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Are Bots the Second Coming of BPM?


There is an interesting discussion initiated by Peter Schooff @bpm.com

Are Bots the Second Coming of BPM? What do YOU think?

My Thoughts:

Bot adoption is definitely growing exponentially (if not on implementation in many places, in discussions for real). Sometimes it is a bit chaotic too – as everyone leverages the buzz words like bots, chatbots, ML, NLP, AI, RPA and many more to reach the nirvana state instantly in their enterprise. It’s a good thought – appreciate it, but not all enterprises need a bot for their specific business scenario and it is a journey. It is important to do a reality check if Bots is what you need or just automation.

Bots do complement the processes and provide some breathing space in scenarios like:

  • Developing “Self-Healing processes“, where the system understands and learns to resolve an exception or issue (based on predictive Analytics and historical data)
  • Chatbots – for enhancing customer experience and round the clock support
    • Overcoming the mundane tasks of a customer on boarding process (monotonous & manual intensive)
  • Contact Center applications – avoiding hand-offs, tabbing multiple applications and tedious data entry
  • ..many more

Bot adoption in an enterprise is not a mandate, instead, it’s a trade-off between Customer Experience (if the business really needs it) vs Maintainability (with investment + supporting yet another set of robotic process). It should be adopted judiciously.

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Bots can be considered as a Segway for Business Processes. If the nuts & bolts of the Segway are set-perfectly-right complementing the Business Process riding it, it can help you cover a great distance swiftly – enriching the customer experience; else you never know where you will finally end up, it could even be the bumpy roads of the enterprise or customer sentiment dismantling it”

Happy Learning!! 🙂

Image Source: link1;  link2

What’s your take?? Any thoughts!

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Where Do You See Robotic Process Automation Having the Biggest Impact?


Where Do You See Robotic Process Automation Having the Biggest Impact? #BPM

There is an interesting discussion initiated by Peter Schooff @bpm.com

My Thoughts:

Every Organization has two types of workforce – Head-Down Workers and Knowledge Workers
• Head-Down Workers, perform their duty based on Standard Operating Procedures (SOPs) – this gets monotonous and routine job over time.
○ Example: If we consider a Customer On Boarding Process, it will be a performed, by opening the same form over and again, filling in the details, validating and verifying the IDs and submitting it for approval. The Reviewer, on the other hand, will go through the form details and approve or reject. There is NO EXTRA INTELLIGENCE required for dealing with such a scenario. It is a defined and a streamlined process A-B-C or A-B-D.
• Knowledge Workers, on the other hand, apply intelligence for their judgment and actions. It may or may not be a standard procedure.
○ Example: If we consider an Underwriting or Healthcare Claims Fraud kind of a scenario.  Even though there are standard procedures defined, but still a Person has to validate it based on the customer’s past history, transactions, relationship, health conditions etc etc, before taking a judgment for approving/rejecting a request.

If we map it to automation techniques/terminologies for enabling Workforce Productivity. It will be something like

[Head-Down Workers] : [Robotic Process Automation] : : [Knowledge Workers] : [Cognitive Intelligence or AI]

The journey to AI (“Nirvana State” which every enterprise strives to achieve) can be broadly classified as:
→ BASIC COMPUTING [scripts + repetitive steps in a single application]
→ ENHANCED COMPUTING [rpa + monotonous repetitive job across applications]
→ COGNITIVE COMPUTING [machine learning + analytics]

Detailing it further:

  • Basic Automation :
    • Human with tools | structured data sets | Goal: Labour Efficiency
  • Robotic Process Automation [RPA] :
    • Human augmented with Robots | unstructured + patterned data sets | No Decisioning (targeted for Head Down Workers) | Goal: Labour Efficiency
  • Autonomics :
    • Robots augmented with humans | unstructured + patterned data sets | Goal: Labour Elimination
  • Cognitive Computing :
    • End to end robots with human oversight | unstructured + NO patterned data sets (targeted for Knowledge Workers) | Goal: Labour Elimination
  • Artificial Intelligence – AI :
    • Fully automated with NO human involvement | unstructured + NO patterned data sets  (targeted for Knowledge Workers) | Goal: Labour Elimination

To precisely answer the question:
Robotic Process Automation has a great impact to business in scenarios where manual/mundane and routine activities are being performed. The task force allocated for mundane activities can be utilized for more intelligent activities.
Some of the typical use cases to cite Customer Onboarding (AML, Credit Check, KYC etc); Loan Processing; Payment Processing; Financial Reporting (periodic); Reconciliation checking process; Multiple sources of data extraction & reformatting etc.

