In her recent blog on outcome-based contracts, Christine Ferrusi Ross challenges the industry with Outcome-based Contracts Are A Nightmare –Do Them Anyway, and offers guidance and experience to rally the troops. What is also intriguing about this outcome-based approach is the potential to shatter the so-called “watermelon effect” that often takes shape in an outsourcing engagement that is based solely on key performance indicators (KPIs) and service level agreements (SLAs)… and use those traditional metrics as seeds for new value-based engagement.
What Is the Watermelon We Want to Shatter?
The outsourcing industry grew up on contracts that clearly articulate KPIs and SLAs, providing an agreed upon set of targets for the service providers to get the work done at a level that is satisfactory to the client. As transitions take place and Lean, Six Sigma and continuous improvement methods iron out processes and make them more efficient, these metrics regularly appear “green” on the scorecard. But, even when all the indicators are green, service buyers can be left feeling red—the so-called watermelon effect of green outside and red inside. There is often a sense that while all the targeted metrics for turnaround time, uptime, and transactions processed are being met, clients and service providers “feel” value is still missing.
This effect often leads to questions about the value of the contract and challenges for achieving innovation, price reductions, and competitive re-bids. The key issue is that perceived value changes as relationships evolve; therefore, the benefits received and the associated metrics to measure and manage real performance need to change with it. We once joked that “if outsourcing was an employee it would be fired,” meaning if you took a job and were judged on the same performance metrics every year, you wouldn’t last very long!
There is a Step Along the Path to Outcomes-Based Contracts
As Christine’s blog points out, outcome-based contracts can be incredibly difficult to create, but you can still address the watermelon effect right away while sorting out the outcomes desired. In one such example, we heard of service buyers and providers addressing this point by including a metric and payment based on Net Promoter Score in the contract. That way, all parties in the engagement have to figure out, and proactively address, that feeling of missing value. An example is a simple performance evaluation, on a regular basis, that asks for a rating of partner satisfaction on a scale of one to three. If the feedback comes back as a one, a percentage of the payment is held back, if a two, no movement of money, and, if a three, then a percentage bonus.
The intent is to drive the right attitude, behaviors and cadence of interaction and measure, not just the service levels and performance indicators, but that “feeling.”
Yes, it’s subjective, but isn’t any relationship subject to “feelings”? This “feeling” can be an indicator that the engagement is at a stalemate—that the engagement is no longer driving step change, helping the business to improve or address what matters to their customers today.
Using KPIs and SLAs As Seeds to Grow Outcomes-Based Contracts
How does a business outcome differ from a KPI or SLA? In practice, a business outcome often encompasses multiple KPIs and SLAs. For example, a business outcome in retail could be “increased sales closed by visitors that start a shopping cart,” versus an SLA which could be “ensure website has availability of 99.999%.” In healthcare, “decreasing the cost of care for a targeted population” could be a business outcome, while a KPI may be “percentage of targeted population enrolled in a relevant wellness plan.” They are not mutually exclusive, and when used together, can help advance an outsourcing engagement towards a structured, but more interactive and flexible arrangement for today’s dynamic business environment.
Looking at business outcomes puts the focus of the outsourcing engagement directly on the client and the client’s customers and stakeholders—the ones who are judging and measuring the client’s performance. The business outcomes for an outsourcing engagement in operations are broader than simple transactions, like website uptime or number of bills, invoices or claims processed. Using a healthcare industry example, what matters to a healthcare payer today could include retaining members in their plans, and that means KPIs that could include member satisfaction scores, and SLAs like payer web site uptime, claims processing throughput, and accurate provider data.
The Bottom Line: The point is not to move away from KPIs or SLAs in a contract, but to use them as building blocks for achieving real outcomes that make a difference to the client’s business goals… and in a way that can flex and change in order for the partnership between the service buyer and the service provider to stay relevant over time.
We set out a few weeks’ ago, with support from NASSCOM, to test the views of service buyers, advisors and providers on what the BPO industry needs to do to make the leap from delivering mere efficiency to one that can provide genuine strategic value to clients (if this is indeed possible).
As we filter through the first results, what immediately leaped out at me was the following:
Clients want more women leaders and real case studies… more than anything else
“Why are these providers and advisors dominated by boring men in gray suits?” bemoaned several clients at one of our HfS Summits recently (where more than half the buyers executives present were actually female). This is a serious issue, folks. Our industry has – somehow – become dominated by too many dinosaur service provider executives with their lavish air-miles accounts and two iPhones* (why do some people insist on having more than one iPhone? Are they really that popular?), who have, at the same time, somehow lost all records of actual client success stories that justify their new vernacular around “digital transformation” and “automation”.
