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.

The coming shortage of Analytic Skills

(Article also available here)

A   study by Avendus Capital published recently points out skill shortage in global analytics business.  According to this study, by 2018 the US will face a huge shortage of analytics professionals – a shortfall in the range of 140,000 to 190000 skilled professionals. The coming skill gap has serious consequences for

a)       companies where analytics plays a central role

b)      analytics service providers and

c)       analytics professionals  

Banking and financial services are the biggest users of analytics followed by retail, healthcare and pharmaceutical sectors in that order. Banking and financial services companies lead probably because they started using analytics long before analytics became a buzz word in the IT world. In fact many of the innovations – in data storage, business intelligence and deploying tools and business intelligence software (BI) for analytics - have been powered by demand and investments from this business sector.

While analytics is old game, the industry never attracted the kind of positive attention seen now. The analytics professional, sometimes referred to derisively as quant jock or what have you, never had it so good. Whatever the nomenclature, they essentially formed the bulwark of back office decision support, drawing useful insights from extant data. However, companies that integrated sophisticated analytics into their business decision process knew their importance all along. But in the recent recession, even as late as 2008 – 2009 or even later, they were laid off in droves from banks, retailers and pharmaceutical and other companies. They were on the chopping block whenever and wherever restructuring occurred. But today’s forecast shortage makes that look like ages ago. Clearly the analytics industry has turned around big time. 

It is common knowledge that the massive amounts of data now being generated from all-round in our digital world has engendered the big data genie. More data means more analytics which yields more insights. Suddenly companies have realized that they need a thought structure to handle this genie, else they risk losing their pecking order in their industry. It is this genie that has magically and swiftly created this colossal asymmetry in demand and supply of skillsets that we are currently witness to. 

In the short term – at least next 12 months or so, the demand for experienced analytic skills will outstrip supply. I know from my past experience in building and leading analytical teams that it takes approximately eighteen months to put together highly skilled analytical teams, albeit from ground up.

For companies that rely on analytics, the huge talent gap may force them to turn to third party analytics service providers. This may actually benefit some since if they move to offshore resources, their costs may actually come down. Consequently, these companies may discover new opportunities to expand their analytics infrastructure. On the other hand, companies that shy away from outsourcing, will have to freeze expansion plans or make do with the talent they have.

Major analytics vendors who already have built their teams will continue to stay ahead and will reap a bonanza for being at the right place at the right time. However, their time in El Dorado will be tantalizingly short since the demand for analytics has already spawned more players and most of them are investing heavily in nurturing good talent. I would definitely expect to see this intense competition put pressure on profitability for all the players. Of course, in the interim, I think there will poaching of talent galore!  I would not be surprised to see several mergers and acquisitions in this space. The big boys will swallow up the smaller players. 

There has never been a better time to be an analytics professional. The skill gap and poaching holds promises of greenbacks and an upward career graph.  This space is already attracting the younger and top talent every day which bodes well for the analytics industry.  As I have written earlier, I think the analytics industry is here to stay and will continue to play a pivotal role in constantly leap frogging the quality of decision making in the world of business in the foreseeable future.  

Think about it. The fortunes of the analytics business have been greatly impacted by happenings elsewhere – the genie sired by big data flow and data management technology. But I think in today’s business ecosystem where interconnectedness of data and insight is the key, it is hard to tell where one ends and where another begins.  But for all those who thought these guys were just quant jocks, wait till you see who laughs all the way to the bank. In the truest sense, it is the revenge of the nerds.

Succeeding in the Business Analytics Business

(Article also available here)

Business Analytics has now attracted attention as never before.  Together with Mobility, Cloud, and Social, Analytics is now trending the IT world.

Business Analytics in itself is not new. But the unprecedented flow of data is. This has engendered a new breed of technology that has produced immense scalability and processing power. This has arguably been responsible for the new surge in quest for analytics to provide new business insights. This marriage between technology and the quest for insights promises to radically change the way business is conducted. This is already being witnessed with companies making large investments to keep up with these new changes.

Business Analytics is a big and fast growing market segment and global IT majors have fallen over each other get their fair share. IT majors may have dominated execution and delivery, but are often surprised by the intense competition they face from boutique firms which offer highly specialized services in this space. Round one appears to have gone to the smaller firms since they seem to have a better game plan, the correct skill mix, albeit limited and clever targeting. But it is only a matter of time before the biggies catch up.

But what does it take to succeed in this business?   This piece identifies five areas which are critical for success in the analytics business.

Have a focus area approach: Analytics pervades every sphere of the business. It is important to have a focus area approach to analytics. Deep analytical talent in focus area gives the customer greater confidence in the relationship. For example building expertise and depth in banking loan portfolio analytics – from generating periodic KPIs to using predictive analytics to optimize customer engagement strategies is a great way to deepen relationships with banks. This not only helps get the foot in the door but also build a sustainable relationship with customers. What areas to offer specialized services and how to build the skills is where domain and subject matter experts can contribute.  It is important not to spread the resources thin by offering solution/ services where there is no depth of talent.

Target business leadership: The business leadership in the company is charged with making the right decisions to steer the company forward.  They have always relied on number-crunchers to help support their decisions. Hence they not only consume the end product, but also are the key drivers of analytics in the organization. A successful strategy for analytics companies must be woven around winning the business leadership.

Solicit emerging market segments: According to IBM’s Rob Ashe, mid-sized companies comprise the fastest growing segment in analytics business.  This is because these companies are realizing that they need an analytics strategy of their own, outside of the capabilities in the tools they have invested in. These companies face intense competition and are seeking help to make the right and informed decisions. This is where business analytics helps. However, many global IT companies are pushing business analytics solutions only to their captive relationship base. They must enlarge their strategy to include the middle tier businesses to stay relevant in business analytics space.

Does the client have top Information Infrastructure: A top rated data infrastructure is a must-have since it helps client companies to quickly deploy analytics. In a broad sense, analytics sits on top of the Information food chain, above the reporting / business intelligence layer, which in turn sits on top of the underlying data layer. Good data begets good insights. It is obvious that customers can derive powerful benefits of business analytics when sophisticated data layers are successfully in place. Customers typically tend to seek repeat engagements in their attempts to solve several related or unrelated business problems once they start getting insights from their investments in data infrastructure. Many companies are investing to shore up their data warehousing and BI capabilities so that they continue to maintain their competitive edge.

Build top analytical skill base: The sudden focus and demand for analytics has logically led to a shortage of trained skillsets. The problem only compounds because skilled analytical talent has limited or no exposure to the technical side. Even more limited are crossover skills where technical and analytical expertise coexists. Given the growth potential for this sector, IT majors must focus on developing and nurturing business analytics skill sets – more specifically the cross-over skill sets.

As companies compete and build top class analytical skills, competition will take on a new meaning as the battle focuses on capturing customer’s insightspace; hopefully will prove insightful for both clients and global IT majors. It won’t be a long wait to find out.