Simply put – Robotic Process Automation is primarily targeted for “Keyboard Warriors!!” – showing vengeance with every keystroke for form data entry

In addition, most of the RPA tools have a concept of “Control Room” – a dashboard similar to a helicopter cockpit with all the levers for the Robotic Process Automation defined for all business scenarios. This helps the Business have control and have a hawk eye on the system, than presuming that control & automation has completely slipped from their hands. Control Room also helps Business to have an incremental approach to enable RPA processes in a staged manner by capturing the ground info than going with a big bang approach [which may be risky – as in some cases emotional/sentimental things are involved]

Interesting point by Siva in the discussion thread:

“Applying RPA to a broken process just makes a bad process run faster”

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With recent news on Introduction of “Robot Tax” [link]. The next impact area for Robotics will be the Financial space and enterprises will hunt for Financial Advisors 🙂

The ROBOT TAX is primarily to compensate the unemployment in the market as a result of automation and meet demands for public/Govt initiatives/programs like bridge/healthcare/road development etc.

 

What’s your take?? Any thoughts!

Similar Topic:  How Do You See the Relationship and Interplay Between AI and BPM in the next Few Years?

Happy Reading:-)

Image Source: link  link

Uberization of Insurance Industry!


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In recent times, start-ups and disruptive technologies/innovations have set a mandate for all the industries to have a hawk-eye on the market trends and its impact. The veteran and the notable Fortune 500 groups are given tough times by the mushrooming tech giants. Companies can no longer take a back seat and relax.

It is good to be wise and be proud of the experiences & achievements in the past, but most importantly be vigilant of the present and have a defined vision of the future to sustain! and have existence

The technology adoption and re-incarnation of business strategy/priorities to serve the customers will definitely play a crucial role in the Insurance Company’s journey in making it stand tall and strong in the crowd (as a differentiator).

Following are a few highlights of the “Disruptive Trends” the Insurance Industry is trying to adopt for improved Customer Experience[Cx] and reducing Operational Expenditure[OpEx]:

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  • Rise of InsurTech
    • Similar to FinTech organizations, there has been a rise of InsurTech start-ups [leveraging latest technology and innovation] trying to replace or enhance the usage of insurance services of incumbent companies.
    • InsurTech solutions bring in an incremental or radical / disruptive innovation development of applications, processes, products or business models in the insurance services industry
    • It gives the firms a mix of – Trust built over the years by Insurance Companies & Differentiated experience by newGen Start-ups
    • Enables development of Faster Go-To-Market (GTM) solutions than developing age-old legacy systems and maintaining it over time (costly affair)
    • Alliance accelerates change and transforms the way to think, develop and satisfy the needs of the customers – will foster more collaborations in the futue
  • Making Big Data Actionable
    • “Data” is a powerful currency in the race for fintech supremacy.
    • In addition to gathering data, making sense and actionable items out of the data heap by leveraging contextual data analytics, intelligence, big data will make a difference for the customers and the financial institution as a whole.
    • With enormous data in store, data lake kind of concepts can be adopted and harnessed to reap better benefits
    • Machine learning capabilities can be topped-up with the real-time analytics to form the icing on the cake and help in making human-like decisions
  • Virtual Assistants Chat Bots or Robo Advisors:
    • It is crucial to understand the customer and suggest products for cross sell/up-sell – based on adaptive(real-time) & predictive(historical) analytics on the transaction/similar transactions for prospective customers
    • It is like providing the right product, to the right customer at the right point in time
    • g.: similar to Apple’s Siri; Google Now; Amazon’s Echo
  • Robotics Process Automation[RPA] / Smart Process Automation[SPA]
    • Leveraging RPA / SPA solutions to build Workforce Productivity Solutions [ around areas where there a monotonous, mundane and manual intensive tasks are involved]
    • Typical scenarios are: data entry; head-down worker activities; reconciliation process; on-boarding new customers; sending notification/intimation
    • This helps in reducing the operational expenditure of the organization and improve the workforce productivity
  • Blockchain Technology
    • Blockchain technology provides a shared, trusted and secure public ledger to record financial transactions / digital assets and ‘smart contracts’.
    • These are recorded independently – distributed across a multitude of computers around the world.
    • The records are condensed (into blocks) and interlinked (to form chains), using complex cryptographic algorithms.
    • There is no third party required for secured transaction
    • The verification of data for primary applicant or reinsurance can be validated by leveraging block chain technology model – this will reduce the complexity and tedious ledger process
    • Automated smart contracts can help in quick validation of identity and limited bureaucracy
    • Peer-to-Peer Insurance models or Smart Policies can be envisaged[ based on data feed for climatic conditions by Meteorological Dept. pay-outs can be done or initiated for crop/agricultural insurance]
    • Key areas where it can be leveraged in Insurance sector:
      • Smart Contracts
      • Customer Identity Validation / Verification
      • Regulatory and Compliance Benefits [Audit]
      • Smart Underwriting
      • Fraud Management
  • Digital Data as a Service [Microservice based model – functional segregation of business]
    • Leveraging the Microservices ways of working / implementation to expose some common functionalities and processess as a service
    • Few services for example: getting insurance details, capturing policy details, policy payment etc.
    • A standard API layer with a SOAP/REST protocol can be can be leveraged to access the functionality from multiple devices / external or other legacy systems
    • With this approach – the concentration and focus can only be on the Business Functionality – than building the same functionality for multiple applications / customizing or maintaining it.
    • This will help in avoiding development of monolithic application
    • It will also give rise to new breed of providers offering data on a subscription model
  • Mobility
    • Mobility or omni channel experience has already been adopted by some of the major insurance companies
    • More personalized and advanced features with a good customer experience will make a difference
    • Mobile Health Apps to gather data from the customer and monitor the health – thereby reducing the spending on healthcare and importantly enable insurance companies to understand the customer’s risk profile
  • Omni-Channel & Opti-Channel Delivery
    • An ‘opti-channel’ experience delivers solutions using the best (optimum) channel based on the customer’s need and preferred channel
    • This delivery model is beyond multichannel (delivery on multiple platforms), or Omni channel (delivery through all channels similarly)
    • The proliferation of channels will begin to consolidate and improve in efficiencies
    • Designing of “Digital Persona” is a key component
    • This helps in targeting right customer, at the right time, with the right offer via the right/preferred channel
  • Driverless Car [defining new policies]
    • With the driverless cars hitting the road – definitely the insurance policy model needs to be revisited [as there will be no human driving it – to claim whose fault]
    • Variation based on regional regulatory and compliance will add other dimensions
    • For eg: things like black-box in the car similar to ones used in aircrafts can make a difference
    • There will be incremental changes to the policies based on the adoption and faith the human race gains over machines
  • IoT [eg: Wearables, Devices]
    • The Internet of Things’ is becoming a buzzword and the technology trend with repercussions across the business spectrum
    • It opens up a new world of opportunities by connecting the internet with billions of devices – wearable gadgets, fancy vehicles, fitness gadgets or industrial equipment
    • Sensors, Beacons, Wearables and Devices etc generate humongous amount of data which can be leveraged, aggregated and analyzed by financial institutions to improve operational performance, customer experience, and product pricing
    • The dump of data gathered from these devices on a daily basis can be instrumental in defining new services, improve efficiency or achieve other health and safety benefits
    • We hear a lot about Smart Home, Fitness Trackers etc. IoT kind of models can be leveraged to optimize and provide customer specific service [house insurance, vehicle insurance or personal health insurance]
    • And importantly, with data in hand the Insurance Providers can either help or challenge the customers [eg: in healthcare industry with fitness gadgets]
    • With advantages that can be reaped from the data are also associated security, privacy & risk concerns areas
  • Leveraging Advanced Machine Learning & Artificial Intelligence
