In case you’ve been asleep for the last month, we recently announced the industry’s most comprehensive analysis (by far) of RPA product functionality, covering AntWorks, Automation Anywhere, BluePrism, Kofax, Kryon, NICE, Pega, Thoughtonomy, UiPath, and Workfusion.
We interviewed 359 superusers of RPA products (172 enterprises, 87 RPA advisors and 100 service provider RPA practitioners) across 40+ customer experience dimensions across the following 6 key dimensions:
Features and functionality
Integration and support
Security and compliance
Flexibility and scalability
Embedding intelligence
Achieving business outcomes
Here is how the overall satisfaction for RPA customer experience came out looking across the products
RPA’s core functionality works but deployments are not as easy as promised.
RPA products offer adequate client support and training but IT skills are required. Some RPA products have made significantly more investments than others around client support.
Most RPA products performed well on security and compliance related assessment.
RPA products have shown satisfactory flexibility but clients are still confused about pricing models.
RPA products are not as intelligent as they claim to be (at least not yet!).
RPA satisfaction is middling. Clients have largely realized cost savings, but speed-to-market has not met expectations.
Take time to delve into the realities of RPA and some of the findings may just surprise you:
There aren’t too many people you can listen to today where you feel all those sticky layers of hype just fall away from your brain, as this guy actually knows what he’s talking about and (as we English love to put it) he just doesn’t mince his words. So, after a terrific meeting with Hans-Christian (Chris) Boos, Founder, and CEO of leading AI platform vendor arago, I pinned him down to share some of his views with the HfS crowd…
Phil Fersht (Founder and CEO, HfS Research): Chris – you’ve been a terrific guy who adds so much energy and colour to the intelligent automation industry… but can you shed a little light on your story? How did you find yourself setting up the business in 1995? Was the focus on intelligent automation back then? I thought we were all going nuts about ebusiness!
Chris Boos (Founder and CEO, Arago): Phil – I originally wanted to do AI research at a university and then I saw how slow academic research is today with the way it is financed. I chose to do it inside a company instead. We could control the pace there. We setup arago to research general AI and my belief has always been that general AI is all about automation. If it is intelligence – even the quite boring artificial version – I guess you could say that smart automation was my goal, then.
Most people are surprised about the research phase. But if you look at most people who are doing significant work in AI they all plan or have done a roughly 20-year research phase. The one thing that is special about arago is that we financed it ourselves. We split the company down the middle, half was doing research and the other half was doing projects to get the money. That way we did not only get to do basic work on AI and make money to finance the work, but we also had a testbed for all our components in real businesses. A brilliant idea I cannot take credit for, it was my uncle who founded arago together with me who came up with the model. It worked out really well for us. We did pure research from 1995-2008, then used our own toolset to start automating IT operations and slowly turn it into a product and do some deployments till 2014, then scaled automating IT operations on top of more static approaches while collecting a dataset that is descriptive of all kinds of companies in all kinds of industries and 2017 we finally started applying AI generally in other industries and processes than IT.
By the way, 1995 was before the e-business boom started. I remember we did the first online banking on the web in Europe then and the page said, “your browser should support tables”. Can you still remember these days?
Did you ever expect to be where you are today?
Absolutely not. I am still being surprised every day. If you had asked me about feeding animals with an AI a year ago, I would have looked at you like you just tole me the aliens had landed. Now we are feeding animals with an AI. This is what is so absolutely fantastic about the industry, there is a new frontier to be pushed further every day.
Fortunately makes up for all the crap you have to hear because everything that has the slightest bit of math inside is called AI these days. I would like to reverse that saying: It is only called AI as long as it does not work. As soon as it works, it gets a real name like “facial recognition” ????
So you’ve been talking about some very real and honest stuff regarding machine reasoning… what’s this all about?
In the area of AI, we have made one mistake since 1954 now. Whenever we found a new algorithm or were finally able to actually apply an algorithm we found a long time ago, we declared this algorithm to be the one solution to everything. This one-size-fits-all approach is not only stupid but lead to AI winters which were periods in research and commerce when no one would touch AI with surgical gloves – except for the crazy ones of course; did I mention 1995 was during such an AI winter? We are making exactly the same mistake again, by declaring deep-learning equivalent to AI. One algorithm will not be a solution for everything, it is a solution for a defined set of problems. This means it will fail miserably at other problems and also have clear limitations in the scope it was originally built for. Let’s stick with machine learning for a bit. The clear limitation is data. At some point, there will not be enough data to describe “now”.
I believe there are three basic sets of algorithms to be considered when building a general AI:
Machine learning. The ability to learn to recognize patterns and associate positive actions with them. This is like evolution, everything that behaves favorably survives, everything else dies. Adding a temporal memory to this system was what started deep learning with long-term-short-term-memory networks. But there are many other learning algorithms. In biology, we call this “instinct” and all species have them.
Natural Language Processing. Now this is where it gets tricky, because language has so much compression. Think of how many different pictures you can imagine on the 3-byte input of “cat”. Your implicit knowledge of context and an internal argument narrows what you understand when you hear “cat” in a conversation down to a very likely correct interpretation. Machines, unfortunately, do not understand anything, and they also lack all the context. This is why NLP is still one of the hardest parts of AI. There is no way to “learn” the meaning of language through machine learning (yet), especially because the context, is so volatile. This is why the hype around chat-bots has lead to a lot of disappointed customers. They work well if you can predict the dialog with a high degree of certainty, for example, if you offer a telephone line where people can call in sick you know that there are only so many ways to say “I am not feeling well” and the only result you want out of the dialog is “when will you be back”. But all other more general cases are very difficult. This is why you have to change your language structure quite drastically if you want Alexa, Google Assistant et al to do anything for you. There are a lot of very advanced algorithms in this area which are mainly very advanced statistics to create probable context, probable synonym, probable XYZ and then math this to a pre-determined understanding structure. These are the least self-reliant algorithms in the AI family. In biology, language was the single differentiating factor that made us as a species outperformed everything else on the planet. We no longer had to go through long cycles of observation as well as trial and error to have only the ones with the right solution to a problem survive. We could simply tell each other “if you see a Tiger, run away” and no evolutionary iteration was needed. This is a huge advantage which machines are completely missing.
Machine Reasoning. The one you were actually asking about. This was how AI started. The idea was to make a logical argument to find a solution to a given problem. The first attempt was to use decision trees to “write down the one and only answer for every situation”. This does obviously not work, because the more interesting a problem is the more different ways of reaching a solution there are. The industry moved from decision trees to decision graphs. Then we found out that logic does not govern the world and that ambiguity, contradictions, overlapping information, wrong information and unexpected events have a huge influence on how to really solve a problem. The type of algorithms that create a solution by outputting a step-by-step execution instruction for a more complex task by choosing the best step to take out of an existing pool of options and then the next and so on are called machine reasoning. The limitations of these algorithms used to be in the knowledge base because the maintenance effort of such knowledge bases grew exponentially and the benefit grew polynomially. In the world of biology, this is called “imagination” of if we want to be less philosophic the ability to simulate a bit of the future in our heads to make the right choices of what to do in order to reach a defined goal.
Looking at only one algorithm set to solve all problems in the world seems dumb, yet if you read about AI, it seems that machine learning has become synonymous with AI. This literally guarantees a bursting bubble once the limits of data availability are reached. My prediction is early 2019.
We have set out to combine these algorithms to produce a single engine with a single data pool to mitigate these problems and this is why we started in IT automation and are expanding to more and more complex automation across all kind of different industries.
And you’ve been quite poignant regarding your views on AI actually substituting human intelligence and how unrealistic a “singularity” is – can you share some of your candid thoughts here with our readers?
