Digitization Leaders Share Robotic Process Automation Best

Digitization Leaders Share Robotic Process Automation Best PracticesRPA Shows Value But Can Disrupt Automation Goals

by Craig Le ClairMay 2, 2016

FOR ENTERPRISE ARCHITECTURE PROFESSIONALS

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Key TakeawaysC-Suite Profit Pressure Can Lead To Misguided RPA ProjectsEnterprises lack a solid approach to mine RPA process value.

Prioritization Is Simpler Then You ThinkPrioritize use cases based on risk, return on investment (ROI), and cognitive potential.

Best Practices Look Beyond Replacement Of Full-Time Equivalents (FTEs)Following best practices for process discovery, workforce assessment, and technology management will ensure a successful RPA effort.

Why Read This ReportEnterprises, in their quest to reduce labor costs, are applying robotic process automation (RPA) technologies. Yet many lack a well-defined set of principles and best practices. This report isolates the most important practices for enterprise architecture (EA) professionals, explores how to prioritize RPA use cases, and provides best practices for process discovery, workforce assessment, and technology management.

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Table Of Contents

Enterprises Lack A Solid Approach To Mine RPA Value

RPA Best Practices Are Still In Their Infancy

Critical Process Questions Help Focus The RPA Effort

Recognize The Importance Of Change Management To RPA Success

Technology Management Takes The Lead In Integration And Monitoring

Recommendations

RPA Needs To Go Beyond Eliminating FTEs

Notes & Resources

Forrester interviewed robotic process automation (RPA) and machine learning customers and providers, including Blue Prism, Cognizant, Earley Information Science, IBM, IPsoft, Lexmark International, Salesforce, and Tata Consultancy services. Forrester also fielded client inquiries from line-of-business executives and individual workers performing routine production services jobs where RPA is in use or planning is underway.

Related Research Documents

The Future Of Jobs, 2025: Working Side By Side With Robots

The State Of Robotic Process Automation

TechRadar™: Digitizing Operational Processes, Q2 2015

FOR ENTERPRISE ARCHITECTURE PROFESSIONALS

Digitization Leaders Share Robotic Process Automation Best PracticesRPA Shows Value But Can Disrupt Automation Goals

by Craig Le Clairwith Alex Cullen, Shaun McGovern, and Diane Lynch

May 2, 2016

http://www.forrester.com/go?objectid=RES119861





http://www.forrester.com/go?objectid=BIO1226

http://www.forrester.com/go?objectid=BIO1761

For EntErprisE ArchitEcturE proFEssionAls

Digitization Leaders Share Robotic Process Automation Best PracticesMay 2, 2016

© 2016 Forrester research, inc. unauthorized copying or distributing is a violation of copyright law. [email protected] or +1 866-367-7378

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RPA Shows Value But Can Disrupt Automation Goals

Enterprises Lack A Solid Approach To Mine RPA Value

Repeatable tasks that search, collate, update, access multiple systems, and make simple decisions are the best RPA targets.1 Matching RPA to the right process is challenging, and today, it’s an art form. The healthcare, finance, insurance, and banking industries are awash in overlapping systems that must work together, and few firms have an approach that helps direct RPA project efforts. As one director and project transformation lead from a major credit card issuer describes it:

“We had no framework to assess RPA automation. We tended to just trip over an opportunity such as scripting a reconciliation report or customer correspondence. We found the continuous payment authority (CPA) process in that manner. We automated CPA in two weeks — but did we select this with an overall process analysis? No.”

To get started, enterprise architects must recognize that:

› Manual effort should be the focus. A major European bank, as part of a program to improve operational excellence, found that manual operations were a barrier. A fast, simple, and flexible banking experience adapted to the modern customer’s impatient and connected lifestyle was just not possible. The bank developed a thirteen-point model to measure and target manual effort across the board. The senior director at the bank described it: “It’s a structured approach to rooting out manual activity using multichannel management, supported by simplification and digitization of processes, that will help us move on operational excellence.”

