean Teory, Outcome-driven

Innovation, the Customer Development Model, Lean Startup, Discovery-driven Growth,

the Business Model Canvas, the Value Proposition Canvas, Open Services Innovation,

Innovation Ecosystems, Design Tinking, and RIZ. Te AVID methodology is a

contemporary best practice or structuring the discovery phase o innovation projects (see

figure 1.5).






(indicated by the outward pointing arrow labeled “Execution Phase”).

Stages, Action Steps, and Critical Outputs

AVID structures the discovery phase into our incremental stages o development:

(Stage 1) Identiy growth opportunity

(Stage 2) Design solution

(Stage 3) est/validate assumptions and critical success actors

(Stage 4) Develop execution strategies

Each stage consists o three action steps that are required to complete that stage in

the discovery process. Tis results in a total o 12 action steps through our stages odevelopment. Te 12 action steps are iterative while the our stages are incremental.

Specifically, the team will cycle back to previous steps when:

Assumptions ail the reality test

New knowledge is acquired in later steps that impacts earlier assumptions

It becomes clear that the pieces or logics o the ormative value targets do not

fit together into a coherent whole

Te our stages represent the incremental development o the value targets and systematic

resolution o innovation risks.

Te three action steps or Stage 1 are:

(Step 1) Define target value space

(Step 2) Create a compelling value proposition

(Step 3) Delineate a viable business model


(Step 4) Capture customer outcomes



19INRODUCION

(Step 5) Identiy customer segments

(Step 6) Design an optimal solution


(Step 6) est/validate solution utility

(Step 7) est/validate critical demand

(Step 8) Optimize the business model

We call these three action steps the “success filters” because collectively they prevent any

product/service that will not succeed rom getting through.


(Step 10) Resolve ecosystem constraints

(Step 11) Develop an operational change model

(Step 12) Prepare the final deliverables

Te third action step in each phase (indicated in bold text in figure 1.5) produces the critical

output or that stage, which serves as the input into the subsequent stage. Te exception is

the third step in Stage 4, which produces execution strategies that serve as the input intothe execution phase o the project.

Critical Output 1 is a viable business model

Critical Output 2 is an optimal solution design

Critical Output 3 is an optimized business model

As previously mentioned, the critical outputs rom Stage 4 are execution strategies which

are passed on to the execution phase o the project. Critical Outputs 1-3 are expected to

change as new knowledge is acquired as a result o the iterations between action steps. Te

changing o these three critical outputs through iteration is represented by the three large,

red, circular arrows positioned between each o these three stages. Te text inside each

iteration arrow is the critical output that is passed on rom the proceeding stage to the

subsequent stage.




Te Decision Gates

Tere are three decision gates. Decision Gate 1 requires a “Go Forward” or “Go Back”

decision on Critical Output 1 (a viable business model) rom Stage 1 beore proceeding

to Stage 2. Tis decision involves evaluating the business model to determine its viability,and whether it is capable o meeting the growth target or the product/service based

on what is known at that point. Prior to Gate 1, however, it is expected that the team

will cycle through Steps 1-3 to come up with the best viable business model beore it is

ormally evaluated by management. With a Go Back decision, the team iterates through

the previous three steps until another growth opportunity is identified and developed into

a viable business model, or the current viable business model evolves to the point where it

can meet the growth target.

Decision Gate 2 requires a Go Forward or Go Back decision on Critical Output 3 (anoptimized business model) rom Stage 3 beore proceeding to Stage 4. Notice that there is

no decision gate or Critical Output 2 rom Stage 2.

Decision Gate 3 requires a Go Forward or Go Back decision on Critical Output 4 (final

deliverables) rom Stage 4 beore proceeding to the execution phase o the project. Again,

multiple iterations between steps will be required to evolve the three critical outputs to the

point where they are capable o passing through the decision gate. Tat is, a team should

know beorehand i a critical output will meet the decision criteria or its respective gate.

Te Five argeting ools

Te value targets or a product/service innovation are systematically revealed and then

developed during the AVID process, and the innovation risks associated with these value

targets are systematically resolved. Te AVID methodology uses five methods/tools to

accomplish this:

Te Customer Value Model

Te Business Model

Te Innovation Risk Profile

Reverse Financials

Te Ecosystem Blueprint



21INRODUCION

We collectively call these the targeting tools because together they orm a synchronized

targeting system. Tese tools are represented in the gray area along the periphery o

the AVID methodology graphic. Te targeting tools play a crucial role in the AVID

methodology because they connect the 12 action steps to the our stages o development.Although many other methods/tools can and should be used rom the core innovation

technologies (also represented in the gray area along the periphery), the targeting tools are

essential in all our stages.

Te targeting tools travel around the AVID methodology and are used in tandem as

though they were one mega tool with different dimensions. All the targeting tools are

interconnected and thereore interdependent. As such, any addition/change in one tool

has some impact on the other tools. ogether, these five targeting tools enable a team to

see the big picture as they move through the 12 steps o the AVID methodology. Four othe targeting tools have been adapted rom the ollowing sources — the Business Model

Canvas (rom Osterwalder & Pigneur: Business Model Generation), Innovation Risk

Profile (rom Slywotzky: Te Upside), Reverse Financials (rom McGrath & MacMillan:

Discovery-driven Growth), the Ecosystem Blueprint (rom Adner: Te Wide Lens). Te

Customer Value Model is proprietary to the AVID methodology.

Enabling Organizational Factors

Certain enabling actors are critical or any product/service innovation project to succeed.Tese actors are represented in the middle o the AVID methodology:

Leadership

Culture/teams

Knowledge creation

We call these the enabling actors, because without them successul value innovation is not

possible. Te three enabling actors are in the middle to underscore their importance.

Te arrows moving around the enabling actors represent the dynamic nature o their

influence throughout the discovery process. Te arrows also indicate that each actor is a

component o a single engine that drives successul innovation projects.

Leadership within the project team is crucial to provide cohesion and purpose, to ully




leverage the talents and insights o all those involved via effective collaboration, and to

liaison with others in the company whose support is needed or the project. Leadership

outside the project team is crucial to prioritize the value innovation project within the

company, ensure a ast response at decision gates, expedite the allocation o resourceswhen needed, and quickly resolve any problems/issues that impede team progress.

Culture is a powerul driver o innovation when organizational values and norms are

aligned with the kind o capabilities required or the discovery process. Cultural norms

and values, in turn, drive the efficacy o team dynamics. At the heart o the discovery

phase is learning and knowledge creation. Collaborative interactions and empirical

eedback drive the learning process. Knowledge creation as the output o the learning

process inorms action steps and decisions. Without effective knowledge creation, the

discovery process is a non-starter.




ExecutionTeams


Design Solution


Strategy & Plan













Viable

BusinessModel


OptimizedBusiness

Model

Creation

Gate1

Gate2

Gate3

Leadership

Culture

KnowledgeCreation

GrowthTarget

ExecutionPhase


Design Solution


Strategies













Viable

BusinessModel


OptimizedBusiness

Model

Gate2

Gate3

Knowledge

Leadership

Culture/Teams

Creation

Gate1

IDENTIFY GROWTH

OPPORTUNITY

1STAGE :



IDENTIFY GROWTH

OPPORTUNITY

1STAGE :

Step 1 - Define Target Value Space

Building Powerful Growth Engines

The Customer Job To Be Done

Disruptive Innovation Lens

Defining The Target Value Space

Step 2 - Create Compelling Value Proposition

The Customer Value Proposition

The Customer Value Model

Verifying The Job To be Done

The Structure Of A Compelling Value Proposition

Verifying The Value Proposition

Step 3 - Delineate Viable Business Model

The Business Model Canvas

The Ecosystem Blueprint

Reverse Financials

The Innovation Risk Profile

Decision Gate 1 Criteria



25SAGE 1: IDENIFY GROWH OPPORUNIY

Step 1: Define arget Value Space

Building Powerul Growth Engines

Te input into the AVID methodology is a growth target or a yet-to-be-identifiedproduct/service. Te growth target specifies the net profit that the product/service

innovation must generate over some time period to deliver on its pro rata share o the

company’s overall strategic growth plan. Te net profit is expressed as earnings beore

interest and taxes or EBI. Te growth target is important because it specifies the “power” o

the growth engine that is needed to meet this strategic growth objective.

Specifically, we define a growth engine as a value platorm that is exploited over time to

generate net profit. Growth engines, whether they originate via value extensions or value

innovations, are the primary means by which companies grow. Metaphorically speaking,a growth engine has a certain amount o horsepower to propel a company orward. Te

power o a growth engine is measured by the amount o net profit it can generate — the

more net profit, the more horsepower it has. Te key question or the company is: how

much horsepower is needed to move the company rom where it is today to where it

wants to be in the uture? Does the company have this horsepower now? Probably not.

Te reality is that all growth engines become commoditized over time as a result o price-

based competition. Te maturity lie cycle o growth engines depends on the industry

clockspeed — the aster the clockspeed, the aster growth engines mature.

One thing is or sure — all companies need to build growth engines, and they need to be

building them more ofen to keep up with the times. Te most powerul growth engines

originate rom successul product/service innovations. Tese new value platorms can be

extended or years, creating a generous stream o profitable cash flows. But they are also

the riskiest engines to build. oo many companies build these innovation growth engines

only to see them sputter or quit working all together. Te ultimate objective o the AVID

methodology is to build powerul growth engines by consistently discovering the best

product/service innovations. Te AVID process starts with defining the target value space.

Te Customer Job o Be Done

Te target value space defines the scope o a lucrative growth opportunity rom three

perspectives — the customer circumstance perspective, the solution perspective, and the

market perspective (see figure 2.1). Te customer circumstance perspective ocuses on






the “big” job, or the outcome that the customer is trying to achieve by doing all the smaller

jobs. For example, a customer has the big job o traveling to a distant location to attend a

workshop. Te related jobs that need to get done to make this happen include planning

the event, purchasing an airline ticket, booking a hotel room, renting a car, getting to theairport, getting to the plane, getting to the hotel, etc. Te steps that customers have to do

to perorm most big jobs have a very similar pattern, as shown in figure 2.2.

Plan

Select

Determine

DEFINE

Gather

Access

Retrieve

LOCATE

Set up

Organize

Examine

PREPARE

Validate

Prioritize

Decide

CONFIRM

Store

Finish

Close

CONCLUDE

Update

Adjust

Maintain

MODIFY

Verify

Track

Check

MONITOR

Perform

Transact

Administer

EXECUTE

Troubleshoot

Restore

Fix

RESOLVE

Figure 2.2: Universal Job Map for Product or Service.

One o these related jobs may be underserved by existing solutions. Another possibility is

that there are a number o related jobs that are served by many different solutions, but the

patchwork o solutions adds complexity, cost, and time or customers. Offering a solution

that replaces these smaller jobs with one job will save time, money, etc.

o recap, the team wants to identiy a new job or related job that is both important to

customers and is unsatisfied by existing solutions. I a certain job is unsatisfied, it is very

likely that customers are seeking a better solution that will enable them to do this job. I

the new/related job is a good fit with the company’s existing capabilities, then it could

signal a good growth opportunity.




Once a customer job(s) has been identified that is both important and unsatisfied and

is a good fit or the company’s capabilities, the next thing to consider is why customers

are unsatisfied with existing solutions. Specifically, the solution perspective ocuses on

the utility issues and consumption constraints o existing solutions that could signala potential opportunity or the company. O course, it is possible that customers are

unsatisfied because there are no existing solutions. In this situation, customers may

be using a makeshif solution created rom off-the-shel components to get the job

done. Such a scenario may signal a new market opportunity. However, new market

opportunities are relatively rare. More than likely, there are existing solutions. Customers

may be unsatisfied with existing solutions because there is some constraint that prevents

them rom consuming the solutions or consuming the solutions in a certain context.

Customers may also be unhappy with the utility o existing solutions. A solution’s utility

has to do with enabling customers to do the job the way they define the perect executiono the job — their desired outcomes (this concept is discussed in detail later).

Disruptive Innovation Lens

An alternative entry point into Step 1 is to examine three customer groups through the

lens o the Teory o Disruptive Innovation:

Non-consumers who are not using existing solutions or who cannot use

existing solutions in a certain context Customers who are underserved by existing solutions

Customers who are overserved by existing solutions

Each group creates unique growth opportunities. First, a company can create a new-

market disruptive innovation to reach non-consumers. Non-consumers are everywhere.

Even individuals currently using a solution can be non-consumers, because they might

not be using the solution in a particular context or environment. For example, customers

may be using a land line, but not a mobile phone. Non-consumption occurs when

individuals or businesses cannot get a job done because the existing solutions are too

expensive or too complicated. Tey put up with getting the job done in an inconvenient,

expensive, or unsatisying way. Generally, our different barriers can constrain

consumption — skills, wealth, access, and time. Each can be identified in different ways.




A new-market disruptive innovation “competes with non-consumption” by offering

a more affordable and simpler solution than the existing alternatives. As a result, the

new-market solution enables a new group o customers who were previously unable

or unwilling to consume the existing solutions to begin buying/using the new-marketsolution. A new-market disruptive solution initially competes against non-consumption

in its value network o origin. As the perormance o the solution improves, the solution

ultimately becomes good enough to pull customers out o the original value network into

a new value network, starting with the least demanding customer tier. Tus, the disruptive

solution doesn’t invade the mainstream market, but rather it pulls customers out o the

original value network into a new value network.

Te second option is that a company can introduce an up-market sustaining innovation to

reach underserved customers. Underserved customers demand a better solution — moresophisticated, more specialized, simpler, less expensive, etc. Underserved customers exist

when a solution is not yet “good enough”. An up-market sustaining innovation exploits an

existing value platorm by moving the value proposition up a sustaining value trajectory.

An up-market sustaining innovation is sometimes aimed at the most demanding

customers, who are willing to pay a premium or a state o the art solution. At other

times, an up-market sustaining innovation results in a better quality solution at a more

affordable price.

Te third option is that a company can introduce a low-end disruptive innovation toreach overserved customers. Certain customer groups can become overserved when

incremental improvements no longer provide meaningul benefits to these customers.

Tat is, an existing solution can become “too good” and hence overpriced relative to

the value existing customers can use. As such, these customers may be unwilling to pay

or the improvements. I they do, they are likely using the existing solution because it is

the only available alternative, but they are unsatisfied. Tey are paying or unctionality

and eatures that just aren’t important to them. Tese customers will quickly abandon

the existing solution or a new solution that offers lower prices or more convenience. A

low-end disruptive innovation is an effective strategy to establish a beachhead amonga competitor’s least demanding customers who are overserved. Tis can be done by

developing a business model that makes money in a different way than established

companies — or instance, lower prices but higher asset turnover, a different mix o sales

and post-sales support revenue, and so on. Understanding the market perspective is

important because it defines what sorts o innovations will or will not flourish in a given








Step 2: Create a Compelling Value Proposition

Te Customer Value Proposition

Now that a target value space has been defined, the next step is to create a valueproposition or a new product/service (solution) aimed at the target customers. Te value

proposition articulates a compelling reason why a customer would want to buy/use a

solution rom the customer’s point o view.

We have ound that many companies do not understand how to create an effective

value proposition. A good value proposition is not speculative. It ollows a very specific

structure. A well-ormed value proposition describes the customer’s job-to-be-done

context and how the solution will enable them to get the job done better than the existing

solutions. However, a value proposition should not describe the specific characteristicso a solution design. In act, the solution design is not considered until Stage 2. Tis is

intentional. Te objective o Step 2 is to conceptualize potential value proposition(s) ree

o solution thinking. In this step, the team ideates on generic solutions without the design

details to maximize “degrees o reedom” in the search or a really good value proposition.

Companies ofen do this the other way around — solution thinking comes first, then

the value proposition. Te problem with this order is that companies get locked into

a solution design beore accurately understanding the target customers’ perception o

value with regard to getting an important and thus ar unsatisfied job done. In doing so,they place constraints on the innovation process early in the game. When this happens,

it is easy or companies to develop new solutions that they assume customers will value.