The entire debate about singularity does not make sense, Phil. We pretend that simply by rebuilding the electrical part of the brain we get a self-conscious self-reliant entity, why should that happen? If you build the skeleton of a dinosaur you don’t get a dinosaur either.
Ok, to put this down in numbers. A large neural network used in deep learning has about a million nodes today. Is uses up the power of half a powerplant. An average human brain has 84 billion neurons and uses 20 Watts. According to Moor’s law, we can achieve rebuilding this by 2019 and I am one of the guys who believes that Moor’s law will hold. Yet, that is not all there is to the brain. The brain also has a chemical system creating a literally infinite number of configuration of the brain’s 84 billion neurons. Infinite because the chemical system is completely analogue. And then for good measure, there are a lot of well-reviewed research papers arguing that the brain also must have a quantum mechanical system injecting probabilities. So there are two entire dimensions we are missing before we can really reproduce a brain-like structure.
And even if we could… We don’t understand or know what consciousness and self-awareness are, do we. So how do we think we can build it? Is “by accident” really a good explanation? “Build the field and it will come” is definitely not the answer here. This is why all the talk about killer AIs and ethical machines is far too early. I am not saying there will never be a super-intelligent AI, but not in the new future.
That does not mean that current AI technologies cannot outperform us at tasks we have already mastered. Tasks that we as humans already have the experience for and thus tasks we can transfer to the machine. But why would we mind? A crane is outperforming my weight-lifting ability everyday and I think that is perfect, I have absolutely no desire to become a crane, do you?
What will AI truly evolve into over the next 10-15 years, based on your experience of the last two decades? Is there any real reason why change will accelerate so fast? Are just getting caught up in our own hype?
What will happen is that automation leaves the constraints of standardization and consolidation. With AI systems based on today’s tech, we can automate tasks, even if they only occur once and even if they have never been posed like this before.
I think I was a bit too abstract here. I believe that AI will make any process that we have mastered and that is not entirely based on language autonomous. Machines will most likely do 80% of what we are doing today. Which means that our established companies get a fair opportunity to catch up with the tech giants. This is why I believe that we need RPA as a transition technology, because it basically puts an API to everything that there is in the corporate world. On top of that, we can use AI to automate almost everything allowing every enterprise the wiggle-room to actually evolve
So what’s your advice to business and IT professionals today, Chris – how can we advance our career as this intelligent automation revolution takes hold?
I think in IT we are in a unique position. What click-data was for commerce, IT ops data is for the enterprise. IT ops data describe everything a company is doing and thus forms the foundation of applying the next generation of automation and autonomy.
The only thing we as IT professionals really have to do is open our minds. If we do so, we can revolutionize much of the business and not be the “laggards” who are slowing everything down as we were in the ecommerce revolution. You know I am German, so I get to be blunt: I think we have to “grow a pair” and take on the risk of automating everything from IT, otherwise business will do it for us and then who needs IT?
And finally… if you were made the Emperor of AI for one week and you could make one change to mankind, what would it be, Chris?
Mankind? That is too big for me… It would have nothing to do with AI, I would force people to think rationally for at least 50% of the day instead of 0.5, but let’s not go that far or people will think I am a cynic.
Let’s say I was made king of AI in the enterprise world for one day. I would decree to stop every POC, POV, Pilot, or whatever other terms you can find for trying to be half-pregnant and force people to start doing things in production right away. There simply will not be enough speed if we keep on “trying”. As master Yoda said, “Do or do not, there is no try”. We really need to adopt this behavior pattern.
Thanks for your time today, Chris. Am looking forward to sharing this discussion with our community.
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Digital is all about an organization’s ability to respond to the needs of their customers as those needs happen – or even be smart enough to anticipate those needs before they happen. This is all enabled by interactive technologies to create those touchless interfaces with the customers. Smart analytics and AI enable organizations to anticipate these needs based on the ability to recognize patterns and inferences over time, but nothing can really substitute for human intelligence to bring customers, suppliers and employees closer together, unimpeded by frustrating silos and legacy processes.
Remember, every broken process chain, or poorly converged dataset, slows down an organization’s ability to do business in real-time and stay ahead of its market. Traditional barriers between front, middle and back offices hinder the true ability of companies to operate in this real-time, responsive and anticipatory digital fashion, which is why we coined the term “OneOffice”, where the unification of digital business models, intelligent automation, analytics and creative talent is happening before our very eyes.
The HfS Digital OneOffice Framework (see below) describes how organizations must integrate their digital customer interfaces with their operations in order to fulfill and anticipate their customers’ needs. It is the organizational end-state to survive and succeed in a world where digitized processes dictate how responsive, agile, cost-effective, predictive and intelligent firms have to be to stay competitive.
To this end, we have delved deep into all the four dimensions of the Digital OneOffice, and conducted deep analyst discussion to aggregate service provider performance at delivering the sum of the Digital OneOffice parts:
So how did the Winner’s Circle service providers fair?
Accenture
Strengths
Well-rounded portfolio across OneOffice: Accenture has the best performance overall across the OneOffice portfolio, and a breadth of industry expertise to complement it. Accenture placed in the Winners’ Circle for each of the Blueprint studies used to compile this OneOffice assessment.
Strong marketing operations capabilities to support integrated digital OneOffice offerings. Accenture has 16,000 business-focused staff dedicated to delivering digital marketing assignments – a considerable asset that goes well beyond the firm’s IT delivery.
Strong intelligent automation capabilities. Acquisition of GenFour and exciting partnerships, with significant investments, with the likes of Automation Anywhere, Blue Prism and IPSoft.
Winning with thought leadership: Accenture is well-known as a thought leader across many of the change agents as well as within individual industries.
C-Suite relationships beyond IT. Digital business and intelligent automation decisions are largely being driven by both IT and business C-Suite executives in the Global 2000. Accenture has the combination of strategic relationships outside of IT, in addition to the managed services execution.
Leveraging creative assets for CX and UX design: Accenture has developed an industry-leading focus on becoming a customer experience expert, as evidenced by its 30+ design agency assets, by the broadest portfolio of digital design assets in the services industry (click here for a full list of digital M&A in services.)
Challenges
Size can work in its disfavor: Its size and success have given Accenture a reputation as a premium, high cost, and less responsive organization. In particular, for smaller companies, just this perception in the market can steer buyers instead toward more niche specialized agencies and the attention, flexibility, and experience they receive from a smaller provider.
Finding the right culture balance: Accenture is well known for its results-driven, traditional consultancy culture, which will need to be balanced out or effectively blended with the more left-brain focused acquisitions in order to retain creative talent and remain generally effective.
Proving to the industry it can deliver the end-to-end Digital OneOffice portfolio: There is no doubt that Accenture can pick up strategic work and execute for clients, but being able to demonstrate to the industry it can deliver both the strategic design integrated with complex operational delivery – at scale – is still in its infancy. Many of its competitors will fight hard for execution work where Accenture is delivering the high-end design and consulting. It needs to demonstrate the “one-stop OneOffice shop” is where it wins.
IBM
Strengths
Strong intelligent OneOffice offering: Market leading capabilities to drive the OneOffice underbelly (automation, security, cloudification) and neural networks (AI, smart analytics, blockchain, and IoT). Impressive development of credible global automation capability and several notable early wins.
Portfolio breadth: End-to-end and scaled IT and business process services across front, middle, and back-office.
Horizon 4 investments: Very strong investments and IP in horizon 4 (and beyond) technologies that will shape the future (e.g., Quantum Computing).
Design Thinking: Has made some considerable investments in recent years, but needs to align more aggressively with OneOffice approach
Watson: The analytics/cognitive powerhouse has a significant role to play as a cognitive virtual agent, an analytics resource that has huge scalabiity and a long-term investment area for firms with deep interests in their cognitive capabilities.