In fact, during one service provider briefing last week (which will remain nameless), we asked an executive to explain how he defined “Digital Transformation” (after many utterances of said phrase) and the poor chap was positively floored that he was asked to define what he was talking about. These people seem to be obsessed with recanting the vogue buzz phrases, without the need anymore to know what they really are. Can we just call it “technology” again and go back to sharing real examples of how technology can enable and transform client performance? Can we just explain what all this hype is surrounding automation and emphasize that most of today’s RPA technology has actually been around for more than a decade in many shapes and forms?
Here, it’s abundantly clear that we need to see more women – and, dare I say it, more youthful executives, who can simply connect better with the clients. Everything has become so dominated by the men in gray suits, who talk in increasingly more impressive riddles that are becoming increasingly distant from reality. Moreover, we need to dispel much of the hype surrounding automation and jobs impact: Gartner’s unsubstantiated claim that “more than three million workers globally will be supervised by robobosses in just 18 months’ time”, is simply irresponsible and unprofessional. It’s time to make it real and drop the hype and scaremongering…
The Bottom Line: It’s time for progressive change from within to break ourselves out of this legacy holding pattern
The industry has spoken, and it’s not pretty – clients are fed up with the same old selling, the same old unsubstantiated hype and the same old cronies dishing it out. Change only comes when we look at progressive change, not successive change. This means we must stop making the same old mistakes by replacing jaded middle managers with more faceless middle managers with a hype-upgrade; this means we must stop plastering out turgid marketing that was really a rip-off of the other ten competitors, with a different logo slapped on it.
We need real people selling and delivering our solutions, who can listen to what clients need and can really empathize with them, who are diverse across the genders, the age groups and the ethic backgrounds. We need to start talking real English again, and less of the manifested garbage we can’t resist spewing out to mask our insecurities. As our whole 2017 research theme at HfS is centered on… it’s simply time to start making everything real again and redefine our industry as something that is geared up for our clients’ real needs, not needs we are trying to convince them they have!
*In full disclosure, the author of this article has been seen once sporting a gray suit and did possess two iPhones for a brief period of time. He has since changed his ways…
One thing about testing services that continues to strike me is that the development is largely out of sync with the broader IT market. That is not to suggest that the testing community lacks sophistication or innovation, but we cannot just use the usual mindset, concepts and monikers without adaptions when we discuss testing services. Much of that has to do with the reluctance of buyers to invest in testing. For many organizations, testing services remain a secondary concern when setting strategic IT goals or embarking on transformation projects. Yet, as organizations journey toward to the As-a-Service Economy is accelerating, and in particular Intelligent Automation is fundamentally changing the way we deliver services, the discussions on testing have to move center stage. HfS had the opportunity to sit down with executives of Capgemini and TCS to discuss their strategies for test automation and how the notion of Intelligent Automation will shape the future of testing services.
Desperately seeking an organizational model for testing
Testing services have never fully mirrored the broader IT market in the way it was seeking to optimize its organizational models. Be it aiming to centralize large parts around the notion of shared services or be it by embracing large-scale outsourcing. The build out of Test Centers of Excellence (TCoE) has always been a litmus test for the progress with centralization efforts in testing. However, as executives at Capgemini put it:”TCoEs have flat lined”. The reasons for that a likely to be twofold. First, the lack of maturity on the buy-side. Second, the traction of Agile and DevOps methodologies. The latter has two direct consequences: On the one hand the requirement for more co-location, yet as Capgemini put it with more intelligent solutions than just aligning delivery teams. On the other hand, both executive teams agreed on the rise of Distributed Agile. While Agile is intrinsically aligned with the journey toward the As-a-Service Economy, the testing community has to articulate and demonstrate what the concept exactly means. Not least in the context of vastly varying buyer maturity, or in the exasperated words of a Capgemini executive:”99% of the market is still Waterfall.” As a result, both Capgemini and TCS see Distributed Agile as the next key development phase for testing services.
Deconstructing Test Automation
Distributed Agile is the logical evolution of testing services to support the journey of organizations toward the As-a-Service Economy. Yet, as we have suggested, we need clarity around the different methodologies and monikers compared to the broader market. Historically the notion of Test Automation was largely defined as test case automation, and to a lesser degree as the automatic provisioning of test environments. For Capgemini, the direction of travel is toward the notion of a Virtual Test Factory (VTF) that can be embedded in heterogeneous test factories through virtual delivery management and governance. Over time it will also be key for the alignment with Automation Drive suite of services that is aiming to leverage the disparate, broader automation skills as well as four CoEs across the traditional business units. Thus, progress with VTF is crucial for pushing competitiveness and distributed agile as well as moving toward the As-a-Service Economy. The two key building blocks for that journey are Smart QA, an end-to-end ecosystem that includes smart assets, zero touch testing, smart environment provisioning, 360 degree view insights and smart analytics to drive down cost of delivery and cycle times significantly while improving customer experience. Furthermore, the Intelligent Test Automation Platform (ITAP), comprising of intelligent frameworks and robotic agents that underpin analytics and rules driven smart test strategy, quality gates, job chains with no manual intervention leading to continuous testing and delivery. Both platforms are centered around end-of-end life cycle automation along with smart dashboards to offer a service catalogue as well as a heat map of critical issues. Consequently, these platforms are evolving toward notions of self-remediation. However, in this context self-remediation means more providing knowledge-based solutions for business agents than self-remediating engines.
