Designing a Program that Increases Your Intelligent ... · Broader Process Evaluation Robotic Process Automation Virtual Agents and Chatbots Artificial Intelligence Level of Adoption

Copyright © 2018 ScottMadden, Inc. All rights reserved.

Designing a Program that Increases YourIntelligent Automation “Velocity”

Intelligent Automation Week

Chicago

July 30, 2018


ScottMadden Areas of Focus

1


Adding Velocity to Your IA Program

2

Today’s Discussion

Shop for Knowledge

with RPA Pilots

Flip to a Broader IA

Process Evaluation

Expand Digital Vision

across the Enterprise

Paint an IA

Governance Picture

Shopping for Knowledge with RPA Pilot


￭ What types of licenses do I need to buy?

￭ How much RPA scripting can fit on a license?

￭ When should I run RPA applications?

￭ How much will this cost in licenses, training,

communications?

￭ How long will it take me get this set up?

￭ Do I need a recording device?

￭ What types of access will I need?

￭ Can robots run on my laptops, or do I need servers?

￭ What level of skill do I need to program robots?

￭ What types of processes lend the most impact?

4

RPA Knowledge Shopping

You Will Learn More from a Pilot than a Conference!

Answers to these questions differ for every company and RPA scenario


Don’t Overanalyze…Just Get Started!

Move through a pilot in four phases:

5


Strong champions are not hard to find

these days

“Thunderous rivers” are more

interesting than “trickling creeks”

You don’t need the perfect RPA

vendor just yet

This will force governance

applicable to broader IA

▪ Find a problem

▪ Find an influencer

▪ “Gut feel” what to fix

▪ Find the team

▪ Introduce the players

▪ Avoid flow charts

▪ Think “volume flow”

▪ Think “batching”

▪ Look for forms

▪ Ask your staff

▪ Path of least resistance

▪ Go get a trial license

▪ Set up environment

▪ Get a few laptops

▪ Find your “scripter”

▪ Document

▪ Train/communicate

▪ Assign roles

▪ Point to production

▪ Showcase and expand

Move into ProductionSelect the Right ProcessDevelop and Test

the BotsFind a Business Partner

Your learning on smaller RPA pilots will be applicable to building out broader IA programs


Find a High-volume Flow…with Lots of Easy Follow-on

6



Automation Potential

More is better

￭ Are there any forms involved in the processes?

￭ What percentage of the process is rule-based (logical if… else… then) steps?

￭ How many applications and data sources does the process need to integrate with?

Less is better

￭ Has this process changed frequently in the past two years?

￭ Does IT make frequent changes to the systems involving this process?

￭ Does your process involve secure data?

7


Also consider business criticality—less critical processes offer less risk but also less “wow” factor to

gain enterprise momentum. Find the right mix for a pilot

Flip to a Broader IA Process Evaluation


You’ve Successfully Completed Some RPA Pilots…What’s Next?

Your options…

￭ Declare RPA pilot victory and quit

￭ Do another pilot, then another…and another

￭ Start randomly pushing to production as pilots become ready

￭ Develop/promote an enterprise-wide program

9

Broader Process Evaluation


Understanding Where to Go from Here

10


Robotic Process

Automation

Virtual Agents and

Chatbots

Artificial

Intelligence

Level of Adoption 55% 10% 5%

Characteristics of

Data Input

Structured, rule driven, static

Structured data, but requirescognitive computing

Unstructured/structured data with hidden patterns

Nature of Ideal

Process Fit

￭ Digital repetitive steps

￭ Rule based/logic driven

￭ Time consuming

￭ Documented

￭ Static rules

￭ Customer interfacing

￭ Requires access to solve?