    • Machine-based learning is described as the science of getting computers to act without rules-based programming
    • Cognitive computing capabilities and development of algorithms that team themselves [self-healing processes] are an integral part leveraging Machine Learning
    • The data gathered via IoT [structured + unstructured] can be put to use by crafting ML[Machine Learning] algorithms
    • Natural Language Processing – NLP can also be leveraged for providing a more customized / personalized experience
    • The Data & Algorithms can help in defining the Digital Persona of the customer
  • New Payment Models
    • With the ease of regulations, we are back in the era of Money Virtualization
    • Every section of the industry food, travel, ecommerce etc. have come up with the Mobile Wallet features – making life easy for the customer to move without carrying cash/coins/cards
    • Customers demand powerful services to be delivered at the swipe of a smartphone screen, wherever and whenever they happen to be. As it is delivered in the more efficient way – it is getting easier for them to step over the inertia of the traditional banks
    • As many players are entering this space – there is a race for dominance. Insurance Companies can’t walk solo with their offerings, collaborative partnership with mushrooming mobile wallets is the key
    • This will help them to : enter competitive market space; save cost; ease of operation; customer demand
  • Contact Centre Modernization
    • Customer Experience
      • Customers are dissatisfied with their customer service experiences
    • Better Service
      • Providers struggle with critical service and support capability gaps (e.g.: Mobility, outbound emails, personalization etc.)
    • Futuristic Platform
      • A new generation of “social” customers is setting the agenda for contact centers of the future.
    • Competitive Market
      • Organizations are taking the first steps toward building next-generation customer management platforms
  • Usage based Insurance Models [PAYD, PHYD]
    • Auto insurers are shifting towards usage-based insurance models that will help them to enhance claims handling capabilities and perform better customer segmentation
    • The insurance premium will be calculated based on usage and/or behaviour
    • Vehicle Telematics [in car installed devices for sending data at real time] will be leveraged to estimate the usage, driving pattern and driving behaviour
    • Some of the models can be;
      • PAYD – Pay as You Drive – Insurance premium is calculated based on the number of kilometres/miles coved by the vehicle
      • PHYD – Pay how You Drive – Insurance premium is defined based on the driving pattern/style
  • Gamification
    • Games are a great way to engage the customers across all age groups
    • Insurance companies are adopting gamification to simplify the complex and tedious processes – this in turn enhances the Customer Experience, training and adoption
    • Gamification uses strategies like points, challenges, leaders board, incentives and different levels of engagement
    • It is an integral part of the insurer marketing campaign
  • Use of Aerial & Digital Imagery
    • Insurers have started using aerial and digital imagery for accessing the property and other relevant details
    • This helps in reducing the claims processing time
    • Eg.: for a house insurance – aerial and digital imagery can help in getting the exact dimension details, location, proximity to identified risks [if any] – e.g.: seismic zone for earth quakes
    • Very helpful for remote locations and primarily for Agriculture based Insurance [for farmers] – Unmanned Aerial Vehicles – UAV [Drones] can be leveraged
    • There may be regulatory and compliance challenges which needs to be addressed in case of Drones [to avoid infringement related issues]
  • Patient Adherence Apps or Patient Care Monitor
    • Non adherence to routine medicine intake or timely check-up might lead to increased healthcare spending for the Customer and at times also hits back to the insurance companies
    • With Apps for Care Monitor the patient’s adherence towards medication will improve
    • These apps regularly follow-up with the patients for medication, treatment and check-up via games and reminders
    • The objective of these apps is to: remind; follow-up; educate; simplify; counsel; reinforce
    • The data gathered will be helpful to provide incentives to patients who follow medication regularly and on a timely basis.
  • Establishment of “Insurance Innovation Labs”
    • The marriage between the traditional insurance and new age start-ups give rise to insurtech “innovation labs” or “digital factory”
    • Innovation Labs envision an evolutionary process that re-examine the original purpose of the business (institution) before altering the DNA to redefine the purpose to go beyond the original intent.
    • This establishment creates an open space to research, develop and showcase creativity and connect with the customers in enhancing the experience
    • This develops a curiosity factor and an experimental approach with the vision of embarking on the digital journey
    • The labs can be used to define new opportunities and to test the hypothesis
    • It also creates a platform to engage customers with technology / business related discussions, different from the routine transaction related activities
    • Insurance Innovation Labs can help in defining:
      • Strategic / business thinking – with a focus on business and brand
      • Design thinking – product or service creation
      • Agile – technological design
      • Human / Customer centred design – interface, environment, product design
  • Virtual & Augmented Reality[AR]
    • The year 2016 was remarkable in terms of the excitement, craze and the impact Virtual & Augmented Reality can bring for any business model [How can we forget Pokemon Go]
    • Augmented Reality is a technology that generates sound, video or graphics over real world environment and thereby enhancing the people’s experience.
    • Customers are tired of the same marketing models and customer service [ via Contact center call or printed/scanned flyers and brochures]
    • VR/AR will be a new space to excite the customers and help them understand the policies/products better
    • Customers no longer have to browse through multiple links; flip through multiple pages of the attachments; presume something or spend time in calculating the premium and selecting the right product
    • Augmented reality has the potential to bring a paradigm shift in the insurance sector and many of the advanced-thinkers had already started adopting the technology as a major marketing tool.
  • Others Trends to watch-out and Adopt
    • Leverage Telematics in vehicles to gather data and communicate at real-time
    • Connected Health – Stitching the data from wearable and other fitness devices to analyse and recommend the best policy for an individual
    • Providing Next-Gen Customer Experience
    • Developing Customer Centric Applications (primarily self service enabled – eg: Kiosk)
    • Welcome & Leverage Open Source Stacks (OSS)
    • Crowd Sourcing Initiatives
    • Improvise efficiency and reduce operational expenditure by adopting DevOps

