beyond rpa - sigsig.org/docs2/ws09_beyond_rpa_revamping_operations_with_new...moving beyond rpa to...

Revamping Operations with New Digital Process Models

Beyond RPA:

NelsonHallJohn WillmottCEO

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© 2017 by NelsonHall.

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Moving beyond RPA to “fully” digitalized operations

Transforming Operations with New Digital Process Models


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NelsonHall – The Leading Source of BPO Information

NelsonHall is the leading BPO and IT outsourcing research firm with analysts in the U.S., U.K., and Continental Europe. The company takes a global approach to analysis of vendors and outsourcing markets and is widely respected for the quality and depth of its research.

In addition, with its “Speed-to-Source” initiatives, NelsonHall is taking the lead in making access to BPO and ITO research much easier than ever before.

Independent & objective information

• All analysis by onshore analysts (U.S. & Europe)

• All research interviews carried out by analysts – no online surveys, no vendor form-filling

• Process domain experts with global remit

• 16-years experience in BPO market and vendor analysis

• Independence & objectivity – not amplifying the hype

With analyst access to ask the difficult questions

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Topics to be covered

1. Disruptors & impact on customer requirements

2. Why RPA is the Start of the Automation Journey

3. Moving to New Digital Process Models

4. Conclusions


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Disruptors & Impact on Customer Requirements


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BPO Successes & Room for Improvement

What Worked Room for Improvement

Caliber of delivery teamAbility to apply increased automation to business processes

Ability to improve process execution Ability to improve business outcomes

Ability to standardize & consolidate processes

Ability to provide future process vision & roadmap

Ability to implement process improvement initiatives

Ability to use analytics to incorporate process learning

Ability to deliver process cost changes promised

Ability to reduce process costs

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Convergence of maturing customer needs, new technologies,& new competitors


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Digitalization No Longer Constrained to Customer-Facing Activity

Potential Initiative High Intent in 2016 (%)

Digitalizing & automating back-office operations 84

Reducing cost of doing business 79

Freeing up expenditure for new initiatives 60

Digitalizing customer-facing operations 52


Impact of digital:• 65% of U.S. organizations have

initiatives in support of “developing new ways of doing business to compete with new market entrants”

• 71% developing their positioning as digital enterprises

Removing detrimental impact of back-office on the customer


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Developments in Q1 2014: Global and Landscape

Journey from RPA to Digital Operations


Standard RPA

RPA Combined with SoE/NLP/Machine

Learning/NLG

RPA with Minor Process Reengineering

RPA with Improved Document Classification

& Data Extraction


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BPO Market Developments in Q1 2014: Global and Landscape

New Digital Business Models Typically Combinations of Disruptive Thinking and Disruptive Technologies


5. Robotics/RPA

1. Internet of Things

6. SaaS/BPaaS

2. Digital Channels

4. Analytics

3. Cognitive

Design Thinking

7. BPM



Why RPA is the Start of the Automation Journey


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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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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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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

• Establish Center of Excellence

• 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

• Don’t run before you can walk

• But be prepared to reorganize process steps



Moving to New Digital Process Models


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Combining Data Mining, Analytics and Execution

• “Sense”: ability to assimilate and mine diverse data sources, both internal and external, both structured and unstructured (via text mining techniques) (cognitive)

• “Think”: ability to identify trends & patterns and make predictions and estimate risk (predictive analytics)

• “Act”: execute context-aware autonomous actions (RPA)

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



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Example of New Digital Process Model: Source-to-Pay

• Sourcing strategy & category management• Vendor investigation: cognitive

• Vendor decisioning: Predictive analytics

• Contract management• KYV data extraction: cognitive

• Ordering & Supply Management• PO communication: RPA

• Supplier master modification: RPA

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

• Helpdesk• Chatbot: cognitive

• Compliance/Analysis• Online reputation monitoring: social media analytics

• Preventing fraudulent transactions: predictive analytics


Other Elements in S2P Digital Process Model

• BPM backbone

• Supplier portal

• Procurement SaaS platform


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Example of New Digital Process Model: Claims Processing & Underwriting

• Mobile & self-service customer interfaces and/or broker portal

• Analyze and cross-reference public domain and claim report information• Cognitive: machine vision, voice recognition & NLP

technologies

• Vendor investigation: cognitive

• Detect anomalies while processing claims• Machine learning

• Predict probability of fraud• Predictive analytics using data from internal and external

sources

• RPA for automated processing of claims achieving STP for low-risk claims


Underwriting

• Prediction of success for deal conversions• Broker quotation analysis using

predictive analytics

• Prioritize underwriting

• RPA to auto-identify appropriate underwriter

• RPA to queue quotations for underwriters


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Example of New Digital Process Model: eKYC

• Scan and download relevant documents from multiple sources• Access external web sites, registries & trusted sources

alongside internal information• Vendor investigation: cognitive

• NLP-based cognitive search• Extract contextualized information using

machine learning


Benefits

• ~40% reduction in KYC effort

• 60%-70% reduction in turnaround times for customer onboarding


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Contact Center enablement

• Organizations principally looking to move queries to self-service & automate agent assistance

• Typically buying sub-set of functionality and implementing channel by channel

• Key components

• Web self-service: contextual response, predictive analytics

linked to knowledge-base, customer info, billing systems etc.

• Guiding & pivoting to appropriate channel

• Live agent assisted chat: co-browsing, multi-media sharing

• Automated chat: natural language processing

• 2-way SMS

• Video chat

• Social media




Conclusions


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Conclusions – Impact on Operations

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

• Makes continuous improvement realizable rather than a major hurdle for rule-based processes

• New digital process models now emerging combining RPA with AI technologies

• Key characteristic include:

• Digital inputs & outputs

• Minimize customer effort but maximize customer feedback

• Complement internal sources with external sources

• Directly impact business metrics and aim for STP/end-to-end digitalization

• Means re-imagining business processes

• RPA largely retains “As-Is” processes

• “To-Be” processes & outcomes fundamentally different for NDPMs



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Q&A

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@John_NH


John Willmott, NelsonHallSourcing Interests GroupMarch 14, 2017

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