Challenges
Size can be a disadvantage: IBM is a large and complex organization, which makes it hard to seamlessly deliver all that it has to offer.
Translating tech to business outcomes: IBM is often perceived as a technology powerhouse, but one lacking the business translation and context to successfully apply emerging technologies.
Agility: Lacks the nimbleness and flexibility of smaller players.
Focus on cognitive may impede its ability to compete for design-focused end-to-end deals: IBM has substantial credibility to drive analytics-driven, cognitive/automation projects, but its lesser focus (over the last couple of years) on true digital design may see it lose out to firms such as Accenture and Cognizant, where digital is firmly established at their core.
Cognizant
Strengths
Digital marketing is leading front office services: Cognizant performed well in our digital marketing services Blueprint, primarily based on its targeted acquisitions and proprietary IP and frameworks.
Solid portfolio for the digital underbelly: Cognizant landed in the Winners’ Circle for each digital underbelly-focused Blueprint.
Strong thought leadership: Cognizant has a very compelling and polished messaging around customer experience focus and automation with forward-thinking leadership, bolstered by design-oriented acquisitions.
Simple, focused strategy: Unlike several of its Indian-heritage counterparts, Cognizant has always kept its focus simple and business focused. It’s “SMAC stack” approach was the perfect prerequisite to digital.
Challenges
Integration of key acquisitions will be key to success: Cognizant has made targeted acquisitions such as Cadient, whose capabilities the service provider is still working to integrate in order to bring value to clients.
Expansion of Design Thinking across services capabilities: Cognizant needs to develop its Design Thinking capabilities to other elements of services outside the front office in order to help its clients on the journey to realize the OneOffice endgame.
Keeping the momentum going: Cognizant has grown faster than any of the major service providers over the last decade. Keeping its scale aligned with its growth is going to be a challenge to the firm, with greedy investors still expecting 10%+ annual growth in a slowing market.
Infosys
Strengths
Portfolio across OneOffice capabilities: Strong capabilities across all dimensions of the Digital OneOffice—digitally enabled front office, digital underbelly, intelligent support functions and the nervous system. Recent re-focus on digital expansion is a plus.
Focused go-to-market approach: Digital platforms, automation, and AI have emerged as key pillars of the go-to-market strategy.
Digital OneOffice transformation services: All-rounded and scaled IT-BPM capabilities required for Digital OneOffice transformation.
Data DNA: Infosys has already been very strong with its data capabilities and provided it stays focused on this new course (see the recent interview with its new CEO), the future should be bright as a OneOffice heavyweight.
Strengthening BPM capabilities: InfosysBPM has demonstrated some of the strongest growth in the industry with some impressive BPM wins over the last 18 months. With deep competencies in middle/back office, in addition to marketing and analytics, the firm can make a strong run at the likes of Accenture, IBM and Cognizant, provided it keeps investing in its digital capabilities.
US onshore investments: Infosys has targeted 10,000 new staff to locations such as Indianapolis and Dallas. This is being well received by politicians and clients alike and helping align the firm with clients needing more onsite/onshore support.
Challenges
Relatively conservative M&A outlook: Despite recent acquisitions, overall outlook to M&A continues to be conservative.
Leadership turnover: Frequent changes to top leadership impact market positioning and consistent messaging. The new regime has to keep this ship firmly focused.
Market perception as a tech player: Infosys continues to be perceived as a technology player and needs to double down on driving business context in its solutions.
Needs to spend some of its war-chest: Infosys needs more depth in front-end digital delivery than Brilliant Basics and WONGDOODY. Salil needs to go shopping and spend some of his massive war-chest.
Wipro
Strengths
Key acquisitions bolster digital transformation capabilities: Wipro’s acquisitions of Designit and Topcoder (Appirio) give Wipro some significant assets for strategic design and UX, and also strong talent in the realm of data science, design, and development.
Services delivery excellence: Wipro has a strong execution approach to BPO and RPA with its Enterprise Operations Framework and is known as a solid delivery partner across a broad portfolio of services. Strong global presence and competitive aggression to win strategic deals.
Partner ecosystem: Wipro Ventures’ investment highlights its partner-focused approach. it’s reputation for being easy to work with has helped the firm develop exciting alliances with emerging firms in the fintech, startup space.
Much improved thought leadership: In previous years this was a major weakness for the firm, but a successful rebrand and a consistent delivery of market positioning and client experiences has change the percpetion of Wipro significantly with clients and market influencers alike.
Reputation for execution: Wipro has done a lot to up its game in recent years to deliver a multitude of touch, complex global deals. Many of its clients have a strong level of trust in the firm to move further up the value chain.
Challenges
Integrating acquisitions for a more consultative capability: Clients are looking for stronger thought leadership from Wipro and could use a stronger business- outcomes approach to its messaging. Further integration of acquisitions like Designit can help Wipro be a better innovative thought leader for clients on the journey to OneOffice.
Development of marketing of HOLMES platform: Wipro should invest in messaging for its HOLMES platform, one of the first broad automation frameworks on the market, to highlight its deep capability and assets in the bot library.
Needs more front-end digital acquisitions: Not dissimilar to Infosys and TCS, Wipro needs to keep focused on further front-end acquisitions to boost its digital presence with the design areas of the market.
TCS
Strengths
Client relationships: Appreciated for its engagement with clients, proactive focus on process improvements, and flexibility. Good account management skills. Clients mention factors such as understanding their business and unique operating models and being flexible to work with.
Embedded analytics: TCS is one of the top service providers with analytics reported as embedded in contracts. Has positioned much of its talent in its data analytics areas as a front-end strategy.
Intelligent Automation: Major focus on internal capabilities, including ignio platform. Impressive record with clients and a willingness to cannibalize revenues to grow emerging areas.
Partner ecosystem: TCS has a strong partnership ecosystem for emerging technologies. Its work with academia and startups has been most impressive, with significant funds being invested to create strong talent programs and joint business ventures with innovators.
Challenges
Thought leadership needs a lot more focus: TCS needs to be more proactive and vocal about ideas around innovation and best practices. It is often challenging to pinpoint the core focus of the firm beyond being a competent technology firm.
Behind on M&A: While most of the big service providers are scaling up their portfolio through acquisitions, TCS has made a few acquisitions, but is relying primarily on organic growth. While this is clearly a desire from leadership to grow organically, it could significantly stunt TCS’s ability to evolve into more creative design areas where the firm is currently lagging. A reversal of strategy is probably likely in the future as the market shakes out.
IT services and middle office focused: Aside from a strong digital marketing offering, TCS is more back and middle office, with more of an IT services presence in the middle office. BPM was a core focus, but seems to have faded somewhat in the last couple of years.
Heavy India delivery: TCS could increase recruitment in specific geographies for more diversification.
Other notable service providers
Outside of the winner’s circle, Capgemini was one of the most notable exclusion, despite a well-rounded OneOffice portfolio across front and back office. The firm still struggles with its North American portfolio, despite its IGATE acquisition and its co-CEO structure and lack of thought leadership has held back progress. Genpact has impressed clients with its LEAN Digital approach, its depth in processes and recent acquisitions in AI, but its lack of scale in IT has kept the firm of the Winner’s Circle. HCL has performed well its strong breadth of services, strength in automation and notable flexibility with clients, but lags the leaders in terms of digital design, change management analytics and innovative messaging. DXC is still trying to find its feet since the HP/CSC merger but has very strong IT delivery capability. The firms does need a strong injection of market positioning and expansion beyond its infrastructure capabilities. Tech Mahindra has quietly emerged as a high performer, boasting a series of impressive digital front-end platforms, a real appetite for innovation and strong client partnerships. We expect the firm to keep improving its market position, providing it can diversity effectively beyond telco, make some astute analytics investments and leverage its M&A for effectively (its Pininfarina acquisition has largely been considered to be misaligned).