Tey are surprised when they miss the target. Te better way is to first accurately and

completely understand what customers value in the context o the job they are trying to

get done. Capturing this first provides a blueprint or designing the perect solution rom

the customers’ point o view. Why speculate on what you think customers want? It is better

to know exactly what they want and then design a solution that you know they will buy/use.

Tere should be no speculation about this.

Decoupling the solution design rom the value proposition and developing these in

reverse order is counter-intuitive or most people. Te advantage is that creating the value

proposition beore the solution design shifs the ocus o innovation rom a conventional

“inside-out” orientation to an “outside-in” orientation.




o create a compelling value proposition, we must first understand what our target

customers value. We start by asking a undamental question — what is value? Value can

be viewed rom multiple points o view — customers, the company, partners, and other

stakeholders. In this step, we look at value rom the customers’ point o view — customer value. From the customers’ perspective then, value is anything that they want to use

to get a job done. But what determines how valuable something is to a customer? Te

customers’ perception o value is not binary — that is, it is not simply valuable or not

valuable. In reality, customer value runs along a continuum rom not valuable at all to

extremely valuable. We want to create a value proposition that will reflect the customers’

perception o value on the extremely valuable side o the continuum. o do this, we need

to better understand the dynamics that drive customer value. When we understand

these dynamics, we can create more effective value propositions and design solutions

that customers will want to buy/use. Any degree o speculation about what customerswant introduces risk into the innovation process. Te more speculation is introduced, the

more customer value becomes marginalized. As customer value becomes marginalized,

customer demand or a new solution decreases to the point where it is no longer relevant

to customers.


We introduce a new tool called the Customer Value Model to help explain the actors that

determine a customer’s perception o value. We want to emphasize the word “perception”.Customer value is ultimately defined by the customer. Tis perception o value is driven

by a mental model that exists inside the head o all customers — the real customer value

model, i you will. Value mental models probably differ quite a bit rom customer to

customer. Tere is certainly a lot o things going on within these mental models that we

may never figure out. Yet based on what we do know, these value mental models have

certain commonalities that can put into a conceptual ramework. Te Customer Value

Model is an abstraction o a customer’s mental model that delineates the actors that

influence the customer’s perception o value with regard to evaluating market solutions.

O course, the Customer Value Model can never be a substitute or the real thing, but itexplains enough o the critical dynamics to be very useul or the innovation process. Te

entire Customer Value Model is depicted in figure 2.3. Te three boxes that are shaded

green are the parts o the Customer Value Model that will be used to create a compelling

value proposition in Step 2. We will explain these three parts in more detail below. Te

other parts o the Customer Value will be used in subsequent steps and will be explained




in detail at that time. What ollows is a general overview o the entire Customer Value

Model.

Utility Value

Extent that ImportantDesired Outcomes

are Satisfied

Job Priority

Extent that Job-to-be-Doneis Important

Solution Priority

Extent that Job-to-be-Doneis Unsatisfied

Situational Value

Extent that theSolution is Accessible

Market Price

Extent that the Cost ofAcquiring/Using

Solution is Acceptable

Customer Demand

Value Surplus

Customer

Perception of Value

C i r c u m s t a n c e

S o l u t i o n

M a r k e t

Relative to Substitutes

& Alternatives


& Alternatives

Relative to

Personal Values


S o l u t i o n

M a r k e t

Relevance

Intrinsic Value

Market Value

Figure 2.3: Customer Value Model - Value Proposition Construction.

Te Customer Value Model depicts five value actors that influence the customer’s

perception o value with regard to evaluating a new market solution: job priority,

solution priority, utility value, situational value, and market price. Tese five valueactors ultimately determine whether a customer decides to buy/use a solution (customer

demand) via a decision criterion called value surplus (discussed in detail at Step 8).

Te Customer Value Model conceptualizes these five value actors extending over three

different levels — the circumstance level, the solution level, and the market level. Te

dynamics o customer value is different at each level.

Te circumstance level has to do with the context that initially motivates customers to

seek out a market solution. Te job priority and solution priority value actors on this level

determine the perceived relevance o a solution to the customer’s need to get a job done.

When a solution becomes sufficiently relevant to customer need, the solution level has

to do with how customers evaluate the utility and accessibility o the solution. Te utility

value and situational value actors on this level determine the perceived intrinsic value o




the solution relative to other available solutions (substitutes and alternatives).

When a solution has a sufficient amount o intrinsic value relative to other available

solutions, the market level has to do with the cost o acquiring/using the solution in themarket context. Te market price value actor on this level determines perceived market

value o the solution relative to other solutions. Market value then becomes customer

demand via a final buy/use decision criterion called value surplus.

Tus, the Customer Value Model explains why customers seek out market solutions,

how they evaluate solutions, and why they choose to buy/use one solution over other

competitive solutions. Once we understand exactly how customers perceive value, then

we are in a better position to create value propositions and design products that customers

will want to buy/use. We do not need to speculate about what we think customers want.Te Customer Value Model is one o the five targeting tools o the AVID methodology

and is used extensively throughout the AVID process.

We now go into the circumstance level in more detail. A customer is motivated to seek out

a new market solution to the extent that a job-to-be-done is important — in other words,

job priority. Te importance o any job is relative to a customer’s personal values, and

these values can change over time. Customers have many jobs to do. But not all jobs are

important enough to motivate them to seek out a market solution. Companies sometimes

create what they think is a great solution or customers only to find that the customer isnot sufficiently motivated to buy the solution. Te job is just not important enough to the

customer to justiy the expenditure. Second, a customer is motivated to seek out a new

market solution to the extent that the job-to-be-done is unsatisfied — in other words,

solution priority. I the job is sufficiently important to the customer, then the question

is: how are they currently doing this job? Customers may have developed a homemade

solution by cobbling together off-the-shel components or services. Tis may or may not

work well or them. In other cases, they may be using an existing market solution(s). Te

priority to seek out a market solution increases to the extent that customers cannot do an

important job the way they want to with existing solutions. Tis may be because there isno available solution, or the existing solutions do not allow customers to do the job in a

satisying way. In either case, the job-to-be-done is lef unsatisfied.

As indicated by the wording “to the extent that” in the Customer Value Model, all

value actors that drive the customer’s perception o value lie along a continuum. In the




case o job priority, a job-to-be-done can range anywhere rom very important to not

important at all. Te question is: how important is the job to the customer? In the case o

solution priority, dissatisaction lies along a continuum rom very satisfied to completely

unsatisfied. Tus, the question is: how unsatisfied are the customers with the currentsolutions? A good value proposition will ocus on a job-to-be-done that is very important to

customers and very unsatisfied. Both value actors are necessary conditions. It is possible,

or example, that a job is very important, and customers are sufficiently satisfied with their

ability to do this job the way they want to with existing solutions. Tus, a new solution

that targets such a job will be an uphill battle. Tere are times when this is appropriate.

However, it is always best to look or the low-hanging-ruit opportunities first. Tis makes

things a lot easier and involves much less risk.

At the solution level o the Customer Value Model, situational value reers to the time,place, and means that a customer can access a solution — in other words, the contextual

conditions o consumption. ime conditions determine when a customer can buy/

use a solution, how long it takes to purchase, how to receive, to access, to maintain, or

to dispose o a solution, and or how long they can use the solution. Place conditions

determine where a customer can buy/use a solution (in a certain environment or on a

certain machine; a type o channel such as physical, Online, direct, indirect channel,

etc.), and receive/access a solution. Means conditions determine how a solution must

be purchased/used (authorization, volume, pre-requisites such as skills, technology,

licenses, etc.). As discussed earlier, many solutions impose situational constraints onconsumption that decrease the overall value o those solutions in the eyes o customers.

Tis, in turn, increases the extent that customers are unsatisfied with available solutions

and consequently drives the priority to seek out a better solution. (O course, no solution

can be completely ree o constraints due to the trade-offs involved.) Te opportunity lies

in exploiting this dissatisaction by designing a solution that removes key constraints and/

or increases situational value in other ways.

Veriying the Job o Be DoneYou will recognize that we used a simplified variant o the Customer Value Model in Step

1 to help define the target value space. Tat’s because finding a lucrative target value space

is largely an exercise in finding customer value opportunities in the context o the job-to-

be-done, along with the strategic intent o the innovation, and other considerations. Te

team defined a target value space in Step 1 which specifies a group o target customers and




an important job they are trying to get done, among other things. In Step 2, the team will

develop a value proposition around this job aimed at these customers. However, beore

the team can ocus on creating a value proposition, they must first empirically veriy that

the job is very important to the customers and that these customers are very unsatisfiedwith their ability to do this job with existing solutions. I the team finds that either o these

two value actors at the circumstance level are not high enough, then the team will need

to cycle back to Step 1 to find another job opportunity or this customer group that is very

important and very unsatisfied.

A detailed job map is an excellent way to scope and refine a customer job or the purpose

o creating a compelling value proposition. Figure 2.4 shows a universal job map or

obtaining a service solution. A similar job map can be developed or product solutions.

Contact serviceprovider and/oraccess service

Define and/orcommunicateservice needs

Evaluate and/orselect serviceoptions

Confirm and/orfinalize serviceplan

Adjust serviceplan and/or itsexecution

Contact serviceprovider and/oraccess service

Get questions

answered and/or problemsresolved

Evaluate and/ormonitor servicedelivery

Fulfill customerresponsibilities

Receive Service

Initiate servicedelivery

Pay for service

Figure 2.4: Universal job map for a service.

o empirically veriy a customer job, the team prepares a job-to-be-done presentation

and then presents this to a sample o the target customer group or eedback. Essentially,

the team asks: “We believe that this is an important job that you want to get done and

that you are unsatisfied with your ability to get this job done with current solutions. Do

we have this right?” Once this basic assumption is verified, then the team ollows up

with additional questions such as: “How important is the job?”; “How unsatisfied are you

with existing solutions?”; “Specifically, why are you dissatisfied with existing solutions?”;

“Do you have issues with accessing existing solutions (time, place, and means)?” Using




the Customer Value Model as a guide, the team verifies that their understanding o the

circumstances surrounding a customer’s job is the same as the customer’s version. I the

team is off on their assumptions, then customer eedback helps the team to re-calibrate

their job-to-be-done assumptions. Te process is repeated until a qualified job has beenidentified and verified that meets the criteria.

Te Structure O A Compelling Value Proposition

Te team is now ready to create a compelling value proposition or a generic solution that

the customers will want to use to get the target job done. Te value proposition articulates

a compelling reason why a customer would want to use such a solution. Specifically, the

value proposition translates the job priority, solution priority, and situational value actors

into a parsimonious statement(s) that will be highly relevant to the target customers. Itis critical that the value proposition be worded in such a way that reflects value rom the

customers’ point o view. Te purpose o a value proposition is to establish the relevancy

between the solution and the customers’ need. Once a value proposition makes this

connection, customers will be motivated to evaluate the solution.

Remember, customers do not decide to buy/use a solution based on the value proposition.

Te job o the value proposition is to move the customer value dynamic to the solution

level where they will evaluate both utility value and situational value. For this reason,

the specific characteristics o a solution are not part o the value proposition. In act, theinclusion o solution characteristics weakens a value proposition, making it less likely that

the customer will evaluate the solution. Companies unwittingly work against themselves

when they do this. A value proposition should be constructed in a way that is predictive

o consumption because it perectly reflects the customers’ perception o value and

thereore is compelling to them. Conventional methods produce value propositions that

are speculative because they imperectly reflect the customers’ perception o value due to

constraints that are put on the value proposition early in the innovation process.

Veriying Te Value Proposition

Te final task in Step 2 is to empirically veriy the value proposition with a new sample o

the target customer group. Tat is, this sample will be a different group o individuals than

the group that provided eedback on the job-to-be-done assumptions.




Veriying the value proposition can be done in many different ways and is easier than

veriying job assumptions. Te team will design a very simple pass/ail test. Tat is, either

the value proposition can achieve threshold relevance or it cannot. One way to veriy the

value proposition is to put up a micro website (two or three pages) articulating the valueproposition and then drive targeted customer traffic to this site. An affirmation o the

value proposition could be when a prospective customer clicks the button to request more

inormation or to be included in early beta trials. Alternatively, social media platorms like

Facebook can be used to veriy a value proposition. Prospective customers can indicate

whether or not they like the value proposition. Tere are many other ways as well. I the

value proposition ails to achieve threshold relevance, then the team will need to cycle

back through Step 2 until a value proposition is created that can be empirically verified.

Helpul Strategic Models, Methods, ools:

Teory o Disruptive Innovation Lens — JBD Analysis, Job ree, Customer

Interviews, Structured Brainstorming, Passive Customer Observations,

Compensating Behaviors, Job Scoring Sheet

Blue Ocean Strategy Lens — Strategy Canvas, Four Actions Framework,

the Eliminate-Reduce-Raise-Create Grid

Customer Development Model, Lean Startup Lens — Customer JBD Presentation,

Design ests, Customer Archetype

Outcome-driven Innovation Lens — Customer Jobs Matrix, JBD Outcomes,

Job Map

Te Value Proposition Canvas

Design Tinking




Step 3: Delineate Viable Business Model

Te Business Model Canvas

With a verified value proposition in hand, the team proceeds to delineate a viable businessmodel that is capable o profitably ulfilling the value proposition. Te business model

depicts the core logic o how the company will create the value or the target customers,

deliver the value, and how the company and its business partners will profit rom doing

this. Te Business Model Canvas is one o the five targeting tools and is used to structure

the various components o the business model (see figure 2.5).

Te business model consists o nine interwoven components:

Customer segments Value propositions

Customer relationships

Channels

Key activities

Key resources

Key partners

Cost structure Revenue streams

Each component is a piece o the overall logic that makes the business model work. As

such, each component involves assumptions. Because the business model works as a

system, flawed assumptions associated with any component weaken the business model. A

weak business model results in a marginal innovation that produces disappointing results,

even with a verified value proposition. Enough flawed assumptions will result in the

complete ailure o an innovation project.

Te task or this step is to articulate a viable business model that is capable o working as a

whole and to rigorously veriy the assumptions associated with each component. It should

be noted that verification is not the same thing as validation. In this step, verification is

about confirming internal accuracy and consistency o the business model components




and that components are capable o working together as whole. In contrast, validation

is about confirming the efficacy o the business model — that it actually does what it is

designed to do. Validation is addressed later in the AVID methodology.

ValuePropositions

KeyPartners

KeyActivities

KeyResources

Revenue StreamsCost Structure

Customer Relationships

Channels

CustomerSegments

Figure 2.5: Te Business Model Canvas.

Te centerpiece o the business model is the value proposition. Te team begins by

clariying the relationship between each business model component and the valueproposition. Each component has a critical role to play — a component can be a means

to generate the value proposition, a component can be the target or a means to deliver

the value proposition, or a component can be a means to capture value or the company.

It is helpul to think o this exercise as reverse engineering the value proposition into its

constituent parts.

Tere are many different ways o doing this. In act, the team is expected to come up

with multiple business model designs that can ulfill the value proposition. One o the

business model designs will stand out as the best. During this process, the team alsotakes into consideration the target value space dimensions defined in Step 1, such as

the strategic intent o the innovation, anticipated competitive response, key trends, etc.

Tese considerations will be “baked into” the business model in different ways. Te best

solution business model will be difficult or competitors to imitate, which is important i

the growth engine is going to be sustainable over time. Te team will replicate elements




rom the company’s existing operating business model into the solution business model as

needed.

For example, the team may use the company’s existing key partners, existing channels,key resources, etc. It is important to color code those replicated elements on the solution

business model. Later in the AVID methodology, we will need to distinguish existing

elements rom new business model elements. Ultimately, the solution business model

will either be a stand-alone operating model or the company’s operating business model

will be extended to commercialize the solution (this is true in most cases). In the case o

extension, the solution business model will need to be integrated back into the existing

operating business model. Tis is accomplished by developing a change model (covered in

Step 11).