TCS is echoing many of the sentiments on Distributed Agile. To adapt its existing client relationships to this methodology the company is creating “virtual rooms” on the account level. Thus, assuring that the “distributed” work streams are being aggregated to support business processes. Therefore, the vision for its 360 Degree Assurance Platform is to evolve into an Adaptive Assurance Ecosystem. To progress toward the notion of “adaptive”, TCS is aiming to leverage Machine Learning and AI to evolve into self-healing capabilities. This is predominantly done by leveraging a set of neural networks (i.e. beyond its flagship platform ignio). Use cases are test suite optimization, automated defect analysis and the prediction of outcomes through linear regression algorithms. TCS executives were pointing to the fact that customers are starting to look for value chain execution rather than just test case execution. Another reference point that testing services are starting to move up in the value chain.
What are the testing strategies for Intelligent Automation?
While the two discussed approaches indicate that the testing community is closing the gap to the broader IT market both in terms of development as well as maturity, one obvious question has still not been answered: What are the testing strategies for Intelligent Automation? When we put this question to the supply side, the standard answer tends to be pointing to the broad portfolio of existing testing services. Yet, are these service sufficient to test Deep Learning and broad scale Cognitive Computing? Traditional approaches can look at outcomes or deal with user acceptance testing, but how should we deal with the ever more sophisticated algorithms that underpin those concepts and how can we assure that those algorithms are crunching the right data sets? If the testing community wants to be included in the decision-making for the large transformational projects it has to find answers to those questions.
Bottom-line: The testing community has to find its voice – one that is being understood by the business
The more the market is moving toward the As-a-Service Economy and outcome based models, the more the testing community has to find solutions as to how to support those strategies. While we see a clear maturation in testing services, the community has to change its mindset and embrace business-led discussions. Thus, the supply side has to move beyond conversing in jargon around function and features to align itself with the broader IT stakeholders. In Q4 we will launch a Blueprint on Application Testing for the As-a-Service Economy and look forward to exploring these themes with stakeholders.
Perhaps the best example of the evolving As-a-Service delivery model that immerses all the value levers of global delivery; namely offshore talent, cognitive automation tools, analytics and the digital customer experience, can be found in the burgeoning mortgage processing industry. With banks going all out to sell highly competitive mortgages at record low interest rates, the onus to manage the whole process both efficiently and intelligently, while battling all the regulatory demons, has never been so great.
Two years after our inaugural Blueprint in Mortgage BPO Services, we took a fresh look at this industry… here’s announcing the findings of the HfS 2016 Mortgage As-a-Service Blueprint, led by HfS banking analyst, Reetika Joshi.
The concept of delivering mortgage As-a-Service, using plug and play digital business services is still in its infancy. We’re not quite at “push button, get mortgage” as an industry – and the verdict is out on whether this is the right message to send for a lending environment that is still rebuilding itself, seven years after the 2008 housing crash. How do you do this without raising eyebrows? You’ll have to ask Quicken Loans, as they learn from the backlash of their Super Bowl campaign with that very slogan.
Reetika, how do you view the 2016 Service Provider Landscape?
Our HfS Blueprint methodology assesses service providers based on two critical axes: Execution and Innovation. We gather data to support our analysis from client reference interviews, market interviews, RFI submissions and exhaustive service provider briefings.
In this Blueprint, we identified four As-a-Service Winners: Accenture, Cognizant, TCS and Wipro. These service providers have the strongest vision for As-a-Service delivery in the mortgage industry, and are driving collaborative engagements with clients to bring this vision to life. They are making significant investments in future capabilities in automation, technology and borrower experience to continue to increase the value over time.
The High Performers in this year’s Blueprint are a highly competitive set of service providers: Genpact, Infosys, ISGN/Firstsource, Sutherland Global Services and WNS. They have high execution capabilities and are growing their client bases as a result of investments in future capabilities and innovation. These service providers have the pieces in place for As-a-Service delivery, and need to focus on consistently bringing these capabilities to clients and scaling up with broad, multi-client solutions. We expect them to challenge the Winner’s Circle leaders in the next couple of years, with each building on unique strengths and assets in this vertical.
