Category: Automation/RPA/AI

Reimagining Global Services: How to get MORE out of Technology | Sherpas in Blue Shirts

Much has been written and said about the Bimodal IT model Gartner introduced in 2014 – with forceful arguments for and against. Not at all intending to bash that model, it’s safe to say that the digital explosion over the last three years demands that enterprises’ technology strategies be much more nuanced and dynamic.

The MORE model for global services

Let me explain with the help of the following chart. I call it the Maintain-Optimize-Reimagine-Explore – the MORE – model.

Global Services and Technology in the MORE model

I’ve tried to plot (intuitively) a bunch of technology and service themes on their current and future innovation potential.

  • Maintain: On the bottom right are themes like mainframes and traditional hosting services that are unlikely to go through dramatic changes in the near term. These are exceptionally stable and commoditized, and will not attract exciting investments. Enterprises still need them, and CIOs should Maintain status quo because it’s too risky and/or expensive to modernize them.
  • Optimize: Seven years back, that cool AWS deployment was the craziest, riskiest, hippest tech thing we could do. But, I guess we’ve all aged (just a little bit) since then. The needle of cloud investment for most enterprises has moved from AWS migration (USD$200 per application, anyone?) to effective orchestration and management – a clear case of the enterprise seeking to Optimize its investments in the bottom right corner of my diagram.
  • Explore: On the top right, we have the new wild, wild, west of the tech world. Blockchain can completely transform how the world fundamentally conducts commerce, IoT is working up steam, and artificial intelligence can shape a different version of human existence, much less business models. Enterprises need to Explore these to stay relevant in the future.
  • Reimagine: What we cannot afford to miss out on is the exciting opportunity to Reimagine “traditional” global services into leaner and more effective models using a combination of enabling themes like automation, DevOps, and analytics. These are immediate opportunities that many enterprises consider essential to running effective operations in a traditional AND a digital world. For example:
    • In a world where “the app is the business,” QA is being reimagined as an ecosystem-driven, as-a-service play built on extensive automation and process platforms. The reimagined QA assures a digital business process and a digital experience – not just an app.
    • We are getting into the third generation of workplace services (first hardware-centric, then operations-centric, and now software and experience-centric.) The reimagined workplace service model delivers a highly contextual, user-aware experience, without sacrificing the long-range efficiency benefits.
    • Application management services (AMS) are being reimagined through extensive outcome modeling, automation instrumentation, and continuous monitoring.

Three principles for reimagining global services

It’s interesting to note that many of these reimagination exercises are based on three common foundational principles:

  1. Automation first: Automation and intelligence lie at the heart of our ability to reimagine technology services, because automation helps us deliver breakthrough outcomes without blowing the cost model out of the water.
  2. Speed first: The need to run ALL of IT at speed is driving reimagination and the corresponding investments. If you’re at the reimagination table, throw away your tools to build the perfect (and the biggest) mousetrap. A big part of the drive for reimagination is to move from scale-driven arbitrage first models to speed-driven digital first models.
  3. Alignment always: This is important and good news. For decades, we’ve all complained about the absence of Business IT alignment. Reimagination hits out at this issue by focusing on technology architecture that is open and scalable, and by delivering as-a-service consumption models that are closely linked to things that the business really cares about.

Over the next several months, Everest Group is going to publish viewpoints on each of these topics and more. But we’d love to hear any comments and questions you have right now. Please share with us and our readers!

Software Eats World, AI Eats Software … Ethics Eats AI? | Sherpas in Blue Shirts

Marc Andreessen’s famous quote about software eating the world popped up often in the last couple of years. However, the fashionable and fickle technology industry is now relying on artificial intelligence to drive similar interest. Most people following AI would agree that there is a tremendous value society can derive from the technology. AI will impact most of our lives in more ways than we can think of today. In fact, it often is hard to argue against the value AI can potentially create for society. Indeed, with the increasing noise and real development around AI, there are murmurs that AI may replace software as the default engagement model.