Bottom-line: Winning at OneOffice services is about delivering the four dimensions as a true client partner with co-defined outcomes and investments on both sides
The traditional services model was all about delivering incremental productivity and efficiency for clients. There was rarely much purpose behind the client/service provider relationship beyond attaining a series of predefined cost/delivery metrics and KPIs. And once the first set of metrics were met, the next set was normally more of the same, but with added pressure on margins, which ultimately led to a degrading of quality and talent. “They sold us the A team and we ended up with the B and C team” is probably the most worn services catchphrase of the last two decades in the services industry. However, if clients wanted the cheap and cheerful model, that’s ultimately what they ended up with: getting exactly what they were paying for. All you have to do is look at the depressing number of legacy services relationships littering the Global 2000, where most the value has been squeezed out, and both client and service provider are stuck on a depressing treadmill where both often want out, as they just don’t get much business value from the relationship.
Fortunately, the business imperatives have been changed forever with the evolution of digital business models, which is having the impact of driving much smarter, value-driven partnerships for ambitious clients and service providers. Sure, there will always be the laggards who will persist on cranking out the same old business models until they fade into insignificance, but 57% of digital decision markets among the highest performers (based on revenue and profitability) in the Global 2000 now view their primary service partner as a co-creator of innovation and value, as opposed to a provider of prepaid services that merely provides efficient services as our recent study looking at digital transformation to the OneOffice reveals.
This data speaks volumes – enterprises digital leaders need providers which can work with them to achieve outcomes that are increasingly challenging, with only a third viewing their service providers solely as a resource to provision skills and scale via a headcount model.
A true digital business cannot succeed without unifying front, middle, and back offices – it’s no longer about being great at one component, it’s about weaving together the disparate parts to bring customers and employees as closely together as possible to create the best possible customer experience that wins out in cut-throat markets. Sure, there will always be niche opportunities to support certain needs for enterprises, but the ultimate winners will be those which can partner with their clients to help define and deliver their business outcomes over the long-term. This means providing the business intelligence, market understanding, and technical abilities to help their clients be as competitive as possible. The stakes are higher than ever, and the smart providers are those placing their investments in clients with whom they can thrive over the long-haul.
Salil Parekh, recently appointed CEO and Managing Director for Infosys took some time out of his busy schedule during his client partner conference to catch up with me to talk about his vision for all things Infosys and the future of services…
Phil Fersht, CEO and Chief Analyst, HFS Research: Welcome to your first HfS interview Salil! Maybe you could take us a little bit back to your early career. When did you get the appetite to lead one of the largest IT services firms in the world? You know, was this something you always wanted to do? Was this planned, or have you always been an opportunist?
Salil Parekh, CEO, Infosys: Thank you, Phil, this was quite an un-planned scenario for me. So, maybe when I finished with Engineering, a Master’s in Computer Science, and I was working with a consulting firm for years. Then we got acquired by a consulting and tech company, so I’d basically been in the same company for 25 years. And then this opportunity showed up a few months ago. It’s a tremendous privilege to have this opportunity. It’s one of those things you dream about, in your career, as you sort of think, ‘Maybe it’s possible,’ but when it happened, at least, for me, it was completely unplanned. So I’m delighted to be here, I wish I could plan such things, but I can’t [laughter].
Phil: So, how would you compare this new Infy experience with Capgemini, you know, both global services powerhouses, one with a Parisian epicentre, the other one Bangalorian, so – what haves been your observations?
Salil: Well, I think, Cap’s a fantastic company. I think I would focus much more on the strengths that I’ve found within Infosys. The first few months, I’ve spent essentially meeting with our clients and our employees. I met with just about 50 clients, and it’s been just amazing to see how much the clients trust Infosys, and our delivery capability, and the strength of the organisation. And then, with the employees, it’s been much more the pride in being with a number one company. And so to me, we have, at least in my mind, an incredible platform, from which, if we can execute right, we can become partners for our clients’ digital journey. So, that’s really the joy, of where I am at Infosys right now.
Phil: Salil, your predecessor unleashed some of the passion and culture in Infosys; it didn’t quite end up, I think, how he wanted it to, but how do you think you’re going to be different from him?
Salil: So, my thinking is, the way we’ve built our strategic direction, which I’ll spend a minute on, maybe later, is, what are our clients looking for and where are they going? So, how do we evolve with them? Then, what other new areas, new clients, can we target from our asset base, or our foundation? And those are the two ways in which I have looked at the business. From our clients, they all want to progress on their digital journey. They have the foundation tech in good shape, and my focus is going to be to see how we scale up our own digital focus to go on that journey with them.
It’s interesting, already one fourth of our revenue is in those Digital areas, so it’s not that we’re starting from zero. The new Digital areas that we want to go after, there’s new sets of clients, there’s expansion in the European markets, there’s more expansion in the Asia-Pacific. There are some sectors we are underpenetrated, healthcare, or life sciences, or manufacturing, and we have great strengths which we can leverage, I think, to go after those. And in terms of the strategic direction, it’s more in the services area, with 4 pillars – scale agile digital services, energize core services, reskilling of our people, and localising, that is a new approach where we’re starting to build delivery capacity here in the US, in the European markets, in Australia, to make sure that we are closer to our clients. So, that’s the direction that we’ve charted out, and so far, it’s something that’s resonated with our clients, with the market, (I know you had presented a set of views after our analyst day), the sales teams within the company. So, I think there’s a lot of support and traction for this approach, and now it’s more really, an execution play for us to make sure we get this organized properly.
Phil: I think you’ve excited the market, acquiring two interesting digital firms in the UK, and US: Brilliant Basics and WONGDOODY. What’s the plan to bulldoze your way to the front of this market? Do you have an M&A strategy lined up, or is this going to be more opportunistic? How do you think this is going to play out for you?
Salil: There we have a very focused approach to what we call ‘Programmatic M&A’ and we’ve defined five dimensions of digital: experience, insights, innovate, accelerate and assure. Behind that, we’ve put each of our service lines. So, our head of M&A, Deepak is now looking at, from the landscape of companies that are in the market, how do they map on to this framework? And then which are the areas we should invest in. From these, we want to create multiple $1 billion businesses. So, you can take an example, on the cloud migration journey. There’ll be large plays in Azure, AWS and Google Cloud, and we want to be in that space. There’ll be large plays in data and insights. On experience, which is where these two companies are, Brilliant Basics and Wongdoody. Traditionally, we do not have a strong position in these areas, so I want to make sure that we build up our position, so that we can engage with our clients on any aspect of this digital journey. Different clients start at different places, and then go on to the different parts. And what we have noticed is, that it’s not really a transformation with a start and a finish, it’s more a journey that people are going through different components, some going faster, some taking a longer path. My approach, through this five-pronged, Digital ‘pentagon’ that we’ve put together, is that we want to be part of any digital journey. Therefore the experience side, is where we thought we should build out some strengths. But overall, we’ve got, I think there’s a shortlist of companies that he has built, from some companies that we’ve been meeting over the last three months. With M&A, as you know, it’s more a question of availability, price, and, sort of, a lot of other factors going right at the last minute, culture, integration, fit. So, hopefully we’ll start to execute on that.
Phil: M&A’s been a key issue in our industry for a while, Salil. There’ve been far more failures than successes when we look across the board at all that’s happened over the last few years. As you look at bringing on some of these emerging companies, with a very different mindset, what’s your view on how to integrate them into your business?