› Firms are underserving opportunities to enhance customer experience. Many processes, such as client onboarding, suffer from poor communications across the customer journey. Enterprises can use mail, SMS, output reports, customer letters, and spreadsheets more effectively to trigger workflows, gather needed data, and pass off communication tasks to further processes.

RPA Best Practices Are Still In Their Infancy

Not all RPA projects have the same potential. Routine production services are the prime RPA target today. Tellers, loan interviewers, general office clerks, logistics staff, order processors, fraud/compliance workers, credit authorizers, current business process outsourcing (BPO) services, and customer support staff all perform tasks with high potential for automation. Yet the best processes for RPA automation depend on their importance for operational excellence, customer value, ROI profile, cognitive support, and risk (see Figure 1). Enterprise architects are at risk of bringing in RPA technologies without a best practice approach that covers change management, identifies gaps in the formerly human-driven process that affect compliance, supports customer experience, and prepares for cognitive enhancement.




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FIGURE 1 RPA Use Cases Span Front And Back Offices

ROI land grab

Ris

k an

d c

han

ge

man

agem

ent

Low

Proactive customer service

Order managementDocument validation and categorization

BPO labor arbitrage offset

Customer-sensitive exception management

Hig

h

Fraud chargeback processing

Low-risk arrears review

Direct debit cancellations

Internet application processing

Business account onboarding

Excess transaction approvals

Check approvals

Customer communications

Address and customer account updates

Transaction duplication

Automated branch risk monitoring

New loan product blitzes

Insurance claims awards

Automated marketing campaigns

Customer complaints automation

Financial planning and analysis

Regulatory and compliance reporting

Low High

Tread carefully

Cognitive potential

Back burner

Bonus territory

QA/application testing

Self-service automation

Patient data integration

Market research

Unstructured content transformation

Freedom of information requests

Licensing and registration

Critical Process Questions Help Focus The RPA Effort

To date, few are asking the right questions about RPA. Many don’t recognize RPA as a force that will lead to a restructuring of work and that’s more far-reaching than anticipated. The first step? Use best practices to gain the right understanding of the process (see Figure 2). Take a thoughtful approach and:

› Identify data entry and review tasks that cross multiple systems. More channels, expanded products, and a spaghetti code of systems lead to complex customer service and operational tasks. For example, a mortgage origination process, pre-RPA, had three separate groups that interacted with 15 systems in a serial fashion. RPA bots (short for robots) now enter and review captured data. The RPA deployment eliminated one complete group. Training, not job reduction, was the primary focus of this initiative, but now, instead of needing training on 15 systems, staff now need training on only seven.




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› Prepare for diving into process minutia. To program a bot, you need to know exactly where to grab a particular field on a screen and precisely which events will trigger an action. If a screen changes orientation and the user takes the wrong field or no field, it will throw off the bot. Interestingly, cognitive platforms that execute from recorded patterns or use machine learning algorithms that statistically assess system behavior and reprogram themselves can be less precise than skilled analysts are.

› Design with experts, but let the “worst and dullest” assess readiness. EA pros should design the RPA process with expert employees, as they know the ins and outs of how things work better than anyone else does. But some enterprises suggest that the normal approach of taking the most senior production staff for RPA testing may not be the best. This group is the most experienced in the current process but the most offended by the replacement of tasks they have mastered.

› Explain what you’re doing to compliance and legal (note: It may not be easy). RPA affects compliance in both positive and negative ways. On the plus side? RPA is good at generating reports needed for compliance reporting. It pulls data from desktops and web-based apps, servers, and core systems. Combined with analytics, it can further relieve expanding compliance reporting.2 As for the negative side, the use of bots to replace human functions introduces a new category of risk. Cover both potentials: Early in the game, review your RPA approach with compliance and legal.

