Back to the Future - SIG

Understanding New Digital Processes

with Robotics Process Automation and

Artificial Intelligence

Back to the Future:

NelsonHall

John WillmottCEO

sig.org/eval

© 2016 by NelsonHall.

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John Willmott, NelsonHallSourcing Industry GroupOctober 18, 2016

Back to the Future: Understanding New Digital Processes with Robotics Process Automation and Artificial Intelligence


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NelsonHall – The Leading Source of BPO Information

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Topics

NelsonHall-Proprietary – Not for distribution without permission 4

1. What are RPA and AI

2. Benefits and RoI Achieved Via RPA

3. Commercial Implications of RPA for Outsourcing Contracts

4. RPA Operating Model Guidelines

5. What’s Next for RPA & AI?

6. Conclusions


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Filling the Gap between Macros and Platforms

Definition and Application of RPA


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The Robots are Coming: New Possibilities for Continuous Improvement


RPA is “macros on steroids” and reduces the investment threshold for continuous improvement. Makes improvements realizable that were previously unviable due to cost of platform implementations …..

• Presentation-layer automation software that sits on top of the client’s existing Systems of Record to access and enter data and make simple calculations

• RPA can be used to mimic the steps of a specified business rules-based process to automate specified standardized tasks where human judgement is not required, e.g. data entry

• 1 robot can process, on average, the number of transactions as 1.5 to 2 FTEs (though can be higher)

• Useful for business processes that require “swivel-chair” access to access data from several existing systems

• Robots can easily scale up or down to meet demand

• RPA can be used for specific tasks in activities in BPS areas such as F&A, procurement, SCM, accounting, customer service, banking industry-specific


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Definitions

• RPA is a technology which:

• Accesses the user interface of third party applications

• Is configured to execute steps identically to a human user (workflow plus execution)

• Currently solely used for rule-based activity and incorporates zero cognitive capability

• Deterministic in nature

• Example products: UIPath, Blue Prism, automation anywhere

• AI is cognitive in nature and encompasses machine learning, natural language processing etc. Key characteristics of AI/cognitive that RPA lacks are:

• Ability to undertake judgmental processes

• Ability to adapt the process as it learns

• Largely based on statistical techniques so probabilistic in nature whereas RPA is deterministic

• Example products: Celaton, IPSoft Amelia, TCS Ignio, IBM Watson, Wipro Holmes



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A quick hit to reduce levels of rule-based processing…

Benefits and RoI Achieved via RPA


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Examples of RPA Application & Benefits within F&A BPS

• Within finance & accounting, RPA most applicable to procure-to-pay• P2P: supplier management & catalog management, 3-way matching,

reconciliations

• O2C: customer data management, cash application, reconciliation

• R2R: reporting, inter-company accounting, reconciliations

• Examples• Vendor master creation: 35% FTE saving

• Invoice processing (3-way matching & posting): 35%

• Invoice data capture & data entry: 20%-25% productivity

• Vendor queries: 20%-25% FTE savings

• Remediating errors in billing data: 25% cost reduction

• Overall impact across entirety of F&A is ~20% cost reduction, typically achieved over 2-3 year period



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Examples of RPA Application & Benefits within BFSI

• Automation of application sign-on process• 28 applications/multiple log-ins due to time-outs

• Automation of login and access to required application page

• eAdjudicator• Automated matching of claims parameters against rule library

• 70% reduction in “support FTEs”

• New business data entry (insurance)• Swivel-chair across multiple, unsynchronized screens

• Automated data entry

• 30%-40% efficiency improvement

• Trauma quotations• Approve endorsements, update cases, & generate quote documents & letters

• Healthcare Payer• Provider contract data management, largely contract validation (75% automated)

• 4 bots in 90 days

• Productivity improvement of 40%



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RPA Benefits

• RPA capable of delivering 20%-50% cost take-out on applicable sub-processes

• Cost take-out in RPA largely a function of proportion of process addressable

• Within highly transactional processes such as F&A BPS and industry-specific BPS this is translating into ~20% cost reduction typically achieved over a 2-3 year period

• Additional benefits beyond cost include:• Error reduction/improved SLA adherence

• Cycle time reduction



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…provided the commercials can be agreed

Commercial Implications of RPA for Outsourcing Contracts


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How are vendors approaching RPA?

• Typically partnering with third-party RPA software companies such as “automation anywhere”, Blue Prism, UiPath

• Many developing own machine learning and AI software to protect process IP in short-term and develop competitive advantage in emerging forms of AI

• Developing libraries of RPA applications as their value-add

• RPA libraries are typically cross-functional e.g.

ROBOextractor

ROBOformater

ROBOuniter

ROBOimpresario

• Though often packaged by function e.g.

AccountSetupBOT

CashAppsBOT



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What about the commercials?

