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RPA and BPM – The Twain Shall Meet after All | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

It was not long ago that I was talking to a German manufacturer about the relative merits of different types of automation solutions on the market. The client did not want any services-layer, API or connector-based process integration. He said those were in the realm of Business Process Management (BPM) and IT. That is why he was going for Robotic Process Automation (RPA), for integration through the user interface. We discussed the pros and cons of these different approaches – but the point is that he was looking for an alternative to traditional BPM. He, and many others, have come to view RPA as that alternative. Yet, recent announcements by leading vendors show that RPA and BPM are coming together. Announcements by IBM and Automation Anywhere, and Appian and Blue Prism, indicate that we have really come full circle and that the RPA and BPM twain have already met.

This was inevitable:

  • The recent success of RPA was a bolt out of the blue for the BPM market, distracting and taking away many potential customers and reaching business users that BPM providers could only dream about. BPM vendors had to take steps to protect their share of the market
  • The growing scale of RPA deployments is another driver for the twain to meet. It is one thing having a few robots running basic processes, but as organizations’ automation ambitions have become loftier, the need for integration with workflow to increase control and orchestration has grown too
  • Robotic Process Automation is not the answer to all automation requirements and, therefore, combining it with BPM for a full set of capabilities to handle different situations is a no brainer. Some of the most successful automation deployments combine RPA with BPM-based large strategic system integration and transformation. In these scenarios, RPA complements the BPM integration by connecting core business platforms to other disparate enterprise systems

IBM and Automation Anywhere

With their announcement, IBM and Automation Anywhere have taken their partnership to the deeper level of integrated offerings:

  • IBM will include Automation Anywhere Enterprise edition in its BPM software catalogue. Currently BotFarm and Automation Anywhere’s cloud offerings are not included
  • It will resell and support Automation Anywhere
  • IBM will integrate Automation Anywhere with the software becoming a part of its IBM Digital Process Automation platform. This included IBM Business Process Manager (BPM) and IBM Operational Decision Manager (ODM)
  • Automation Anywhere will be the standard RPA software offering unless clients ask for another

As things stand today, IBM Digital Process Automation orchestrates processes between core systems while Automation Anywhere RPA automates repetitive rules-based tasks. IBM’s vision for the future is that BPM and RPA will be integrated into a flexible offering with software, services and consultancy provided from a single source. In the future, we will see IBM add cognitive capabilities to this mix. The question is how much of Automation Anywhere’s intelligent capabilities will feature in IBM’s software catalogue.

While the move by IBM to build this partnership is part of the maturing RPA market, it must have been partly driven by a move by its other major RPA partner, Blue Prism, to join forces with Appian, a BPM vendor with whom Blue Prism has built deeper software integration. Last year, another BPM player, Pega, acquired Open Span, which also offers Robotic Process Automation.

An additional driver is that RPA offers integration at a relatively low cost of entry, and this partnership allows IBM to bring in customers at a lower starting point to traditional BPM projects.

Appian and Blue Prism

This week, Appian and Blue Prism, which, had already built some plug and play capabilities together, took their relationship to the next level with the announcement of an extension to Appian’s platform that is based on RPA from Blue Prism. The partners are also aiming for a one-stop-shop to all automation requirements and seamless integration between their combined BPM and RPA products.

Interestingly, the Blue Prism partnership with IBM is going on, unaffected by these pairings. The groups involved are different: Blue Prism started in IBM’s Global Process Services and expanded to GBS Digital. Automation Anywhere’s relationship is with IBM Software.

It is important to note that the Appian move is part of Blue Prism’s strategy to turn its software into a platform that other solutions can be plugged into easily. The Blue Prism Technology Alliance Program (TAP) will see integrated offerings from partners in cloud, virtualization, analytics, process mining, artificial intelligence including computer vision, as well as BPM. IBM is a TAP partner. Others, include Celaton and Instream, its intelligent automation software.
These alliances open new opportunities for Blue Prism, for example, to handle processes that use unstructured content and to access services that are run on cloud solutions. In summary, interoperability is going to be a key feature of the Blue Prism platform and the Appian move is a major step in that direction.

