How Cognitive Computing Unlocks Business Process Management's

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Cognizant 20-20 Insights

Business Systems & Technology How Cognitive Computing Unlocks Business Process Management’s Performance-Enhancing Virtues Extending process management to business logic offers enterprises increased flexibility, agility and adaptability in evolving and complex business ecosystems.

Executive Summary

The ability to successfully maintain momentum in any seamless partnership between humans and the machine economy requires processes that can sustain growth at environments in which they operate. scale. To achieve such status, supporting technology and By extending process management from process logic IT administration must be evaluated in the context of to business logic, a cognitive approach to business present and future states. process management (BPM) offers flexibility, agility What’s more, how business processes manage complex and adaptability in evolving and complex business activities, while also supporting continuous awareness ecosystems. This white paper describes a systematic of situations and real-time decisions, requires a approach to achieving cognitive BPM.

June 2018 Cognizant 20-20 Insights

BPM & cognitive computing in a nutshell

BPM refers to the systematic method to improve just as humans do. business processes. More often, it involves Cognitive computing accelerates, enhances and cohesive systems that go beyond the management scales human expertise by: of people and information. BPM experts study, recognize, manage, optimize and monitor business ❙❙ Understanding natural language (or sensory processes that support enterprise goals. data) and interacting naturally with humans. Over the years, these activities have evolved >> It provides non-biased advice, autonomously. significantly to include systems that can learn ❙❙ Reasoning (forming hypotheses, making at scale, employ logic and reason, and interact arguments and planning). naturally with human beings. We call this extended form of BPM “cognitive computing.” >> It interacts with and assists users by analyzing both content and context. Cognitive computing systems (referred to variously ❙❙ Learning (sensing and applying meaning). as robotic process automation, intelligent process automation, cognitive automation, cognitive agents, >> It creates new insights and value. etc.) are not explicitly programmed, but instead are ❙❙ Offering progressive support. trained like humans. They gain experience and hone >> It improves operational efficiency. processes over time, and manage both structured and unstructured data using artificial intelligence Cognitive systems can simulate human brain (AI) and machine learning (ML) algorithms. They can activity to solve the most complex problems in also adapt to new usages and formats in real-time, business process management.

Defining cognitive process

A cognitive process is one that makes BPM more businesses the potential for massive returns. In dynamic and probabilistic by enabling decision conjunction with social, mobile, analytics and management systems to understand, evaluate and cloud (SMAC), smarter processes are more than comprehend business events. just a tool for planning and execution; they are an intelligence engine that delivers cognitive decision- For instance, cognitive data management can fuel making based on operational insights in context. process automation with machine learning, offering

A cognitive process is one that makes BPM more dynamic and probabilistic by enabling decision management systems to understand, evaluate and comprehend business events.

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Over the years, these activities have evolved significantly to include systems that can learn at scale, employ logic and reason, and interact naturally with human beings. We call this extended form of BPM “cognitive computing.”

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Combining business processes with machine that insights from various devices are processed learning produces cognitive solutions that can efficiently and that the field service team is utilized enhance customer experiences. These solutions in the best possible way. These insights also help to compare the data that business activity generates optimize the process by automatically releasing a with data from other sources, enabling dynamic remote patch to a device, or by providing guidance and context-sensitive decision-making. This to customers with self-service steps. opens the door to an entirely new level of straight- The evolution of business process management is through processing. For example, in a predictive synonymous with the decades-long evolution of the maintenance process, machine-learning algorithms automobile industry. Just a few years back, driverless can be applied to sensor data to identify situations, cars seemed like fiction, but now they are nearing which indicate that a machine breakdown is reality. In the same way, basic workflows are evolving imminent. The cognitive business solution ensures into cognitive automated processes (see Figure 1).