￭ Multiple languages required

￭ Multiple time zones required

￭ Requires research

￭ Non-routine inquiries

￭ Formula driven

￭ Requires pattern anddetailed analysis

Process Candidate

Examples

￭ AP/AR management

￭ Billing and invoices

￭ Data entry/management

￭ Customer service

￭ Vendor inquiries

￭ Delivery/scheduling

￭ Forecasting (e.g., FP&A)

￭ High volume research

￭ Exception handling

Data structure and integrity is essential across all IA


A Process Breakdown Will Lend Clues to IA Opportunity

11


Analytical = AI? Transactional = RPA? Customer Facing = Cognitive?

1.1 Establish credit

policies

1.2 Analyze/approve

new account

applications

1.3 Review existing

accounts

1.4 Produce

credit/collection

reports

1.5 Reinstate or suspend

accounts based on

credit policies

1.0 Process customer

credit

2.1 Maintain

customer/product

master files

2.2 Generate customer

billing data

2.3 Transmit billing data

to customers

2.4 Post receivable

entries

2.5 Resolve customer

billing inquiries

2.0 Invoice customer

3.1 Establish AR policies

3.2 Analyze/approve

new account

applications

3.3 Apply cash

remittances

3.4 Prepare AR reports

3.5 Post AR activity to the

general ledger

3.0 Process accounts

receivable

4.1 Establish policies for

delinquent accounts

4.2 Analyze delinquent

account balances

4.3 Correspond/negotiate

with delinquent

accounts

4.4 Discuss account

resolution with internal

parties

4.5 Process

adjustments/write off

balances

4.0 Manage and process

collections

5.1 Establish

policies/procedures

for adjustments

5.2 Analyze adjustments

5.3 Correspond/negotiate

with customer

5.4 Discuss resolution

with internal parties

5.5 Prepare chargeback

invoices

5.6 Process related

entries

5.0 Manage and process

adjustments/deductions

Perform Revenue Accounting


Process Analytical Tools Provide Great Insight

Process tools can assist with:

￭ Collecting process step data

￭ Identifying characteristics that lend themselves to RPA, Virtual Agents, and Artificial Intelligence technology

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Check all that apply or those that most closely resemble your process. If your process is not

listed, please type in the cells below "Other".

Use drop down menu to make

appropriate selection

Use drop down menu

to make appropriate

selection

Use drop down menu to

make appropriate

selection


make appropriate selection


select whether there is a

national, area, or global policy

for this activity

Type the description of

the related policy in the

cells below

Type any related gov't

regulations in the cells below

Type any related tax law in the

cells below

Type any additional notes; If

responded as "Other" in any

column, please describe here

Process Donations / Accounts Receivable

Instructions:

Process customer credit

Establish credit policies

Not Applicable

Establish/revise national credit policy as necessary. No defined process

Other: Please describe below

Analyze/Approve new account applications

### Not Applicable


###

Review existing accounts and balances

### Not Applicable

### Perform review of existing accounts and balances periodically and as needed


###

Produce credit/collection reports

### Not Applicable

### Generate reports from accounting software

###Draft emails to notify debtors of delinquent accounts either based on knowledge of debtors or

by looking within the accounting software


###

Reinstate or suspend accounts based on credit policies

### Not Applicable


###

Drop down menu • Rule driven • Repetitive

• Static steps

Drop down menu • Customer contact • Repetitive Q&A

• Knowledgebase driven

Chat Bot/Virtual Agent

Opportunity

Work Characterization

Field

RPA

Opportunity


Process Analytics – Example

13



Process Analytics – Example for Customer Credit

Number of frequencies, parties, and technologies involved in processing customer credit

14



Process Analytics – Example for Order-to-Cash

15



Build a Process Opportunity Dashboard to Help Prioritize

A process tool helps:

￭ Organizations understand standardization in process approach, execution, efficiency, and technology use

￭ Identify process steps that can benefit from RPA and other IA solutions

16



Prioritize Automation Opportunities

Early identification of which process steps present the greatest opportunity for automation solutions will allow your organization to maximize the benefit of its automation roadmap.