Everest Group has addressed aspects of automating different levels of processes with different solution types in a paper titled “Pushing the Dial on Business Process Automation”.

Everest Group has just positioned IBM as a Leader in a PEAK Matrix™ assessment of Business Process Services Delivery Automation (BPSDA).

I Can’t Get No Satisfaction – The CSAT View of RPA in BPS Contracts | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

Everest Group’s latest research shows that while there is growing adoption of Robotic Process Automation (RPA) within Business Process Services (BPS) contracts, customer satisfaction (CSAT) with service providers’ is distinctly average at 3.6 out of 5. Service providers need to do more to achieve better CSATs.

Everest Group’s research titled Business Process Services Delivery Automation (BPSDA) – Service Provider Landscape with PEAK Matrix™ Assessment 2017, which assesses the automation capabilities of leading service providers, shows that the number of automation proofs of concept run by service providers for their BPS clients has on average quadrupled in one year. Furthermore, the number of BPS contracts with automation has gone above 1,000. Yet, the scale of deployments is small; the average number of robots deployed per BPS client hovers at just below 10.

Unsurprisingly, at 85%, the vast majority of deployments are robotic process automation as opposed to automation based on Artificial Intelligence (AI).

The other finding from the report, based on interviews with reference clients of the service providers shows that CSAT with service providers automation services is fair to middling. The average overall score was 3.6 out of 5. Clients rated the need for RPA skills very highly with service providers achieving 3.9 for their RPA related services. The scores were dragged down by the CSAT for AI capabilities that scored only 3.1.

The kind of issues that the reference clients reported were mainly related to the immaturity of RPA in the global services market and the skills for deploying it. Examples of feedback include:

  • It feels like they used us as a training arena for some of their staff
  • They (the BPS provider) should communicate opportunities better. It feels like they were late to bring this to us
  • They took a long time to learn how to code in xyz RPA software. It took a long time to integrate the RPA with our systems
  • The service provider should have done more due diligence on the RPA technology vendor
  • Change management and governance need improving

What can we expect with Robotic Process Automation?

Some of this dissatisfaction is a result of the hype in the market about the ease of robotic process automation deployments and rapid returns on investment. Clients have high expectations from all RPA projects, and this is showing in projects that they deploy for themselves or through system integrators as well.

The good news is that service providers continue to invest in automation. On average, 60% of service providers’ technology staff are working on automation products, solutioning and related services. This will enhance their skills and capabilities in SDA technologies, both RPA and AI.

We expect to see skills grow alongside the market in the coming months. We’ll be watching this space closely to provide our clients with updates over the year.

Explainable AI? Why Should Humans Decide Robots are Right or Wrong? | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

I have been a vocal proponent of making artificial intelligence (AI) systems more white box – able to “explain” why and how they came to a particular decision – than they are today. Therefore, I am heartened to see increasing debate around this. For example, Eric Brynjolfsson and Andrew McAfee, the well-known authors of the book, “The Second Machine Age,” have increasingly spoken about this.

However, sometimes I debate with myself on various aspects of explainable AI.

What are we explaining? If we have a white box AI system, a human can understand “why” the system made a certain decision. But who decides whether or not the decision was correct? For example, in the movie “I, Robot,” the lead character (played by actor Will Smith) thought the humanoid robot should have saved a child instead of him. Was the robot wrong? The robot certainly did not think so. If humans make the “right or wrong” decision for robots, doesn’t that defeat the self-learning purpose of AI?

Why are we explaining? Humans seek explanation when they lack understanding of something or confidence in the capabilities of other humans. Similarly, we seek explanation from artificial intelligence because, at some level, we aren’t sure about the capabilities of these systems. (Of course, there’s also humans’ control freak characteristic.) Why? Because these are “systems” and systems have problems. But humans also have “problems,” and what each individual person considers “right” is defined by their own value system, surroundings, and situations. What’s right for one person may be wrong for another. Should this contextual “rightness or wrongness” also apply to AI systems?

Who are we explaining? Should an AI system’s outcome be analyzed by humans or by another AI system? Why do we believe we have what it takes to assess the outcome, and who gave us the right to do so? Can we become more trustworthy, and believe that an AI system can assess another? Perhaps, but this defeats the very debate on explainable AI.