Certain value actors in the Customer Value Model drive business model design. In Step

2, we integrated the job priority, solution priority, and situational value actors into a

compelling value proposition. Once a job-to-be-done is both important enough and

unsatisfied enough, the customer is sufficiently motivated to seek out a new market

solution to help them do this job in a more satisying way. Under these circumstances,

an effective value proposition becomes relevant to the customer’s need. I the value

proposition resonates with the Customer Value Model, the customer will be motivated to

evaluate a new market solution based on three actors — utility value, situational value,

and market value. Notice that the situational value actor is part o the value propositionand also affects other aspects o the business model. In this step, we will consider how

situational value and market value impact business model design.

Te shaded green boxes in figure 2.6 depict the value actors in the Customer Value

Model that are important in this step or delineating a viable business model. Utility value

has to do with the solution itsel and will be addressed in Step 4. It should be noted that

the solution design may also have implications or the business model design. I so, the

business model will be modified at that time.




Utility Value


are Satisfied

Job Priority

Extent that Job-to-be-Done

is Important

Solution Priority

Extent that Job-to-be-Done

is Unsatisfied

Situational Value


Market Price



Customer Demand

Value Surplus

CustomerPerception of Value

C i r c u m s

t a n c e

S o l u t i o n

M

a r k e t


& Alternatives


& Alternatives

Relative to

Personal Values

C i r c u m s

t a n c e

S o l u t i o n

M

a r k e t

Relevance

Intrinsic Value

Market Value

Figure 2.6: Customer Value Model - Viable Business Model.

I the value proposition offers a better way to improve the time, place, and means that

a customer can access a solution (the conditions o consumption), then the situational

value actor will be a significant dynamic in the business model design. Tis is because the

business model determines the ways that a solution is accessible to customers via touch

points with the company and its supporting ecosystem. So the question or the team is:

what business model decisions need to be made to deliver on the situational value component

o the value proposition? Tis will involve looking at different channel options, different

ways that partners can interace with customers, and the different ways that a company

can establish a relationship with customers.

Te revenue streams component o the business model specifies the pricing model (part

o the revenue model) that drives various revenue streams rom the purchase/use o

the solution. o create sufficient market value, a viable business model must position

the solution in such a way as to make it attractive to customers relative to competitive

offerings. Te market price value actor drives this aspect o the business model design.

Counter-intuitive to many, a solution design is not required to delineate a viable business

model. In act, it is better not to develop a solution design prior to developing a business

model. Te viable business model replaces the “business case” in the traditional phase/




stage gate methodology. Like the traditional business case, the business model is a tool

or making the decision to pursue or not pursue an opportunity. Unlike the traditional

business case, a business model views the business opportunity rom a design perspective

(the big picture) without all the analytical noise, which is ofen based on projections(speculation). A business model is ar more dynamic than a traditional business case

because a team can look at many possible business model designs beore choosing the

best one. Can you imagine developing multiple business cases? Te business model is

a blueprint or ulfilling a value proposition rom the company’s perspective. It shows

the choreography o the various parts o the business required to support the value

proposition. Te solution delivers on the promises made by the value proposition.

What companies ofen miss is that a business model has implications or the design o a

solution. A certain business model will require a specific solution design, while anotherbusiness model will require a very different solution design. Unortunately, companies

ofen lock themselves into a solution design too early in the discovery process. By

doing so, they reduce the “degrees o reedom” or finding the best value proposition.

Tey also restrict the business model possibilities, because the business model becomes

subordinated to the solution design. Tis is why the AVID methodology does not address

the solution design until Stage 2.

Te Ecosystem BlueprintTe business model does not exist as an island. Various components o the business model

thread to business partners that are necessary or the business model to unction. For

instance, the Key Partners component specifies the critical inputs, key resources, and key

activities sourced outside o the company. Te Channel Partners component includes

distributors, retailers, and other intermediaries that are required to ulfill part o the value

proposition to end customers. Even the Customer Relationships component may rely

on partners to acilitate interactions and/or communications between a company and its

customers. It is seldom the case that an innovation project is a stand-alone endeavor. o

the extent that the ulfillment o a value proposition relies on innovation partners to dosomething, ecosystem dependencies are created. Tat is, collaboration equals dependence,

and this dependence means risk. Companies tend to have blind spots with regard to

these ecosystem dependencies. An innovation blind spot is ailing to recognize how the

company’s success depends on suppliers who themselves must innovate and/or adopt

something in order or the company’s innovation to succeed. Tey take or granted that




everything that needs to converge in the ecosystem to ulfill a value proposition will just

happen because agreements, contracts, and inormal understandings are in place. Even

when innovation partners share a vision o what they are trying to accomplish, they will

ofen have different visions o how their separate efforts come together. Te reality isthat many innovations ail because the ecosystem does not come together as planned.

Companies need to recognize their hidden dependencies in the ecosystem and pro-

actively manage this risk i they are to succeed in the high stakes game o innovation.

Tere are two distinct types o ecosystem risks that are addressed in the AVID

methodology — co-innovation risk and adoption chain risk. Co-innovation risk increases

to the extent that the successul commercialization o a company’s innovation depends

on the successul commercialization o other partner innovations. Te extent o co-

innovation risk depends on the joint probability that each o a company’s partnerswill be able to satisy their innovation commitments within a specified time rame.

Adoption chain risk increases to the extent that partners will need to adopt the company’s

innovation beore end customers have a chance to access the ull value proposition. While

co-innovation risk has to do with whether innovation partners can deliver the required

co-innovations, adoption chain risk has to do with whether innovation partners will see

the value proposition as beneficial to themselves as well as to end customers. Tat is, there

must be an acceptable value proposition or innovation partners that aligns their interests

with that o the company’s regarding the new solution. When interests are not aligned,

ecosystem riction occurs. Unlike co-innovation risk that is driven by joint probability, allinnovation partners in the adoption chain must cooperate or the innovation to succeed.

Cooperation in the ecosystem is critical because a single rejection by an uncommitted

partner is enough to break the entire adoption chain.

Te AVID methodology uses a tool called the ecosystem blueprint as a way to pro-actively

manage these ecosystem dependencies (see figure 2.7). It is one o the five targeting

tools and is used extensively throughout the AVID process. Te ecosystem blueprint

is a map that makes a company’s innovation ecosystem and the dependencies explicit.

It lays out the arrangement o the ecosystem elements that are required to ulfill the value proposition — how the activities are positioned, how they are linked, and who is

responsible or what. Te ecosystem blueprint identifies all the innovation partners and

specifies their positions — the suppliers a project relies on, the intermediaries that lie

between the company and its end customers, and the complementors whose offers are

bundled at different points along the market path. Te ecosystem blueprint shows how








example, they can design a business model that can achieve the desired ROA via a low

margin, high asset turn scheme. At the other extreme, they can design a business model

that achieves the same ROA with a high margin, low asset turn scheme. Tere are a lot

o possible scenarios the team can consider. We underscore that only bare bone reversefinancials are required or the purpose o delineating a viable business model.

In the same way, the team develops a reverse balance sheet showing the maximum

assets or resources that can be used to ulfill the value proposition while still meeting or

exceeding perormance benchmarks on the reverse financials sheet. Troughout the AVID

process, the team allocates assets rom the allowable sections in the emerging reverse

balance sheet as the need or these assets becomes known.

Reverse financials are a powerul tool when combined with the other targeting toolsbecause they address the financial realities o innovation. All too ofen, companies simply

don’t consider all the aspects o developing a successul innovation, and they tend to

engage in wishul thinking. For instance, the practice with a conventional business plan is

to increment revenue projections, compounding each successive uture year by 10 percent.

Tis is pure speculation. Sometimes the size o the addressable market can make the

uture look brighter than it actually is. When innovation projects are perceived as “big,”

companies assume that things will magically work themselves out. Many companies find

out that this kind o wishing thinking ofen ends up in costly disappointments.

Te Innovation Risk Profile

We have discussed extensively the role o risk on the success or ailure o innovations.

Innovation risk increases to the extent that the assumptions underlying the value targets

are either omitted or flawed. Tus ar, we have discussed assumptions associated with

various components o the business model, assumptions regarding how customers

perceive value, assumptions associated with ecosystem dependencies, and financial

assumptions. In the case o ecosystem risks, success can be an all-or-nothing matter.

Unless all the ecosystem elements required or success line up in time, a project canail completely. In such a situation, “90% right ofen = 0”. When you start to look at the

innovation landscape with a wide lens, you begin to understand that the true odds o

success at the outset o most major innovation projects are less than 20%.




Without this wide lens perspective, there is the human tendency to be overly optimistic

about the odds o success. Companies look at an innovation project with a 5 percent

chance o success, and they think the odds are 40 percent. Tey look at a 10 percent

chance and think that it is 60%. It’s natural or business people to look on the bright side,because optimism generates energy and imagination. Te reality is that the typical ailure

rate o a new innovation project is about 70-80%. Tis explains why so many companies

ocus on incremental value extension rather than on value innovation; they accept the

trade-off o a low growth rate or saety. We would suggest that most companies are living

well beneath their privilege. Once armed with the knowledge o how to identiy the best

innovation opportunities and how to resolve the innovation risks associated with these

opportunities, companies can continually build strong and enduring growth engines.

Te first step in “de-risking” an innovation project is to careully estimate the true oddso success rom the start. Te purpose is not to discourage a team early in the game, but

rather to give a clear, accurate sense o what’s really needed to make an innovation a

success. Te tool that is used to accomplish this is the Innovation Risk Profile (see figure

2.9). It is one o the five targeting tools and is used extensively throughout the AVID

methodology. In Step 3, the Innovation Risk Profile helps the team to evaluate the risks

associated with viable business model designs and the odds that each will succeed. Te

team then selects the viable business model with the least amount o risk that is capable o

hitting the growth target.

InnovationRisk

Impact?How

Likely?Uncertainty

SourceRelated

AssumptionEliminate - Mitigate - Exploit

Best Way to Resolve Risk?

Odds of Success Scoreboard (Steps 3 - 11)

3 4 5 6 7 8 9 10 11

1.

2.

3.

Figure 2.9: Innovation risk profile template.






that customers will want to buy/use. Tere is no speculation. Because we have perect

knowledge o the value target, we can hit the bull’s eye every time.

Conventional wisdom is that risk is an undesirable thing. It is something to be eliminatedor mitigated. Much o the time this is true. However, there are occasions when an

innovation risk can be resolved by exploiting it to create a more profitable business

model that is harder or competitors to imitate. In such situations, a potential upside

may exist within the risk i a company has certain capabilities to manage that risk better

than competitors. I so, the company can exploit the risk by taking on more o it. ake,

or example, a business model that requires that a large variety o products/services

be available when customers need them. In this scenario, the job-to-be-done may be

contingent on dynamic circumstances that cannot be predicted, creating dynamic demand

or multiple solutions. At certain times customers quickly need solution A. At othertimes, they need solution B, C, D, and E. Te risk is not having the solution available

when needed, compromising a value proposition high on situational value. raditional

thinking would be to decrease the risk by having all the product/service variations ready

at any time, resulting in a lot o assets sitting around. A slow asset turn (Sales/otal Assets)

would make the business model cost structure very high. However, i a company has

enough operational speed and flexibility, it can standardize a common pool o assets that

can quickly be configured to accommodate dynamic demand. Customers may be willing

to pay a premium or such availability. Te business model becomes more profitable and

less risky or the company, but it becomes more risky and less profitable or competitorsthat do not have this operational capability.


Te Customer Value Model, the Business Model, the Innovation Risk Profile, Reverse

Financials, and the Ecosystem Blueprint are used in tandem throughout the AVID

process. Tese five targeting tools provide the means to identiy the best growth

opportunities and to develop these opportunities into successul innovations. Te

AVID stages and steps structure the effective use o these tools in the context o valueinnovation. A host o other innovation technologies and strategic models supplement the

targeting tools when needed. Te five targeting tools travel around through the steps and

stages, inorming thinking and actions. As new knowledge o the value targets is generated

rom interactions and eedback loops, the targeting tools are developed/modified until the

value targets are clarified and a successul innovation is discovered. Te targeting tools are







Teory o Disruptive Innovation Lens — Disruptive Channels, In-Source/Out-SourceDecisions, Disruptive Potential Map

Blue Ocean Strategy Lens — Strategic Sequencing, Buyer Utility Map, Strategic

Pricing, arget Costing, Price Corridor o the Mass

Hamel & Prahalad Lens — Core Competence

Michael Porter Lens — Five Forces, Value Chain

Resource-Based Teory Lens

Customer Development Model, Lean Startup Lens — Business Model Hypothesis

esting and Verification

Te Business Model CanvasTe Wide Lens — Ecosystem Blueprint, Co-Innovation Risks, Adoption Chain Risks

Discovery-Driven Growth Lens — Reverse Financials, Discovery-Driven Planning

Slywotzky’s Upside Lens — Innovation Risk Profile






ExecutionTeams


Design Solution


Strategy & Plan













Viable

BusinessModel


OptimizedBusiness

Model

Creation

Gate1

Gate2

Gate3

Leadership

Culture

KnowledgeCreation

GrowthTarget

ExecutionPhase


Design Solution


Strategies













Viable

BusinessModel


OptimizedBusiness

Model

Gate1

Gate2

Gate3

Knowledge

Leadership

Culture/Teams

Creation

DESIGN SOLUTION

2STAGE :



Step 4 - Capture Customer Outcomes

Understanding Customer Needs

The Problem With Conventional VOC Methods

Customer Desired Outcomes

Capturing Desired Outcomes

Prioritizing Desired Outcomes

Step 5 - Identify Customer Segments

Customer Segments

Outcome-Based Segmentation

Business Model Dynamics At Step 5

Step 6 - Design Optimal Solution Targeting The Optimal Solution

The Design Funnel

Design Prototyping

The Case For Open Innovation


DESIGN SOLUTION

2STAGE :



57SAGE 2: DESIGN SOLUION

Step 4: Capture Customer Outcomes

Understanding Customer Needs

Te second stage in the discovery o a successul innovation is designing a solution thatwill deliver on the value proposition. However, beore proceeding to actual solution design

(Step 6), the team must urther develop the Customer Value Model (see figure 3.1) to

ascertain the criteria that customers will use to evaluate how well a solution enables them

to get the target job done. While the accessibility o a solution is part o the evaluation o a

solution’s intrinsic value, the ocus o Step 4 is on the utility value criteria (the situational

value actors were defined in previous steps). Once these value criteria are known, then

efforts can be ocused on designing that value. Tese criteria provide the team with a clear

target to design a solution that customers will want to buy/use. Tere is no speculation.

A Customer Value Model that is flawed or incomplete will increase uncertainty aboutwhat the customer values, which orces a company to make design assumptions in lieu o

actual customer knowledge. Tese assumptions, in turn, drive up the risk o ailure. Te

variance between what a company thinks customers value and what customers actually

value is the root cause o why so many product/service innovations disappoint. Knowing

the criteria that customers will use to evaluate a solution in advance enables companies to

consistently develop successul products/services in less time, with less effort, and using

ewer resources.

Utility Value


are Satisfied

Job Priority


Solution Priority


Situational Value


Market Price



Customer Demand

Value Surplus

Customer

Perception of Value


S o l u t i o n

M a r k e t


& Alternatives


& Alternatives

Relative to

Personal Values


S o l u t i o n

M a r k e t

Relevance

Intrinsic Value

Market Value

Figure 3.1: Customer Value Model - Customer Desired Outcomes.