We see Unisys and Xerox as the Execution Powerhouses. These service providers are strong in operational excellence with ubiquitous technology platforms in their respective markets, and need to focus on value chain expansion and innovation in their services stack:
Why does mortgage needs to have a different approach and response to “digital disruption”?
Despite this sensitivity, other industry forces still march on; regulation, homebuyers and a new breed of disruptive fintech firms are steadily shifting the entire mortgage industry towards generally being more digitally enabled. Lenders have this big ask today: how to carefully balance their investments in new technologies, with changing consumer needs, volatile rate environments with rampant M&A, their company’s own appetites to write off/augment internal legacy systems, and all while continuing to remain compliant in an increasingly watchful regulatory environment.
Borrowers are increasingly looking for three key benefits in their interactions with agents, brokers, and lenders:
Simplification in the processes, handoffs and interactions
Transparency in the loan terms and costs, application progress
Control in document and information exchanges, decision making
The use of digital technology can greatly help lenders to achieve these experiences, in both facilitating interactions and in creating operational efficiencies at the back-end to speed up applications and free up loan officers’ time. In becoming digitally driven, lenders have a long way to go in thinking about e-mortgage beyond digitization, and borrower experiences that are built on new engagement strategies, especially as the market shifts to more purchase originations and persistent refinancing dictated by flat-lined interest rates.
So what’s fundamentally changed, since the inaugural Mortgage Operations Blueprint in 2014?
HfS believes that the Mortgage Operations market for both residential and commercial loans is on the cusp of a significant transformation. Several lenders in our research described their mortgage processes as complex, broken and in need of help to compete with non-traditional lenders and faster cycle times. Said one, “Our industry needs to go through massive business process reengineering efforts…so many lenders don’t have processes documented still. We need to start there [with our providers], to find ways to improve cycle times and create better experiences for borrowers.”
There is a marked departure in the market dialogue, away from labor arbitrage and manual “lift and shift” processes, and towards using a combination of technology platforms, analytical insights, automation, digitization and other accelerators to redesign processes and drive more value in sourcing engagements.
Some areas that have changed since our last Blueprint include:
With greater purchase originations, we see the mortgage operations market more broad-based in the work sought from lenders. Accordingly, service providers have grown both their technology and process capabilities in originations and servicing in the last two years, with a few that have foreclosure and default management work today.
Great examples of service provider capability in creating and embedding analytical insights and data into different parts of the mortgage value chain, understanding the key triggers/outcomes in the process such as predictive modeling for loan origination to help prioritize underwriter time and understand likelihood to close.
New services and technology accelerators coming from service providers to address regulatory pressures such as the audit and due diligence reporting back to CFPB, which is increasingly getting more complicated and frequent. Clients expect more guidance and recommendations in regulatory changes and their impact on technology systems/processes/data to maintain compliance.
And what are the HfS Predictions for the Next 2-3 years of Mortgage As-a-Service?
The biggest developments we see in the mortgage market in the next few years are:
Greater Alignment of Services Around MOS Platforms: Service providers like Wipro, Accenture and Genpact that have made investments in acquiring MOS technology vendors have goals of providing a broader, end-to-end portfolio in mortgage, including people, process and technology. This is an indicator of a vision for providing Mortgage As-a-Service. However, most of the acquisitions made were of independently branded software solutions, accompanied by their own branding legacies. Infosys took a different approach with its startup acquisition to create CreditEdge. In the next two years, we expect these service providers to further articulate and demonstrate how these technology buys change their value proposition, towards greater clarity and examples of delivering Mortgage As-a-Service.
Mainstreaming of Process Automation: It has taken a while for process automation to cautiously make its way to the forefront of conversations in mortgage operations, due to its troubled “robosigning” past. We are now seeing greater understanding by both service providers and buyers to start thinking practically and implementing different kinds of automation technologies (RPA, intelligent OCR, etc.) across various parts of the mortgage services value chain. Today thus represents the early vanguard and the arrival of RPA in mortgage, leading us to believe that adoption will be fairly rapid over the next 12-18 months.
Digital Driving Disruption at the Top: Several of the big lenders that HfS interviewed are still playing the “wait and watch” game on digital disruption, in particular the strides made by fintech startups and non-traditional banks in the mortgage industry. While “push button, get mortgage” as we discussed above might not be the path for all the Top 50 to go down, lenders are initiating more conversation and strategy around how digital components can help them look at traditional operations differently. Service providers will have a big role to play in this, from a process reimagining perspective, as well as ultimately configuring the digital components that link these activities back to onboarding and origination platforms.
HfS readers can click here to view highlights of all our HfS Blueprint reports
HfS premium subscribers click here to access the new HfS Blueprint: HR Mortgage As-a-Service 2016.
