Tuesday, October 30, 2012

Succeeding in Banking Analytics – Choosing the right business model

Also available here

What is an appropriate business engagement model for succeeding in the analytics business?  This is a great question, but has no simple answer. This question seems to be on the minds of leadership in analytics service providers. What engagement model do you choose to build long term trusted relationships with your clients? What is unique in banking analytics space?  In fact, this question also came up recently, rather unexpectedly, when I was having dinner with two old friends in beautiful Los Angeles.

Professional services provided by the vendors range from staff augmentation on one end of the spectrum to high-end solutions consulting that seeks to solve complex business problems.  All this emanates from the thought construct insiders refer to as the engagement maturity model.  This model tracks the morphing of provider-consumer relationship as the two embark on their journey over time. High-end consulting offers higher and obviously desirable ROI. Hence vendors strive to attain this utopia in each of their relationships. In an ideal world, if you can design solutions / offerings that will move clients up on the value chain - from staff augmentation to high end consulting, you have a winning recipe that will make you the top vendor with an enviable revenue stream.  All this is an ideal world. But, how do we work this magic in banking and financial services space in the real world?

Businesses that serve banking and financial services clients face hidden challenges.  It is well known that analytics is what differentiates successful banks. Large, well-run institutions have star-studded analytical teams that have the depth and skills to crunch through well-organized data and come up with insights to make the right decisions.  That is the upside. The down side is that, these teams may sometimes engage in dueling analytics in an effort to be one up on the other, an avoidable waste of resources and talent horsepower. Smaller institutions on the other hand, have smaller talent pool, less organized data and limited capability to undertake complex analytical projects on their own.  

Another key dynamic is that the outcomes of analytical projects impact the banks’ core decisions.  Hence banks often prefer to work with the crème-de-la crème in the business that they can trust. This provides the vendors a great window of opportunity to showcase their excellence in domain expertise, execution and delivery to win the trust of banks. Winning the trust of banks is a prerequisite for deeper, long-term engagements.  

In other words, the analytical ecosystems in these institutions are very different – ranging from the highly competitive and sometimes counterproductive to those with less sophisticated analytical infrastructure. Understanding the extant analytical ecosystem is critical in choosing the right business model for banking analytics providers.

But in the real world what engagement mix should we choose?  Seriously it depends on the prevailing analytical ecosystem of the banking customer. My personal view is that emerging and growing businesses tend to generate a significant proportion of their revenue via an on/off site staff augmentation model. Smaller boutique vendors have successfully demonstrated this as a key entry strategy in a very competitive business.  On the other hand, there seem to be fewer examples of providers choosing high end solutions as the dominant component of their mix. But I think an understanding of the nuances of this industry and the interplay of analytical ecosystem is fundamental to succeeding in banking analytics. This understanding helps discover the right mix.

Friday, October 19, 2012

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.