The evolution of workflow automation

Basic Automation Robotic & Autonomic Process Cognitive Automation • Workflow CX-Aligned Process Automation • Autonomous decision-making • Macros Automation • Address common obstacles • New insights and data • Screen scraper discovery • Experience aligned of unstructured data and • Auto emailer • Personal and interactive workflow complex rules support driven by insights • Extensible and adaptive • Automation of complex & contexts prebuilt process object rules, electronic data libraries capture Linkage to Artificial Intelligence

Unstructured Data/Complex Rules Structured Data/Simple Rules

Structured Data/ Simple Rules Full Self-Driving Under All Full Self-Driving Conditions Under Certain A fully autonomous Conditions system enables the Limited vehicle to perform at Self-Driving Fully autonomous vehicles perform all the same level as a An automated driver critical safety driving human driver. assistance system for Driver Assistance functions and steering and The driver mostly has monitor roadway acceleration uses control over everything, conditions. Basic Automation but the car automatically information about The driver controls everything performs some specific the driving inside the vehicle – steering, functions. environment. brakes, throttle and power.

Figure 1

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Raw materials that fuel cognitive computing

Cognitive Business Cognitive Process Learning API-fication of Agent Automation Based on AI & ML Process

Cognitive Decision Intelligent Predictive and Cognitive Support Insights Adaptive Decisions Interactions

Knowledge- Email, Chat, Messaging Workflow BPM Case Intensive Ad-hoc, Unstructured Engines Engines Management Processes Processes

Unstructured Routine Processes Structured Process

Cognitive Process Enablement Mobile, Social, Communication (email, voice, video), Documents, Notes, Sensors Figure 2

Specifically, these capabilities can be bifurcated by: interaction, it can then communicate the results for a clear and orderly post-analysis. ❙❙ Enhanced decision-making and optimization: Cognitive computing enables a business ❙❙ Advanced intelligent automation: Cognitive process to make decisions on behalf of humans agents can process human interactions over any based on rich experience and large amounts preferred communications channel. Using AI of unstructured data. By digesting a myriad of and ML, these systems can effectively capture unstructured information, cognitive systems can insights and codify process specifications, inject intelligent insights into the decision-making revealing new automation opportunities that can process. Using predictive and adaptive decision be leveraged using robotic process automation capabilities, they also add value to preventive (RPA) to augment and mimic human intelligence. decision-making. Cognitive interaction improves When combined with application programming channels of communication by supporting interface (API)-enabled business processes, new channels and devices. For instance, the existing assets can be made available to business system can guide an individual through a partners, supporting innovative business models process or conversation and effectively leverage that shift the step cycle from “define-execute- that person’s channel preferences. After the analyze-improve” to “learn-plan-act.”

Cognitive process automation patterns

Cognitive decision support, cognitive interaction, ❙❙ Robotic process automation. cognitive process learning and cognitive process ❙❙ Deep integration to automate system steps. enablement help to automate business processes. ❙❙ Smart integration to leverage cognitive services Figure 3 explains several high-level patterns of and organizational APIs. cognitive business automation, including: ❙❙ Seamless hand-off between machines and humans. ❙❙ Robotic desktop automation. ❙❙ Cognitive agents for contextual conversations ❙❙ Automated decision-making based on rules and and anytime, anywhere interactions. analytics.

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Deconstructing cognitive process automation

BPM PLATFORM Automation Automate Automation Deep Smart Cognitive Leveraging Decision-Making Leveraging Integration Integration Agent Robotic Leveraging Rules, Robotic Process (Service) (API) Desktop Analytics Automation

Manual Operator Web Automation to Either Pull/Push Uses Robot to Complete Task Task by Robot Automate Manual Steps Final Decision is Gateway Made by Robot Final Decision is ESB Contextual Made by Human Coversation

IoT Blockchain Org.API Cognitive API

CLIENT Cognitive Robotic Desktop MACHINE application capabilities: Automation/ Understands human Business interaction Cognitive Step Automation Generates & evaluates Decision evidence-based hypothesis CLIENT MACHINE Adopts and learns Figure 2 from user selection

Figure 3

Cognitive process: A case illustration

The concept of cognitive BPM can best be capabilities to determine present stock and future understood through the lens of a real-life retail reorder levels. What happens if the manager wants example. Consider a retailer that has automated an this system to also make informed decisions based inventory system to manage stock inventory at a on customer feedback about a product? He may given time. The retailer uses BPM and operational deploy a cognitive system to analyze internal data decision management to carry out the operations. and social media content, such as Twitter, Facebook, Additionally, it maps business events to the process to Instagram, etc. to formulate a response. Based on capture the data required for monitoring the activity that response, he can then modify the cognitive and preparing reports. All these help the retailer’s process to either place an order for additional stock inventory manager understand, in real time, historic or suggest a better line of products to enhance the information and, eventually, make better business operations. Consequently, key benefits of this process decisions. This can be summarized as follows: include incorporation of customer-centric decision- making, enhanced customer satisfaction and smarter Let’s say an inventory manager applies business investment in products by companies. processes, decision management and reporting