Te Problem With Conventional VOC Methods

One reason why companies do not get a complete and accurate picture o what customers

want is that they are not getting the kind o inormation required or innovation. Many

companies use conventional Voice o the Customer (VOC) methods to capture customerneeds and requirements, which then serve as inputs into the innovation process. While

these VOC methods are effective or the purpose o process improvements and extending

existing solutions, conventional VOC methods are not ideal or the purpose o innovation.

In the process/quality improvement context, the ocus o VOC is on the solution as

an output or as a process. Conventional VOC methods are designed to capture the

attributes and characteristics that customers value in these outputs and processes. Tis

VOC data provides an effective target or process improvements and value extensions

because customers are already using the solution — the trajectory o value improvement

is relatively straightorward. Te innovation context, on the other hand, requires a ocuson the job-to-be-done, not the output. In act, the solution (the output) does not yet

exist. Outputs and jobs are undamentally two different perspectives. For the purpose

o innovation, we want to know the criteria that customers use to define the successul

execution o a job, not the desired characteristics o a solution or process. Conventional VOC

methods do not provide this inormation.

Popular VOC methods include ethnographic research, customer visit teams, customer

ocus groups, lead user analysis, customer advisory boards, customer brainstorming,

customer interviews, customer surveys, to mention a ew. Tese VOC methods all involveactive or passive interaction directly with customers. However, the data collected is ofen

too unstructured and ambiguous to be useul in the innovation process. One problem

is that the concept o customer requirements can be defined as many things, including

solutions, specifications, needs, and benefits. Tese terms are ofen used synonymously.

Customers are perectly willing to share their thoughts and opinions, but they are not

aware o the types o inormation that a company needs to create successul product/

service innovations. Customers are rarely technologists, designers, engineers, or

strategists, and they seldom innovate. Because interviewers are not always clear about the

type o inormation that is needed or innovation purposes, they let customers articulatetheir needs/requirements in language that is convenient and meaningul to them.

Interviewers then simply accept the customer statements as requirements, which are

then used as inputs into the innovation process. Passive VOC methods like ethnographic

research are great or understanding the customers’ circumstances — how they are doing

jobs and the circumstances surrounding these jobs. Yet passive VOC methods are not




able to capture the unarticulated value criteria that exist in the mind o the customer.

Companies may use a combination o VOC methods, but this generates even more data

that obscures what is really needed or innovation purposes.

Customer Desired Outcomes

Specifically, companies need three distinct types o data or innovation purposes: they

must know 1) the jobs their customers are trying to get done, 2) the metrics customers

use to define the successul execution o a job, and 3) the constraints that may prevent

customers rom consuming a product/service. In Stage 1, the team identified a job-to-

be-done that is both important and unsatisfied, and they created a compelling value

proposition that offers customers a new way to get that job done. Customers not only want

to get the job done, but they also want to be able to do it aster, do it better in some way,or do it less expensively than they currently can. Yet to define just what “aster” or “better

in some way” means, the team will need to capture a set o metrics rom customers that

define how they want to get the job done, and what it means to get the job done perectly

rom their perspective. Just as companies use metrics to evaluate the output quality o a

business process or strategy, customers use metrics to measure the successul completion

o a job. Customers have these metrics in their minds, but they seldom articulate them,

and companies rarely understand them. Tese metrics are the customers’ desired outcomes

and they represent the customers’ needs with respect to getting a job done. Tus, customer

desired outcomes are associated with specific jobs. A simple job may only have a handulo customer desired outcomes, while a complex job may involve a dozen or more steps

with 80 to 120 desired outcomes.

Customer desired outcomes are value criteria statements that have a specific orm. An

outcome statement always ollows the structure shown in figure 3.2. Because an outcome

is a measure o success, it includes a direction o improvement, a unit o measure, and

the outcome desired (an object o control that defines what is being measured by the

customer). As with a job statement, an outcome statement may contain a contextual

clarifier to describe the conditions or circumstances under which the value criteria isrelevant and serves to urther clariy the outcome desired. o use the example in figure

3.2, a contextual clarifier is added to the end o the outcome statement: “minimize the

time it takes to see a doctor during an office visit” . o avoid introducing unnecessary

variability into outcome statements, only the terms “minimize” or “increase” are used

or direction o improvement. In act, because customers most ofen measure success






debate which ones, i any, may have value to customers. Instead they figure out which o

the desired outcomes or a given customer job are important and unsatisfied, and then

they systematically develop solutions that will better satisy those underserved outcomes.

Since they know which outcomes are underserved, they know where to ocus theirknowledge and creativity to develop solutions that customers will value. Because team

members are ocused on these criteria, they do not waste their time devising or deending

solution designs that satisy other less important needs. Tis way, a company is able to

ocus its time and resources only on developing solutions that it knows will create value or

customers and the company, eliminating all other non value-adding efforts.

Capturing Desired Outcomes

o capture the desired outcomes, the team maps the job-to-be-done that is the target othe value proposition, breaking the job down into discrete process steps, making a job

map. For each step, the team then ascertains rom customers what desired outcomes

or metrics they use to judge the successul execution o that step and o the overall

job. Figure 3.3 shows a universal job map or obtaining product support. Te desired

outcomes or each o the 12 steps that customers must perorm to get this job done are

listed below the job map. Each o these metrics is a criterion that customers use to define

the successul execution o that particular step o the job. Although this example only

shows one desired outcome or each step, in reality there may be several or each step.

Once these metrics are known, the degree to which they are satisfied by existing solutionsbecomes measurable, enabling the team to uncover unsatisfied needs that can be targeted

by a new solution. During this process, new knowledge may be generated that challenges

earlier assumptions, in which case the team will cycle back to modiy these assumptions

beore moving orward.




1. Increase the likelihood of being aware of a problem that requires support before the problem occurs

2. Minimize the likelihood that multiple contacts with support are necessary to address different issues or problems

3. Minimize the time it takes to determine what steps to take to resolve an issue or problem prior to contracting support

4. Minimize the time it takes to gather the information that support will require to address an issue or problem5. Minimize the number of contacts that are necessary to address a particular issue or problem

6. Minimize the time it takes to get a support person to visit once the visit is scheduled

7. Minimize the likelihood that support does not understand an issue and/or problem

8. Minimize the likelihood that the recommendations are unclear (technical terminology or unclear instructions)

9. Minimize the time it takes to implement support recommendations

10. Minimize the time it takes to determine whether support recommendations achieve the intended results

11. Minimize the likelihood that the same information must be provided again if the company is recontacted

12. Increase the likelihood of remembering what steps to take if an issue or problem reoccurs

Arrange forand/or receivea support visit

6Gathernecessarysupport inputs

4Actions beforecontactingsupport

3

Explain thequestion orproblem

7

ContactSupport

5Determine howto contactsupport

2Determine ifcontact shouldbe contacted

1

Address futureproblems

12

Recontactsupport

11Evaluatesupportresponse/results

10Executesupportinstructions

9

Get supportresponse and/or options

8

Figure 3.3: Universal job map for obtaining product support and associated outcomes.

Customers consider only three types o desired outcomes to define the successul

execution o a job:

Outcomes that are related to input

Outcomes that are related to processes

Outcomes that are related to output

Tis makes sense, given that jobs are processes and job steps are subprocesses. Te

primary ocus o input outcomes is speed — reduced time to complete something related

to getting the job done. On occasion, however, there are also other ocuses or input

outcomes, including reduced mental effort or reduced number o supplies required, and so

on. Te primary ocus o process outcomes is reduced variability — elimination o problems,

bottlenecks, and so on that cause job execution to go off track. Finally, the primary ocus

o output outcomes is optimized results. With the job as the anchor, and recognition that




input, process, and output are the three primary types o outcomes, it is straightorward to

ask customers questions that will elicit the outcomes that they use to measure success. For

each step in a job map, the team asks customers the ollowing questions:

What makes [job step] time consuming or slow? What makes it cumbersome

or inconvenient? --> [o elicit input outcomes]

What makes [job step] problematic or challenging? What causes it to be

inconsistent or to go off track? --> [o elicit process outcomes]

What makes [job step] ineffective or the output o poor quality? What would

the ideal result look like? --> [o elicit output outcomes]

Because customers use desired outcomes to evaluate solutions, it is possible to uncover

these outcomes by asking customers the reasons why they choose to buy/use one

particular solution over the other competitive solutions to get a certain job done. A good

question to ask is:

What makes one solution better or worse than another competitive solution

or getting [job step] done?

Te team will rely on a combination o one-on-one interviews, small group interviews,

and observational interviews as the means to capture desired outcomes. As with jobs,customers can articulate the outcomes they desire even when there are no solutions

available to get the job done. From a dozen interviews with a diverse group o customers,

a trained interviewer can uncover 80 to 120 or more distinct outcomes that customers use

to measure success in getting a job done. Tis list o outcomes represents the “needs” o the

customer rom the customer’s point o view — not the company’s point o view. Tis gives

us a way to predict customer buy/use behavior, because customers will evaluate a new

solution based on how well it satisfies these needs. Companies do not have to speculate

about what customers want. However, no company can design a solution that will satisy

all desired outcomes or a given job — there are just too many o them. Even i this couldbe done, trying to be everything to everybody is a recipe or ailure. Te design o a

success solution requires ocus.

How, then, do we go about selecting the outcomes that will be used to create the best

solution design? As described in the Customer Value Model, customers prioritize these









Outcome-Driven Innovation Lens — Job Mapping, Opportunity Score Calculation,Outcome-based Competitive Analysis

Disruptive Innovation Lens — Overserved Outcomes as a Signal or Potential

Disruptive Innovation, Value Migration

Blue Ocean Strategy Lens — Strategy Canvas

Survey Instrument Design and Analysis




Step 5: Identiy Customer Segments

Customer Segments

In the previous step, the team captured the desired outcomes or a customer group thatrepresented their needs with respect to getting the target job done. Ranking the outcomes

by opportunity score, the team selected a group o outcomes that will serve as the criteria

or designing an optimal solution in Step 6. However, individuals in the customer group

may not prioritize these outcomes the same way. Although individuals are doing the

same job and share a set o common desired outcomes, individuals may differ in the

importance they place on certain desired outcomes and the degree to which they perceive

these outcomes are satisfied by existing solutions. In other words, certain desired outcomes

are more important to some individuals than to others, and their levels o satisaction

differ as well. Tis is the reason why “one size fits all” solutions seldom work, becauseindividuals doing the same job may have a different Customer Value Model based on how

they prioritize certain desired outcomes. I a solution is developed without taking these

differences into consideration, the result may be a product/service that is more costly and

does not ully satisy any customer. Again, a successul solution requires ocus. Tus, the

task or the team in step 5 is to identiy subgroups o customers, or customer segments,

within the larger customer group that prioritize certain desired outcomes the same way.

Outcome-Based SegmentationWith the survey data rom Step 4, the team uses the statistical technique o cluster analysis

to identiy customer segments, using the opportunity score as the segmentation criteria.

Individuals that have a unique set o prioritized desired outcomes are put in the same

cluster. As mentioned previously, even though all the customers in the larger group are

doing the same job, there may be clusters o customers who have a unique Customer

Value Model based on differences in the way they prioritize certain desired outcomes. Say,

or example, that a team captures and prioritizes 50 desired outcomes or customers in a

group all needing to do the same job. Cluster analysis reveals that there are two distinct

clusters within this group — cluster 1 prioritizes desired outcomes 1, 4, 6, 22, and 34, andcluster 2 prioritizes desired outcomes 2, 8, 16, 28, and 39. Both clusters prioritize the other

40 desired outcomes the same way.

Tus, these two customer segments are differentiated based on the way they prioritize

a certain 10 desired outcomes out o 50 outcomes, which identifies each group as a




customer segment. What this means is that cluster 1 and cluster 2 will differ in the way

that they evaluate a new solution because their Customer Value Model is different. Tis

signals an opportunity or a company to design solutions that both customers will find

very valuable, while lowering the cost to the company. I the team discovers that differentcustomer segments do exist or the solution, then the company will need to consider how

this will affect the solution design in Step 6. More undamentally, the company will need

to decide how to pursue the different customer segments and the implications o doing so

on the target value space, the value proposition, and the viable business model.

Conventional methods ocus on segmenting customers using a combination o

demographic, psycho-graphic, and unstructured “needs” data as the segmentation criteria

rather than the job-to-be-done. Tat is, the primary unit o analysis is largely the personal

characteristics o customers rather than the job. But, as mentioned earlier, a customer’smotivation to seek out a new solution comes rom the act that they have an important

job to do and that they are unsatisfied with existing solutions that offer to help them get

that job done. Further, customers evaluate new solutions based on prioritized desired

outcomes that define how they want to get this job done and what it means to get this

job done perectly. Tereore, the job, not personal characteristics, should be the primary

unit o analysis or the purpose o establishing customer segments. Conventional methods

that use personal characteristics as the primary segmentation criteria drive companies to

target phantom segments, or groups o customers that do not really exist. Tese customer

segments are not homogeneous and may overlap significantly with other segments,making it difficult to design solutions that such groups will value.

By contrast, the AVID methodology uses an outcome-based segmentation method that

is ideally suited or the purpose o innovation. Outcome-based segmentation enables a

company to determine which desired outcomes are valued across all customer segments

and which ones are uniquely prioritized by specific segments. Knowing this means that

companies can create low cost solution platorms that address common outcomes while

offering differentiated solutions to customer segments that prioritize a unique set o

outcomes. Building differentiated solutions or multiple segments on top o a commonsolution platorm reduces the overall number o solution platorms that are needed (see

figure 3.5).




Product/Service Platform CharacteristicsCommon to All Market Segments

Add Segment 1Characteristics



Segment 1Solution

Segment 2Solution

Segment 3Solution

Figure 3.5: Solution differentiation for customer segments built on a common platform.

Te outcome-based segmentation method makes it easier to identiy hard-to-find growth

opportunities in mature markets. Because companies in these markets find it more

difficult to discover growth opportunities, they compete primarily on price, accelerating

the industry towards commoditization. Using the outcome-based segmentation method,

companies can identiy one or more customer segments that are underserved by the

competition and develop solutions that will appeal to these customers. Tis makes it

possible to compete along new dimensions o value rather than price. Outcome-based

segmentation is effective or:

Identiying demanding customer segments that may be willing to pay more or

more sophisticated solutions

Identiying growth opportunities in mature markets

Identiying customer segments that are unattractive and should not be targeted

Determining the best way to enter an existing market as a new entrant

Discovering overserved market segments that make attractive entry points or

disruptive innovation Discovering segments o high potential growth in all markets






Step 6: Design Optimal Solution

argeting Te Optimal Solution

Now that customer segments and customer value criteria have been clearly defined, theocus turns to creating a solution design that will best deliver that value. Specifically, the

objective or Step 6 is to design a solution using the customers’ prioritized outcomes (their

needs) as the design criteria that will profitably deliver the value proposition to them.

While we took caution not to impose constraints on the innovation project up to this

point, we now define constraints in this step as a means to establish the boundaries or the

solution design process. However, “constraints” as we use the concept here, differs rom

consumption constraints discussed earlier, in that design constraints are used to enable

rather than limit the design process.

Design constraints consist o three overlapping and competing sets o criteria that

establish boundaries or the solution design, the benchmarks by which the team can

measure progress, and a set o objectives to be realized. Te three constraints are:


Te business model

Available technology/resources (technologies, inormation, methods,

specialized knowledge, patents, people, capabilities, environment, machinery

and equipment, and acilities) that determine what is unctionally possible in a

solution today

Te available technology/resources are the “pieces and means” or creating point in time

solutions that can best ulfill the customers’ needs. Recall that desired outcomes are stable

over time, while technology/resources change requently. Te team will need to determine

the best combination o available technology/resources that can best ulfill the customers’

needs within the constraints imposed by the Customer Value Model and the business

model.

o be clear, a value proposition is not the same thing as a solution. A solution, whether

it is a product and/or a service, is the means by which a value proposition is realized or

ulfilled. Te value proposition is the value offer and promise. Tere are many means

by which a value proposition can be ulfilled that involve different combinations o




technology/resources, different business model designs, and different aspects o the

Customer Value Model. Tus, many solutions can be designed that are capable o

ulfilling the same value proposition. Some are better than others. However, in light o

the boundaries defined by the three constraints, there is only one optimal solution design.