17


Automation Potential

1.1

1.2

1.3 1.4

2.12.2

2.3

2.5

3.1

3.4

3.5

4.1

4.4

5.1

5.25.3

5.4

1.5

2.4

3.23.34.2 4.3

4.5

5.55.6

Bu

sin

ess B

en

efi

t

Specific Process Steps

Paint an IA Governance Picture


What Do You Want to Achieve with Intelligent Automation?

19

IA Governance Picture

Answers help define program design and funding requirements


There Is No “One-Size-Fits-All” Governance Model

What others are saying (quotes from past SSON conferences)

￭ Yes, maybe the system should do this, but it doesn’t and it’s not going to because IT is busy, so we use RPA (Walgreens)

￭ Our IT preferred in-house servers (vs. cloud) for data security, others may not… (Walgreens)

￭ Standardize and eliminate waste before robotizing (Ascension)

￭ Processes may not require standardization or optimization before automating (ANZ Bank)

￭ ROI increases as people begin to think digitally – opportunity becomes increasingly apparent (AA)

￭ Fish where the fish are – if there are a lot of people working on particular tasks, it’s probably a good place for RPA (AA)

￭ We set up robots in the system as contractors (McKesson)

￭ We set up robots as existing workers who had access but did not work the process (Ascension)

￭ We reinvest our IA savings into IA (Aruna, MasterCard)

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The Answer Is Typically Some Degree of Hybrid (But There’s a Broad Range)

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Description Enterprise Role Challenges

RPA launched from within

enterprise COE or shared services

with high visibility and control of

efforts

Almost entirely enterprise-led

approach (typically IT, though it

could be led by another centralized

business function)

Less responsive

Development time reduces impact

opportunity

Baseline guidelines, controls and

QA

Core team provides automation

services for areas unable to support

own needs

Provides:

• Direction and leadership

• Orchestration and quality

assurance

• Optional process selection/

design

• Optional scripting

Potential conflicts between central

and local efforts and authority

RPA efforts are launched locally

within business functions

Can have business or function-

specific COEs

Little/no involvement at enterprise

level

Informal ad-hoc coordination

Varying quality

Potential bot impact on other

departments/bots

Robot chaos


Governance – Program Decisions

22


An IA program without central standards and quality assurance is a weaker “program,”

but tradeoff may be a reduced speed to implementation

Governance Approach (Example)

Support Type IA Program Decisions COE Process Owner IT Dept.

Program Decisions

Standards – Define IA requirements and

performance metricsX

More Autonomous

(Decentral)Certification – Approve qualified vendors

to develop IA projectsX

Training – Enable business units to

identify and implement IA projectsX


Governance – Execution Decisions

23


IA prioritization and project execution warrants business unit knowledge of needs,

but an IA COE can help keep this organized and avoid surprises



Project Execution

Project Planning – Manage IA

implementation schedule and budget

More Regimental

(Central)

X

Demand Management – Track and

prioritize IA project requestX

Process Identification – Assess

applicability of an IA solutionX

Development – Program and apply IA to

process stepsX


Governance – Maintenance and Planning Decisions

24


Running IA programs without IT is a fallacy—IT will need to be involved in maintenance at a minimum.

But, an IA COE can serve as a great “head on the horse” to promote IA visioning and planning



Project Execution

Technology Infrastructure – Create the

foundational elements for RPA operationsX

Program Operation – Orchestration and

optimization of IA scheduleX

More Autonomous

(Decentral)

More Regimental

(Central)Program Planning

Vision Development – IA program

leadership and promotionX

Future Planning – Reflect the

enterprise's technological change in IA

portfolio

X


IA COE Framework – Hybrid Example

25


Consultative to Process Owner

Consultative to IT

Expand Digitization across the Enterprise


Transactional

￭ Low-cost transactional centers and BPOs

• AP, AR, accounting transactions

• Master data entry and maintenance

• Customer issue assignment

Functional – Customer Facing

￭ Service hubs and call centers –“Amelia-like” virtual agent, chatbots

• Vendor help desks

• Employee service centers

• IT help desks

• Customer service order taking

AI Specialist

￭ Centers of expertise

• Credit and risk analysis

• Fraud prevention and controls

• Forecasting, planning, and budgeting

• Tax strategy

• M&A targeting

• Compensation design

• Recruiting and retention

• Workforce planning

• Demand planning

• Spend-reduction opportunity

27

Expanding Digital Vision

What Types of Work Will IA Impact?