 Who do we hold responsible for the decisions made by Artificial Intelligence?

The mother lode of complexity here is around responsibility. Due to human’s beliefs that AI systems won’t be “responsible” in their decisions – based on individuals’ biased definition of what is right or wrong – regulations are being developed to hold humans responsible for the decisions of AI systems. Of course, these humans will want an explanation from the AI system.

Regardless of which side of the argument you are on, or even if you pivot daily, there’s one thing I believe we can agree on…if we end up making better machines than better humans through artificial intelligence, we have defeated ourselves.

Impact of organizational fatigue on digital transformation initiative | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

 

If you follow my blogs, you won’t be surprised that I’m passionate about helping organizations drive to success in business transformation and achieve breakthrough performance. As the demand for digital transformation accelerates, I find companies setting out on the required multiyear journey without understanding what lies ahead – and then failing. I’ve blogged about several pitfalls such as the need to determine and develop support up front for the strategic intent, issues around budgeting and funding the initiative, how to de-risk the transformation journey, and much more. In this blog post, I want to alert you about the risk of “organizational fatigue.”

 

The number of challenges that usually arise during a business transformation initiative is not a small number. But the challenge of organizational fatigue stands out as a common point where many initiatives hit a major roadblock. The phenomenon of organizational fatigue has three significant characteristics:

  • It occurs after, and despite, having experienced success in several projects in the transformation initiative
  • It always causes major delays and often causes the overall transformation initiative to fail
  • It can be avoided by taking the right approach up front.

 

Read more here

Technology is the Key to Innovation in Pharmacovigilance | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

The critical nature of Pharmacovigilance (PV) is obvious. For patients, it can mean the difference between better health or death from an Adverse Drug Reaction (ADR). For pharma companies, it can mean the difference between a profitable, life-saving drug, or multi-billion dollar fines and loss of reputation and revenue.

Although global PV spend has increased from 0.3 percent of total sales in 2003 to 1 percent (the equivalent of ~US$15 billion) in 2016, some of the pharma industry’s most expensive drug recalls/fines/lawsuits occurred during this timeframe.

Everest Group does not think that a further increase in PV spend is the best way for pharma companies to curb safety breaches. Rather, we believe the answer lies in creating a more effective PV process through use of technology, including analytics, automation, cloud, and mobility.

There are some well-publicized technology use cases in the pharma industry. For example, led by a consortium of world-leading experts from industry, regulatory agencies, and academia, the Web-RADR project will deliver an EU-wide mobile phone app that enables users to report adverse drug reactions directly to their National Competent Authority (NCA). And the U.S. Food and Drug Administration (FDA) has launched Sentinel, a distributed data system through which it can rapidly and securely access information from large amounts of electronic healthcare data from a diverse group of data partners.

And there are myriad ways in which technology can support pharma companies’ PV initiatives. For example:

 

 

eg pv

 

 

Digitized medicines: Smart pills with ingestible sensors can be used to track and collect patients’ health data, which can be used to run analytics for Adverse Event (AE) detection.

Mobile apps: These apps can enable pharma companies to collect ADR data much more quickly.

Cloud-based solutions: Cloud-based databases can enable pharma companies to collect data from multiple stakeholders to build an integrated ADR repository – even at a global level.

Artificial intelligence (AI): AI can help pharma companies to move beyond basic automation by identifying patterns in unstructured data.

Automation: RPA solutions can help pharma companies process structured data much more rapidly than via manual efforts.

Big data analytics: Analytics can help pharma companies use the vast amount of digital data available on the Internet (e.g., on Facebook and Twitter, and in patient forums such as Doctissimo) to supplement traditional data sources such as primary calls, EHR data, and claims data for AE detection.

Proactive PV: Robust IT solutions and advanced systems can help pharma companies monitor drug safety during the research and trials process and post-launch.

 

How Pharma companies capitalize on technology?