Te optimal solution design delivers the most value to customers or the least cost, risk,

and effort. Te optimal solution satisfies the largest number o customer needs, given the

constraints imposed by the business model and available technology/resources. o the

extent that a solution is less than optimal, customer value will be lower, profitability will

be lower, and time to market will be greater.

Te Design Funnel

Te process o resolving the Customer Value Model, the business model, and availabletechnology/resources into an optimal solution out o the universe o possible solutions

is called the design unnel (see figure 3.7). Tis process cannot be done ormulaically.

Rather, it involves both art and science, using insights gained rom team learning during

the design process. Whether the team develops the best solution or not will depend on

how effectively they resolve the Customer Value Model with the boundaries imposed by

the business model and available technology/resources. Tere is considerable variance in

the way teams can translate/resolve customer needs to solution characteristics (eatures,

content, and processes). Tese perceptions and choices determine the scope and selection

o available technology/resources. Tus, teams can take many different routes through thedesign unnel, producing many potential solutions that all ulfill the value proposition.

Yet just because a solution delivers on the value proposition, that does not guarantee its

success with customers. What customers want is a solution that reflects how they define

value, not how the company defines value. Step 7 is about validating that customer needs

have been effectively translated/resolved to solution characteristics in the design unnel.




The Universeof PossibleSolutions

Customer Value Model

Business Model

Available

Technology/Resources

OptimalSolution Design

Figure 3.7: Te design funnel.

Te boundary conditions defined by the Customer Value Model, the business model, and

available technology/resources typically do not provide the team with a clear blueprint

or designing the best solution. Instead, these boundaries can be dynamic in the sense

that they are subject to change during the design process, or several reasons. First, the

team may need to cycle back to revise/refine business model assumptions based on what

is learned during the design unnel process. Second, the raming o available technology/

resources or a solution will change as business model assumptions change. Tird, the

team may decide to revise the value proposition and/or the mix o customer needs

targeted by the solution based on new insights revealed through team and/or customer

interactions. Te prioritized outcomes selected in the previous steps now become the

customer needs criteria or designing a solution customers will value. Without these

criteria to guide the solution design process, the other boundary conditions are less useul.

Tat is, a solution that is commercialized via a great business model using the best mix

o technology/resources will still disappoint i the customer does not value the solution.

Tis is why it is critical that these value criteria be known beorehand so that the team has a

clear target to guide the design unnel process. o the extent that the Customer Value Model

is incomplete or flawed due to poor customer interactions, bad survey design, sampling

issues, bias issues, or sorting and calculation errors, risk will increase or the innovation

project.




Design Prototyping

Assuming the team is working with a good Customer Value Model, design prototyping

is used as a way to propel the design unnel process towards the optimal solution design

(see figure 3.8). Design prototyping acilitates a “reflective practice” that drives double-loop learning during the design process. Reflective practice is defined as the capacity

to reflect on action so as to engage in a process o continuous learning (“thinking on

your eet”). Double-loop learning is a mode o learning where the learner may change

his/or underlying assumptions about something as a direct result o eedback (rom

prototyping). Te primary purpose o prototyping in this context is to generate learning that

will help the team discern the best path orward or designing the best solution, using the

constraints to propel the process orward .

The Universeof PossibleSolutions

Customer Value Model

ViableBusiness Model

AvailableTechnology/Resources

Optimal

Solution Design

P

P P

Figure 3.8: Prototyping accelerates the design funnel process.

Other innovation methodologies such as the Customer Development Model and the Lean

Startup Model use prototypes (ofen called the “minimum viable product”) as a way to

discover what customers value via a succession o simple pass-ail experiments. Tis is an

effective method o innovation discovery or startups where there is no operating business

model. Te very premise o a startup is an idea or a solution based on the vision o its

ounders. A startup is essentially trying to match a solution design to a value proposition




or target customers that have yet to be identified.

Tis is the opposite o what we are doing with the AVID approach. In our case, the

innovating company has existing products/services that the company delivers through anoperating business model. Te company wishes to identiy a new product/service that will

provide the company with a lucrative growth engine that leverages its existing resources

and capabilities. Te business model, the Customer Value Model, and the other targeting

tools in the AVID methodology inorm the solution design process, not the other way

around. Tat is, the objective is to design a solution that best satisfies well-defined

customer needs, commercialized through an explicit business model design. Because

we already know what target customers value, we do not need to acquire this knowledge

through trial and error experiments. Instead, the objective is to promote learning and

knowledge creation to “translate” the customer needs into the best solution within theconstraints o the business model and available technology/resources.

Te goal o design prototyping in the AVID context is not to create a staged working

model o a solution, as is the case with the minimum viable product technique. In act,

the discovery phase is not about developing a solution per se, but rather designing an

optimal solution that will be developed during the execution phase. Prototyping is used

to give orm to an idea or the purpose o learning about its strengths and weaknesses

relative to the design targets and constraints. Prototyping helps the team to effectively

“translate” the prioritized customer needs into solution characteristics. Learning generatesnew directions or the next generation o more detailed, more refined prototypes. Any

additional work beyond what is required or this kind o learning is a non-productive

use o time and resources. Prototypes should only involve as much time and effort as are

needed to generate useul eedback to accelerate the design unnel process. In act, the

more “finished” a prototype seems, the less likely its creators will be to pay attention to

and profit rom eedback. Te team should apply a simple rule o thumb or prototypes:

exclude any eature, process, or effort that does not contribute directly to the learning that is

needed to move the design process orward .

It should be noted that a prototype or a service innovation will not be a physical thing,

as with a product, but the prototype will still need to be tangible. A good method used to

prototype a service experience is scenario-based storytelling — a technique commonly

used by filmmakers to storyboard their concepts beore production. Storytelling involves

the description o some potential uture scenario, using a combination o words and




pictures sequenced over time. Te advantage o using scenarios is that it keeps the

customer at the center o the story, preventing the team rom getting lost in process

details.

A simple scenario-based tool that is useul in the development o new services is the

“customer journey” map. Using this tool, the team maps the stages through which an

imagined customer passes rom the beginning o a service experience to the end. Te

starting point may be imaginary or come rom customer observations. A helpul eature

o a customer journey map is that it shows where the customer and the service interact.

Every one o these experiences’ “touch points” ulfills some aspect o the value proposition

— the service is the solution.

A more sophisticated tool is service blueprinting. Like the customer journey map, serviceblueprinting shows the steps that a customer goes through to receive a service. But service

blueprinting goes urther by building out a richer map underneath the experience points,

depicting the documents, technology, and other artiacts that the customer sees during the

service, as well as the ront line workers who interact with the customer. Both customer

journey maps and service blueprints can be used as simple prototypes during the design

process.

Te Case For Open InnovationAs mentioned earlier, value rom the customer perspective is any solution that satisfies

their needs with respect to getting an important job done. Te objective here is to

design a new market solution that customers will want to use that makes the company

money. By “new” we mean a solution that enables a customer to get a job done in a

new way relative to other available solutions — the very definition o innovation. What

makes a solution an innovation is not the underlying technology/resources, regardless

o how novel or proprietary they might be. Rather, what makes a solution an innovation

is that the underlying technology/resources are combined in such a way as to deliver

value to customers as they perceive it through a profitable business model. Underlyingtechnology/resources enable point-in-time solutions that deliver customer value. While

the underlying technology/resources will change requently over some time period,

customer needs (desired outcomes) are stable over a long period o time. Innovation is

about creating the best point-in-time solutions that well satisy customer needs. Tereore,

we always want to be on the lookout or new technology/resources that will optimally




deliver on the value proposition. Tus, there is a strong case to be made that companies

should look or the best combination o technology/resources wherever they might be

ound — inside and outside o the company (open innovation). I the team discovers a

key technology/resource that belongs to another company, this can ofen be licensed ora reasonable ee. Expanding the search or technology/resources beyond the walls o a

company opens up many possibilities that will enable the company to innovate more ofen

and less expensively than i they restrict themselves to proprietary technology/resources

only.

Business Model Dynamics at Step 6

From the business model perspective, the task or the team is to design an optimal

solution capable o ulfilling the value proposition or the least cost, risk, and effort (seefigure 3.9). As the team moves through the design unnel, it may be necessary to revise/

refine the logic within and between business model components. Te Innovation Risk

Profile, the Reverse Financials, and the Ecosystem Blueprint are revised/updated as well to

bring them into alignment with the changes. Using all five targeting tools in tandem enables

the team to see the big picture at all times, which steers them away rom making solution

design decisions that are less than optimal .

KeyPartners

KeyActivities

KeyResources



Channels

CustomerSegments

[ Clusters byValue

Criteria ]

ValuePropositions

[ CustomerValue

Defined ]

[ OptimalSolutionDesign ]

S u b s

t i t u t e s &

A l t e r n a t i v e S o l u t i o n s

Operational Innovationand/or Improvements

May Be Necessary

Figure 3.9: Business model dynamics at step 6.





Design-Driven Innovation Lens — Rapid Prototyping, Smart eams, ServicePrototyping

Outcome-Driven Innovation Lens — Customer Scorecard, arget-driven

Brainstorming

Open Innovation Lens — Open Business Model, Open Services Innovation

Customer Journey Map

Service Blueprinting

RIZ




ExecutionTeams


Design Solution


Strategy & Plan













Viable

BusinessModel


OptimizedBusiness

Model

Creation

Gate1

Gate2

Gate3

Leadership

Culture

KnowledgeCreation

GrowthTarget

ExecutionPhase


Design Solution


Strategies













Viable

BusinessModel


OptimizedBusiness

Model

Gate1

Gate2

Gate3

Knowledge

Leadership

Culture/Teams

Creation

TEST / VALIDATE

3STAGE :



Step 7 - Test/Validate Solution Utility

The Utility Value Factor

Customer Evaluation Prototypes

Screening and Testing Procedures


Step 8 - Test/Validate Critical Demand

Market Value

Value Surplus As The Decision Criterion

Critical Demand

Customer Sales Presentations

Solution Sales Roadmap

Levers For Lifting Value Surplus Problems Reaching Critical Demand


Step 9 - Optimize Business Model

Opportunistic And Defensive Strategies

Optimize The Revenue Side

Optimize The Cost Side

Breaking Key Operational Constraints Business Model Dynamics At Step 9


TEST / VALIDATE

3STAGE :



81SAGE 3: ES/VALIDAE

Step 7: est/Validate Solution Utility

Te Utility Value Factor

Te task or the team in Step 7 is to test and ultimately validate the utility value o thesolution. Using the Customer Value Model as a lens, we are testing the extent that the

solution’s eatures, content, and/or processes enable customers do a job in a way that best

satisfies customers’ prioritized outcomes relative to competitive offerings (see figure 4.1).

At this point, we are not concerned with how many customers actually will buy/use the

solution; nor are we concerned with the profitability o the solution. Tose issues will

be addressed in the next two steps. Rather, this step is about making sure the solution’s

utility is sufficient to make it a success with customers. Without enough utility value, the

other issues won’t matter, because customers will not buy/use the solution. Specifically,

we want to answer the ollowing question: did the team translate the prioritized customerneeds (desired outcomes) into solution characteristics such that the solution delivers enough

utility value in the eyes o the target customers? Due to the many different paths a team can

pursue within the design unnel, it is unlikely that a team will design the best solution the

first time around. Based on direct customer eedback, the team may need to cycle back

and modiy the solution design to reduce the variation between the current and optimal

designs.

Utility Value


are Satisfied

Job Priority


Solution Priority


Situational Value


Market Price



Customer Demand

Value Surplus

Customer

Perception of Value


S o l u t i o n

M a r k e t


& Alternatives


& Alternatives

Relative to

Personal Values


S o l u t i o n

M a r k e t

Relevance

Intrinsic Value

Market Value

Figure 4.1: Customer Value Model - testing the utility value of the solution.




Customer Evaluation Prototypes

In order to test solution utility, customers are provided with a tangible prototype to

evaluate. Te team has a solution prototype at some stage in development which may or

may not be appropriate to present to customers. I the solution is a product, the qualityo the prototype may require some more attention so that customers are not distracted by

rough edges and unresolved details. We want customers to ocus on the utility value o

the prototype, not on the materials or ashion in which it was built. Generally, the more

tangible a prototype, the better customers can evaluate the solution. However, this does

not mean that the prototype has to be sophisticated. It is a waste o time and resources

to overly invest in developing sophisticated prototypes, because prototypes will change

requently. Putting too much time into developing prototypes can create an attachment

bias, which creates resistance to changing it. Tird, adding unnecessary time between

the customer eedback and solution design cycle intereres with the learning process.Feedback and then immediate action based on that eedback provide the strongest link

between cause and effect. Te bottom line is that a prototype only needs to be good

enough or customers to evaluate it.

I the solution is a service, it is likely that a storyboard, customer journey map, or a service

blueprint is being used as an internal prototype. Although internal prototypes are effective

or the design unnel process, they are too abstract to present to customers or evaluation

purposes. o create a more tangible prototype, consider a video or computer animation

that describes the customer journey through a service solution. Te video starts with adescription o the job-to-be-done, articulates the value proposition, and then visually

depicts the journey through the various touch points o the service. Te team might also

consider an experiential prototype which can make a service very real to customers.

Tis kind o prototype engages customers via a physical or “hands on” simulation, where

customers interact with people, processes, and artiacts as they move through the service

touch points in the simulation. Such a simulation (called a micro world) does not have

to be complicated, expensive, or time consuming to build in order to be effective. Use

common materials such as olding tables, paper mats, orms, timers, bells, multimedia,

lights, signs, masking tape, cards, and other common materials to create the serviceexperience. Te amazing thing is that customers will react almost identically to this kind

o simulation as they would in the real world.






I customer behaviors do not sufficiently validate solution utility, the team will need to:

Cycle back to previous steps to question assumptions.

ake a critical look at the Customer Value Model. Evaluate the design unnel process to make sure that the team is effectively

resolving the customers’ needs into solution characteristics.

Te test/design loop should continue until enough customers validate that the solution

utility is greater than that o competitive offerings.


From the business model perspective, we are validating the fit between the value

proposition and customer segments via solution utility (see figure 4.2). Should customer

eedback indicate that additional design work is needed, the team cycles back through the

design stage, updating the business model and the other targeting tools that are impacted

to reflect any changes made to the solution.

KeyPartners

KeyActivities

KeyResources



Channels

CustomerSegments

ValuePropositions


[ Utility Value ]

Test

S u b s t i t u t e s &

A l t e r n a t i v e S o l u t i o n s






Design-Driven Innovation Lens — Rapid Prototyping, Smart eams, ServicePrototyping

Customer Development Model, Lean Startup Lens — esting Problem-Solution Fit

esting Protocols

Experiential Simulations






choosing the best one.

Since this balance scale is purely a customer construct, companies cannot “produce” value

surplus; however, they can influence it. Te two key variables that a company can controlto influence value surplus is economic value and market price. Te economic value is the

perceived benefit a customer receives rom the solution measured in economic units, or

the “internal currency” o the customer. In classic economics, this internal currency is

called the customer’s “willingness to pay”, which reflects what the customer is willing to

give up in exchange or the solution.

Te economic value o a solution is determined by the relevance (job priority and solution

priority) and intrinsic value actors (situational value and utility value) o the solution

(see Figure 4.3). Te market price is what the customer must give up in economic units toacquire/use the solution. Te difference between the economic value and the market price is

the value surplus o the solution (see figure 4.4).

Market PriceJob Priority

Utility Value

Solution Priority

Situational Value

Value Surplus

Economic Value

Figure 4.4: Te value surplus concept.




