Taking an ‘Intelligent’ Approach to Revenue Growth ...poinstitute.com/wp-content/uploads/2017/11/TakinganIntelligent...Management Matthew Campbell, Managing Director Accenture

Taking an ‘Intelligent’ Approach to Revenue Growth Management

Matthew Campbell, Managing DirectorAccenture CG&S Digital Customer Transformation

EVERY BUSINESS WILL EXPERIENCE

SOME FORM OF DISRUPTION

ENTIRELY NEW MARKETS OR CHANNELS

SMARTER, FASTER DECISION MAKING, AT SCALE

BREAKDOWN OF TRADITIONAL CONVENTIONS

Copyright © 2017 Accenture. All rights reserved. Accenture Confidential Information |

WHAT’S HAPPENING RIGHT NOW

CPGS NEW NORMAL

Growth among top 50 CPG brands has eroded

Consumer purchase decisions are increasingly influenced online; yet trade promotion spend has doubled since 2000, representing 15-30% of revenue

CPG share of in-store space has been reduced as private label has grown 23%

Digital and mobile are fueling consumer transparency and online competition

* Nielsen Breakthrough Innovation Report June 2016; food and beverage manufacturer analysis.

45% 3% 23% 25% 49%TOP 25 CPG* TOP 25 CPG PRIVATE LABEL TOP 26-100 CPG 101-20,000 CPG

OF CATEGORY SALES OF CATEGORY GROWTH OF CATEGORY GROWTH OF CATEGORY GROWTH OF CATEGORY GROWTH


Rules of the game have changed and will continue to change faster than ever before

OWNED / M&A PARTNERSHIPS

MASS APPEAL

MARKETING

PERSONALIZATION,

CURATION &

AUTHENTICITY

SCALE,

EFFICIENCY &

STANDARDIZATION

AGILITY &

AUTOMATION

COMPLEX

WORKFORCE

WHAT ARE THE CLEAR

IMPERATIVES

OPERATING MODELS

NEED TO EVOLVE

PARTNERSHIPS &

ECOSYSTEMS

FASTER BRAND

LIFECYCLE

MULTIPLE BUSINESS

MODELS

Vs.

Vs.

Vs.

NEW DRIVERS OF GROWTH FOR CPG



End to End Experience,

Personalization &

Customization

Business

models shaped

by level of

engagement

Data and

predictive

analytics

Omni-channel platforms

accelerate aided by

digital assistants

Stores shrink and become

experience driven

Manufacturing

transformation

The workforce

becomes liquid

and augmented

Product

democratization

Marketing E2Me

Ecosystems and

supply chain co-

operation

DATA & ANALYTICS ARE PIVOTAL TO CONSUMER

GOODS MANUFACTURER SUCCESS

What We are Seeing Across Industries:

Data, Technology, Analytics, and Organization

Pace of Technology Innovation

Embedded Analytics(Analytic “Apps”)

Immersive Analytics Environments

New data sources and technology trends…

Rise of theMachines

New Data Sources(e.g., Social, IOT)

The “Agile” Analytics Operating Model

Experience Design Led(Analytics Marketplace)

New Delivery Models(Pod Teams, Cloud)

Fit for PurposeTechnologies

Emphasis on changing the “Cultural DNA”

…leading to new ways of enabling analytics and driving adoption.


TRENDS & PREDICTIONS


Copyright © 2017 Accenture All rights reserved. |

DATA

DATA EXPLOSION DATA COMPLEXITY

DATA MONETIZATION DATA & DESIGN THINKING

Big data was characterized by an explosion of data. Now, in addition to big data volumes, we are seeing an explosion in the number of data sources and the speed of data.

Companies are realizing the economic value of their data and are making strategies to directlyor indirectly monetize it.

The number of data formats is growing, from unstructured data such as images and audio/video to IoT. The ability to capture and act on multi-speed data is a core requirement for next-gen analytics.

Driven by Data Explosion, Complexity and Monetization, businesses arere-designing business processes with-and-for data to provide points of action rather than just points of information.All of which is enabled by data.

“By 2019, 75% of analytics

solutions will incorporate 10 or

more exogenous data sources from

second-party partners or third-party

providers”

“By 2018, 90% of deployed data

lakes will be useless as they are

overwhelmed with information for

uncertain use cases”

“By 2020, 10%

of organizations

will have a highly profitable

business unit for productizing and

commercializing their information

assets”

“This isn’t just about providing

employees with an iPad-controlled

dashboard with a glut of data.

It is about creating points of action

instead of points

of information”

Fjord


ORGANIZATION

ANALYTICS COE RISE OF CAO/CDO

WAR FOR ANALYTICS TALENT

Shift from business intelligence competency centers to analytics centers of excellence that no longer report directly into IT.

Inability to source, develop, grow, andretain advanced analytics talent. Plus analysts are spending more timegathering data doing analysis.

Companies are beginning to build entire business units focused on analytics with senior representations reporting directly into the c-suite.