Salil: So, yeah, just as an example, with Wongdoody (and with Brilliant Basics); we are recruiting, in the US, students from design schools as well and those will essentially be under the direction of the Wongdoody leadership. Plus, two individuals from Infosys that will join that team, and that will drive the scaleup. So, they know how that must be done.. So, we will leverage their knowledge and experience, and build it out, under that umbrella. Then, our service line leaders have put together a plan for how all the experience assets, user experience, or creative, come together. We are also thinking about what we should do with the branding because at this stage, we’ve not made any changes; however, over a three-year period, we want to align to a branding position that we want to develop.
Phil: Salil, we’ve seen a few other providers try and influence their culture too much on their niche acquisitions (especially with digital firms)… and I think what you’re saying is, “buy some of these special firms, and nurture them, grow them, build them, retain the culture, and then figure out the synergies”
Salil: Absolutely, yes – because, as you know, there are two basic models of acquisitions in our business. One is, buy it, make it look exactly like them, and then go ahead.
My experience has been much more than you buy something, learn the culture, and try to build the best of both, as opposed to overwhelming one or the other. And this is what we are trying to do by not changing the culture, in fact, enhancing it. We still need to have some guidelines in how the overall strategy comes together, but the culture is very difficult -if we start to impose upon these companies, as you mention, it will destroy value quickly.
Phil: There’s been a lot of talk, Salil, about investing in products .v. services. It feels like Infosys is moving down the services path. Going higher-value, looking at more consultative, digital mindsets…
Salil: My focus today is much more services. But what I would say is, first, there are things that I call platforms, and what I mean is, within Infosys, we have an insurance platform called McCamish. You may have heard of it.
Phil: I know it very well…
Salil: So, that, I will scale up. So, we just announced, three weeks ago, a large win with John Hancock, it’s in the public domain, $175 million win. That is a phenomenal approach, we think, in the insurance market of today, where we can use that platform. So, it’s not just a product play for us. Equally, we are not (and we’ve announced that we are exploring to sell Panaya), which to me, is not a product that I can scale that much. The market there, for SAP upgrades, has changed and there’s always bandwidth issues and management. So, if there are platform plays, we will actually buy and expand. We are not going to, at least at this stage, look at standalone product plays. Some of these also require multiple third parties to implement them, which is not easy, when you sit within a services company. So, given all of those dynamics, that’s the approach we’ve taken, primarily services. If you can build a platform that would be phenomenal, like this McCamish one, there could be others you could imagine, on mortgage processing, or trade settlements. There are areas which lend themselves to platform. But we have to find something, or build it ourselves, and that we will scale.
Phil: I’m sure your BPM guys’ll be thrilled to hear that =)
Salil: They’re delighted and BPM’s growing very well for us right now, so we are very happy with that.
Phil: Good. I’ve known them since the Progeon days!
Salil: Oh, brilliant! Okay. Yeah, no, I think if you saw that, we went through a bit of a dip, but the last 24-36 months, we had a good trajectory. In fact, if you look at it on a standalone basis, it’s probably the highest, fastest-growing BPO business, if I look at competitors, and it’s also the best margin BPO business. So, I think that, in that business, I will happily invest in platforms.
And there is Finacle, where we are leaders, and that is a product and a platform play for us, that we are scaling up. We have seen recently two very successful Digital banks being built on Finacle – one here in the US and one in Asia. That is a strong business for us and we will look to scale.
We also have our AI platform Nia – which will become the foundation of all our services re-invention. We will enhance and build that out.
Phil: So we’re looking at a lot of these interesting insurtech/fintech businesses. What’s the approach there? Are you going to look to acquire these, or maybe do more partnering?
Salil: So, today we are more on the partnering, but it also depends. There are some fintech players, which could become a platform. But today, as you know well, they’re very expensive, if you’re going to buy. So, you’ve got to figure it out first. And we’ve not done a lot of partnerships yet. We’ve got an investment fund, through which we invest, we haven’t tried yet to have a partnership where we do many client projects together. So, first we’ll try a bit of that with the fintechs, and then, if it looks like we can build, again, a scaled fintech play, which is more a platform, so it’s not just a product play, then we will look at it eventually.
Phil: So, one final question, Salil… You’ve been annointedthe Emperor of the Services Industry for one week, and you have one wish, to change the industry for the better. What would that wish be?
Salil:[Laughter]. Give all your business to Infosys, of course [laughter]. But, no, I think, you know, it’s a bit ironic, notwithstanding what people outside think, I feel like we are in a uniquely good position, so I’m not sure I would change many things. We are doing many things to enhance our position. The industry, itself, is in a nice phase where there is massive opportunity in the future, clients are changing. For any company that’s ready to invest and position themselves, within the next five years, you will have a new set of leaders emerge, and to me, that’s as good an opportunity as anyone can get, when you have a huge incumbent company, which still has an opportunity to win again in a different area. So, I’m delighted. There’s not too many things I would change. I think the best wish is, try not to be the Emperor beyond a week [laughter].
Phil: There you go, that’s a fantastic answer =) Good luck in the new role, Salil… you sound very geared up for it!
As am sure most of you noticed, HfS quietly released the most comprehensive customer satisfaction benchmarking of the 10 leading RPA solutions, authored by Saurabh Gupta, myself and Maria Terekhova. We covered 359 super users of RPA products (enterprises, advisors and service providers) across 40+ customer experience dimensions across the following 6 key dimensions:
Features and functionality
Integration and support
Security and compliance
Flexibility and scalability
Embedding intelligence
Achieving business outcomes
As an example, here is how dimension 6, “Business Outcomes” came out looking across the products:
So why did we undertake this research?
Our industry is plagued by many consultants with limited depth in RPA, who have no access to product level data that supports the tough decisions facing enterprises. In addition, most analysts deliver these 2 x 2 matrices which offer very limited insight or value (and all look remarkably similar). It’s time to dispel myths and provide enterprises with unbiased, credible and highly statistically significant data. The HfS RPA customer experience benchmarks are designed to help enterprises with RPA product selection as they formulate their intelligent automation roadmaps.
It’s more than a report… it’s an online RPA decision-support tool
In addition to the report, HfS is also launching an online RPA decision-support tool for enterprises to enable client-specific due diligence on RPA providers. This tool will allow HfS clients to customize the decision criteria and associated weights from the available 40+ customer experience dimensions. It will provide clients a customized report detailing the top three RPA products that the client should consider, based on the rich insights that HfS collected as a part of the RPA study. HfS analysts are also supporting RPA clients through collaborative ThinkTank sessions, half-day workshops designed to problem-solve and validate strategies. These ThinkTanks go beyond the data where HfS analysts can share HfS IP, perspectives, and experiences on RPA tool selection, best practices, and common pitfalls to avoid.
So take time to delve into the realities of RPA and some of the findings may just surprise you
The industry is still struggling to solve challenges around the process, change, talent, training, infrastructure, security, and governance. Our mission at HfS is to dispel this confusion and uncover the truth to successful RPA deployment. It’s time to separate the hype and propaganda from reality – and here is the reality!
However which way we look at it, driving out costs from business operations still dominates the directives of C-Suites across the Global 2000 – just revisit our 2014 study to see how little has changed. Fast forward to today, and the only real differences, since then, are the methods to slake this thirst for cost elimination, as traditional operating models are no longer delivering much more than incremental value.
Our new State of Operations and Outsourcing Study, conducted with KPMG, covers the dynamics of 381 operations leaders from the Global 2000 and reveals these rapidly changing C-Suite directives to drive out their number one nemesis: cost.