Who Are the As-a-Service Winners in Energy Operations? HfS’ inaugural Energy Operations Blueprint reveals frontrunners Accenture, EPAM, Infosys, Wipro and TCS
Why An HfS Research Blueprint for the Oil & Gas Industry?
Tumultuous times in the Oil & Gas industry. Understatement of the day I hear you say… Time for a rigorous look at the role service providers play to help Oil & Gas clients battle adversity.
The Oil & Gas industry is on the cusp of a significant transformation. Economic, societal, market, political and regulatory pressures are coming together bringing immense challenges for companies to solve through more effective and lower cost operations.
HfS sees a significant role for next generation services providing flexibility to scale up and down, agility to deal with a volatile environment and fully leverage digital technologies and digital enabled business and operating models now and in the future.
What does this Blueprint cover?
This is not a beauty contest about size, revenue and global scale. There is a place for smaller providers that excel in a niche and help clients on their As-a-Service journey.
One of the key attributes we looked for in this Blueprint process was if the service provider has a real Oil & Gas practice, not a collection of contracts with a sign “Oil & Gas Practice” slapped onto it. In this light we are interested in the way service delivery is organized, the availability of industry domain expertise, investments in industry talent, acquisitions of companies with industry specific capabilities and partner ecosystems. Another point of emphasis in our research is the move to As-a-Service, how service providers are enabling new ways of working, how automation and analytics are used to tackle industry specific challenges and the level of innovation brought to clients.
Key Market Dynamics
Two dynamics jumped out at us during the Energy Operations Blueprint process:
Oil& Gas Companies Looking for NewLevers: As the focus of the industry is on cost reduction, production optimization and operational efficiency, automation and outsourcing are two principal levers available to the industry. The name of the game for Oil & Gas is: Fix the basics and leverage new technologies. Oil & Gas executives are forced to have a good look at their strategy. Key questions include:
What is the core of our enterprise?
What do we need to do internally, what differentiates us from the competition?
What parts of our processes can we automate?
Can we outsource what we can’t automate?
Buyers Perception of Service Provider Becoming More Strategic: A pivotal changing dynamic in the market is how buyers look at their service providers. With the renewed focus on outsourcing as a lever to deal with the pressures in the volatile business environment, Oil & Gas clients tell us they look beyond labor arbitrage and see service providers as an extension of their organization. They want deeper relationships with their providers and forge stronger ties between internal and external staff. They look at their service provider(s) to help the organization become more flexible and scalable, ramping up and down in the cyclical business of Oil & Gas.
Who is Standing Out? The Service Provider Landscape and Blueprint Grid Performance
All of the 13 service providers that participated in this Blueprint share the conviction that innovation is crucial to helping their Oil & Gas clients through this volatile environment. Most of them have a unique set of offerings and capabilities. There are a couple of clusters of expertise. For example, KPIT and HCL, focus on a specific area of the value chain; TCS, Infosys, Wipro, Accenture, IBM and Cognizant, focus on strong domain expertise and consulting-led delivery; and EPAM, Atos, Luxoft, Harman and Tech Mahindra, lead with engineering or Digital Transformation with credible experience from other industries.
As-a-Service Winners are service providers that are in collaborative engagements with clients, and making recognizable investments in future capabilities in talent and technology. These providers are also leading in incorporating analytics and BPaaS to deliver insight driven services: Accenture, EPAM, Infosys, TCS and Wipro. I’ll highlight two Winners here:
Accenture has tremendous breadth and depth in its capabilities and experience serving the oil and gas industry. Its commitment to innovation in technology and service delivery and bringing digital platforms to the industry make it one of the leading service providers in the move to the As-a-Service Economy.
Wipro’s Oil & Gas practice holds a lot of domain expertise, which Wipro combines with innovation in digital, cognitive computing and automation (Holmes) and commercial models. What stands out is Wipro’s ability to bring valuable, new As-a-Service propositions to the market, enabling the introduction of clients’ new reimagined digital business models, a crucial capability for success in Energy Operations.
High Performers show solid performance in either technical execution or services innovation but may not show an innovative services vision or lack execution momentum against what is potentially possible: Atos, Cognizant, HCL, KPIT and Tech Mahindra. Atos impressed us with their vision on Holistic Security and Industry 4.0 experience, two key areas for the future of Oil & Gas.
Harman, IBM and Luxoft are ranked as High Potentials, emerging players bringing highly innovative approaches and overall vision to the market, but lacking in the complete build-out. IBM is struggling to transition from being firmly entrenched in ‘traditional’ services, and has been on the wrong end of consolidations in the industry. However, what caught our attention is IBM’s capability that puts it on the forefront of advanced analytics services, with heavy investment in cognitive capabilities. We have seen a number of interesting applications of Watson with Oil & Gas clients, for instance using predictive data science to leverage more than 30 years of collective knowledge and experience in a cloud based knowledge platform. With the Big Crew change firmly underway, this an important area for Oil & Gas companies.