General Distribution of Back-office Impact Potential

28


Strategic6%

Specialist11%

Customer Facing23%

Hands On16%

Transactional32%

Robotic12%

Repetitive task, often

related to admin or routine

data entry

(low-cost labor spots)

Deep specialist focus

typically associated with

decades of experience

(COE where talent is)

In-depth subject matter

expertise and closer

proximity to customer

(regional support hub)

Total FTE

RPA work fits a small COE

for controlling work,

developing programs, and

maintaining “bots”

Hands-on touching of work,

government interface, legal

requirements

(local, on site)


Global Business Service Models Today

29


AMERICAS EMEA

APAC

Transaction

Center

Transaction

Center

Corp HQ

Service

Support

Hub

Service

Support

Hub

COEs

Service

Support

Hub

▪ Low-cost locations

▪ High-volume transactions

▪ Standardized

▪ BPO sweet spot

• Regional knowledge

• Language requirements

• Time-zone sensitivity

• Specialist knowledge

• Experience to recognize patterns

• High-volume research/analytics


Transactional Shift – Away from Lost-cost Areas?

30


AMERICAS EMEA

APAC

Transaction

Center

Transaction

Center

Corp HQ

RPA

Center


Service Shift – Virtual or Smaller Service Hubs?

31


AMERICAS EMEA

APAC

Corp HQ

AI

Agent

Hub

Service

Support

Hub

Service

Support

Hub

Service

Support

Hub

Service

Support

Hub


Specialists COEs – Smaller, Intelligent, Data Driven?

32


AMERICAS EMEA

APAC

Corp HQ

HR

COE

Supply

COE

IT

COE

Finance

COE

AI

Analytics

COE

AI

Analytics

COE

Legal

COE

Manufacturing

COE

Engineering

COE

Marketing

COE


GBS Model of the Future

33


AMERICAS EMEA

APAC

Corp HQ

AI

Analytics

COE

Legal

COE

Mftg

COE

Eng

COE

Marketing

COE

Service

Support

Hub Service

Support

Hub

Service

Support

Hub

Transaction

Center

Transaction

Center

RPA

Center

AI

Agent

Hub

HR

COE

Supply

COE

IT

COE

Finance

COE


Impact to Future Work Types Will Change Our Business Cases – Example

34


Today

Transactional

(Low-cost Center)

Hands On

Functional

(Service Hub)

Specialist

(COE)

Strategic

Tomorrow – with IA (hypothetical)

Hands On

Functional

(Service Hub)

Specialist

COE

Strategic

RPA Transactions

30%?

Cognitive

Agents and

Chatbots

15%?

AI Analysis

5%?

Transactional

(Low-cost

Center)

45%

15%

20%

10%

5%

Future impact to our rationale for existing GBS models may require rethinking and result in completely

different delivery frameworks than we have today


How Can You Prepare Now?

Avoid surprises and create your future model now

￭ Find process steps that lend themselves to IA

￭ Observe process characteristics and align to IA technology (RPA, virtual agents, AI)

￭ Build the case for investment and a realistic pace for your company

￭ Prepare your data (governance, structure, cleaning)

￭ Start formulating a beginner governance model

￭ Assess upcoming long-term strategic decisions vs. a highly likely future of disruptive technology

• BPO decisions

• ERP decisions

• Service support decisions

• Location decisions35


Preparing the future conceptual model and business case now will avoid the potential for costly

initiatives that may not add value in the near future (e.g., call center builds, BPO contracts, etc.)

Documents

Designing a Program that Increases Your Intelligent ... · Broader Process Evaluation Robotic Process Automation Virtual Agents and Chatbots Artificial Intelligence Level of Adoption