Traditional cost savings models are running out of steam, as robotics, predictive analytics, OneOffice and cognitive become the new operating value levers
Little tweaks here and there to delivery locations and headcount allocations are becoming less and less effective, as it becomes clear only the fundamental rewiring of underpinning data repositories – and the digitization of manual processes – are going to progress operations to a place where real efficiencies can be enjoyed. In addition to fixing data and manual processes that clearly hit that old cost button, C-Suites are also recognizing the dire need have their customer needs being addressed by their employees as and when they occur (OneOffice), and also to invest more in cognitive tech and machine learning to drive more value from their current pool of talent:
Cost reduction mandates still fall well short, but expect to see them improve as data-driven initiatives bear fruit
The perennial issue here is clearly one where C-Suites rarely feel exhilarated by the cost reduction impact of their operations leaders. Of all their mission-critical directives this year (see above), none disappoints them as much as their ability to impact cost reduction (only 28% are very satisfied), while there are much larger numbers of C-Suite leaders already a lot happier with their robotic process investments (40% ‘very satisfied’ and a further 30% ‘satisfied’). However, as we continue to see this strong impact in these areas aligned to robotics, OneOffice, and predictive analytics, surely it’s merely a test of time until we see these initiatives having greater visibility, in terms of ironing out unnecessary costs and inefficiencies in the system.
The Bottom-line: It’s taken several decades, but our enterprises finally have no choice but to make fundamental changes to the very make up of their processes, data, and people if they are going to survive
Ever since my first blog 11 years ago (right here), we’ve pretty much repeated the same conversation that’s been continually refined over the years. The only game changers have been the gradual need for less people to run operations as cloud-based software platforms take-hold, offshore talent is optimized, and the more recent introduction of robotic process automation solutions to remove manual workarounds and create broader digital processes, that can be aligned with common business outcomes and metrics.
However, these changes are more fundamental than merely slimming down the number of cooks in the kitchen and making the food taste better: it’s forcing a complete rethink from ambitious firms to redesign operating frameworks where revamped business processes are enabling true digital business models, where emerging AI capabilities can be weaved in… where innovation is native to the culture of the firm and its people. Yes, it’s redesigning the entire kitchen, not merely hiring some better chefs with better recipes.
The toughest challenge is fixing many years of poorly-constructed data repositories, where the corporate IT ancestors that built them have likely long-since departed, and other IT stormtroopers from the midst of time have plastered on countless workarounds and spaghetti coding to keep the back end (somehow) functioning. These are the deep, murky areas where it’s frighteningly difficult for many firms to take the risk of investment and change to find their way out of the dark data ages. Somehow ripping out the very fabric of what got you here is what you may have to do to survive in the future… and that can be one very painful, risky and costly experience. Sure, you can keep papering over those yawning cracks, but the wallpaper just isn’t working like it used to…
We’ve talked a lot about the HfS Digital OneOffice operating framework – it’s the HfS vision for the business operations endstate for digital organizations:
The Digital OneOffice is where teams function autonomously across front, middle and back office functions to promote broader processes with real-time data flows that support rapid decision making. It’s where front, middle and back offices will cease to exist, as they will be, simply, OneOffice.
Why Digital OneOffice?
Digital organizations must have an operating framework that maps out how they have to operate in the future. Traditional operating models, while creating some incremental productivity value if managed effectively, struggle to drive the unification of digital business models with emerging technologies across a business’s operations:
A true digital business cannot succeed without unifying front, middle, and back office
Traditional approaches (organizational restructuring) have failed to have a purpose beyond incremental efficiency / productivity
The Digital OneOffice is the organizational end-state to survive and succeed
What is the Digital OneOffice?
The Digital OneOffice focuses on real-time customer and employee engagement. OneOffice is:
Collaborative (Collective outcomes)
Unified (Without silos and hierarchies)
Dynamic (Agile and scalable)
Intelligent (Predictive, not reactive)
Responsive (Real-time)
Simple (Touchless and autonomous)
How to achieve Digital OneOffice?
The Digital OneOffice is the framework for achieving a true digital organization:
CX is not just fancy UI. Make CX the core of all your business operations from front to back. Cost reduction is not a strategy. Drive organizational alignment and metrics that measure value creation, not only cost reduction. Weed out the people unprepared to change. Invest in an inclusive talent strategy, based people who want to learn and share. Your tech infrastructure is everything. Automate, digitize, cloudify, and secure your organizational underbelly. Build co-innovation relationships and shed legacy relationships. The partners who got you’re here may not be the ones to take you where you want to go. Stop kicking the intelligent technology can down the road. It’s all here and now you need to make decisions on where you go with it Stop thinking about the Future of Work. It’s already here…act now!
The Bottom-line: Traditional operating models have been focused on incremental improvements, not creating genuine frameworks for digital organizations
While traditional models such as outsourcing, shared services and global business services promote incremental efficiencies based on centralization of support functions and use of offshore to lower operating costs, none of these models have provided an ideal endstate for ambitious digital organizations. Without having a true picture of how you want to operate in the future, you will be perennially be searching for short-term fixes to drive out further costs, and never be able to map out a strategic journey that will bring together your two most critical assets: your customers and employees.
Let’s be honest, the services business needs dynamic leaders, if we’re ever going to step up to being these innovators and true partners we keep claiming we are.
One such character I have enjoyed getting to know over recent years is Nitin Rakesh, who spent a good part of his earlier career at Syntel, eventually taking the CEO mantle for three years, until moving over to Mphasis just over a year ago, to revitalize the $1bn financial services focused IT services firm, which spent many years are part of HP, before being divested.
Nitin is also very active in the thought leadership sphere as chairman of the IT services council for NASSCOM, and serves on the advisory broad for Knowledge@Wharton (among other activities). But one of the things you’ll get to know about Nitin is his brain typically works faster than most mortals, especially when it comes to his favorite topic about aligning technology to the needs of the customer, and working those desired outcomes right through to the back office, which is a philosophy very close what we believe in at HfS, with our Digital OneOffice conceptual framework.
So let’s hear a bit more from Nitin about how to get ahead in today’s IT services industry, and what we need to do to be effective in the wake of intense competition and the leveling off of traditional IT services…
Phil Fersht, CEO and Chief Analyst, HFS Research: Good morning, Nitin. It’s great to have you on here. To start with, I’d love to hear a bit more about you personally – you’re a technical guy, you’re an engineer at heart. So how did you wind up running a billion-dollar IT services firm? Tell us where this all started and why you’ve been so successful at it.
Nitin Rakesh, CEO Mphasis: Thank you for that, Phil. I think I am an engineer at heart, I love building stuff. Early on I started experimenting with newer areas – as I came out of college, back in the days in the early ’90s looking at how do you apply technology to things like image processing, character recognition. Those were very early days of artificial intelligence because you are teaching the software how to actually recognize handwriting.
So I think early on I got really excited about the impacts technology can have on our daily lives, and how we can change the world surely but certainly. I think from then I’ve never really looked back even though I’ve done a few stints in financial services. How do you apply technology and innovation? Back in the day, in the mid ’90’s, there was a field which is now also pretty prevalent called ‘Technical Analysis of the Markets’. And that was nothing but pattern recognition to see how do you analyze human behavior looking at the patterns in stock markets or their price behaviours.
So I think the theme started to get clearer to me over the years, but I’ve been lucky that I was at the right place at the right time as well. More importantly, I am really passionate about applying technology to everyday problems and ended up running a technology services company.
Phil: We got to know each other when you were at Syntel, but you’ve since taken over Mphasis, and now it’s free of the HP empire (or former empire). So how is that business refocusing itself… and where are you taking it?
Nitin: I think this company has got some unique capabilities despite having gone through both shareholders in the last 12 years. I think we have retained and maintained our focus on applied technology. The company was founded by two ex-Citi bankers, so the focus was always applying tech to financial services and banking.
One of them was a business leader and the other one was a technical leader, a CTO. I think they built a techno-functional mindset into the business more than just a functional approach to applying problem-solving. I think it was always about embedded technology. And I think under EDS and HP, some them flourished, but some of them were impacted due to the overall global empire of HP, and the fact that we were a small piece of their overall business.