“Gartner has noted that the number

of CDOs has grown from 15 in

2010 to over 1400 in 2016”

By 2018, 75% of technology-

oriented BICCs will have evolved

into strategy-oriented analytics

centers of excellence

“On average, there are 160

resources in the analytics

organization and 43% of

companies expect that number to

increase moderately over the next

3 years”


ANALYTICS

COGNITIVE COMPUTING DATA DISCOVERY

INSIGHTS MARKETPLACE REAL TIME ANALYTICS

Computer inherently building a human brain that moves from a storage device to abilities of self-learning, data mining while instant pattern recognizing capability.

Development of Amazon-like enterprise insights marketplacefor users to consume and exchange insights through one unifying channel.

Rapid exploration of data to identify patterns out of large pools of data (using Big Data concepts).

Moving from looking at historical results to a continuous feed of data which allow to support artificial intelligence.

“According to Gartner, 40% of

organizations currently have

adopted some form

of data discovery; this will grow to

55% by 2020”

“By 2018 half of all consumers will

interact with services based on

cognitive computing on a regular

basis”

“By 2018, 50% of agent

interactions will be influenced by

real-time analytics”

“By 2020, 30% of enterprises will

use a Data as a service(DaaS)

approach to provide consistent, on-

demand and reusable data

delivery”


TECHNOLOGY

HYBRID ECOSYSTEM OPEN SOURCE

CLOUD & AS-A-SERVICE NEW IT

Industrializing and scaling analytics solutions requires Hybrid Architectures that integrate the strengths of big data tools and tech with the strengths of traditional and pre-existing systems.

Cloud & As-a-Service providing the means to quickly and easily trial new solutions without paying the high-entry and/or -effort toll that characterized on premise solutions.

The advent of cheap storage, high-speed networks and world-wide communication has driven a renaissance of software development, allowing companies to use cutting-edge software for free.

Technology has become the business. The world’s fastest growing companies leverage technology to deliver their products at previously impossiblespeeds and costs.

“By 2016, at least 25% of the major

advanced analytics vendors will

offer functionality via analytics

open source software

communities”

“More than 10% of enterprises

have some form logical data

warehouse (LDW) architecture,

and it has emerged as the primary

enabling architecture to support

bimodal demands on data

management for analytics”

“By 2017, fewer

than 50% of IT organizations

will have tried to

put a bimodal IT organizational structure in

place; half of them will struggle through

multiple attempts before reaching

a working state”

“By 2019, 14% of

BI software will

be deployed in

a SaaS model”

The age of intellectualand human empowerment.


TRANSFORMCORE

BUSINESS

APPLYING INTELLIGENCE

to

UnTRAP VALUE

TRAPPED VALUE

EXPAND

MARKET SHARE

ACCELERATE

TIME TO MARKET

DRIVE INNOVATION

AGENDA

INCREASE

REVENUE

REDUCE COST

TO SERVICE

PIVOT TO THE NEW


HOW WE APPLY INTELLIGENCE

INTELLIGENT SOLUTIONS

CREATE NEW CULTURE

OPERATE WITH NEW AGILITY

DEFINE NEW OPPORTUNITIES

UNTRAPNEW DATA

DISCOVER WITH NEW SCIENCE


NEXT GEN INTELLIGENT REVENUE MANAGEMENTPOWERED BY ARTIFICIALINTELLIGENCE

Backward Performance Tracking. Focused on few Top Customers and Competitors

Actionable predictive insights at a granular level to drive action

Siloed view, leading to a lack of collaboration among Finance, Sales, Account teams and Marketing (and different sources of truth)

Use the same Math/Statistics to drive transparency across the organization

Commercial plans (e.g., price and promotion) not cascaded timely to the field

Actionable target and timely communication with the Field Reps using simplified visualization and Execution tools

Limited and/or aggregated data More granular data (POS) and new data sources (e.g., social, demographic, macroeconomic trend) with higher signal value

Challenges to scale “One” cloud based open architecture powered by artificial intelligence and advanced analytics to achieve a single version of the truth

TRADITIONAL REVENUE MANAGEMENT

INTELLIGENT REVENUE GROWTH SOLUTIONS


INTELLIGENT REVENUE GROWTH: TRANSFORM TO LEAD WITH INSIGHTS

SFA, TPM, E-COMMERCE TOOLS

ANALYTICS INSIGHTS

Analytics

bring the insights

PLANNING

Planning

makes it concrete

SALESEXECUTION

Sales Execution

puts it into action

INSIGHTS PLATFORM

Technology integrates

and articulates

INSIGHTS TOWER

Processes and people

support the process

INSIGHTS TO ACTIONS

FEEDBACK FROM MARKET



INTELLIGENT REVENUE GROWTH: TRANSFORM TO LEAD WITH INSIGHTS

StorageValidated, Analytical Storage

VisualizationSelf-service Analysis visualization

Analytics ApplicationsScenario Prioritization

CloudCloud infrastructure & Security

Data Sources

Advanced Analyticsbuilding blocks for modelling &

processing analytics applications

Data Ingestion Data capturing & Integration

Few Key Business Users, responsible

for decision making

Wide Biz Users group, focused on

execution & progress monitoring

Data Scientists and analytics modelers

Granular DATA – Data Lake & DWHCleansed, Harmonized, Certified for Analysis

& Advanced Analytics and Raw data

Decision Support – “So What ?”embedded predictive and optimized recommendation

Analysis, Reporting & CommunicationNext Best Action and revised Targets

tuned by decision makers above

WHAT IS IT, HOW IT HELPS? WHO IS IT FOR?