Artificial intelligence may replace software

Think about it. When we use our phone or Amazon Alexa to do a voice search, we simply speak, hardly using the app or software in the traditional sense. A chatbot can become a single interface for multiple software programs that allow us to pay our electric, phone, and credit card bills.

Therefore, artificial intelligence replacing software as the next technology shift is quite possible. However, can we rely on AI? Or, more precisely, can we always rely upon it? A particularly concerning issue is that of bias. Indeed, there have been multiple debates around the bias an AI system can introduce.

But can AI be unbiased?

It’s true that humans have biases. As a result, we’ve established checks and balances, such as superiors and laws, to discover and mitigate them. But how would an AI system determine if the answer it is providing is neutral and bereft of bias? It can’t, and because of their extreme complexity, it’s almost impossible to explain why and how an AI system arrived at a particular decision or conclusion. For example, a couple of years ago Google’s algorithms classified people of a certain demography in a derogatory manner.

It is certainly possible that the people who design AI systems may introduce their own biases into them. Worse, however, is that AI systems may over a period of time start developing their own biases. And even worse, they cannot even be questioned or “retaught” the correct way to arrive at a conclusion.

AI and ethics

There have already been instances in which AI systems gave results for which they weren’t even designed. Now think about this in a business environment. For example, many enterprises will leverage an AI system to screen the resumes of potential candidates. How can the businesses be sure their system isn’t rejecting good candidates due to some machine bias?

A case of this type could be considered an acceptable, genuine mistake, and it could be argued that the system isn’t doing it deliberately. However, what happens if these mistakes eventually turn into unethicality? We can pardon mistakes but we shouldn’t do the same with unethical decisions. Taking it one step further, given that these systems ideally learn on their own, will their unethicality become manifold as the time progress?

How far-fetched it is that the AI systems become so habitually unethical that users become frustrated? What are the chances that humanity stops further developing AI systems when it realizes that it’s not possible to create AI systems without biases? While every technology brings a level of evil with the good, AI’s negative aspects could multiply very fast, and mostly without explanation. If these apprehensions scare developers away, society and business could lose AI’s tremendous potential positive improvements. That would be even more unfortunate.

As the adoption of AI systems increases, we will likely witness more cases of wrong or unethical behavior. This will fundamentally question and push regulators and developers to put boundaries around these systems. But therein is a paradox: developing systems that learn on their own, while putting boundaries around that learning – quite a contradiction. However, we must overcome these challenges to exploit the true potential of AI.

What do you think?

The United Nations Looks at Security Of Artificial Intelligence | Sherpas in Blue Shirts

I recently had the privilege of attending at the United Nations an invited gathering of individuals active in the Artificial Intelligence (AI) space. The meeting was hosted by UNOPS with a view to consider how AI can be better deployed to support the UN mission. The attendees included leaders in AI and its related fields with the AI leaders for companies such as Facebook, Google, IBM Watson, Intel and IPSoft, along with government entities and distinguished academics and journalists.

At the dinner, a great number of topics were discussed with the United Nations representatives challenging the community to use its collective resources to support the UN’s mission of cleaning up the oceans, feeding the hungry and delivering medicine to the underserved. As the discussion progressed, security emerged as an important topic and that AI has the potential to both make a vital contribution and to be co-opted and weaponized as an agent of attack.

Read more at Peter’s Forbes blog

AI: Democratization or Dumbing of Creativity? Pick your Cause | Sherpas in Blue Shirts

The earlier assumption that artificial intelligence (AI) would impact “routine” jobs first is not holding ground anymore. Indeed, we might be deluding ourselves by thinking that the time in which AI could be the most used interface to engage with technology systems is far in the future. But I’m getting ahead of myself. Let’s look at what’s happening today in the creative sector.