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The automated natural processing journey

Cognitive Process Automation

Traditional BPM Cognitive BPM

Process that Does Process that Thinks Process that Learns

Core BPM Decision & Optimization Cognitive Capabilities Capabilities Capabilities

Cognitive Process Automation: A journey toward automated natural processing

Figure 4

Cognitive process transition and adoption

Transition from traditional business processing to and identifying process candidates through a cognitive business processing requires systematic cognitive opportunity assessment. execution and adoption. Figure 4 describes our proven ❙❙ Define: The next phase is to define actionable roadmap to cognitive BPM. insights captured from actual process usage and To be cognitive, the process must think and learn on top business pain points. These findings will help of the traditional framework. We break this down into catalog potential areas for cognitive capabilities, processes that: leading to plans based on the list and associated technology needs. ❙❙ Do, by enriching the traditional process with knowledge. ❙❙ Design: In the design phase, the future cognitive process model is identified along with a strategy ❙❙ Think, by enhancing the system with decision- to extract insights (“think” and “learn”) from non- making. structured data. The “think” strategy integrates ❙❙ Learn, by expanding the business with insights. available input sources and decision modules to support timely decisions based on relevant The overall approach can be subdivided into four high- data. The “learn” strategy depends on capturing level phases: decision outcomes and leveraging those insights to rectify issues. ❙❙ Discover: On a high level, the journey to cognitive processing starts with collaborative ❙❙ Develop: Finally, the identified, recognized and discovery to learn and define existing business explored capabilities are implemented using processes in a launch workshop (the “do” part). prototypes for testing in real-life use cases. This requires assessing organizational readiness

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A transformation approach to cognitive processes

Learn, Discover Plan Next Steps Interact, Integrate Develop, Probe, Sense

Iterative Journey with Continuous Improvements

Develop Prototype, Future Recommendations

Complete Develop: 35% of total tag">e ort Design Cognitive Process

Complete Design: 35% of total e ort Design Completed Deﬁne To-Be Processes

Complete Discovery: Deﬁne Completed Deﬁne Completed AS IS Process 15% of total e ort

Complete Discovery: Discovery Discovery Discovery 15% of total e ort Completed Completed Completed 15% 65% 30% 100%

DISCOVERY DEFINE DESIGN DEVELOP Design Cognitive Enrich the Processes Discover Process Define Process Models Process Models with Knowledge Define Cognitive Enhance the System Discover Knowledge Design Cognitive Capabilities Services with Decision-Making Expand the Business Discover Cognitive Need Define Automation Design Automation Strategy Model with Learning Insights • Process discovery • Define to-be processes • Design to-be processes • Develop to-be leveraging current based on levers • Identify cognitive services processes, UX, appropriate models, artifacts workshops • Define intersystem • Design appropriate integration & data • Check digital enable- dependency models (e.g., conversa- services ment readiness • Define scenarios for tion, decision, entity, • Use cognitive API • Validate process process automation, learning, etc.) toolkits for quick & easy leveraging cognitive context extraction, • Design cognitive & integration checklist cognitive interactions and automation experience experiences • Train models with sample • Identify agent-oriented, • Design user hand-o interactions cognitive and intelligent • Define KPIs & scenario business process recommendations • Apply continuous

METHODOLOGY • Design contextual model integration, deployment, • Gather appropriate • Deﬁne cognitive BPM testing & improvement samples for model model and collaborate cycles learning with system and cognitive (AI) models

Figure 5

From here, the iterative journey repeats the discover, define, design and develop cycle, enabling continuous improvement (as revealed in Figure 5).