But as I came onboard about a year ago, we do have a fairly progressive shareholder who encouraged us to find our footing based on our areas of strength. What we’ve really been doing over the last 12 to 18 months is, essentially, differentiating ourselves by being an applied-tech firm that focuses on looking at how to apply new technologies to everything that banks, insurance companies and financial services firms do.
This is really about looking at, in the current age, how we make every enterprise customer-centric for their end customers and consumers, and how do you apply technologies to help them get closer to their customer in order to improve customer experience, reduce downtimes, offer targeted products and services with hyper-personalization? And all of this at a lower cost, with a fast time to market. So that’s kind of the mantra that we’ve set for ourselves.
Phil: A billion dollars in revenue: Surely, Nitin, that should be the ideal size to be big enough to be dangerous, but small enough to be sort of nimble and disruptive. What does this mean though, in reality? Can you share an example or two of how you can disrupt with your clients, while also delivering the bread-and-butter work that keeps the machine going?
Nitin: Absolutely Phil. That’s a great positioning statement! We actually use a variation of that quite often. But I think our positioning almost always is that of a ‘champion challenger”. And from that, one, we obviously have the agility and the customer-centric focus on our side. We aim to give clients a personalized white glove service experience and we continue to invest significantly in our capabilities to stay ahead of the curve. In fact, there are multiple examples where we’ve been fairly nimble – but also aggressive – about going back to our clients and proposing to them things that challenge how they run their current operations, whether technology or business.
I’ll give you a small example: Why should we not apply something like predictive analytics to an offering as standard as infrastructure application management? Why should we not turn AMS or an IMF into a big data analytics problem, and why should we wait for something to fail or break, so that we can go and fix it, which is (let’s face it) the traditional IT outsourcing model?
So, I think, from that perspective, it means that we end up shrinking the overall footprint of the ITO team, but that’s okay with us because I think that’s the right thing to do for the customer. So, I think from our perspective, we’ve been fairly aggressive in moving clients along this journey of applying technology to traditional services as well.
And given that our scale is normally a fraction of some of the very large players, we are able to go back in and propose something very creative, even if it means that it actually shrinks the core and has an adverse impact on us as well. I just think that’s the right thing to do. So that’s how we are able to challenge the status quo, and in the process, carve out a position for ourselves.
Phil: One of the big discussion topics we talked about at our recent New York FORA summit centered on emerging technologies like automation, machine learning not being an end – they are just a means to get from one place to another. So, what are these places? What – in your view – is the real end-game for clients these days?
Nitin: Great question, Phil. I think I’m a big believer in the fact that every next technology isn’t anything more than a tool, and what you do with it depends on how you are able to align it with one or two objectives. I talked about the fact that one of the biggest reasons why we are seeing fairly high degrees of disruption, especially in consumer-facing industries, is because, over the years, enterprises became so complex in the way they ran their back office systems and operations, that almost every business that’s been around for 25-30 years is essentially run back-to-front what that means that the back office determines when you can launch the next product, the back office determines what’s the next recycle for you to be able to make changes to your system, so you can have the new functionality.
The back office determines how much flexibility do you have, and so on and so forth. Whereas if you look at the new age, truly digital companies, they actually put the end customer in the middle of everything, and work backward from that. So how do you really pivot the focus of large enterprises from being functionally operationally back-office driven, to being customer-driven. And that’s how you should think of applying all new technologies, whether it happens to be analytics, which should give you the ability to understand every customer, or whether it is some form of AI, machine learning or robotics, which should really be able to reduce the time and cost it takes for you to service customers.
I think applying this customer-centric transformation, starting at the front of the customer and moving towards the back office, is really what we think that today’s technology should be applied for. Beyond that, IT has always been about automation of an existing workflow or a business process, so I think automation is really nothing but the next generation of that.
So I’m a big believer that if you keep customers at the center of everything and if you apply this transformation, essentially to provide a hyper-personalized and a great experience to the end customer, I think every large enterprise will find the digital pivot that they are looking for to avoid disruption.
Phil: As you look at expanding your own company’s footprints, Nitin, does this have a big impact on the profile of people you are looking to bring in, the backgrounds, the talent base, the business mindset? How is that changing your whole growth and talent strategy?
Nitin: I think It’s very much central to the transformation, Phil, that we need to drive as service providers in our business. I think a little bit of everything you just said absolutely, first and foremost we need our people to be aware that this business is not about just throwing resources at a problem but it’s about applying technology to the problem. So I think that’s the first realization that we’ve driven through our org.
Secondly, it’s not just about understanding one aspect of the functionality. You can’t just be a tester or a developer anymore – you have to be able to understand the entire stack of what goes on and, from that perspective, I think what becomes really front and central is what we are calling the architecture or the design layer. i.e. How do you combine an architectural solution mindset with a developer (with a software engineering mindset) to create that sweet spot of what we call a T-shaped developer or a T-shaped employee . On the one hand, you want them to understand a certain particular functional domain and, on the other hand, you also want them to be steeped into the technology horizontal domain. So, I think driving this T-shaped approach has really been our core focus.
Again, we’ve had, as I mentioned, a long track record of a techno-functional approach. We’ve got an architectural mindset and are, in fact, one of the first companies, more than 12-13 years ago who set-up an architectural community, and we’ve got to double-down on that, which is why we are driving it top-down from that perspective.
Phil: Nitin, try and think ahead three years, beyond the current horizon. What do you think our world of technology is really going to look like? When you look at the pace of change, how fast we are moving today when you consider the speed at which we’ve developed in the last decade? What do you think we’ll be talking about in three years time?
Nitin: I can give you some guideposts and some megatrends that I think will continue to evolve. Which technology will be front and central is hard to call. A good example is, who knew 18 months ago that everything in the world would be powered by Alexa. So similarly, I think it’s hard to call these technologies, but I see no reason why we shouldn’t see the continued focus on applying all forms of new tech to the customer experience. If that means that we end up evolving to a contact-less UI, whether it’s voice or AR, VR, some combination. I think that will definitely be a good example of how all things customer-centric will probably drive a lot of the technology implementations.
Secondly, I think most the enterprises will continue to focus on shrinking their core technical debt legacy footprint, applying technologies like cloud, and some form of cognitive as well.
I think, directionally, how do you improve customer experience, how do you continue to drive personalization, how do you reduce time to market, how do you drive a higher ability to monetize and understand the customer to cross-sell? And, finally, all of it must be done at a fraction of the cost, because that’s essentially what the problems of new tech are. So I think those four or five business priorities don’t look like they’ll change in the short to medium term and I think that’s the reason why almost all large enterprises will have to learn to adapt everything to the customer.
Phil:Do you think that the IT services industry is genuinely poised for a massive change, or do you think it’s going to be slow, gradual and uncomfortable? What’s your prediction there?
Nitin: I think what’s definitely happening is that as the growth rates in the core services, (the traditional ABM/IMS/BPS/Service manager), those growth rates mature to the flat lining of the S curve – as they have been on a steady cliff for the last twenty years or so and now, as they settle into mid to high single digits, I think there are a whole lot of questions being asked by investors as to whether this is still a growth industry or are we genuinely starting to look at a value mindset. I think that’s what you are starting to see with some of these large activist investors.
I think there’s still growth in the industry, but the growth doesn’t seem to be just in traditional services, which is why I think it’s important to point new items of growth, new pockets of investment that the client is looking to put money behind. Whether it happens to be tangible consumer-facing tech, it happens to be large data initiatives, maybe triggered by platforms and all things AI. I think how you really add those engines of growth to your core business, and still continue to drive the business in a way that you are seeing in growth companies, is really the challenge that a lot of our peers will have to face, especially if they are public.