IBM Watson was used last year to create a 20th Century Fox movie trailer. Adobe Sensei is putting the digital experience in the hands of non-professionals. Google is leveraging AI with Autodraw to “help everyone create anything visual, fast.” Think about anyone, any one of us, taking a picture and then telling photo editing software what to do. No need to work with complex brushes, paints, or understanding of color patterns.

AI and creative talent

This is scary for creative people such as graphic designers, digital artists, and others who may consider artificial intelligence a job killing replacement of their skills, despite pundits’ claims that it will “augment” human capabilities. Antagonists proclaim that AI systems will at best reduce the overhead with which creative people deal. But removing overhead is just the first step; the next step is surely the creative. More so, AI systems can ingest so much data, and will increasingly rely on unsupervised learning to correlate so many behavioral traits to create compelling creative content that a human creative artist cannot possibly fathom or understand. Thus, these artists will begin leveraging AI systems to create exceptional, “unthinkable” user experiences that have no “baseline” of reference, but soon may be replaced by these very systems.

AI and businesses

Businesses have always struggled to hire highly skilled creative professionals, and have paid through the nose to secure and retain them. That they will be able to leverage artificial intelligence to take charge of creativity to drive messages and communication to their end users, rather than relying on creative experts, will make them extremely pleased. As the intent of most AI systems is to enable non-specialists to perform many tasks by “hiding what is under the hood,” businesses might not need as many specialist human creative skills.

However, despite this seeming upside of AI systems, their under the hood nature will create problems of accountability. The complexity of their deep learning and neural networks will become such that even the teams developing the systems won’t be able to provide answers to specific decisions they make. Thus, if something goes wrong, where should the blame be placed? With the creation team, or with the AI system itself? The system won’t care – after all, it’s just a technology – and the team members will argue that the system learned by itself, far beyond what was coded, and they cannot be held accountable for its misdeeds. This is scary for businesses.

AI and the impact beyond business

Imagine the impact this will have on the society. Although you can track back how any other technological system arrives at an answer, AI systems that are now supposed to run not only social infrastructure but also much our entire life won’t be accountable to anyone! This is scary for everyone.

I don’t want to add to the alarmist scare going on in the industry, but I cannot be blind to successful use cases I witness daily. People will argue that AI has a long way to go before it becomes a credible alternative to human-based creativity. But, the reality is that the road may not be as long as is generally perceived.

The Disruption and Promise of Artificial Intelligence | Sherpas in Blue Shirts

There’s no shortage of books, news articles and comments in social media about how artificial intelligence (A.I.) is shaping our future. Although it’s still blazing a trail, we’re on the brink of A.I. disruption that will change all industries and society at a very deep and fundamental level. I believe it will be one of the next great wealth generators.

My optimism about A.I.’s growing potential arises from many successful use case examples as clear evidence that A.I. is now getting the scale, maturity and the ecosystem in which it can be effective. Although A.I. has been developing for 20 to 30 years, it’s gaining enough elements necessary for a supporting ecosystem.

Read more at Peter’s CIO.com blog.

How To Accelerate Value Creation Through Artificial Intelligence | Sherpas in Blue Shirts

Major advances in Artificial Intelligence (AI) technology are happening rapidly, and many organizations are excited about the possibilities AI presents. However, some successful companies fail in their innovation efforts to create new value by leveraging disruptive technologies. Others haven’t yet embarked on this innovation journey because they lack use cases. My advice: First define the strategy you’ll use to create value through AI. And Facebook is good role model when it comes to AI strategy.

Your strategy for value creation needs to include how to maximize and expedite the development process. This is the foundational core of Facebook’s strategy. I recently attended a dinner focused on AI at the United Nations. Hosted by UNOPS, attendees included distinguished academics, software companies, government entities and AI leaders in companies successfully using AI.

Read more at Peter’s Forbes blog

How Low Can They Go? Pricing and Margin Pressures Abound for IT Service Providers | Sherpas in Blue Shirts

The business environment in which today’s IT service providers are operating is one of the most challenging in recent times. A host of buy- and supply-side factors are impacting the prices they can feasibly and competitively charge their enterprise clients in the U.S., and their margins are being constricted at every turn.