Value surplus only exists when economic value is higher than the market price. Tis

implies that when a customer buys/uses a solution, they place a higher economic value on

that solution; otherwise they would not buy/use it.

We use simplified proxies or the value surplus concept all the time such as “price/value”

and “cost/benefit” without ully appreciating the deeper implications o value surplus.

Yet or innovation purposes, we need to understand this concept at a more granular level

to be able to manipulate the actors that influence customer buy/use decisions. Beore

commercializing a solution, we want the ability to accurately predict demand or that

solution rather than relying on projections and orecasts (speculation).

I the market price o a solution is higher than the economic value, then the solution has

no value to the customer. Consequently, the customer will not buy/use the solution. Ithe economic value o a solution alls outside o an acceptable range or a customer, then

it doesn’t matter how low the price is. Te customer will not even consider the solution.

Likewise, i a solution alls outside o the acceptable market price range, the customer will

not consider the solution (see figure 4.5). From among all solutions wherein the market

price is less than the economic value and which are within an acceptable economic value

range and market price range, the customer will choose the solution with the greatest value

surplus. Te chosen solution represents the “best value” or the customer relative to the

other competitive offerings in the market. For this reason, value surplus, not the market

price, is the ultimate decision criteria or choosing one solution over other competitiveofferings.

Te market price is very important to be sure, but it is only the means or comparing the

value o competitive solutions (market value), not the final decision criteria or selecting

a particular solution. Likewise, economic value is the means customers use to compare

what they are willing to pay to a solution’s intrinsic value, but it is not the final decision

criteria or selecting one solution over another. It is the combination o economic value

and market price that inorms the final decision to buy/use a particular solution in a

competitive marketplace.

Because value surplus is a construct in the mind o the customer, it cannot be quantified

directly. Nonetheless, value surplus is the invisible orce that is present every time a

customer makes a decision to buy/use a solution. Value surplus can be inerred rom the

collective buying behavior o customers in a market context.




Hi

LowHi

Low

Acceptable Economic Value Range

Same Price

Same Economic Value

Lowest Price

Highest Economic Value

S o l u t i o n 1

V a l u e S u r p l u s

S o l u t i o n 2


S o l u t i o n 3


S o l u t i o n

4

V a l u e S u r p

l u s

S o l u t i o n 5


Best Value

Out of Range

Highest Price

Economic Value

Market Price

A c c e p t a b l e M a r k e t

P r i c e R a n g e

Figure 4.5: Value surplus as the ultimate customer decision criterion.

o give a detailed example, say a customer is looking to buy/use a solution to help them

get an important and unsatisfied job done. Te market offers about a dozen solutions

relevant to the customer’s needs. Based on the advertising claims o economic value

and the market price, the customer quickly determines that there are five solutions

worth evaluating. Te five solutions are within an acceptable economic value range and

price range or the customer. Solution 1 and Solution 3 have the same economic value,but solution 3 is less expensive and thereore offers greater value surplus. Solution 1 is

eliminated. Afer an evaluation o solution 2, the customer decides that this solution does

not live up to its advertising claim — the utility value is too low and thereore it does not

meet the customer’s needs (desired outcomes). Solution 2 is eliminated, even though

it is the least expensive. Solution 4 has the highest economic value and is also the most

expensive (the premium solution). Te customer eliminates solution 4 because the value

surplus is significantly less than solution 3, which is good enough to get the job done.

Solution 5 is the same price as solution 3, but offers significantly less economic value.

Tus, solution 5 is eliminated because it offers less value surplus than solution 3. In theend, the customer determines that solution 3 is the best overall value. Te perception

o internal currency based on a willingness to pay drives customers to maximize value

rather than minimize price or every economic exchange. Te value surplus is the ultimate

decision criteria that customers use in a competitive marketplace.






o the revenue streams will be addressed in Step 9.

Te reason or this is simple. otal revenue is driven purely by customer demand, which

has nothing to do with the cost side o the business model. Simply put, customers arenot concerned with a company’s profitability when they evaluate solutions. Tey are

only concerned with maximizing value or every economic exchange. Tereore, it is the

customer’s perception o the value o a solution in a competitive market that determines its

revenue-generating potential .

Step 8 determines i the solution is capable o attracting the mass o customers necessary

to generate the required total revenue — the critical demand . I the solution cannot

generate this revenue, then it will not be capable o delivering the desired net profit under

the current profit margin assumption.

Te team works backwards to delineate the actors that drive the desired net profit on

the revenue side. As figure 4.6 indicates, net profit is the product o total revenue and the

profit margin on that revenue. Since the ocus is on total revenue in Step 8, the cost side

o the business model is held constant or now, using a fixed profit margin assumption

(we work specifically with the profit margin in Step 9). otal revenue is the sum o all

revenue streams. Revenue streams are the product o market price and the number o

customer transactions (in the aggregate). Depending on the complexity o the business

model, multiple combinations o transaction type and market price are possible. Te masso customers that are needed to generate the transactions that will produce the required

revenue streams is the critical demand. Stated another way, critical demand is the number

o customers needed to generate the required net profit.

o recap, the team calculates the critical demand by working backwards rom the

desired net profit. Using the spreadsheet version o the cost structure and the revenue

model, the team calculates the total revenue required to generate the desired net profit

with the current profit margin. For example, i the desired net profit is 1.0 million and

the profit margin is 40%, then the total revenue required to deliver this net profit is $2.5million. Next, the team calculates the number o transactions (at the current market price

assumption) that are necessary to generate $2.5 million in total revenue. o determine

critical demand, the team will then calculate the number o customers required to

generate this number o transactions.




TotalRevenue

Number ofCustomers

Neeed

RevenueSide

Levers for Lifting

Value Surplus:

1) Economic Value

2) Market PriceCostSide

ProfitMargin

CostStructure

Critical Demand

Substitutes & Alternative Solutions

Work Backwards

MarketPrice

Number ofTransactions

Revenue Streams

GrowthTargetDesired

Net Profit

Figure 4.6: Working backwards to determine critical demand.

Customer Sales Presentations

Te team will test and ultimately validate critical demand by delivering a sales

presentation to the target customers to determine whether these customers will commit

to buying/using the solution. Because the actual customer population is a very large

number, the team will use an inerential statistical method to test a sample o the target

customer population. Using the critical demand value, the team can statistically determinerom customer responses i the solution is capable o attracting critical demand (or even

exceeding it). Because the critical demand is a specific number, the solution either is

capable o attracting this number o customers, or it is not. Te sales presentation consists

o the value proposition, a high-level description o solution characteristics, the market

price o the solution, and a high-level comparison to other competitive offerings.




Recall that a good value proposition includes a description o the circumstances that drive

the importance o the job-to-be-done, the inadequacy o existing solutions, and why a

customer should choose the company’s solution over other competitive offerings. Te

objective o the sales presentation is not to take orders, take payments, sign contracts,or make verbal commitments to deliver the solution to customers (although there are

exceptions to this). Rather, the ocus is to determine i the solution can attract the critical

demand necessary to hit the growth target. All that is necessary to determine this is a

customer commitment to buy/use the solution. It is important to systematically collect

eedback rom customers that do not make a buy/use commitment to understand the

reasons or their decision.

o ensure valid results, the sales presentation must be delivered to customers under

testing conditions. o eliminate potential bias, it is important to target customers thathave not been involved in previous solution evaluations or customers that may have an

affiliation with the innovation team or the innovation project in any way. Blind tests, ocus

groups, paid customer participation, surveys, and outsourced marketing services are not

appropriate testing methods or the kind o eedback that is needed to test/validate critical

demand. Tese conventional marketing methods are typically used to gather customer

requirements, to ascertain customer preerences o one product over another, to establish

market opportunities, etc. Te team is doing none o these things in this step. Instead, the

team is asking the customer directly or a buy/use commitment.

Te testing conditions must reflect inormed choice with no prior expectations or biases

on the part o participating customers. As mentioned in Step 7, the team should take care

to select a diverse cross-section o individuals or the testing sample o target customers

or the solution. o accomplish this, the team will develop a precise customer profile

based on criteria defined by the Customer Business Model. With these customer profiles,

the team can develop a simple screening instrument that ensures the right customers are

selected or the sales presentation. I the team is on a “job site” with actual customers, the

screening instrument can be used to script a short verbal interview that can effectively

qualiy target customers beore the team “pitches” the solution to them.

Customers may have trouble visualizing the solution based solely on a slide deck

presentation containing text and pictures. I customers cannot ully comprehend the value

proposition, and they cannot clearly visualize the solution’s characteristics, the eedback

rom these customers will be unreliable. For this reason, it is a good idea to integrate video




and/or other multimedia into the sales presentation to demonstrate or characterize the

solution. o get customers to even listen to a sales presentation, it may be necessary to first

develop marketing resources such as solution data sheets, a website, and brochures that

effectively communicate the value o the solution. Messaging around the Customer ValueModel communicates the true value o the solution rom the customer’s perspective. In

cases where the solution will be sold through an indirect channel, the team will use the

ecosystem blueprint tool to delineate the linkages and relationships between the company,

channel partners, and the end customer. Te blueprint should describe the responsibilities

o each channel partner in the sale, distribution, and support o the solution, as well

as how end-customer demand will be created. Tis is important because without end-

customer demand, channel partners will not see the business case or why they should

support the new solution. Worse yet, the solution may conflict somehow with how

channel partners make money, in which case the solution will die in the channel beore itever gets to an end customer. A common mistake is to assume that channel partners invest

in creating end-customer demand or a solution, which is seldom the case.

Solution Sales Roadmap

It may the case that the sale o a solution will depend on the influence or approval o key

individuals within the hierarchy o customer organizations or possibly outside o these

companies (such as consultants). Since the ecosystem blueprint does not address this, the

team should also develop a sales roadmap that describes who the true customer is andhow they will buy/use the solution through this chain o influence. Specifically, a sales

roadmap describes the influence pathway that a team must go through in the process

o selling the solution to the true customer. I the intent o the innovation is to create a

new market, the team will be approaching potential customers where no prior business

relationship exists. In this situation, it will be helpul to detail every step rom the first call/

meeting to a customer commitment and how these steps might vary rom one company,

buyer, or job title to the next. Te complexity o the sales roadmap will depend on the

customer’s size, buying cycle and budget as well as the product’s price, the industry, and

the distribution channel selected.

Levers or Lifing Value Surplus

ypically, responses rom non-committing customers will all into two categories: 1) they

question the value proposition (job priority, solution priority, situational value), or 2)




they perceive that the solution is not as good as competitive offerings or various reasons

(utility value, market price, value surplus). I customer eedback indicates that the value

proposition is weak or flawed, this indicates a serious problem. Tis will require the team

to cycle back to Stage 1 to re-think the target value space, the value proposition, and thebusiness model. More ofen that not, however, most non-committing customers will

convey the general message that the solution is not as good as other competitive solutions.

What they are really saying is that the value surplus o the solution is not high enough

relative to the competitive offerings. I most o the eedback alls into this category,

then the ocus should be on lifing value surplus enough to create a preerence or the

company’s solution over the competitive offerings.

Te team has two levers they can use to lif value surplus:

Increase the economic value o the solution

Decrease the market price o the solution

Te team should first cycle back to the solution design stage to find ways to increase utility

value and/or situational value, which will, in turn, increase economic value. Tat is, with

the market price staying the same, increasing the economic value will lif value surplus. I

the team determines that the economic value o the solution is as high as it can get under

current design constraints, then the second option is to lif value surplus by lowering the

market price. Tat is, with the economic value remaining the same, a lower market price

will lif value surplus. O course, this is a trade-off situation, because a lower market price

will reduce total revenue, which will, in turn, lower net profit (all things being equal).

Generally, lowering market price should be the last resort or lifing value surplus, because a

company does not want to rely on market price to drive demand at the expense o net profit .

It is ar better to find ways to boost economic value than to decrease the market price.

Te best approach is to find an optimal balance using both levers in tandem — stretch

economic value as much as possible within the design constraints; then decrease the

market price as necessary to reach the value surplus needed to attract critical demand. Te

objective is to keep the market price as high as possible by letting economic value do the

“heavy lifing” with respect to value surplus.

Tis approach works well i there is a relatively small difference between current customer




demand and critical demand. However, i this difference is much larger, and the team

cannot mitigate this difference via a better solution design, then the company should

consider how to improve its operational capabilities to break the constraints that are

limiting effective value creation. One way to do this is to identiy the one operationalconstraint that, i removed, would have the greatest impact on increasing the economic

value o the solution. Te company should then find a way to remove that constraint. In

the long run, it is ar better to improve operational capability than to sacrifice net profit

by relying too heavily on market price to stimulate demand. Challenging operational

assumptions can lead to an operational improvement that can significantly boost the

economic value without adding additional cost. Tus, accepting without question that

“Tis is the way we do things around here” is naiveté with a price tag that deprives a

company o the vital profits that it needs to uel growth.

Problems Reaching Critical Demand

When value surplus cannot be lifed any urther using the two levers, critical demand may

still be reached by expanding the market scope or the solution. Tis will require that the

team cycle back to Stage 1 to re-think the target value space, the value proposition, and

the business model to find ways to make the solution relevant and appealing to additional

customers. o do this, the team ocuses on the job-to-be-done as the primary unit o

analysis, rather than traditional industry boundaries to find non-consumers. For instance,

the team may have overlooked a certain group o potential customers that are using analternative solution to get the same job done. I the team can position the solution in a

way that can offer these customers a better alternative solution, this will increase current

demand. Increasing the number o target customers in this way may be enough to reach

critical demand.

I the gap in customer demand cannot be resolved using the aorementioned techniques,

then it may be possible to compensate or the gap (rather than close the gap) by increasing

revenue in other ways and/or increasing the profit margin. Specifically, the ocus o

Step 9 is to find ways to reduce the cost structure, thereby increasing the profit marginon current revenue; or to find ways to increase total revenue with the current level o

customer demand. Tat said, the greater the difference between current customer demand

and critical demand, the more challenging it will be to resolve this difference via a lower

cost structure. Te best practice is to work diligently to find creative ways to reach critical

demand beore addressing the cost structure. Tis may require multiple iterations between




the est/Validate Stage and earlier stages. Te work pays off in the end, because i the

team can go into Step 9 having achieved critical demand, then any reductions in the cost

structure will effectively increase net profit or the company and will make the business

model more difficult or competitors to imitate.


From the business model perspective, we are testing/validating that the solution design is

capable o attracting the mass o customers needed to generate the required revenue to hit

the growth target. Te team uses economic value and market price as levers to maximize

customer demand. Te team also considers opportunities to increase the number o target

customers by expanding the market scope or the solution (see figure 4.7). Te other

targeting tools are updated to reflect any changes to the business model or solution design.

KeyPartners

KeyActivities

KeyResources



Channels

CustomerSegments

ValuePropositions


[ Market Pricing ]

Test

S u b s t i t u t e s & A

l t e r n a t i v e S o l u t i o n s

CriticalMass of

Customers

[ Economic Value ][ Market Scope ]





Step 9: Optimize Business Model

Opportunistic and Deensive Strategies

Te purpose o Step 9 is to identiy ways to increase revenue and/or to minimize costswithout reducing the economic value o the solution. In other words, Step 9 is about

optimizing the business model to maximize net profit (value capture) with the current

level o customer demand (which may or may not reach critical demand). Recall that

value capture is the total net profit that a company banks or captures rom the purchase/

use o a solution. I critical demand has already been achieved in Step 8, then Step 9 is an

opportunistic strategy to exceed the growth target by finding ways to generate even more

net profit rom current customer demand. I critical demand has not been reached, then

net profit will all short o the growth target. In this case, Step 9 is a deensive strategy to

compensate or the demand gap by increasing total revenue and/or increasing the profitmargin. By doing this, it may be possible to increase net profit enough to meet the growth

target with the current level o customer demand — essentially “backing into” critical

demand. In short, the demand gap is mitigated or eliminated by increasing net profit

via business model optimization. At the conclusion o Step 9, it will be clear whether the

solution is capable o meeting or exceeding the growth target— a necessary condition to

pass through Decision Gate 2. Te strategy or optimizing the business model is: 1) first

maximize revenue streams and then 2) minimize the cost structure.