› Install airbags when connecting RPA to analytics for critical processes. RPA may be the first step, but cognitive support will be next. When installing RPA, design the system to potentially link with cognitive platforms. For example, you can design active learning into RPA trigger points that can support machine learning, where the bot reprograms itself to take advantage of the training.3 But cognitive designers must recognize that artificial intelligence (AI) systems can end up learning undesirable behavior, as Microsoft recently found.

On March 21, 2016, Microsoft released an artificial intelligent chat bot called Tay, accessible as a Twitter account. The goal was to research and understand conversations. Unexpectedly, and within hours, caustic and demented Twitter users had the naïve AI bot spewing racist, sexist, and Holocaust-denying comments.4 The problem? There were no protective cushions, keywords, content filters, or base domain knowledge about offensive topics.




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FIGURE 2 Critical Process Questions Help Focus The RPA Effort

De�ne the systemcharacteristics

De�ne the humancharacteristics

De�ne the customerexperience effect

Prepare for cognitiveintegration

• Data entered in three or more applications; more than two duplicate data entry steps• Dedicated FTEs with 50% or higher administrative time for one process cycle• Percentage of manual decision higher than 15%• Fewer than �ve automatic validations

• People need to manually ful�l one or more documents.• People print or sign more than three documents and capture one or more.• People make three or more handoffs and two or more back of�ce tasks to complete.

• Project the RPA customer self-service effect and what’s in it for the customer.• Describe potential RPA scenarios that may offend the customer.• Isolate risk points in the journey that may alienate the customer.• Prioritize the top three processes based on the number of customer complaints.

• Install airbags when connecting RPA to cognitive support processes.• Provide a compliance walk-through and documentation of proposed process.• Design RPA with active learning points for future cognitive integration.

Note: Estimates are general guidelines for illustration only and will vary by industry, process scale, and type.

Recognize The Importance Of Change Management To RPA Success

Internal users and immediate managers of routine production services, despite stated desires, have a great fear of change. The current state may be a very bad system, but managers and users have experience overcoming its weakness and also have personal and professional investment in the system. You must not ignore these factors when deploying RPA solutions. The process transformation lead at an international bank holding company told us, “One half of my team focuses on cultural and change management issues that we are just beginning to address. We realize that this involves human change and that we’re taking something away from them.” Several factors influence staff attitudes, including the (see Figure 3):

› Perceived usefulness of the RPA-driven application. Perceived usefulness is the degree to which a person believes that using RPA would enhance his or her job performance. The stability of the new system influences usefulness. It’s typical for early robotic systems, due to their high number of concurrent users and system interfaces, to encounter performance or stability issues. When this happens, no one will perceive the new system as particularly useful. The more unstable an implementation is, the less willing people will be to support the change.

› Perceived ease of use. The degree to which people believe that the RPA system will be free from effort and make their jobs easier is a key determinant of attitude. With a negative early experience, these initial attitudes are difficult to overcome, even with subsequent improvement in ease of use. Test perceived usefulness and ease of use through interviews and prototyping prior to initial deployment.




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› Management support that covers both the tangible and intangible. The third important predictor of attitude is management support, including direct incentives. Explicit incentives and bonuses tied to rollout can help adoption. This works for consumers hesitant to learn customer self-service applications, where lower prices or other incentives correlate with higher adoption. One potential strategy is to offer a pool of bonus money to new users, perhaps to the most enthusiastic and aggressive adopter. If the company will let you do this, it’s money well spent.

FIGURE 3 Change Management — The Most Important Issues

RPA changestasks and roles.

RPA changesgroup functioning.

RPA affectsrequired skills.

• Describe how outsourced functions are changed or terminated.• De�ne new roles, new hires, and changes in business unit responsibilities.• Reduce wide variations between new and old tasks through training and ease of use.• Garner management support (e.g., explicit incentives to ensure adoption).

• Diagram changes in reporting and communication.• Understand the former tasks within and among groups to create a smooth transition.• Incorporate old behavior in the new system to maintain harmonious group interaction.• Realistically assess staff bene�ts and compare them to projected behavioral change.