To fully capitalize on the benefits technology can deliver to the PV process, pharma companies must begin with establishing a clear and robust strategy for what they want to achieve and how they should progress along the technological curve. For instance, if their end-goal is to implement an AI-based solution, they should first invest in basic automation, analytics, and cloud. As pharma companies tend to lag behind those in other industries in terms of adopting new and innovative methods, they may find it valuable to partner with a third-party advisor to assist in the development of their strategy.

Next, they should proactively identify opportunities and partner with specialized technology vendors to fill technology gaps. For example, while many pharma companies are investing in the development of mobile-based adverse event reporting apps, they will not be able to realize their full potential until all the apps are connected with a common platform that precludes patients from having to download apps for each drug.

Finally, they should strongly consider partnering with outsourcing service providers that have a proven history of supporting the delivery, technology, and regulatory reporting requirements of the PV process. Call center, case entry, literature review and insights mining, aggregate reporting, and PV quality assurance are some of the areas in which outsourcing service providers can of great help.

Pharma companies have long been slow to adopt technology in PV. However, the time has come for technology to play a greater role in delivering solutions, with technology vendors and outsourcing service providers serving as force multipliers.

For detailed insights on new technological innovations in the PV market, please refer to Everest Group’s viewpoint: Innovation in Pharmacovigilance (PV): How to Spend Smarter Not Higher?

Voice-enabled Enterprise Applications: NOT a Good Idea | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

With the increasing proliferation of voice-enabled personal digital assistants (e.g., Cortana, Google Assistant, Samsung’s Bixby, and Siri) enterprise application vendors are considering jumping into the fray. In fact, some vendors have gone so far as to believe that, in the near future, 90 percent of interactions with their enterprise applications will be through voice or digital assistants.

But would these vendors actually be solving a real business problem with these capabilities, or perhaps instead getting intoxicated by drinking their own Kool-aid?

True that there are many potent arguments for voice-enabled interaction, including elimination of the need to train users on how to operate a given application, and the implication of higher productivity as the volume of data a person needs to physically enter into a system is greatly reduced.

But consider the realities of the user experience. Picture this: you’re sitting in your office area writing a report for a customer, when all of a sudden you hear your colleague saying to his laptop or smart phone, “OK SAP/Oracle, create an invoice.” How disruptive would this be to your work? Vendors could potentially tune their applications to such frequency that, when coupled with an additional device, a user’s speech couldn’t be heard by others. But that sounds too cumbersome and meaningless.

So what’s the right enterprise application vision for vendors?

The vision vendors should drive toward is one of no interaction between users and the enterprise application. Given that people engage with enterprise applications because they “have” to, not because they “want” to, how about a future where user activities are tracked, and all the related processes execute on their own?

For example, what if an enterprise’s system could manage all aspects of its employees’ travel expenses, rather than each individual filing expenses, and an army of staff reconciling and paying them? Such a nirvana of automated business processes would have tremendous impact on business agility, cost savings, and the user experience.

Voice assistance could potentially be of value in the back-end of enterprises’ systems. Their support staff could get a tremendous boost if they could “speak-fix” a problem instead of debugging complex code every time something went wrong. System designers and builders might also derive some value from voice interactions.

Enterprise applications vendors need to carefully consider whether they are solving the right problem with voice enablement. Could their smart and expensive developers be deployed elsewhere to solve complex and pertinent business problems, rather than creating a potentially unnecessary user experience? I believe that, at the end of the day, voice enablement is likely not the right, broad-based overhaul for the user experience with enterprise applications. Vendors need to focus on what users need, rather than getting caught up in the fancy of using the latest shiny digital toys.

IT faces conflicts in realities of digital world | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

IT faces two realities: a legacy environment and a digital environment. When your company commits to a digital future, your legacy environment doesn’t go away. But adopting a bimodal strategy is not successful. Here’s the reality: digital transformation is a game changer that requires changing your business model; therefore, you must drive change into both environments.

A company’s legacy environment is mature, sedimented and complex with many layers of technologies, applications and processes that are interrelated. It is also overspread with the company’s culture and its organizational structure.