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Automation maturity levels

COGNITIVE BUSINESS AUTOMATION STAGES IN ENTERPRISES

Improves Workflow Mimics Human Action Augments Human Intelligence Mimics Human Intelligence

ROBOTIC PROCESS ENHANCED PROCESS COGNITIVE PROCESS • Structured • Rules engine • Processing of • Natural language processing data interaction • Screen scraping unstructured data • Big data analytics • Optimized • Workflow and base knowledge • Artificial intelligence process • Machine learning • Large-scale processing

Figure 6 Business automation is integral to the improvement 4. Cognitive processing to mimic human cycle and requires four additional steps, including: intelligence (as depicted in Figure 6).

1. Optimized and integrated processing. Figure 7 highlights the steps and actions necessary to go from traditional business processing to cognitive, 2. Robotic processing to mimic human action. automated business processing. 3. Enhanced processing to augment human intelligence.

A recipe for process automation

DISCOVER DEFINE ROI Analysis Process, System, UI, Data Extraction Complexity Analysis Study Process Prioritization Queue Evaluation RPA Fitment Checklist Product Environment Analysis Selection Setup Concurrency Check, Work Separation Workshop & 4 Quadrant Process Data Beneﬁt Analysis Mapping Human Hand-o Collection Capacity Eligible Processes Analysis

Process Process Process Feasibility Define Robotic Architecture Automation Design Discovery Maturity Prioritization Study Road- Define Physical & Start Point map Check Readiness Deployment Arch. End Point Collect Current Utilization and Security Hands-on Design Customer Satisfaction Index Intersystem Dependency, Candidate Identification Enterprise Data Flows

DEVELOP DESIGN

Utility Building Design Process Flow Flow Building Task Assignment Strategy Continuous Monitoring Robotic Step Recording, Data Common Steps Review Audit Data Extraction, Handle Decision Preparing Infrastructure Cognitive Flow Design Validate KPI Cognitive Step Integration Monitoring Plan Identify Improvements Screen Switch, Continuous Unit Testing Log Conﬁguration Rule Interpretation Continuous Improvements Development Security Conﬁgurability Design Flow Design

Deployment Veriﬁcation Reusability & Source Control Auditing, Step Testing Management Integration Graph Regression Testing Decision Integration Automation Testing API Invocation Cognitive Flow Design Data Source Management Interactive Journey with Continuous Improvements Cognitive API Identiﬁcation

Figure 7

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Cognitive business processes applications

Cognitive business operations can be applied ❙❙ The human touch. Companies can use across industries and functional areas of an cognitive technologies to analyze information enterprise. For example: Cognitive business from customers in the form of letters, email operations can be applied across industries and or other communication. For instance, when functional areas of an enterprise. For example: handling customers with strong negative sentiments, companies can deploy sentiment ❙❙ Healthcare. Hospital care management systems analysis. This will help direct those customers can leverage data from social media to examine to the employees who can best serve them, the spread of diseases and track the outbreak which will in turn boost customer satisfaction. of epidemics. For example, during the outbreak In traditional BPM systems, this process eats up of dengue fever in a city, hospitals can monitor hours of labor, but with cognitive BPM, it can be Twitter feeds to identify symptoms experienced automated and expedited. by the public. Technologies such as geolocation can identify local tweets; natural-language For example, our digital contact center solution processing can be applied to determine which uses cognitive automation to provide intelligent tweets concern a particular ailment. Such assistance and preemptive capabilities to real-time analyses can help health insurance proactively anticipate customer grievances. It providers to track and predict outbreaks delivers a superior customer experience, enhanced and take proactive measures, such as urging cross-selling insights and reduced customer churn. community members to get vaccinated or stock ❙❙ Improved decision-making. In recruiting, up on supplies. managers faced with hundreds of applications for dozens of openings typically spend enormous ❙❙ Banking. In the field of banking, cognitive BPM is amounts of time trying to identify the best widely used to determine customer satisfaction. candidates, using just simple intuition and other For example, when customers are approved limited tools. Cognitive BPM can change all this, as for a loan, they are directed to the bank’s loan- it looks beyond the formal attributes of candidates servicing department, which ensures proper (such as their degrees or years of work experience) payment collection, as well as any changes to and incorporates more modern techniques of data the payment plan. This involves inbound and collection. By integrating IBM’s Watson Personality outbound calls that generate call transcripts. By Insights API – which uses linguistic analytics and applying cognitive analysis to this process, the personality theory to infer attributes from a person’s bank can then determine whether its employees unstructured text – with IBM BPM, a candidate’s are asking the right questions, how polite they digital fingerprints (or Code Halo as we call it) can are, and whether they are working efficiently. The be quickly analyzed for character traits and potential net result is inevitably a better experience for the red flags. This information can help managers zoom customer and the bank. in on the right candidates, quickly.