  • Original Image Source : Image

Interesting Read Articles & References:

Keep Reading, Keep Researching & Keep Blogging!!

Please do share your thoughts and views to enrich it!

Happy Reading! 🙂

Disclaimer: Views my OWN not my Employer’s

Image Source

[The intent of using the images was to pictorially share the thoughts and share the learning. Happy to share Credits for the photos and images]

Related posts: [old blogs]

How Do You See the Relationship and Interplay Between AI and BPM in the next Few Years?


There is an interesting thread started by Peter Schooff @ BPM.COM Forum – click here

Some really nice thoughts and comments/links.

My Thoughts:

MyPoV : How Do You See the Relationship and Interplay Between AI and BPM in the next Few Years?

The state we are in the BPM (Business Process Management) roadmap, was not realized overnight. It is getting enriched day-by-day by rattling with BPM in the enterprise playground with experience, learning, implementations, failures, scenarios and tagging along mushrooming disruptive technology trends. BPM with its inception as a process modeler/development /integration/orchestration/BAM etc. has matured as an enterprise wide platform to meet [more or less] the enterprise demands of transformation/mobility/decisioning/ACM/next best actions/mobility/social/analytics etc.

The same holds good for AI/Cognitive Computing. AI (“Artificial Intelligence”) is undoubtedly the “Nirvana” state which every enterprise/organization is trying to achieve as the final destination. But it does not happen over a blink of an eye, instead it is an evolving journey.

The journey to AI can be broadly classified as:

BASIC COMPUTING [scripts + repetitive steps in a single application]

ENHANCED COMPUTING [rpa + monotonous repititive job across applications]

COGNITIVE COMPUTING [machine learning + analytics]

  • Basic Automation :
    • Human with tools | structured data sets | Goal: Labor Efficiency
  • Robotic Process Automation [RPA] :
    • Human augmented with Robots | unstructured + patterned data sets | No Decisioning (targeted for Head Down Workers) | Goal: Labor Efficiency
  • Autonomics :
    • Robots augmented with humans | unstructured + patterned data sets | Goal: Labor Elimination
  • Cognitive Computing :
    • End to end robots with human oversight | unstructured + NO patterned data sets (targeted for Knowledge Workers) | Goal: Labor Elimination
  • Artificial Intelligence – AI :
    •  Fully automated with NO human involvement | unstructured + NO patterned data sets  (targeted for Knowledge Workers) | Goal: Labor Elimination

