‘Analytics market to double to $2.3 billion by FY18’

http://indianexpress.com/article/business/business-others/analytics-market-to-double-to-2-3-billion-by-fy18/

Analytics market in India is expected to more than double to $2.3 billion by the end of 2017-18, the National Association of Software and Services Companies (Nasscom) said on Friday. Nasscom held the second edition of the Nasscom Big Data and Analytics Summit 2014 to address the growing business opportunities in the analytics and big data space. With the theme “Industrialisation of Analytics”, the focus of the summit was to share thought leadership on how to build analytically-mature organisations with analytics embedded at the business core and across the business value chain.
R Chandrashekhar, president, Nasscom, said, “Big data offers a unique suite of advanced analytics and helps derive meaningful insights from customer data to increase sales, better target customers, improve reach and gain competitive advantage. The Indian market is still in early stages of adoption of analytics … However, with surplus talent, established infrastructure, and a mature ecosystem, India is on its way to become a global hub for analytics. Industry stakeholders will need to work on a 6-point agenda which involves raising awareness, creating talent, variabilising cost of offerings, standardising tools and technologies, setting up cross functional analytics teams and getting C-level buy in, to drive industrialisation of analytics.”
The summit witnessed industry leaders share best practices on processes, tools, technology and applications used in the context of analytics.
Nasscom also launched a report in partnership with Blueocean Market Intelligence, titled “Institutionalisation of Analytics in India: Big Opportunity, Big Outcome” on the sidelines of the summit. The report predicts that analytics market in India is expected to more than double to $2.3 billion by the end of 2017-18. It also analyses the current scenario, trends in the India market, factors driving adoption, challenges faced by both users and suppliers.

2020 – US Banks are betting big on Analytics

A recent study by Accenture talks about the future state of banking in US by 2020. Thankfully, the study reports, US banks have emerged from the travails of a battered economy. Two important findings from the study stand out.

1.       Banks face increased competition in coming years

2.       Emergence of a core group of full service banks that will be the backbone of US Banking system.

While we can debate the findings, the current activity stream at banks does indicate that there may be truth to this and that we may be already seeing the contours of US Banks by 2020.

Interactions with bank executives have definitely made one thing clear. There is immense buzz around this future landscape and almost every major bank has already undertaken or is seeking an internal assessment to review their preparedness for change. Branch banking is one area that is likely to see intense competition; many of the big players are already investing in redesigning the branch of the future;

The other 800 pound gorilla in the room is of course Analytics. Banks are very keen to step up their capabilities - technical as well as talent pool and are building structures similar to Center of Excellence for Analytics. COE for Analytics appears to be the widely accepted route to instill an analytics driven decision culture.  Backed by a war chest and executive / board mandates, massive efforts are on to upgrade their capabilities. Truth be told, many bank have discovered that they are woefully under-prepared.

Many banks are even toying with rebuilding their existing data-warehouse to incorporate a fuller and deeper digital understanding of their customers – euphemistically referred to as the 360^o view.

New regulatory standards like Basel III, Comprehensive Capital Analysis and Review (CCAR) and Dodd-Frank Act Stress Test (DFAST), Fraud detection, Anti-Money Laundering (AML), Know Your Customer (KYC) etc. have spawned their own set of internal reviews and investments. However, Analytical capability improvement is at the heart of all these initiatives.

Upgrading analytical tools and platforms is also top on the shopping list. Focus appears to be on investing in emerging technology – e.g automation of predictive analytics modeling, real time offer engines for customer acquisition, transaction (big) data analytics, real time personalization of customer experience etc. Many banks are building Center of Excellence (COE) for analytics.

Internal competitive pressure on executives is intense at banks; many executives are building their own analytics back office groups to have an edge over their peers. This could be counter-productive by building redundancy and generate dueling analytical capabilities and decreased sharing and openness. This is not a healthy development in the long run.

Some Banks are adopting a short term perspective in preparing for the 2020 scenario. For example some banks are recruiting Data Scientists who they think will solve all their quests for insights. However, they do not have a plan to resolve bottlenecks in data flow - all the way from the data-store to the analytical layer. In other words absent the required analytical data infrastructure, their plans are a non-starter and investments wasted. 

This brings us to another dimension to the catch up scenario.  The analytics maturity or preparedness for using analytics varies vastly in banks. Size and deep pockets have not necessarily translated into competitive advantage.  Banks that have sound data infrastructure and a clear 360^o view of their customers – in other words one vision of truth across the enterprise - have a head start and will maintain their tremendous advantage and will end up being the winners. These banks will benefit by deploying latest technologies and analytical platforms and guide business decisions as never before. They will emerge leaders of the pack. As for the rest, they have to do a lot of clean up and then catch up. 