On the buy-side, ongoing commodity slowdown led to overall softening in the global services market in 2016. Uncertainties created by Brexit in mid-year and the U.S. elections in Q4 delayed decisions on new sourcing contracts and temporary cuts in discretionary spending in SI type engagements.

The quantum of large application outsourcing (AO)/systems integration (SI) deals (>US$100 million annual contract value, or ACV) as a percent of total deals fell from 3.3 percent in 2015 to a low of 1.7 percent in 2016, reducing the pricing cushion typically afforded by large deals. And because enterprises continue to maintain a portfolio of preferred AO vendors to foster price competitiveness and innovation, resulting in a price war for deals, the average ACV in AO deals dropped by ~20% in 2016.

Most enterprises are optimizing their portfolios of contracted relationships to reduce overall TCO by improving nomenclatures, rates, service levels, T&Cs, productivity, etc., leading to a dip in realized revenue per FTE for providers.

Additional downward pressure on realized revenue per FTE has resulted from an increase in brownfield automation, especially in compete situations and second generation renewals. And renewals fell sharply, from 55 percent in 2015 to just 27 percent in 2016, driving price wars among providers.

On the supply-side, although resource utilization increased for Tier 1 service providers from ~80 percent in 2015 to >82 percent in 2016, it is beginning to max out as a delivery optimization lever. Consequently, providers are trying to achieve higher efficiencies and sustain margins via better project planning, DevOps, agile staffing, and proactive use of automation.

 

Pricing pressures and automaiton and digital solutions for IT enterprises and service providers

There is extreme competition in most rebid and re-compete situations, which has led to an overall decline in pricing. We saw an average dip of 1-2 percent in AO /SI FTE rate cards, but bigger dips in overall account-level TCVs. And per rate cards, some enterprises have pushed for single onshore rate card that doesn’t delineate between local and landed resources, leading to cheaper onshore rates. That said, the new U.S. government may push for more onshore hiring and localized presence, including sanctions on landed resources. This may push onshore rates higher, marginalize the landed resource model, and put additional margin pressures on service providers in the second half of 2017.

All this paints a pretty gloomy picture for IT service providers. However, they have started pivoting towards a digital first future, which can help stem their margin and profit erosion, and reverse the worrisome growth deceleration. Most are growing their top line and/or capability portfolio inorganically. Most are also investing in and pitching automation capabilities in a bullish manner. While this may led to a near-term cannibalization of their traditional offerings, in the medium- to long-term it will help sustain their margins in a price competitive landscape.

Do you believe that a digital first pivot will help service providers get back to double digit growth rates?

Genpact Makes Bold Digital Move | Sherpas in Blue Shirts

In the heat of battle in the services industry’s rotation from labor arbitrage to digital, Genpact made a significant move today that signals to everyone it’s playing to win. Genpact announced it signed an agreement to acquire Rage Frameworks, a leader in enterprise Artificial Intelligence (AI) and automation technologies and services. Genpact moved the cheese.

Three aspects of Genpact’s acquisition of Rage are especially significant.