What is Next? Sustaining the Momentum of Change The downturn in the Oil & Gas industry and sustained low oil price has created a momentum for change in the industry. But will it continue if the oil price goes up again—what happens when it hits $60 per barrel? Many industry executives shared a concern that without the economic necessity of cost cutting, the industry will return to a complacency that will slow the pace of innovation and change.
This Blueprint shows that, in addition to cost reductions, the industry needs to be focused on business outcomes relating to talent, operational efficiency, organizational flexibility and scalability and time to market. The way forward is through more collaborative engagements that incorporate the achievement of these business outcomes. The Energy Operations Blueprint provides a comprehensive overview of the industry and identifies ingredients for long-term business value along the As-a-Service Journey.
I’ll wrap this up by emphasizing again the importance of true partnerships. To survive the oil price slump and come out stronger Oil & Gas companies need partners that proactively bring innovation and are willing to co-invest in technology, collaboration and talent.
HfS Premium Subscribers can click here to download their copy of the new 2016 Energy Operations Blueprint Report.
As someone who has profited very nicely from social media (I helped build an analyst company with blogging and social at the heart of our culture), I am probably not the most appropriate person to speak out against the negative side of social media’s impact. But, as Gerald Ronson once famously espoused to the editor of the Guardian newspaper, “Opinions are like arseholes, everyone has one”, I just can’t help myself, so I’ll give you mine…
2008 was a financial disaster fueled by greedy bankers; 2016 a political disaster fueled by social media wankers. Opinions on politics. My god – back in the day, people pretty much kept quiet on their views until they had some facts to back them up. Today, they just have a bloody opinion and want to get it out there, regardless of whether they can justify it or not. When they get into an argument, they just try and shout louder, rather than listening to reason. David Cameron has been guilty of one of the biggest political snafus of modern times, where he went to the public with a complex decision to be made. Instead, all he succeeded in doing was allowing every opinionated idiot with a twitter account to air his or her views on society at large, until the vote become one about him and the establishment and not whether Britain should remain in the EU. (And you wonder why Hitler loved referenda…)
All social media has achieved is providing a platform for people to spout off unsubstantiated rubbish, as opposed to a collaborative opportunity for them to learn more about what’s truly going on in the world. Then we advance to the lovely US media and the most insufferable election in history, where reality got somehow lost in a maelstrom of hype, tweets and many unsubstantiated facts that really dumb people actually believe. All I can say is that I cannot wait for the election to be over so we can actually get back to some normalcy of running a country again.
The tech and services industry has complete lost itself in the socially-driven hype. So let’s reflect on what happened to our industry over the last couple of years. For a while, social media was fun – we could debate the trials and tribulations of real services and real technology and how to improve ourselves. Suddenly, the facts have got lost somewhere are we’ve arrived at this dark place where it’s more about who’s making the loudest noise than who’s talking the most sense. Every supplier of tech and services talks up “Digital” but never defines it – with few to no clients to reference their capabilities. They talk “automation” with little clue how to do it, with (again) no clients as reference points. Myself and my team have sat through hours and hours of deathly dull briefings where we’ve actually had analysts bemoaning the fact that the providers failed to brief them on the subject at hand. It’s really that bad.
The Bottom-line: It’s time to find our way (somehow) back to reality
Let’s be brutally honest – we’ve all lost the plot. Why are tech and service providers so obsessed with sounding the best as opposed to proving they’re the best? Why do so many analysts and consultants just parrot each other, as opposed to having real opinions and real substantiated viewpoints? Why have so many enterprise buyers buried their heads under the bedcovers, scared to come out until someone dared to explain to them what this new bullxxxt was all about?
It’s time to make things real again… we owe it to ourselves and our clients to talk about how buyers/end-users adopt these emerging solutions – what are they doing, which processes are being impacted, what outcomes are being achieved. We need to focus on real industry dynamics to learn why is digital so relevant to retail; omni-channel to travel; block chain to banking; cognitive to healthcare etc. We need truly to understand and articulate how today’s workforce grasps these emerging concepts and drives them in practice – how can experienced professionals reorient their capabilities, and the younger generation be embraced into the workforce? What are the career progression plans in these areas? While technologies advance, how are staff advancing (or failing to advance) with them?
Unless we really dig deep to stop using our social foghorns to spout the loudest and start focusing on being the more real, we are truly doomed to a future of increased stupidity, naiveté and confusion. It’s time we all broke form these habits and refocused on what is really happening in the world.
Sometimes it’s all in the fine print. We often put a small comment at the bottom of our charts that gives additional details about the data and a note of anything which specifically impacts the chart. A note we often add to the quarterly bubble charts we do is that we haven’t included one provider or another because if we added them it would skew the chart. One question I get asked fairly frequently is where AWS would feature on the chart.
