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IT majors have been excited about the convergence of Social, Cloud, Analytics and Mobility (SCAM). It is widely believed that these will be the engines of growth in the future. Rightly so. N Chandrasekaran, CEO of TCS, India’s largest technology services provider, recently referred to the SCAM as "digital forces" and estimates that these digital forces would be a $3-5 billion opportunity in the next few years. A Gartner study has reported that the SCAM market will be worth $107 billion by 2017.
It is true that Analytics - has generated excitement all around. Everyone can see and experience the impact that this convergence – that engenders Disruptive Innovations - has on everyone’s life. I personally think that the hype is real and the huge revenue opportunity projected for this market space is based on solid grounds.
What the TCS Chief has not mentioned is that there are significant white spaces – industry-speak for critical gaps and blind spots in the effort to get this revenue. And the fumble, too, is very real. For example, if these projections and forecasts can be translated into revenue, why are we not seeing a Google or a Facebook or even their dwarfs in pure play Analytics? There appear to be several reasons why IT majors have not been able to take advantage of the opportunities. The revenue is for them to lose unless they learn and take corrective action quickly.
Analytics business is a domain specific, hands-on and a devilish details game where domain expertise is all supreme. However, most global players have not been able to get the right folks to lead the practice. This has proved to be a disastrous non-starter. The problem is also compounded by lack of right skills in the marketplace. The analytics practices at the majors continue to be led by professionals who either have consulting or technology background but weak in hands-on analytics. This has blissfully insulated the practice from the analytic humdrum that businesses are experiencing. This is also reflected in the inability to identify or devise the right vehicle to exploit the surging analytic opportunities. In my view, the lack of appropriate leadership is a major roadblock to growth.
The IT majors also urgently need to revisit the internal business structure. The bunching of analytics catering to different industry segments or verticals under a single business unit may be convenient for administrative and bureaucratic reasons, but has not produced optimal results. This agglutination has come in the way of insight dominance since successful thought leadership in one vertical often has not passed muster at another. I think the analytics practice catering to each industry vertical must be a separate business unit by itself.
The outsourcing industry has mastered the art of building the business via the IT organizations of client companies. However this tested path has not helped build the Analytics business because the key players are not on the IT organization of clients. Outsources need to have a game plan for directly engaging the business side of the house.
Further the majors are selling software products and tools that are often peripheral and non-core to generating analytical insights. Aided by an expanded definition of analytics, this may help generate revenue in the short run, but this has taken the focus off the insights business. For example, a hypothetical solution that can build and deliver fraud detection models using large attribute set – including social media attributes – and look-up more than 10,000 datasets and yet instantly deliver accurate detections will be immensely popular. Big data or new modeling techniques by themselves would not produce a disruptive innovation. The marriage of cutting edge technology and new modeling techniques that can scale is the winning recipe. This is a keystone for success in analytics practice, yet conspicuous by its absence.
This success recipe has to be combined with a smart go to market strategy. I call it winning-with-a-thousand-cuts strategy. Instead of waiting for the dream multi-million, multi-year project, the focus must shift to building volumes through a huge portfolio of mid-sized projects. Execute several small to medium sized projects that will provide insights to the businesses in short to medium term - 6 to 12 month time frame. This paradigm has the potential for depth - to open up opportunities in every line of business, business unit or team level at clients and hence build scale in the analytics business.