• Conduct a workforce skills audit to prepare for a potential mismatch.• Assess whether new required skills are a good �t for the organization.• Blend on-the-job training with facilitators and advisors.• Project changes in professional development potential of one group over another.

Technology Management Takes The Lead In Integration And Monitoring

Technology management (TM) plays an elevated role in RPA (see Figure 4). TM pros build the macros, create integrations to the desktop or web user interface (UI), create and digest reports, and deploy the servers that will host the bots. Several enterprises have built their own RPA-like automations but now look to a repeatable approach based on a third-party product. Lessons learned include:

› The bots don’t monitor themselves yet. Imagine you have hundreds of bots running in several data centers and in the cloud. How will you monitor them? RPA vendors are well behind in large-deployment monitoring. A typical experience, according to a senior director of a project management group at a regional bank: “Without realizing it, all of a sudden, we had 100 bots running in our data center. Our focus shifted from deployment to management.”

Organizations can use robotic scripting to monitor application availability and performance. For example, a large health service enterprise used RPA to test availability of key applications. At 3-minute intervals, a bot acts like a human (e.g., logs on and searches for a member name). If there’s a problem, an alert goes to the applications group. Reliability is an issue — when an app




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changes, the script often breaks. RPA reporting is also weak. As a workaround, RPA-collected performance data goes to a data warehouse, where a business intelligence (BI) tool generates needed dashboards.

› Questions on basic architecture requirements remain. Tasked by the C-suite to use RPA to improve customer self-service, one EA team struggled to find reliable scaling and deployment benchmarks. As the business architect from a leading property and casualty (P&C) insurance provider explained: “We provide insurance for motorcycles, boats, homes, renters, condos, lives, and businesses. The more a website can do for a customer, the better. Processes like quick quotes, needs assessments, claims, and trip planning could use RPA to gather information, execute apps, and provide an innovative level of capability. Our concern? How many bots do we need, or how big a box do we need to support a self-service app? Self-service RPA support departs from the one-bot-per-desktop approach we normally use.”

› Trigger points are discovered too late in the process or are inaccessible. Trigger points kick off RPA processes. Screen data, input files (XLS, CSV, or XML), electronic events from external web services, APIs, or databases all provide these triggers. They must be clear and accessible. An early effort to create a checklist will pay off.

› Firms find incompatibility with existing BPM and DCM programs. RPA works independently of or in conjunction with traditional business process management (BPM) and dynamic case management (DCM) solutions. At present, vendors such as Appian and IBM have not entered the RPA discussion, although Pegasystems recently became the first BPM provider acquiring RPA technology with the purchase of OpenSpan in April 2016.5 Look to RPA as an easy extension rather than a competitive solution. For example, the BPM model will have steps external to the process, and the RPA step can be one of those. An RPA step can sit on a BPM queue and wait for execution.

› Teams must develop an automation strategy. RPA’s strongest feature is rapid, noninvasive deployment. This should not translate to tactical, opportunistic problem solving. Develop an automation strategy that aligns with the business (i.e., not just a tech management automation strategy). Attack it as you would any other strategic program.




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FIGURE 4 Technology Management Takes The Lead In Integration And Monitoring

Applications

Installationand operations

• Detail how trigger points are accessed (e.g., VPN, Citrix, or web).• Define application reporting to manage RPA script malfunctions.• Define operations/applications responsibilities to support the RPA technology.• Identify precise events and UI touchpoints to execute bots.• Describe interactions with existing or future BPM or DCM orchestration platforms.

• Define RPA scale assumptions (e.g., server requirements to support self-service bots).• Define operations reporting to manage RPA performance and scale issues.• Describe any latent system dependencies or access constraints.• Define tasks for security administration, backup, recovery, and application support.