• RPA pricing currently a challenge• Returns largely unknown before project undertaken

• Vendor has no desire to remain on FTE-based pricing

• Possibilities include:

• Move to fixed price or transactional pricing plus ongoing productivity target and allow vendor to use robotics to hit productivity goal

• If still FTE-based, then run each RPA project as a separate gainshare

• Arguably rule-based RPA lends itself to transaction-based pricing or fixed price and judgment-based RPA lends itself to outcome-based

• Who pays for RPA licenses?• Price per bot typically quoted as 1/3 of the price of an FTE

• ~$6K per bot



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Critical success factors & key tips

RPA Operating Model Guidelines


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Establishing RPA Operating Model Framework

Activity Key Tips

Preparing a communication plan Ensure senior sponsor for RPAVideos more effective than textAddress potential impact on control, staff, & budgetStress building for growth & staff development opportunities

Establishing a RPA Center of Excellence

Link to reengineering/operational excellence group

Establishing a governance framework

IT representation vital

RPA software selection & procurement

Think toolset rather than individual tool


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Need Assessment & RPA Opportunity Identification

Activity Key Tips

Establish formal framework for opportunity selection

Only select relatively stable processesStart with rule-based processes with strong standard operating proceduresInvolve IT to understand level of change in underlying applicationsGo for some quick wins

Identity security Address bot identity management & security up-front with IT security & legal – this one takes time!

Selection of RPA reporting tool IT should assist in assessment of functionality


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Development of Pilots and Design & Build

Critical Success Factor Key Tips

Address business problem not technology

Think “eliminate/simplify/standardize/automate”

Achieve quick wins Be prepared to redesign and standardize at a later date

Aim for increased straight-through processing

Be prepared to batch @automation tasks@

Don’t underestimate achieving access to applications

Involve IT at an early stage

Operations-centric operational testing

Test using copy of production environment


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RPA Production, Maintenance, & Support

Critical Success Factor Key Tips

Monitor bot performance Implement central monitoring & reporting tool & provide executive dashboard with one version of the truth

Ensure high bot utilization Centralize bot scheduling


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RPA is dead ….long live AI

What’s Next for RPA & AI


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BPO Market Developments in Q1 2014: Global and Landscape

RPA and AI Evolution


Use RPA to Fix Process Joins

RPA Combined with Machine

Learning/Cognitive/AI

RPA with Minor Process Reengineering


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Where Next?

RPA

• Execution of repeatable, rule based tasks which require little or no cognition or human expertise or human intervention by machine or computer by mimicking human action.

• Bot operates enterprise software and applications through existing user interfaces based on pre-defined rules and inputs

• Start with high volume data entry and move to simple rule-based then complex rule-based

• Reengineer to scale


AI

• Judgment-based tasks starting to be supported with cognitive platforms

• Execution of those tasks by machine which require human expertise or human judgment

• Cognitive : Adaptive Learning, Speech Recognition, Natural Language Processing, Pattern identification algorithms

• Typically applied in conjunction with traditional RPA

• Customer service and banking sector are focal points for initial introduction of AI


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Example: TCS Ignio

• Described by TCS as “neural automation platform”

• Capabilities: “Sense”: ability to assimilate and mine diverse data sources, both internal and

external, both structured and unstructured (via text mining techniques)

“Think”: ability to identify trends & patterns and make predictions and estimate risk

“Act”: execute context-aware autonomous actions. Here TCS could potentially have used one of the third-party RPA software products, but instead chose to go with their own software instead

“Learn”: improving its knowledge on a continuous basis and self-learning its context

• Applications Initially used for IT batch performance and capacity management

Delivery failures in order management

Customer journey abandonment

Profiling, detecting, and correcting anomalies in supplier behavior



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Creation of New Digital Process Models e.g. Source-to-Pay

• Sourcing strategy & category management

• Vendor investigation: cognitive

• Contract management

• KYV data extraction: cognitive

• Ordering & Supply Management

• PO communication: RPA

• Supplier master modification: RPA

• Invoice Processing/T&E Management

• 2-way/3-way invoice matching & posting: RPA

• Helpdesk

• Chatbot: cognitive

• Compliance/Analysis

• Online reputation monitoring: social media analytics



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From making continuous improvement realizable to new digital business models

Conclusions


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Conclusions

• RPA is currently a “band-aid” for fixing existing process joins and sources of error

• Makes continuous improvement realizable rather than a major hurdle

• Much quicker and lower transition cost than new platform implementation

• It primarily supports fixing of the current business model rather than introduction of new business models and processes

• Current forms of RPA short-lived in the way that labor arbitrage is short-lived, with 20% one-off benefit for rule-based processes achieved over 3-year period

• Requires same process-centricity & strong “standard operating procedures” as other forms of BPS

• Currently around data extraction, enrichment, & posting and rule-based processes

• Requires change in commercials to reset productivity or gainshare targets

• Cognitive/self-learning platforms beginning to emerge, with high initial focus on customer service and order management

• Digital assets incorporating AI and RPA to establish new process models



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Requirements for successful application of RPA

Guidelines

• Need CxO sponsorship

• Need early proof-of-concept

• Avoid highly volatile processes

• Avoid highly fragmented processes

• Select process for improvement prior to tool selection

• Be prepared to use toolkit rather than single RPA magic bullet

• Design for STP

• Use savings from RPA to fund new initiatives


• Process improvement expertise

• Rule-based process with strong standard operating procedures

• Standardized processes

• Digitized structured data

• Agent change management

• RPA governance

• Involve in-house IT

• Principal focus on data extraction, data enrichment, data validation, & data entry

• Don’t run before you can walk

• But be prepared to reorganize process steps


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Q&A


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Q&A

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@John_NH


John Willmott, NelsonHallSourcing Interests GroupOctober 18, 2016

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Back to the Future:

Understanding New Digital Processes with

Robotics Process Automation and Artificial

Intelligence

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