Optimize the Revenue Side

Te first task is to identiy opportunities to increase total revenue without increasing costs

or decreasing customer value in any way. Te objective is to maximize revenue streams

under the current cost structure. We expand on the revenue stream component o the

business model that converts customer transactions into revenue streams — the revenue

model (see figure 4.8). We want to make sure that the company is not leaving “money on

the table”; that revenue is maximized with the current level o customer demand.

When customers buy/use a solution, they interact with the company in some way.Tese are two-way transactions — the customer receives something o value and the

company captures value. In the case o a multi-layered service experience, the customer

may interact with a company though many touch points beore the company captures a

revenue stream. Tus, the revenue model describes the logic o how a company monetizes

customer transactions into revenue streams.




TotalRevenue

RevenueModel

CostStructure

ProfitMargin

CostStructure

Work Backwards

AccessoryProducts

AccessoryServices

PricingMechanisms

PayoutMechanisms

CustomerIncentives

Revenue Streams

Value-Added Partners

Revenue Model Variables

GrowthTargetDesired

Net Profit

Figure 4.8: Work backwards to maximize revenue streams.

Metaphorically speaking, the revenue model is an engine that produces revenue streams;

customer transactions are the uel that turns this engine. Te efficacy o the revenue

model depends on the logic and the strategic design o the engine. Te aster and

longer the revenue engine turns, the greater the amount o revenue it will generate. Some

revenue models are simple — a customer buys/uses a solution and pays the company.

Te company captures a one-time revenue stream rom that transaction. Other revenue

models are more complex — a company pays or subsidizes certain customer groups touse a solution and then monetizes this relationship by attracting and charging other

customers who want access to these other customer groups. Another example would be

that a company offers a solution to a certain group o customers where the company buys/

acquires something rom these customers (payouts) and then sells the acquisitions to

another group o customers.




Te team works with the spreadsheet version o the revenue model to explore different

configurations and/or strategies that can increase revenue without impacting the cost

structure or the Customer Value Model. Revenue model variables that can be manipulated

include, but are not limited to:

Pricing mechanisms

Payout mechanisms

Customer incentives

Accessory products

Accessory services

For example, the team can consider ways to increase the number o transactions percustomer, which will effectively increase the number o revenue streams. I the solution is

a service, transactions can be increased by adding an accessory product to the service. I

the solution is a product, transactions can be increased by adding product consumables or

offering accessory services with the product.

An accessory is an add-on to a solution that enhances the solution in some way such as:

Improving how a solution is delivered to customers

Helping customers get jobs done related to consuming the solution (i.e.,

selecting, purchasing, installing, learning how to use, maintaining, upgrading,

etc.).

When accessory solutions are provided by value-added partners, more transactions can

be generated without increasing the cost structure while enhancing solution value. By

running pro orma iterations in the spreadsheet, the team tests the viability o different

scenarios.




Optimize the Cost Side

Te second task involved in optimizing the business model is to reduce the cost structure

without decreasing customer value. Te objective is to minimize the cost structure at

the current revenue level. I critical demand has been achieved, either in Step 8 or byincreasing revenue in this step, then reducing costs even urther will increase value

capture or the company. In such a case, urther reducing the cost structure is an

opportunistic strategy to increase net profit.

I, on the other hand, critical demand has not been achieved, then net profit is still short

o the growth target. I so, the only way lef to hit the growth target is to reduce the cost

structure o the business model. Tis is a deensive strategy because it is the “last ditch

effort” to make the solution viable.

Te advantage o an opportunistic strategy is that reducing the cost structure is optional,

since the solution is already capable o hitting the growth target. Any reduction in the cost

structure is “ound money”. I the situation warrants, the company may decide that it is

better to get the solution to the market rather than spend additional time and resources

implementing cost reduction measures. Alternatively, the company may decide to target

cost reduction opportunities that can be implemented quickly and cheaply.

Te deensive strategy, on the other hand, is not optional. Te company must figure out a

way to reduce the cost structure i the solution is going to be viable. Te more significantthe gap in net profit, the greater the time and costs associated with reducing the cost

structure. Further, risk increases as time to market expands. In general, reducing the cost

structure is not a trivial matter. Tis builds a strong case as to why companies should be

engaged in continual process improvement in parallel with innovation efforts.

With the deensive strategy, the team works backwards rom the required profit margin

to delineate a target cost structure — a method called target costing (see figure 4.9). o

achieve this, the team revisits the various components o the business model such as key

partners (KP), key activities (KA), key resources (KR), customer relationships (CR), andchannels (CH) to better understand how these components drive costs. External actors

that contribute to the cost structure are also considered.




ProfitMargin

CostStructure

RevenueModel

TotalRevenue

RevenueStreams

Business Model Components

KP

[Target] CostStructure

External Factors that Drive Costs

Work Backwards

KA KR CR CH

Operational Constraints & Tradeoffs

GrowthTargetDesired

Net Profit

Figure 4.9: Work backwards to minimize the cost structure.

One strategy or reducing the cost structure is to find ways to re-purpose or otherwise

leverage the company’s existing resources and/or processes instead o dedicating new ones

to the solution business model. Extending existing resources/processes in this way reduces

the cost structure or the solution business model and will ofen result in cost savings in

other areas o the business.

Cost assumptions underlying each o these components should be rigorously questionedwith an open mind. It is too easy to make operational cost assumptions based on dogmatic

reasoning. When these assumptions are carried into the innovation process, they can

severely restrict the possibilities or truly breakthrough solutions. Te bigger the gap in

net profit that must be surmounted, the more radical the thinking needs to be with respect

to the cost structure. In some cases, a company may have to come up with a completely




new concept o operations to make the solution viable. A new operational design might

include using a different channel, establishing different relationships with customers,

different processes, different types o resources, different partners, a new supply chain, etc.

Breaking Key Operational Constraints

Because the business model works as a system, all the components are inextricably linked

together as a whole. wo key concepts o systems thinking are trade-offs and constraints.

Te idea o a trade-off is that as one variable/component is manipulated with the intention

o improving outcome A, this action simultaneously worsens outcome B. Te best that

can be hoped or is to find an acceptable compromise between both outcomes (all things

being equal). Te condition or circumstance that orces a trade-off situation between two

outcomes is a constraint. Te astest and most economical way to reduce the business modelcost structure is to identiy one or two key operational constraints that orce poor value-to-

cost trade-offs. A value-to-cost trade-off is the point where urther increasing customer

value decreases profitability. At this trade-off point, a company is not able to transorm its

resources (people, processes, assets, etc.) into additional customer value without reducing

profitability.

o the extent that a company is able to improve the efficiency o resource-to-value

conversion, it can create more customer value without increasing cost (or even at a

lower cost). A company may be able to break these constraints with a single operationalinnovation (doing something a new way) or a ew operational improvements (improving

the way something is already done). By removing these constraints, a company may be

able to shif the value-to-cost trade-off enough to generate the required net profit to hit

the growth target. Such operational innovations or improvements may also make it harder

or competitors to imitate the business model.

It should be noted that the task here is only to identiy potential operational

improvements that can break value-to-cost trade-offs, not actually to implement them.

Implementing operational improvements is part o the execution phase. Identiyingoperational improvements capable o breaking value-to-cost trade-offs requires close

collaboration with process improvement teams.

A company that has high resource-to-value conversion capability can produce economic

value at a significantly lower cost than its competitors. When the economic value o a






KeyPartners

KeyActivities

KeyResources


Channels

CustomerSegments

[ Maximize ]Revenue Streams

[ Minimize ] Cost Structure

ValuePropositions

Revise/Refine

Desired Net Profit

Operational Innovationand/or Improvements

May Be Necessary?

?

?

?

?

E x t e r n a l F a c t o r s t h a t D r i v e

C o s t s

?


Decision Gate 2 CriteriaTe purpose o the est/Validate Stage is to put the solution design and the business

model through rigorous reality testing to determine i the solution can meet the growth

target. Each o the three steps in the est/Validate Stage define specific success criteriathat must be achieved i the solution is going to create sufficient value or customers and

enough net profit or the company. We think o each step as a success filter that provides

the eedback necessary to make one o three strategic decisions:

Advance the project to the next step

Iterate through previous steps until the solution does meet the criteria

Abandon the project

In Step 7 (the first success filter), the team validated that the utility value o the solution

is high enough relative to other competitive offerings. Tis is the success criterion or

Step 7. Te validation o utility value means that the prioritized desired outcomes were

effectively translated in the design unnel to solution characteristics (eatures, content,

and/or processes) within the boundaries o the business model and available technology/




resources. Te success criterion or Step 7 cannot be deerred. I solution utility is not

sufficient, this cannot be “fixed” in subsequent steps. With weak utility value, there is no

point in continuing orward, because the solution will surely ail.

However, a high level o relevance and sufficient intrinsic value still does not guarantee

that enough customers will buy/use the solution to make it a success. In Step 8 (the second

success filter), the team validated that the solution is capable o attracting the critical

demand needed to generate the desired net profit, which is the success criterion or Step

8. Validated critical demand confirms that the solution offers customers enough value

surplus to create a preerence or the company’s solution over the competitive offerings.

I critical demand was not validated, there may be enough demand that the company can

potentially compensate or the shortall in net revenue by optimizing the business model.

In this case, the company may have decided to move orward on a provisional basis toexplore business model optimization. In this case, the success criterion or Step 8 can be

deerred to Step 9, because there is nothing to be lost in trying.

In Step 9 (the third and final success filter), the team identified ways to maximize revenue

and minimize costs, thereby optimizing the business model. I the solution ailed to

achieve critical demand in Step 8, then the mandatory success criterion or Step 9 is

that the solution must be capable o generating the desired net profit. I the solution did

achieve critical demand in Step 8, then the preerred success criterion or Step 9 is to

exceed the growth target by increasing revenue and/or decreasing the cost structure viabusiness model optimization. Once a solution/business model passes through all three

success filters, this indicates that the solution is capable o hitting the growth target.

Beore the team can proceed to Stage 4, the project must pass through Decision Gate 2.

Te team will present their findings to management in the orm o a brie report and/or

a short presentation. Te decision criterion or Decision Gate 2 is that the product/service

innovation is capable o hitting the growth target. Based on the evidence presented by the

team, management will then make the final decision to allow the innovation project to

move to Stage 4.




ExecutionTeams


Design Solution


Strategy & Plan













Viable

BusinessModel


OptimizedBusiness

Model

Creation

Gate1

Gate2

Gate3

Leadership

Culture

KnowledgeCreation

GrowthTarget

ExecutionPhase


Design Solution


Strategies













Viable

BusinessModel


OptimizedBusiness

Model

Gate1

Gate2

Knowledge

Leadership

Culture/Teams

Creation

Gate3

DEVELOP EXECUTION

STRATEGIES

4STAGE :





109SAGE 4: DEVELOP EXECUION SRAEGIES

Step 10: Resolve Ecosystem Constraints

Getting the Ecosystem Blueprint Right

Te team first developed the ecosystem blueprint in Step 3, along with the viable businessmodel (see figure 5.1). At that time, the team may have identified co-innovation risks and/

or adoption chain risks that will become a serious impediment to commercializing the

solution i lef unresolved. It could also be the case that the team has not ully developed

an ecosystem blueprint, because the primary ocus up to this point in the methodology

has been on the solution design, solution adoption by the end customer, and the business

model. In any case, it is paramount that the team ully develops the ecosystem blueprint,

identifies all constraints, and then develops a strategy or resolving these constraints prior

to the execution phase o the project.

Supplier 1

Supplier 2

INNOVATIONPROJECT

Intermediary 1 Intermediary 2 End Customer

Supplier toComplementor 1

Supplier toComplementor 1

Complementor 1Supplier to

Complementor 2Complementor 2

G

Y

G

G

R

G

G

YG

G

Figure 5.1: Ecosystem blueprint showing dependency constraints.

Unresolved ecosystem constraints will significantly increase the risk o ailure. Unortunately,

many companies do not recognize these ecosystem constraints, and they pay the price

when they go to launch a new solution. Te post mortem on many innovation ailures

has shown repeatedly that huge allocations o resources and talent are not enough

to surmount these ecosystem constraints; they will bring even the best innovation

project to its knees. Te tragedy is that much o the time, these constraints are relatively

straightorward to identiy and resolve. For example, i a company’s value proposition

requires multiple partners to collaborate, developing a deep understanding o thestructure o collaboration in the ecosystem is critical to the success o a new product/

service innovation.

Developing an ecosystem blueprint is an exercise in team discipline, because it challenges

the team to be explicit about the all the steps required to ulfill a value proposition to end






Probability ofSuccess 84%




JointProbability of

Success ~ 50%

Co-Innovation BCompany's

Innovation ACo-Innovation C Co-Innovation D

InnovationProject

Figure 5.2: Co-innovation and joint probability of success.

Now say that one o these co-innovation partners is responsible or a challenging part

o the innovation project and that the partner’s probability o success is estimated to

be around 20%. With just one partner having a low probability o success, the joint

probability o success or the innovation project tumbles to 0.84 × 0.84 × 0.84 × 0.2,

or about 12%. In the case where one or more partners may diminish a company’s joint

probability o success, there are our ways to resolve these kinds o constraints:

Option 1 — Add resources to bolster the partner’s development effort. Why should a

company help out a partner in this way? Allocating resources to reinorce a weak link

in the ecosystem can have a much greater impact on a project’s success than urther

reinorcing the company’s own internal efforts. For example, a 10% increase in a

company’s odds o succeeding individually (rom 84 percent to 94 percent) may reduce

risk anxiety, but it improves the joint probability by only 2% (rom 12% to 14%). In

contrast, improving a partner’s odds o success by 10% (rom 20% to 30%) changes the

joint probability by 6% (rom 12% to 18%). Tese odds may look low, but the innovation

project is one and a hal times more likely to succeed than in the previous scenario. In










shifing existing elements to new positions in the ecosystem?

Are there elements that can be added? Can the constraint(s) be resolved by

adding new elements to the ecosystem that are currently absent?

Are there elements that can be subtracted? Can the constraint(s) be resolved byeliminating existing elements?

SEPARATE

Are there currentlycombined elementsthat can be effectivelyseparated?

COMBINE

Are there currentlyseparated elementsthat can be effectivelycombined?

SUBTRACT

Can viability beincreased by removingelements withoutaffecting value?

ADD

Can elements beadded that couldfacilitate productivenew connections?

RELOCATE

Would elementsbundled in one bebetter bundled in adifferent location?

Re-ConfiguredEcosystem Blueprint

with ConstraintsEliminated

Figure 5.4: Ecosystem re-configuration as a way to resolve dependency constraints.

A good ecosystem blueprint structures elements in a way that minimizes co-innovation and

adoption chain risk. Because uncertainty is inherent in any innovation project, risk per se

cannot always be eliminated. In the ecosystem context, the objective o reconfiguration is

to shif risk to other elements where it can be better managed.






Step 11: Develop Operational Change Model

Operational Design as a Critical Success Factor

I the innovation project has cleared Decision Gate 2, then the odds o success are quitehigh, i the project can be executed effectively. Stage 4 is about developing execution

strategies to successully commercialize the growth opportunity. o do this, two things

need to happen: 1) the solution must be ully developed (all we have now is a prototype),

and 2) the solution business model must be executable. Te plan or developing the

solution will be addressed in Step 12. Te task or Step 11 is to design an operating system

that can effectively execute the solution business model.

At this point, the solution business model is a design, not an operating business model. An

operating business model is unctional. A business model design, on the other hand, is notunctional because there is no operating system to make things happen. o commercialize

the solution, an operating system will first have to be developed.