I believe we are in an interesting position because we have a large activist shareholder, and we are partly private equity as well, so we definitely think of how we can apply all things active to the way we run the business. I do personally believe that it’s possible to still be viewed as a growth business, however, it will require a slightly different bent of mind. It will have to be more than a functional pyramid driven people business, to essentially be something that blends in our core technology expertise, some form of IP and platforms, at a pace and scale that can complement our growth and move the needle.
I also think that whoever can find a way to blend new engines of growth – and stay above industry growth will succeed long term. This is an over simplistic view, but I think that’s the way I think about our business, I mean we’ve defined our top-most priority: growth, growth, growth and growth. And we talk about consistent growth, differentiated growth, profitable growth and responsible growth.
I think if we can continue to have that 4G’s of growth mantra, we’ll probably continue to look for above market growth, so we keep taking market share.
Phil: So, I’ll ask you one final question, Nitin. What can we do as both business leaders, but also as educational and government leaders, to help with some of these re-skilling issues we are seeing. At the NY Summit, for example, there was lots of talk about machine learning, and we had a session where 70 percent of service providers claim they are going to re-skill huge amounts of their delivery staff on machine learning, without any real clue on how hard and technical this is.
Is there a crunch coming here? What can we do to get a stronger alignment between these changing needs of the customer, and what we are delivering as digital business becomes so core to our clients?
Nitin: Absolutely, Phil. I think I’ll answer the question in two parts. One is what can we do to make this condition from the way our staff is currently to where we think we need to take them. Fortunately, or unfortunately, some of them probably won’t be able to make this shift because, keep in mind, the business model that they were hired under over the last few years was much more functional. You’re either a business analyst, or a programmer, or a tester or a production engineer. You really were focused to go deep into one of those functional areas, because that’s the way the business was defined. What this means is that since they were hired out of college, and I am talking about these large offshore labor pools, specifically focused on building skill and driving efficiency, since they have been hired out of colleges, they really have this very deep functional view of one activity.
In many cases (and I am not saying all), the students coming out of colleges today have the ability to apply new tech. I think there are two things we need to do there as well. Firstly, we need to be able to drive the most important skillset they need to be successful, which is to have is run-ability, because the applications for change (of all things new tech) mean you can’t be an expert in anything… so you have to be able to learn new things on-the-fly. Obviously, you need foundational elements of software engineering. So I think if you can drive this software engineering mindset, if you can drive the ability to learn new things, then I think we can definitely impact the next few years of generations coming out.
And secondly, I think we also have to – as an industry – go back, shift left, work with these institutions, work with the governments and create technology-driven platforms that can actually give the ability to drive some of this learning even while they are in college.
So I think there are multiple initiatives that have been underway. The Government of India has actually got a Skills Ministry who are focussed on this issue. I know that the Chinese government is doing a lot as well, and I know in the US it’s much more driven by the private sector and the universities. However, I believe we are going through a generational transition, and the realization of how we continue to apply tech to the new generations will effectively differentiate which demographic and which country with the right labor pool, comes out the winner over the next 15 years.
Phil: Thanks Nitin for these great insights. I really appreciate your time today and look forward to sharing this discussion with our readership.
Nitin: Phil, thanks a lot – looking forward to it.
What a difference an election makes. When we ran our State of Operations and Outsourcing study in 2014 (mid-way through President Obama’s final term), Global 2000 enterprises were still planning to increase their short-term investments in offshoring their IT by more than 20%. When we re-ran the study in 2016, offshoring intent was clearly dropping to a 12% intended increase (which is a realistic number for a saturating market), but this year it has nose-dived to a mere 5% increase, which is a clear result of the anti-offshoring sentiment that has hurt offshore-centric deals:
I discussed this trend with one of the lead partners at ISG, the offshore outsourcing industry’s largest deal advisor, and he shared that Trump’s stance against offshoring was considerably slowing down the deal cycle for his firm, and he was even seeing some outsourcing deals going to the likes of Accenture and IBM because it created the façade that work was not being offshored (even though it was). Yes, this is the kind of stuff that happens when a president likes to get fast and loose with his twitter account!
However, while Trump’s open attacks on American firms using offshoring stoked panic into many paranoid C-Suites, what really transpired was a rapid shift in how US firms are viewing their partnerships with global service providers. Today’s reality is technology has become core to business competitiveness by creating new revenue channels made possible by interactive communications technologies with customers, by simplifying business operations to support the business with real-time data, and by supporting broader processes that respond to the needs of customers, as they occur.
Offshoring may be slowing, but the services business is in its best shape for four years
The healthy trend here, for the future of IT and business services, is the fact that the industry finds itself on the healthiest growth footing since 2013 – so clearly offshoring is no longer the primary driver behind IT services investments:
President Trump merely speeded up the development of global services from a cost-reduction to a business-value proposition
Many enterprise leaders are clearly no longer thinking, “How can we shave some more cost off our annual IT budget by moving more work to India?”. Instead, they are thinking, “How can I get quality services delivered at competitive prices that take advantage of the cloud, automation,and global talent.” The subtle shift here is clearly one from an obsessive focus on low cost, to one of getting quality services as the industry matures, where there are many leverage points to find productivity gains, beyond merely relying on FTE rates. The more pricing shifts towards outcomes, volumes and KPIs, the less visible offshoring becomes as a cost-lever.
When you buy electricity, do you care where the supplier houses its generators? When you use public cloud services, do you bother to question Google, Amazon or Spotify where they house their massive data farms? It’s the same when engaging with IT services firms to get work done: business operations leaders are barely thinking about where they are located anymore – and all President Trump has done is shifted the optics, compelled the leading India-heritage firms to make substantially more onshore staff investments – which they needed to do in any case – as the nature of IT work is driving the need for greater client intimacy and physical proximity between service delivery staff and client staff.
Traditional outsourcing is being replaced by partnering, and “offshoring” is not even part of that conversation
Our recent study looking at digital transformation to the OneOffice reveals that the majority (57%) of the highest quartile of performers in the Global 2000 (based on revenue and profitability) view their primary service providers as supporting their digital transformation roadmaps, as co-innovation partners helping them achieve co-defined business outcomes. Only a third viewed their service providers solely as a resource to provision skills and scale via a headcount model:
This data speaks volumes – enterprises digital leaders need providers which can work with them to achieve outcomes that are increasingly challenging – most no longer requisition 500 developers per year to code in ABAP for strategic initiatives – that is a commodity practice today, usually delegated to lower level manager to lead. Nearly all G2000 firms, today, have a Chief Digital Officer tasked with taking their companies through significant business model change, enabled by smart technology provided by partners which understand what is required. Whether the talent for these strategic projects resides in Bangalore, Basingstoke, Bucharest or Baton Rouge is moot – this is about getting results where top talent is hard to source, and the location is just not very relevant anymore.
The Bottom-line: Trump did us a favor and ripped off the legacy Band-Aid for the services industry
Trump’s stance on offshore outsourcing sparked two behaviors which have set up the future of services to be far more value-driven and business oriented: All the major Indian-heritage service providers have been aggressive adding 10,000+ staff right across North America and Europe. Several are also embarking on ambitious acquisitions of niche onshore digital firms (both creative and tech-driven) to engage themselves higher up the foodchain within their clients and be considered for more lucrative digital engagements where there are deeply engaged with their clients redesigning business models that need sophisticated technical support. So while the industry suffered from a couple of flat years trying to squeeze the last vestiges of life out of a dying body-shopping model, the new reality is a global delivery model that is now embedded in engagements where the focus is much more on business value and outcomes than prehistoric effort-based inputs. We are also entering an era where the likes of Cognizant, Infosys, TCS and Wipro will cease to be called “Indian providers” and merely be referred to as global IT services firms. Location is irrelevant… expertise most definitively is not.