  1. Serious Commitment: It’s apparent that Genpact recognizes the future of services will be digital. The global services industry is witnessing unprecedented deceleration. At Everest Group, we closely track the top 20 service providers. As illustrated in the chart below, the labor arbitrage-based businesses collectively stopped growing last year and 21 percent of the industry growth is now in businesses with a digital focus.Genpact acquisition of RageAmong the top 20 providers, growth for arbitrage-first providers actually shrank last year. As we look forward two more years, we think it will further decelerate and go to just under two percent.Accenture has rotated into digital faster than other providers, and already has the highest percentage of work in digital. It’s the biggest and is blowing other providers away. Of note, it’s the only provider that has succeeded in growing its margin while moving into digital. As I’ve recently blogged about the dilemmas at Infosys and Cognizant, for example, the rotation into digital stresses providers’ margins. The faster they grow in digital, the lower their margins are, which is very inconvenient.“Change is inevitable, but growth is optional,” wrote John C. Maxwell, leadership expert and best-selling author. With its Rage acquisition, Genpact bypasses the dilemma other providers are facing and demonstrates its seriousness and its commitment to growth in the digital space.
  2. Accelerating clients’ digital transformation: Everest Group’s research group conducted a study of 132 “best reference” clients of top service providers. Our study found 48 percent of clients are unhappy and 25 percent are very unhappy. A top reason for their dissatisfaction is providers’ capability of helping them with a digital restructure.Rage Frameworks presents an exciting set of technologies that are immediately applicable to Genpact’s existing client base. Leveraging Rage’s no-code development AI platform in cognitive computing, enterprises can gain real-time insights for mission-critical functions, simplify automation, manage risks better and gain competitive advantages. For the last 18 months, Genpact and Rage successfully partnered on strategic client digital engagements including a large global insurer, a global consumer packaged goods leader and several large financial institutions. Their combined capabilities will help clients drive digital transformation at scale and accelerate clients’ digital journey.
  3. Rebranding: The Rage acquisition also enables Genpact to rebrand itself as a digital company in the broader marketplace, not just an arbitrage service provider. Moreover, the AI capability is quickly becoming mainstream for leading enterprises as it enables organizations to change the way work is done and enhance their value proposition and competitive advantage.

Requirement for Digital Rotation Success
When an arbitrage company such as Genpact thinks about its rotation into digital, it must focus on managing three constituencies: shareholders, internal constituencies and customers.

The Rage Frameworks acquisition helps Genpact manage across all three constituencies, as follows:

  • It signals to the shareholders that Genpact is serious about rotating into digital, and it’s joining companies like Accenture, which is the leader of rotation into digital.
  • It equips Genpact’s internal organization with the tools and intellectual property to drive the provider’s transformation into a digital services leader.
  • It helps reposition Genpact with its customer base in Artificial Intelligence and cognitive computing – a very important and quickly growing emphasis in digital capability.

Genpact’s bold move is important to watch. How many other arbitrage providers will follow this path of serious investment to accelerate their journey to become digital-first service providers?

RPA Implemented! But Where are The Benefits You Were Promised? | Sherpas in Blue Shirts

Consider this situation: the head of operations for the finance function at a leading insurance company had heard from both his BPO provider and several technology companies claims of robotic process automation’s (RPA) ability to deliver significant operational efficiencies and cost savings. He decided to take the plunge, obtained leadership buy in, made elaborate RPA implementation plans, set the investment rolling, and finally directed his team to implement RPA across the function in all geographies. A year after deployment, he was still struggling to see significant evidence of the promised benefits. Have you heard stories like this before? Perhaps experienced it in your own organization? Unfortunately, it’s all too common. Various factors contribute to the glaring gap between expectations and reality. They can be broadly categorized as follows:

  • Process – This includes lack of process standardization and an improper process viability study for automation. For example, process-specific differences due to delivery location-specific nuances require greater RPA tool customization. This drives costs higher, and can significantly impact the automation ROI and expected benefits.
  • Delivery – This includes factors such as service placement across locations that can affect the automation levels in a process. For example, if FTEs are fragmented across different locations, they cannot be released because of minimum FTE requirements to service those locations.
  • Governance – Similar to any major transformation initiative, success with RPA depends upon various governance specific factors like buy in from IT, organization alignment, etc. For example, we have seen IT departments causing considerable delays in providing the prerequisite security clearances for RPA environment setup and deployment.