Statistical Models and AlgorithmsLearn cause-effect from multiple historical data and

predict/optimize future effect

Designed with business logic insight, it’s

then an automated process, …

… managed by IT specialists…

….on the Cloud

Data Acquisition ToolsetsTraditional ETL for structured data

Flex Ingestion/Streaming for unstructured data

Cloud Technical InfrastructureProvides the technical environment for all

components above, with Flexibility in sizing, usage &

Security

Bu

sin

es

s

Us

ers

Da

ta

Sc

ien

tis

t

Au

tom

ati

c

Da

ta M

an

ag

em

en

t

Se

rvic

es



Intelligent Industry solutions for CPGnot a single intelligent APP, BUT an integrated SET OF INTELLIGENT SOLUTONS IN A COMMON “APP STORE”

CPG Data

and

Ingestion

Templates

Advanced

Analytics for

CPG Business

CPG Business

User Experience

in Decision

Making

DATA SOURCES

TRANSFORMATION

intelligent BRAND BUILDING

with Consumers & Shoppers

intelligent REVENUE GROWTH

on Trade Channels

intelligent SUPPLY CHAIN

integrated & connected

Granular QUALIFIED Analytic Data Storage

DATA LAKESTAGING , STREAMING, CLEANSING, HARMONIZATION

Sales

Force

Automation

Trade

Promotion

Management

“External Data”Retailers (ePos),

Syndicated, etc.

ERPeCommerce

/ Digital Data

Social Media

Behavioral

Data

IoT Sensors (e.g

Equipment)

Marketing

Campaign /

Loyalty

Insights to Action(targets)

Approved Decision(Plans)

DecisionOutput

iApp 1 iApp niApp 2 … iApp 1 iApp niApp 2 … iApp 1 iApp niApp 2 …

Dat

a to

Info

rmat

ion

Info

rmat

ion

to

Insi

ghts

Insi

ghts

to

Biz

De

cisi

on

s

UNTRAPNEW DATA


Run & Operations

(Reporting)

Delivery Governance

Analytics Pod

(Data Science)

I&A Factory

(scaling analytics)

Focus: repetitive reports/ dashboards• Infrastructure operations• User support• Application operations

• Use Case Governance• Value Tracking / Measurement • Project Management

Focus: problem of the day• Data integration• Analytics modeling• Visualization• Prove value

Focus: ongoing questions/ industrialization• Automate capabilities• Model tuning• Independent certification

• Delivery Management• Implementation Planning• Branding & Communications

Business/ Functional Teams

Sales

Innovation

Marketing

Strategy

Business Stakeholders Agile Analytics Organization

Insights & Analytics Requests

Analysis and Recommendations

Focus: business need• Identification of use cases • Identification of business

questions• Prioritization of use cases Technology (IT + Accenture)

The end state delivery model will

provide a combination of exploratory and

factory services to serve a variety of business users at

scale

Agile Analytics Services

&

Copyright © 2017 Accenture All rights reserved.

ANALYTICS LAB TO FULL OPERATION MODEL

DISCOVER WITH NEW SCIENCE

Copyright © 2017 Accenture. All rights reserved. Accenture Confidential Information | 21

New Ways of Working

TREND 1

Augmenting the

Workforce through

Robotics/AI

TREND 4

New Pools of Talent

TREND 2

Focusing on Workforce Experience

TREND 3

Workforce of the Future

FUTURE OF TALENT

CREATE NEW CULTURE

https://www.youtube.com/watch?v=dO5SKYF3iWE

TO TRANSFORM TO A DIGITAL ENTERPRISE COMPANIES NEED A CULTURE THAT INSPIRES DIFFERENT BEHAVIOR.

Kill linear

processes and

break down

walls

Orient around

customer

outcomes

Assemble and

disassemble

“modular”

capabilities

Stake claim and ID

new partnerships

in ecosystem

Innovate and

fail fast

Expand role of

COO (architect

the modular

processes)

Expand role of

CHRO and CFO

for business

outcomes

Insert new

technology and

liquid workforce to

increase speed,

responsiveness

OPERATE WITH NEW AGILITY


THANKYOU!

Documents

Taking an ‘Intelligent’ Approach to Revenue Growth ...poinstitute.com/wp-content/uploads/2017/11/TakinganIntelligent...Management Matthew Campbell, Managing Director Accenture