Tere are two possible scenarios. First, i the solution business model is to be a stand-

alone company or a business unit within a parent company, then an operating system will

need to be in place beore it can be executed. Second, i the solution business model is to

be executed via the company’s operating business model, then the operating system will

need to be changed/extended to make this possible. Tis second scenario is more complex,

because the solution business model must be integrated into the current operating model.Tis can be challenging, because the differences between these two business models have

to be resolved at the operational level. In either case, an operating system is required to

execute the solution business model.

When a viable business model was first developed in Step 3, the team replicated elements

rom the company’s operating business model required or the solution business model.

As the team moved through the AVID process, they may have added new key activities,

new key resources, new supplier and partner relationships, new customer relationships,

and new channels that do not exist in the operating business model. Further, the teammay have identified things in the existing operating system that need to be modified/

improved to accommodate the solution business model. For example, an operational

innovation or improvement may have been identified that can break a key constraint,

significantly reducing the cost structure. At this point, however, all o these additions

and modifications exist at the design level. o make the solution business model a reality,




the team must descend into the company’s current operating system to determine what

needs to be changed and how to implement these changes. Because a company’s operating

system is complex, there are many different ways o going about this; some ways are better

than others.

It is not unusual to see a company develop a high potential innovation only to all down

on execution. Many companies do not ully appreciate the critical role that an operating

system design plays in the commercialization o a new solution — it can make or break

any growth project . ypically, operational considerations are dealt with during the

execution phase o the project. When this happens, the best way to execute the solution

business model becomes obscured, because execution teams are ofen not aware o

the details o the solution business model design. It is also difficult to execute while

simultaneously trying to discover the best way to execute. Tat is, execution teams areofen not looking or the best way to execute, but rather the path o least effort. For this

reason, the operational design required to commercialize a new solution business model

needs to be part o the discovery phase, not the execution phase.

In the end, a good operational design will make execution go much aster and smoother,

significantly reducing costs and risks. It is interesting to note that we ofen think that it

is the solution that is commercialized when, in act, it is really the business model that is

commercialized. Te business model is what ultimately ulfills the value proposition to

customers and captures value or the company. Te solution is part o the business model.At the end o the day, it is the operating system that determines how well a solution

business model will work.

Exploiting Operational Synergies

Exploiting operational synergies is an important aspect o commercializing a solution

business model, yet it is commonly overlooked. Ideally, the uture operating business

model will perorm better than the operating business model with a new solution merely

bolted to it. Te idea o operational synergy is that an innovation will improve overallperormance beyond what a solution business model would do i it were a hypothetical

startup. Operational synergies can significantly enhance value capture by reducing the cost

structure and increasing asset utilization or the whole company.

One way to do this is to find opportunities to increase economies o scale. Te basic idea




o economies o scale is that the cost o some item is reduced as more volume o that item

is produced/purchased. Te new solution business model will likely require investments

in fixed assets. Te costs o these assets can be lowered i they can be shared across

more transactions or uses. Tus, the team should look or ways that the new assets canbe exploited by the current operating system. Another benefit is that the more o these

assets that are used across the business, the greater the financial return on investment via

increased asset utilization.

Te team should also look or opportunities to increase economies o scope. Te

concept o economies o scope reers to the efficiencies that result rom producing/

offering multiple products/services rom the same source/process(s). Economies o scope

enable a company to offer a wide variety o products/services to its customers while

incurring relatively little additional costs. Tis means that a company can offer customersproduct/services at a lower cost and capture more net profit at the same time. Increasing

economies o scale and scope via operational synergies also makes the business model

more difficult or competitors to imitate.

Operational Change Model

Te adage that the “devil is in the details” is on point when it comes to designing an

operating system to commercialize a solution business model. Companies commonly get

snagged during the execution phase on operational issues that jeopardize the viability o anew product/service innovation. Common snags include:

Te additional costs and capital investments required to execute a solution

business model are not accurately quantified.

Te time and effort involved in changing/extending the current operating

system is underestimated.

Te changed/extended operating system does not effectively execute the

solution business model.

o overcome these potential pitalls, the team develops an operational change model

(hereafer reerred to as simply a change model). A change model is a strategic blueprint

and action plan that delineates the best way to change/extend a company’s existing

operating system to effectively execute a solution business model. A change model gets








We distinguish two general categories o resources:

Resources that are directly exploited/converted by a process to produce

outputs (resources). Resources that pass through a process without being directly exploited/

converted (stocks).

A company’s supply chain provides access to these resources when, where, and how they

are needed.

Working knowledge is an integral component o a process that provides the “know how”

to perorm the activities that comprise a process. A process exploits working knowledge to

unction, but new working knowledge can also be generated rom exploiting the process(organizational learning). Without working knowledge, a process cannot unction any

more than a car can unction without a transmission or on-board computer. Knowledge

ultimately determines the efficiency with which a process can produce critical-to-quality

outcomes (CQ’s). CQ’s are the process outputs required to satisy desired customer

outcomes. Tat is, CQ’s connect customer needs to what the process is producing

(outputs). A company’s processes together with the associated working knowledge

comprise a company’s operational capabilities. A company builds relationships with

partners to leverage some aspect o a partner’s operational capabilities to augment their

own capabilities.

Developing An Operational Change Model

Te entry point to developing a change model is to start with the key activities on the

solution business model. Key activities are abstracted on the business model canvas

because the ocus is on the big picture — the design view. Te team will now work

backwards rom each key activity through the basic operating system concept to

develop the operational inrastructure required to perorm each key activity. Te team

systematically asks a series o questions that guides the development o the change model.




For every key activity that will be perormed by an existing process, the team asks:

What existing process will perorm the key activity?

What are the CQ’s required o this process to effectively perorm this keyactivity? What is the priority o the CQ’s? Are there any CQ’s that can be

phased in at a later time?

Is the existing process capable o these CQ’s? (Te team captures process

perormance measures to make this assessment.) I the process is not capable,

what changes, operational improvements, and/or resources need to be added/

implemented to make the process capable? (Te team develops a simplified

charter or each change/improvement. Te team also develops a simplified

business case or new resources, using reverse financials. Tey estimate

lead time and costs associated with each change/improvement and/oradditional resources. Tey update reverse financials to capture additional costs

and capital investments.)

Are there any opportunities or operational synergies? (I so, the team develops

a simplified business case and updates reverse financials.)

Does the company have the necessary working knowledge to perorm the

key activity via the existing process? I not, what learning needs to occur or

what training needs to be delivered to remedy the knowledge gaps? (Te team

estimates time and cost associated with learning/training events. Tey developa simplified training mandate. Tey then update reverse financials.)

Does the company need to bring in a partner to augment its operational

capabilities to perorm the key activity? What are the critical success actors

or each partner relationship? (Te team develops a simplified business case or

each partner relationship. Tey update reverse financials and the innovation

risk profile.)

Does the existing process have enough capacity to effectively perorm the

key activity? I not, what resources need to be added to sufficiently increase

this capacity? I additional resources are needed, will this require any changes

to the supply chain? (I so, the team develops a simplified business case or

each instance. Tey update reverse financials.) Does capacity need to scale in

the uture? (Te team develops a simplified pro orma business case.)




For each new process that is to be created the team asks:

What are the design parameters o the new process that will meet the CQ’s

or the key activity(s)? What is the time and cost o creating this new process?(Te team develops a simplified charter and updates reverse financials.)

What existing resources will be used by the new process? What new resources

will be needed by the new process? Will new resources require any changes

to the supply chain? (Te team develops the business case and updates reverse

financials.)

Are there any opportunities or operational synergies? (I so, the team develops

a simplified business case and updates reverse financials.)

Does the company have the necessary working knowledge to design/perorm

the new process? I not, what learning needs to occur or what training needs

to be delivered to remedy the knowledge gaps? (Te team estimates the time

and cost associated with learning/training events. Tey develop a simplified

training mandate. Tey update the reverse financials.)

Next, the team then ocuses on the key resources required to execute the solution business

model. For each key resource, the team asks:

What is the key activity and underlying process that will use the resource? How will the process use the resource?

Will the resource be shared or dedicated?

What are the critical actors or the resource to work well with the process?

Does the resource have too much or too little specialization?

Will there be any changes to the supply chain?

Are there any conditions or limitations involved in using the resource?

Are there ways to increase the utilization o the resource across the operating

system?

Can the resource be ully utilized with the current working knowledge?

Using the basic operating system concept, the team proceeds to use this same technique

or key partners, customer relationships, channels, and revenue streams.






Identify Growth Opportunity

Design Solution

Test/Validate

Develop Execution Strategies

Target Value Space Compelling Value Proposition Viable Business Model

Customer Outcomes Customer Segments Optimal Solution Design

Optimized Business ModelValidated Utility Value Validated Critical Demand

Resolved Ecosystem Constraints Operational Change Model Final Deliverables

� � � �

Figure 5.6: Innovation storyboard (war room).

It is important to capture the innovation journey while it is still resh in everyone’s mind

so that others in the company can:

Understand the original context o the innovation

Re-enter the discovery phase or the project in the uture i needed

Vicariously learn rom the team’s experience

Apply knowledge acquired to uture innovation projects

Te task or the team is to create an innovation storyboard presentation that documents

the team’s journey through the AVID process, which will take the orm o a PowerPoint

presentation (see figure 5.7).

Each section o the presentation should correspond to a step in the AVID methodology.




Te objective is not simply to explain the artiacts generated during the discovery process.

Rather, the objective is to capture the investigation as it unolded. Te presentation should

tell a story o how, afer some number o iterations, the team acquired the final value

targets. Artiacts will, o course, be a part o this story, but the emphasis is more on the journey than on the destination. Te storyboard presentation should be about 50-60 slides

— about 4 slides or each o the 12 steps in the AVID process. Pictures and/or service

maps o the solution prototype should be included, along with any visual marketing

materials. Any multimedia, like animations and movies, should be embedded in the

presentation as well. At the end o the presentation, the team should include key lessons

learned that they believe would be helpul to pass along to uture innovation teams.

Figure 5.7: Storyboard presentation.

A good storyboard presentation should enable an individual with no prior exposure to the

project to understand the discovery phase context in 30 minutes or less. Te storyboard

presentation is a knowledge transer tool that acilitates continued learning or all involved

in the execution phase o the project and helps to accelerate learning in uture innovation

projects.




Execution Hand-offs

Te team will prepare execution hand-offs or management and various other

departments within the company that will be involved in the execution phase o the

project. Specifically, execution hand-offs will be prepared or:

Management/administrative unctions

Product development/engineering

Sales and marketing

Various operational departments

While the storyboard presentation is about the discovery phase context, the execution

hand-offs are the final artiacts o the discovery process. ogether, the storyboardpresentation and the execution hand-offs are a complete set o deliverables — the outputs

and the context in which these outputs were generated.

Te execution hand-offs are intended to be actionable or those receiving them.

Specifically, the hand-offs are:

Management — Final reverse income statement and balance sheet, final

ecosystem blueprint with constraint resolution strategies, and final innovation

risk profile. Solution Development/Engineering Hand-offs — solution design parameters,

final prototype, and resources/technologies specifications.

Sales & Marketing — customer segments and segmentation criteria, job

statements, target job map with prioritized desired outcomes or

each customer segment, competitive solutions analyses, categorized customer

eedbacks, marketing materials developed (web sites, brochures, multimedia,

etc.), solution sales road map, and customer sales presentations.

Operational Departments — changes to operational systems, operational

improvements or breaking constraints, cost targets, and customer CQ’s.





Te storyboard presentation and all execution hand-offs will be presented to management

or Decision Gate 3 evaluation. Te purpose o Decision Gate 3 is to confirm that the project

is ready or the execution phase. Decision Gate 3 criteria include evaluating the answers tothe ollowing questions:

Is the ecosystem blueprint complete? Have all ecosystem constraints been

identified and categorized as either moderate or hard stop constraints?

Does the team have an effective strategy or resolving these constraints? I a

new ecosystem must be developed, does the team have a good strategy

or ramping up and scaling this new ecosystem?

Has a complete operational change model been developed? Did the team

include others with a deep knowledge o operations and process improvementin the development o the change model? Does the change model ully

leverage the company’s existing resources and capabilities? Have opportunities

or economies o scale and scope been identified? Does the change

model include well-ormed customer CQ’s? Does the change model

identiy any operational improvements that can be done relatively

quickly and easily? Does the change model include sufficient detail so

that the hand-offs will be actionable or execution teams? Can the

change model be implemented within the time window required? Can the

change model be implemented within the defined budget or the project?

Is the storyboard presentation complete and coherent? Tat is, can someone

who was not on the innovation team grasp, in 30 minutes or less, the entire

discovery process the team journeyed through? Does the storyboard

presentation include key lessons learned?

Are the execution hand-offs complete and organized properly? Are the hand-

offs actionable?

Based on the quality o the aorementioned evaluation criteria, is the

innovation project ready to advance to the execution phase?




A Contemporary Best Practice or Value Innovation

Te AVID methodology offers a better way to structure the discovery phase or value

innovation projects (and radical value extension projects) where uncertainty obscures

value targets. With the AVID methodology, companies can consistently generate valuetargets or lucrative growth opportunities in less time and with less risk than conventional

methods. When used on the ront-end o a traditional phase/stage gate methodology,

many o the steps and decision gates in the execution phase can be eliminated. Execution

goes much aster and more smoothly because the value targets have already been defined

in the discovery phase. Specifically, the testing/validation stage and the subsequent

decision gate in the execution phase are no longer needed, because the solution design

has already been empirically validated in the discovery phase (see figure 5.8). Further,

execution teams can be working in parallel with one another — each receives execution

hand-offs rom the discovery phase that make the value targets actionable or them. Tatis, various management/administrative unctions, product development/engineering,

sales and marketing, and operational departments can all be working on their part o

the execution plan at the same time. Tus, AVID and a streamlined phase/stage gate

component decrease the time to market or new products/services by compressing the

total lead time o the process.

Streamlined

Discovery Phase

Stage5

Stage6

Gate4

Development Launch

Go toLaunch

Execution Phase

Stage1 Stage2

Stage3Stage4

G1

G2G3

Stage1

Stage2

Stage3

Stage4

Stage5

Gate1

Gate2

Gate3

Gate4

Gate5

Ideas

Stage0

IdeaScreen

Scoping

SecondScreen

Build

Business Case Development

Go toDevelopment

Go toTesting

Launch

Testing &

Validation

Go toLaunch

Old Way

Better Way

Less TimeLess CostLess Risk

More Profitable

Figure 5.8: Contemporary best practice for value innovation.









About The Author

APPENDIX



135APPENDIX

About the Author

Dr. Michael S. Jordan is an experienced business executive, entrepreneur and innovator

who has started, bought, sold and merged companies. He has been the CEO o severaltechnology companies and a technology startup that raised 8 million in venture capital

unding. What makes Michael unique is that he is a balance between the “science” and the

“practice” and is well known or his ability to translate complex concepts in a way that can

be easily understood and applied (with a sense o humor).

Michael is the ounder and managing partner o INNODYN, an Atlanta-based firm that

specializes in business growth development. Over the last 15 years Michael has consulted

companies o all sizes in a variety o service and manuacturing industries on operational

excellence, product/service innovation and business growth strategies.

Michael’s recent interest has been developing the Dynamic Growth System, a strategic

entrepreneurship approach that enables any organization to sustain double-digit growth

in today’s complex and ast moving business environment.

In addition to his work with INNODYN, Michael is an instructor at the Robinson College

o Business at Georgia State University where he teaches courses in technology innovation

and entrepreneurship.

Michael received a Doctorate and an M.B.A. rom the Robinson college o Business at

Georgia State University and a B.S. rom he University o Georgia. Michael is a Certified

Lean Six Sigma Master Black Belt.



Documents

Strategic Value Innovation