Automation assessment, or lack thereof, is the most critical factor

The paramount contributing factor to a successful – or unsuccessful – implementation of an automation project in your enterprise is automation discovery, i.e., the assessment of automation potential in your organization’s unique environment. In all too many cases, BPO or RPA tool providers look first just at process viability, e.g., if the process consists of rules-based, rather than judgment-based, activities, and then base their assessment on experiences with other clients or on a pure numeric automation benchmarking exercise provided by an analyst firm. However, mere replication of the same RPA tool across a similar process will not necessarily deliver similar automation benefits.

Our recommendations for enterprise buyers on how to help optimize their RPA investments and achieve the potential ROI include:

  • Make sure your RPA vendor or BPO service provider addresses topics specific to your particular environment, including an assessment of impact of a fragmented technology landscape, regional language-specific nuances to be considered, etc.
  • Obtain a robust automation benefits benchmark mapped to your organization’s context, and safeguard yourself, if possible, with contractual obligations
  • Set the right expectations with internal stakeholders on potential benefits

Our primary recommendation for service providers looking to satisfy their clients’ expectations is to leverage a comprehensive automation benefit benchmarking model that is based on benefits delivered and the underlying context of RPA delivery. This will help them not only better estimate but also realize the potential benefits on their clients’ behalf. Service providers that correctly estimate, communicate, and deliver these benefits consistently will ultimately have more RPA success stories to tell.

Do you work for an enterprise or service provider that has implemented RPA? If so, our readers would love to hear about your automation journey experience, and if/how you were able to achieve the intended benefits!

AI: Revisiting Future Shock | Sherpas in Blue Shirts

In his 1970 book “Future Shock,” author and futurist Alvin Toffler made the argument that the modern world disorients people as it creates so many overwhelming changes that we are unable to handle them. Almost 50 years after the book was published, I was struck by Toffler’s argument during a recent client engagement in which we were helping an enterprise identify virtual agents/chatbots for its customer-facing processes. All of the bots contained a healthy dose of artificial intelligence (AI), and each one was trying to push the envelope.

Is AI starting to overwhelm people to the point that they may get frustrated with developments they cannot fathom or use?

Every day we see and read about new use cases that “wow” us. We are amazed and bedazzled by advances in AI. And some are becoming increasingly commonplace in the consumer arena…just think smart homes.

On the flip side, there have been instances in which consumers have found dealing with these omnipresent home devices scary and frustrating. Humans have already strongly voiced that they don’t need bots to shop. And, feeling the need for peace in their home, they have switched off many of their home assistance devices.

Some may argue that the technology industry, driven by the high intoxication from the ivory towers of Silicon Valley, is getting way ahead of the people who are expected to be the eventual consumers of these technologies. The amount of new AI research and products coming every day out of these factories is mind numbing. A significant number of such products may not have any immediate utility, but they do indeed demonstrate the far-reaching power of such advanced systems.

There is an unending scare around AI, cognitive, and other advanced systems taking away jobs from human beings. In the case of virtual reality, people are entranced by engaging with virtual objects as if they are real. It’s fun, until they realize the negative impacts it can have on their day-to-day lives. And, instead of assuaging such fears, the technology industry continues to create use cases to replace human tasks with robots.

From an enterprise perspective, organizations need to proactively create an AI adoption strategy for their business. Though most now have some vision around using AI technologies, frighteningly few are preparing for the massive change management aspect. Their employees must be comforted around the impact AI can and will have on their lives. Indeed, the significant disruption AI technologies can create within a business context may require a very different approach than other technology adoption we have ever witnessed. Technology vendors need to focus on how AI-enabled systems are assisting or helping human beings. The use cases need to be very precise, clear, and friendly, not overwhelming and complex, which they currently are.

The problem is not AI technology. The problem is the way it is being introduced, and the hyperbole around it that may end up overwhelming a significant portion of the human race, leading to eventual burnout. We are humans, and should create technology for humans. If the very technology we create results in alienating a large percentage of us, we will have failed as a human race. AI systems need to be leveraged for enhancing human lives, not for creating technology marvels that overwhelm people and create the future shock.

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