The “think” strategy integrates available input sources and decision modules to support timely decisions based on relevant data. The “learn” strategy depends on capturing decision outcomes and leveraging those insights to rectify issues.

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Quick Take

Applications in use across industries

One of our banking customers is leveraging cognitive capabilities such as cognitive interaction and expert bots as part of a contact center makeover that has reduced average call handling time by more than 8%, while supporting 5,000 users and 400,000 interactions per month. Cognitive BPM is helping the organization to reduce new agent training time by more than 20%. Similarly, we helped a healthcare organization in leveraging decision-making capabilities based on historical insights to assign claims to appropriate processors who can better serve similar types of claims more accurately and in less time. An insurance customer is applying cognitive process automation for payment processing. In this case, bots are interacting with various downstream systems such as mainframes, as well as machines running Windows-based applications such as Microsoft Excel, to reduce claims processing times.

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Cognitive process: Goals and benefits

Cognitive BPM supports self-learning and adaptive >> Intelligent business model leveraging BPM systems, enabling seamless interaction between cognitive capabilities. systems and humans to achieve better results. >> Support for additional workloads without Cognitive BPM achieves this in the following ways: increasing SME headcounts.

❙❙ Connecting customers, contexts and content ❙❙ Better results and customer experiences: through omnichannels. >> Accurate real-time process insights based on ❙❙ Implementing an anytime, anywhere and events across the enterprise. anything (AAA) process model. >> Removal of manual errors and discretion. ❙❙ Developing automated, adaptive and predictive decision-making capabilities. >> Aggregation of process insights across ❙❙ Establishing intelligent, connected and channels, devices, systems, geographies and contextual interactions with users. lines of business. ❙❙ Automating agent-oriented processes. >> Connected and personalized customer experiences. Organizations that have successfully implemented cognitive computing can expect the following benefits: The question is not whether organizations should adopt cognitive computing, but how. To achieve ❙ ❙ Improved productivity and reduced costs: success, organizations must identify existing in- >> Automation leveraging decision-making and house expertise in the context of an opportunity smart integrations. assessment, define areas where cognitive >> Contextual digital agent advisor for computing can add value, clarify use cases to augmented work capability. leverage these systems across the enterprise, build a business case around the application, assess >> Process automation leveraging cognitive agents. technology vendors that understand cognitive ❙❙ Increased revenues: services, and then implement and integrate the solution with existing business processes to >> API-fication of business assets such as modernize platforms and applications. processes and rules.

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Cognitive technologies make automation possible across all enterprise domains. The organizations that adopt these technologies today will have a distinct competitive advantage once the cognitive BPM revolution spreads.

Looking ahead

Traditional workflows based on predefined process and can drive any process automation, no matter logic offer little support in today’s complex and how complex. dynamic business environment. Now, in the cognitive Software vendors offer cognitive capabilities that keep era, BPM extends beyond traditional process BPM platforms informed, innovative and intelligent. automation and optimization, and is vital to the digital Seamless integration of current systems with business goals of both large and small organizations. platforms, such as IBM Watson, can truly digitize BPM. To get ahead with cognitive BPM, companies must Through high-volume data analysis, rational thinking have advanced end-user interfaces (UIs), and and self-learning, these technologies can unlock access to large volumes of business data that can benefits previously unattainable for businesses. generate the cognition capabilities necessary to Cognitive technologies make automation possible scale human expertise. across all enterprise domains. The organizations The continuous awareness, gradual learning and that adopt these technologies today will have a real-time decision-making of a cognitive approach distinct competitive advantage once the cognitive are essential to managing modern business needs, BPM revolution spreads.