Recommendations

RPA Needs To Go Beyond Eliminating FTEs

While RPA will free up employees for creative and more fulfilling activities, it will also eliminate jobs. Be wary of a new fear in employees that may inhibit the learning and potential benefits of RPA technologies. When it comes to risk, the attitude of the company is in conflict with that of the employee. The company, under profit pressure, is more prone to risk, i.e., pushing new technology successfully is what shareholders measure it on. But RPA will potentially affect employees’ jobs and careers, which will make them more risk-averse. EA pros should:

› Avoid overthinking the problem. It’s not important to optimize a business process prior to RPA automation. The noninvasive aspect of RPA is a great strength and contrasts well with traditional BPM projects. But you’ll need to have a story for how RPA complements other automation efforts in the enterprise. Is it a set of tasks on some higher-order BPM or DCM process map? As you deploy RPA more, it will combine with other processes and technologies.

› View RPA and robotics within a man/machine collaborative context. Collaboration with robots, as opposed to strict human replacement, is an important best practice attitude. NICE, for example, has a collaborative platform that allows robots and humans to interact.6 An agent takes the call and passes information along to the robot, which allows the agent to move on to the next call more efficiently. Prepare a guidepost for moving along the automation continuum.

› Establish an automation maturity framework. Process prioritization, development approaches, skill sets, technology evaluations, and benchmarking best practices are all steps that can track and monitor progress. Shared-service organizations are developing RPA centers of expertise toward this goal, which was a clear theme at the recent Outsourcing World Summit (OWS) event, IAOP’s




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annual global gathering. Shared-service organizations will use centers of excellence/expertise focused on RPA to: 1) select the right RPA tool or deployment approach and 2) identify processes that can benefit from RPA.

› Look at a range of providers. Clients often cite site Automation Anywhere, Blue Prism, and IPsoft as common shortlist candidates. But the market continues to expand, so enterprise architects should be aware of many other vendors, with some better for desktop integration (Blue Prism), others for unattended automation (IPsoft), others for IT infrastructure testing (UiPath), and still others for contact center support (NICE). Vendors you should consider include Arago, Ayehu Software Technologies, Automation Anywhere, Automic Software, Appvance, Blue Prism, Blue Yonder, Celaton, Cicero, Exilant Technologies, IPsoft, LeoForce, Lexmark International’s Kapow, Newgen Software, NICE, OpenConnect, OpenSpan, SolveXia, and WorkFusion.

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Endnotes1 To learn more about robotic process automation, see the “The State Of Robotic Process Automation” Forrester report.

2 For example, Narrative Science uses analytics to read tabular data, draw inferences, and transform these inferences into natural language reports.

http://forr.com/1einFan

http://www.forrester.com/Analyst-Advisory/-/E-MPL172





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3 Wikipedia defines active learning (machine learning) as “a special case of semi-supervised machine learning in which a learning algorithm is able to interactively query the user (or some other information source) to obtain the desired outputs at new data points.” In statistics literature, it is sometimes all called optimal experimental design. Source: “Active learning (machine learning),” Wikipedia (https://en.wikipedia.org/wiki/Active_learning_(machine_learning)).

4 Tay was designed to “learn” over time, absorbing and integrating what people told it into its conversational streams. While exceptionally powerful, this capability ultimately backfired without the emotional cushion of background knowledge to recognize what it was saying. AI systems can end up sinking deeply into the mirror image of their creators. Source: Elle Hunt, “Tay, Microsoft’s AI chatbot, gets a crash course in racism from Twitter,” The Guardian, March 24, 2016 (http://www.theguardian.com/technology/2016/mar/24/tay-microsofts-ai-chatbot-gets-a-crash-course-in-racism-from-twitter).

5 Pegasystems acquired OpenSpan, based in Atlanta, in April 2016. Source: “Pegasystems Acquires Robotic Automation Software Provider OpenSpan,” Pegasystems press release, April 12, 2016 (https://www.pega.com/about/news/press-releases/pegasystems-acquires-robotic-automation-software-provider-openspan#sthash.TLtm8Kaj.dpuf).

6 With the RPA approach, NICE met service levels 100% of the time and improved accuracy to 99%. Source: Forrester interview with NICE.

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