The chart speaks for itself, demonstrating why we tend to leave AWS off the chart! Frankly, if we include them it’s hard to see anything going on with the other providers. The growth rates of the other firms just blend into one another. Because this chart is limited to financial results there are few sizable IT or business services firms that operate at that level for any sustained period. So it would be great to show Microsoft cloud and Google bridging the gap between the groups. However, neither provider publishes a clean revenue / margin statement for this part of its business. However, Microsoft has started to report some information about its public cloud business, Azure, stating that its revenues grew over 100% in the same period, albeit from a smaller base than AWS.
Another part of this preliminary data which is interesting is the clustering around the 10% growth mark – with the left shift of the offshore providers (see in this blog) and Atos, Accenture, Capgemini, and NTT Data all moving into this space – we are seeing a cluster of providers around the 10% growth mark.
Zooming in on the 10% growth mark shows the phenomenon more clearly. The shift left of the offshore and a shift right of some on-shore players – we are seeing a convergence of some players around the 10% mark this quarter. This adds to the arguments made in the offshore blog last week, that the shift left isn’t merely an indication of a slowdown in the market overall, with an acceleration in Q2 2016. Given the good performance of many of the on-shore traditional providers.
We will be publishing our full review of the results in the first part of September and we will add a blog about the final positionings in more detail.
As the leading authority on Intelligent Automation, HfS gets inundated with requests to size and forecast the market.
Our standard answer continues to be another question: “How can you size a market that is not defined?” Suffice it to say, we have seen some of our peers put numbers out. Yet, how do we actually size the market? Do we aggregate licensing revenues by the tool providers? Do we draw a big mind-boggling number on AI into the sand? Or can we assess the addressable market beyond the bleeding obvious that every IT or business process is conceivably an opportunity for providers?
Until we have clearly segmented and defined markets, the value of market data is probably on the limited side. But don’t get me wrong, my learned colleague Jamie Snowdon can model any of those markets. He not only publicly declared his love for market sizing and forecasting but his Twitter handle is statement of modesty: he is one of the best in the business. And where it makes sense, we draw very visible lines in the sand, as in the case on the impact of automation on talent and jobs.
While we are shying away from confusing the market even more with bold claims on data points, we have very strong views on how the market is evolving. We share those regularly with our clients in strategy sessions and help them optimize their investments and fine-tune the marketing messages. Increasingly, those discussions get extended to investors who are trying to assess the opportunity. Intriguingly, those conversations are not confined to individual companies but comprise discussions on building strategic portfolios. On top of that, a spike in the share price of Blue Prism did fan rumors that were flying around already. Enough reasons for HfS to take stock where the market is—but more importantly to look at a couple of scenarios that could transform the provider landscape.
The market is moving toward exponential growth
HfS is just at the tail end of our research into the inaugural Blueprint Report on Intelligent Automation. Thus, the plethora of discussions with providers and customers provide a litmus test as to where the market development is at. The key exam questions for the project are how service providers are moving the discussions on Intelligent Automation from a narrow focus on RPA toward a more holistic approach. Similarly, how are providers moving beyond a stovepiped view from the traditional business units? Here is just a sneak preview of some of the insights we’ve gleaned.
Despite the blurred perception on the state of Intelligent Automation, the market is headed toward exponential growth. We see significant scale in the deployments both in business processes as well as in IT centric scenarios. These deployments are increasingly underpinned by automation frameworks and the notion of service orchestration. The leading providers are moving beyond the obvious buckets of RPA and Autonomics by building offerings around virtual agents and by getting ever deeper into cognitive scenarios. So stay tuned for the final results and insights!
Four market scenarios
Against this backdrop of a burgeoning and maturing market what could be shifts in the provider landscape that could conceivably disrupt or accelerate the market? Four scenarios jump to mind.
M&A through ISVs: Having just had the opportunity to catch up with the CEO of OpenSpan who has just been acquired by Pega, their example provides the Blueprint for such a development. Similarly, we hear of automation juggernauts circling for opportunities to prepare for catapulting themselves into new era, having heard enough about the Innovator’s Dilemma.
VCs and private equity firms demonstrate an at times remarkable knowledge about the space: We hear about scenarios akin to what General Atlantic did in the heydays of BPO in contemplating a portfolio approach, generating synergies between portfolio assets.
The emergence of an Automation Ecosystem: We already have seen the impact of Watson. Suffice it to say, IBM could be the driving force to extend those capabilities, as my esteemed colleague Phil mused some time ago. But it could equally be one of the tool providers significantly expanding its reach.