When we talk about the relationship and interplay between BPM & AI in next few years, the targeted enterprise audience is presumed to have matured over “enhanced computing” and addressed/identified all the underlying challenges w.r.t. monotonous manual intensive repetitive jobs/activities.

ai_bpm

Some of the interesting use cases that enterprises can adopt based on the BPM + AI/Cognitive Computing duo are:

  • General
    • Developing Self-Healing Processes [process optimization, exceptions and anomalies that are resurfaced during execution being auto corrected based on the past resolution steps → analytics & machine learning driven]
    • Evidence based learning – data driven
    • Adaptive and Predictive analytics + Past scenario based Actions [Machine Learning] for decisioning
    • Virtual workforce controlled by Business Operation Teams
    • Handwriting to Text or Speech (Identification & Learning Graphology Techniques)
    • Debugging, Troubleshooting and Solution Wizard
    • Text & Mail categorization/recommendation
    • Support Issues and enriching KeDBs (Knowledge Error Databases)
    • Self-Driving Cars – by building artificial intelligence and algorithms
    • Image Processing
  • Banking / Retail / Telecommunication
    • Identifying Prospective Customers and Partners
    • Satisfactory index of the Customer (based on relationship, transaction, marketing campaign etc.)
    • Fraud, Waste and Abuse of Claims
    • Forecasted Credit Risk and credibility of the customer
    • Effectiveness of a Marketing Campaign
      • Eg: How many accepted the offer and how many rejected it. Any decisive factors leading to acceptance.
    • Cross Selling and Recommendations
      • Eg: Ecommerce sites : People who purchased this product also purchased this
    • Contact Center (helps the CSR to engage the customer during the call with the relevant data)
      • Eg: We have seen that you have ordered the cheque books to a separate address (different from the registered address) – would you like to change your Address Details
  • Healthcare & Life sciences
    • Scanning & Screening –  Biometrics
    • Drug Discovery based on the component mix
    • Diagnosis and remediation based on the Symptoms, Patient Record and Lab Reports
    • AECP – Adverse Event Case Processing Scenarios based on drug, patient, geo, climatic conditions, past history, food intake etc.
  • Security
    • Handwriting / Signature / Fingerprint / Iris / Retina Verification
    • Face Recognition
    • DNA Pattern Matching
  • ….and many more

Definitely, there are concerns in adopting the Artificial Intelligence on the Day-1 [it may not be a cake walk]. There are lot of factors that are getting disturbed from our traditional paths, and it is only a matter of time for the thoughts to sink , the dust around the buzz to settle down and most importantly GETTING the CONFIDENCE of RELYING BLIND-FOLDED on a MACHINE/ROBOT.

To cite a few scenarios: Are we comfortable and confident enough to sit in a driverless car or airplane? Or are we fine as a financial institution to manage all our high-profile privileged customers based on an algorithm? May be / May be NOT always.

To summarize,

  • it becomes crucial from organizations to define the a bucket or business scenarios which can be an eligible candidate for BPM/Process & AI – avoiding RISKS that can have catastrophic effect on the customers/organization. To be precise, the RISK of Loss should not be more than the investment on AI.
  • time and exhaustive scenarios are the key factors that will enrich the intelligence of the system based on real time transactions good[favorable] or bad[un-favorable] – is the business prepared for the same?
  • it is important to have a balance between the enhanced customer experience and the operational cost reduction with virtual workforce

The business benefits that Enterprises can reap by augmenting BPM with Artificial Intelligence are:

  • Reduced Operation Cost
  • Elevated Customer Satisfaction / Experience
    • Right Product to the Right Customer at the Right Time via the Right Preferred Channel
  • Reduce Customer Churn
  • Personalization through Prediction and Intelligence
  • Increased Workforce Productivity
  • Help organizations unlock the value of the wealth of data they have in-house
  • Close the gap with the new online providers by offering real-time decisions

New terminologies like SPA [‘Smart Process Automation] are also coined, considering the process and cognitive computing/AI duo. Enabling the Process to select the best performing algorithm on the fly.

What is your take – How Do You See the Relationship and Interplay Between AI and BPM in the next Few Years?

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Happy Learning 🙂 

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