Read More at my CIO Blog

What Matters Most for Success In Using An Incubator For Blockchain Or Other Innovative Technology? | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

Is innovation to improve competitive positioning at the top of your company’s agenda? A common approach is to look at the technologies leading companies use to transform their business, then set up an incubator or innovation lab (either internally or externally in a service provider’s business) and provide funding to experiment with the technology. I’ve observed incubators and innovation labs for almost 10 years. Unfortunately, very few of them resulted in meaningful changes to competitive positioning of the company. Let’s look at what you need to bake into your strategy at the outset so you can capture the greatest value from an incubator or innovation lab.

Proponents argue that it’s a cost-effective way to gain clarity on the risks and challenges around implementing a new technology, and they see it as an opportunity to gain greater understanding of the possibilities of new technologies. It’s also a way to identify myths vs. facts around an emerging technology. Certainly, these are wise steps in a business where new technologies have to win the battle for attention among other priorities. But they largely fail to succeed.

 

Read more Here

Product Quality Management: You (Don’t Have To) Walk Alone | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

My most recent blog focused on why quality management (QM) is a critical contributor to enterprises’ ability to take great products to market. Now, let’s turn our attention to who can – indeed, perhaps should – perform product QM work for organizations.

Viewing QM activities as a core competency, enterprises have traditionally conducted them in-house. In some cases, they’ve engaged their global in-house centers (GICs) to handle some aspects of QM in order to reap the benefits of factors such as talent access and cost arbitrage, while still retaining control over issues such as IP protection and close integration with the parent entity, which is key for product design and development.

However, the advent of innovative engagement models (e.g., outcome-based pricing, collaborative IP, etc.), the pervasiveness of digital technologies, and advancements in data and IP security measures are instilling confidence among enterprises to partner with third-party service providers for their product QM activities. Recent investments by service providers in building IP and enhancing their capabilities in this space – spurred in part by slowing growth in more traditional ITO and BPO areas – is strengthening their case with enterprises. Indeed, Everest Group research shows that global sourcing in the QM space will grow at an impressive 16 to 18 percent through 2020 – higher than the growth expected in the global sourcing space for overall engineering services.

Following are some of the ways in which third-party service providers can deliver product QM value to clients.

 

Engineering Services, Product Quality Management, Quality Management, Quality Management Services

 

Of course, outsourcing product QM does come with risks and challenges. Factors that enterprises should consider when weighing a product QM outsourcing decision include:

 

Engineering Services, Product Quality Management, Quality Management, Quality Management Services

 

When evaluating a particular outsourcing service provider for product QM work, enterprises should evaluate factors including talent availability, infrastructure availability, delivery capabilities, ability to scale up/down, innovation-focus, expertise in digital themes, inclination towards outcome-based business models, and client satisfaction.

Everest Group has conducted deep-dive research on the global sourcing landscape in the product engineering space, covering all the activities involved in the validation, verification, and testing of both hardware and software across the product lifecycle. We have studied twenty-three of the leading engineering service providers in the QM services space, and have analyzed them on parameters including capabilities, scale and scope of services, and IP/investments. Following is a sneak peek into our relative analysis of these players based on their engineering services play, revenue and revenue growth, and coverage of QM services.

 

Engineering Services, Product Quality Management, Quality Management, Quality Management Services

 

Please click here to read a preview of our report, “Identifying the Right Partners for Quality Management in the Engineering Services Industry – Service Provider Landscape.”

How Digital Transformation Skyrockets Lean Six Sigma In Impact | Sherpas in Blue Shirts

By | Sherpas in Blue Shirts

The promise of Lean Six Sigma is continuous improvement and that it will deliver business performance improvement by 3% every year. That was great in a business world where 3% was enough. But not today, when organizations can gain performance breakthroughs of 40-60% or more. Plus, Lean Six programs didn’t enable organizations to change their competitive position. Those two facts are why digital transformation is overwhelming Lean Six Sigma. But to capture the value that digital promises, it’s important to understand how it differs from Lean Six Sigma.

What is it about digital transformation that makes it so much more powerful than Lean Six Sigma? The outcomes from Lean Six Sigma depended on adjusting business processes. In contrast, digital transformation enables the opportunity to reconceive the underlying business model and completely transform the business.

Read More at My Forbes Blog Here