While banks are in a hurry to catch up and not miss the bus, they need external help for a successful transformation. They would need expert advice so that they do not have the re-invent the wheel. They need external help to carve a broader picture and pick the best practices or solution set that will be most appropriate for their bank.

Most US Banks – small and big are on board this transformational journey. These initiatives involve great investments and outcomes are keenly tracked. Many careers are at stake. But those that succeed will form the backbone of US Banks 2020. This obviously will result in intense competition and change the banking landscape in the US forever.

As scores of banks embark on this exciting journey, the IT majors are closely watching the opportunities that this is creating.  Unfortunately, the fact is that it does not automatically translate into revenues for them. Many are still clueless on how to cash in. They have to do their homework and come up with crystal clear vision to help banks in this challenge.

Analytics Revolution - Why the struggle for growth?

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 they 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 the resulting new innovative analytical 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.

Social Analytics – New uses of Social Intelligence

Article posted SmartData  -  B2C -  Analytic Bridge

We all live in a digital world or rather ‘social digital’ world. This is because so many of us have taken to Facebook, Twitter and other social networking sites/tools that this has become an obsession to many.  

Obviously, the huge social media traffic has provided companies an unprecedented opportunity to showcase and message themselves. Marketers and bankers have happily followed the traffic.  Now every company has a social media strategy,   mostly directed at messaging and feeling the pulse of the customers.  I often think many companies have a strategy more as a ‘place holder’  than to deduce any ‘monetizable’  intelligence ( if there is no such word, I have coined one!). 

How are retailers using social intelligence? Retailers arguably have the largest presence on social media and have successfully used it to build brand recognition by driving traffic to their sites. Yet, many big retailers had negative return on their investments on social media sites since ‘likes’ often did not result in purchase.  Definitely this is not the end of retailers’ social media adventure.  I do expect sharper social analytics will help craft a renewed and financially sustainable strategy in the near future. Why? The traffic is simply too finger licking good to ignore.  So do expect more here. 

How are banks using social intelligence? Definitely banks have made some headway in extracting actionable risk intelligence from social data. For example, to detect fraudulent loan applicants, some banks now seek to cross-match applicants’ personal details like date of birth, location, photos etc. with social data that is readily available from Facebook, Twitter etc. Mismatches are subject to greater /manual scrutiny. 

Risk managers and collection agencies can identify social network behavior of customers whose payment behavior is already known. We can use the same analytical paradigm by taking a set of existing customers (known behavior) and matching it with social networking data – travels (location), payment transactions etc  to glean insights. For example we can track delinquent customers’ travels and see if their delayed payments arise from travel and travel related splurges.  Frequent holiday travel / vacation data emanating from social network intelligence can alert lenders to proactively minimize / reduce / freeze credit lines. The legal and regulatory ramifications of such actions are unclear and will be tested in courts or when regulators take a stand.  But it is well known that Banks have used, are using and will not hesitate to use customer intelligence in creative ways to manage their profitability.

While social analytics is gaining ground, my personal view is that overall impact of social intelligence today has been a mixed bag of success. One key reason is that the extant social analytics tool kit is evolving. Often we find we are not able to garner cool, actionable, disruptive intelligence because we don’t know what to do with this ocean of social data. But that is changing and better tools are coming into the market.

A new paper published by McKinsey points out that social intelligence is now playing a powerful role in helping companies gain strategic insights and develop competitive strategy. New tools are helping social analytics teams to look into user groups, user forums etc. and catch up on what customers are complaining about. 

A talented social analytics team can piece together information on competitor’s new product strategies!  How?  If you listen closely to Twitter chatters, technical help forums etc. , there is wealth of ‘confidential’ information.  For example, techies while seeking help on complex problems they are trying to solve, inadvertently let the cat out of the bag.  That gives you the ‘what’ in the puzzle. Cross matching this user forum posts information / twitter handles with face book or Linkedin can lead to ‘who’ and ‘where’ puzzle pieces. Now thinking social analysts can collate the ‘what’, ‘who’ and ‘where’ and come up with missing pieces. The paper says it is often surprisingly easy to get at confidential information on competitors by deploying appropriate social analytics tools.  

Well, this is scary for companies and do expect more restrictions on employees after the CEOs have taken the time to read this paper.  Behind this emerging scenario is the hidden hand of intelligent social analytics.