A new set of data centric partnerships: To build out cognitive and AI capabilities and to optimize the engines, access to data is critical. As many customers remain coy giving provider access, we might see a new set of partnerships accelerating these capabilities. While it might sound trite, datareally is the new currency. Obviously, these scenarios might overlap. Equally, M&A is often not rational. Thus, I am sure the market will continue to spring many surprises on us.
The Bottom Line: The discussion on Intelligent Automation has to move to center stage
In light of the strong growth and maturation of both service provider and tool provider, the discussion on Intelligent Automation has to move center stage. Despite the blurred perception the fundamental question is how do we align service delivery to accelerate the journey toward the As-a-Service Economy. To really fast track this transformation, we need to address issues such as governance, testing and the transformation of knowledge work. And as always I would love to hear your views on all this.
We’re excited to fly over some of the HfS star analysts to meet with the delegates at this year’s NASSCOM BPM Strategy Summit, where HfS is the exclusive content partner with the theme “The Next Big Goal – From Effective to Strategic, can BPM get this one Right?”. And the more discerning of you will notice that the theme is centered on HfS’ own Eight Ideals of the As-a-Service Economy.
So what are you waiting for? Book your flight and place now!
Venue: Hotel Leela Bangalore
Date: 22-23 September 2016
And if you’d like to meet with some of the HfS team, drop us a quick note and we’ll see what we can do.
When I was in college, I heard an incident involving Bill Gates and his comments about innovation in the automotive industry in the late 90s. Later, I found that Bill Gates comments were extrapolated and converted into a then very popular joke among automotive engineers. The irony is that joke is coming true now for car makers, but it is a good opportunity for engineering service providers.
It goes like this–
Bill Gates: If the automotive industry had kept up with technology like the computer industry has, we would all be driving 27 dollar cars.
Automotive Industry: Yes, but would you want your car to crash twice a day?
And guess what? Two decades later, cars have become more like software and vehicle recalls have skyrocketed.
High-end cars now have about 100 million lines of code, a steep increase from about 1 million lines of code in 2000. The code volume per car will grow further and expected to reach 300 million lines of code in the next few years. In fact, in 2016, the new Ford F150 pickup has 150 million lines of code. In comparison, Facebook has only 60 million lines of code (see infographics).
Parallel to the growth of lines of code in cars is the growth in vehicle recalls in the US. The recalls, which were in the range of 10-15 million per year a decade back, have skyrocketed to over 50 million per year in the last two years.
The above recall numbers are just for US but I am sure situation will be no different in other regions.
These recall numbers highlight there is something seriously wrong with the testing process. And one of the major culprits in recalls is software.
Beyond recall numbers also we have heard about disturbing stories in automotive sector such as the Volkswagen emission scandal, where the culprit was software. Even Tesla’s recent autopilot crash was related to software. As it turns out, the Tesla’s braking systems radar and camera may have failed to detect the tractor-trailer.
Where does this software code go in the car? It is in all the cool features, such as air bag system, anti-lock brakes, automatic transmission, climate control, communication system, dashboard control, engine control, entertainment system, power steering, etc. Also, the possibility of so many variants and consumer choices creates volume and complexity in car software.
The core expertise of automotive OEMs and tier 1s is mechanical engineering. They need help and external expertise in embedded engineering in design, development, testing, and manufacturing. The embedded software has been a growth driver, especially for Indian engineering service providers.
For car manufacturers, the pressure to push the products early creates pressure on testing. Now, amidst vehicle recalls, emission scandals, and auto pilot crash the importance of vehicle testing will increase further.
As software is eating up the car, the automotive industry needs all the help it can get in testing, verification, and validation. The testing requirements will only become stronger with self-driving cars. And we are still not talking about mass customization, where OEMs can design and manufacture car in the lot size of one economically. This will be a testing nightmare for OEMs but a goldmine for engineering service providers. (And don’t get me started on the fear of hacking and make you paranoid, but testing requirements will only increase!)
The major engineering service providers in the automotive vertical offer testing, verification and validation services. My observation has been that the current approach to testing is more at the compliance level. Service providers I talk to tell me that they help OEMs and tier 1s in getting certain certificates in few countries (the technical term is homologation). The providers want to be able to crow about their testing being recognized by OEMs and certification authorities.
This is all good and that’s why majority of testing outsourcing is being done. But today, we need to think beyond compliance level and instead think about how to prevent vehicle recalls, emission scandals, autopilot crashes and even support mass customization.
Service providers need to think what kind of testing services they can provide to the Teslas of the world. The compliance approach will be table stakes. How can they help Tesla in preventing another autopilot crash? (Read Lessons from Tesla’s Master Plan)
Currently, the percentage of the engineering services providers’ revenue from automotive testing is in single digits, which we think has the potential to go into double digits in the next few years if service providers move from compliance to solutions. This is no joke!