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References

• “Cognitive Computing Defined,” Cognitive Computing Consortium, https://cognitivecomputingconsortium.com/ resources/cognitive-computing-defined/.

• “Rethinking BPM in a Cognitive World: Transforming How We Learn and Perform Business Processes,” https://researcher. watson.ibm.com/researcher/files/us-hull/Hull-Motahari-Cognitive-BPM-at-BPM-2016-v10.pdf.

• “Cognitive Computing ”IBM Research, http://researcher.watson.ibm.com/researcher/view_group.php?id=7515.

• Motahari Nezhad H.R., Akkiraju R. (2015) Towards Cognitive BPM as the Next Generation BPM Platform for Analytics- Driven Business Processes. In: Fournier F., Mendling J. (eds) Business Process Management Workshops. BPM 2014. Lecture Notes in Business Information Processing, vol 202. Springer, Cham “Cognitive Computing: What’s in for Business Process Management? An Exploration of Use Case Ideas,” https://www.researchgate.net/publication/322522862_ Cognitive_Computing_What’s_in_for_Business_Process_Management_An_Exploration_of_Use_Case_Ideas.

• “The Fourth Industrial Revolution – Cognitive and the Future of Work,” Medium, September 15, 2017, https://medium.com/ the-future-of-financial-services/the-fourth-industrial-revolution-cognitive-and-the-future-of-work-c07d4425c24f.

Endnote

1 Malcolm Frank, Paul Roehrig and Ben Pring, Code Halos: How the Digital Lives of People, Things, and Organizations are Changing the Rules of Business, John Wiley & Sons, April 2014, http://www.wiley.com/WileyCDA/WileyTitle/ productCd-1118862074.html.

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About the authors

Harish Dwarkanhalli Senior Vice President, Cognizant Salesforce and Digital Customer Experience

Harish Dwarkanhalli is the Senior Vice President and the Global Delivery Head of Integrated Process Management, Salesforce and Digital Customer Experience practices in Cognizant’s Enterprise Application Services business unit. In his 21-year tenure at Cognizant, he has held numerous key positions in relationship management, account management and delivery management across multiple industries and technologies. In his current role, he is responsible for shaping and driving business strategy, technology innovations and delivery management across the mentioned practices. He is passionate about exploring how enterprises can transform business models and drive value innovation through the nexus of digital technologies. He can be reached at [email protected] | https://www.linkedin.com/in/ dvharish/.

Mohan Ananthanarayanan Chief Architect, Cognizant Enterprise Applications Services’ Integrated Process Management (IPM) Practice

Mohan Ananthanarayanan is a Chief Architect within Cognizant’s Enterprise Applications Services’ Integrated Process Management (IPM) Practice. He serves as the leader for IBM (integration and BPM) as well as its digital integration practices. Mohan has about 20 years of experience in middleware integration, business process management, and other digital systems and technology-related integration, including cognitive service offerings, covering strategizing and incubating new business segments, product offerings development and delivering large programs. He can be reached at Mohan.Ananthanarayanan@cognizant. com | www.linkedin.com/in/mohanananthanarayanan/.

Arindam Mazumder Senior Architect, Cognizant Enterprise Application Services

Arindam Mazumder is a Senior Architect within Cognizant’s Enterprise Application Services business unit. He has over 14 years of experience in IT solutions, delivery and consulting – predominantly in the healthcare, banking and financial services, as well insurance industries. He has extensive experience in BPM and integration technologies, and serves as a connected enterprise and process architect for IBM digital transformation technologies, cognitive process management and hybrid integration. He can be reached at [email protected] | www.linkedin.com/in/arindam-guha-mazumder-93aa60124.

15 / How Cognitive Computing Unlocks Business Process Management’s Performance-Enhancing Virtues About Cognizant Business Consulting With over 5,500 consultants worldwide, Cognizant Business Consulting offers high-value digital business and IT consulting services that improve business performance and operational productivity while lowering operational costs. Clients leverage our deep industry experience, strategy and transformation capabilities, and analytical insights to help improve productivity, drive business transformation and increase shareholder value across the enterprise. To learn more, please visit www.cognizant.com/consulting or email us at [email protected].

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