Should you have an analytics team?

In an earlier post a couple of weeks back, I had talked about the importance of business people knowing numbers and numbers people knowing business, and had put in a small advertisement for my consulting services by mentioning that I know both business and numbers and work at their cusp. In this post, I take that further and analyze if it makes sense to have a dedicated analytics team.

Following the data boom, most companies have decided (rightly) that they need to do something to take advantage of all the data that they have and have created dedicated analytics teams. These teams, normally staffed with people from a quantitative or statistical background, with perhaps a few MBAs, is in charge of taking care of all the data the company has along with doing some rudimentary analysis. The question is if having such dedicated teams is effective or if it is better to have numbers-enabled people across the firm.

Having an analytics team makes sense from the point of view of economies of scale. People who are conversant with numbers are hard to come by, and when you find some, it makes sense to put them together and get them to work exclusively on numerical problems. That also ensures collaboration and knowledge sharing and that can have positive externalities.

Then, there is the data aspect. Anyone doing business analytics within a firm needs access to data from all over the firm, and if the firm doesn’t have a centralized data warehouse which houses all its data, one task of each analytics person would be to get together the data that they need for their analysis. Here again, the economies of scale of having an integrated analytics team work. The job of putting together data from multiple parts of the firm is not solved multiple times, and thus the analysts can spend more time on analyzing rather than collecting data.

So far so good. However, writing a while back I had explained that investment banks’ policies of having exclusive quant teams have doomed them to long-term failure. My contention there (including an insider view) was that an exclusive quant team whose only job is to model and which doesn’t have a view of the market can quickly get insular, and can lead to groupthink. People are more likely to solve for problems as defined by their models rather than problems posed by the market. This, I had mentioned can soon lead to a disconnect between the bank’s models and the markets, and ultimately lead to trading losses.

Extending that argument, it works the same way with non-banking firms as well. When you put together a group of numbers people and call them the analytics group, and only give them the job of building models rather than looking at actual business issues, they are likely to get similarly insular and opaque. While initially they might do well, soon they start getting disconnected from the actual business the firm is doing, and soon fall in love with their models. Soon, like the quants at big investment banks, they too will start solving for their models rather than for the actual business, and that prevents the rest of the firm from getting the best out of them.

Then there is the jargon. You say “I fitted a multinomial logistic regression and it gave me a p-value of 0.05 so this model is correct”, the business manager without much clue of numbers can be bulldozed into submission. By talking a language which most of the firm understands you are obscuring yourself, which leads to two responses from the rest. Either they deem the analytics team to be incapable (since they fail to talk the language of business, in which case the purpose of existence of the analytics team may be lost), or they assume the analytics team to be fundamentally superior (thanks to the obscurity in the language), in which case there is the risk of incorrect and possibly inappropriate models being adopted.

I can think of several solutions for this – but irrespective of what solution you ultimately adopt –  whether you go completely centralized or completely distributed or a hybrid like above – the key step in getting the best out of your analytics is to have your senior and senior-middle management team conversant with numbers. By that I don’t mean that they all go for a course in statistics. What I mean is that your middle and senior management should know how to solve problems using numbers. When they see data, they should have the ability to ask the right kind of questions. Irrespective of how the analytics team is placed, as long as you ask them the right kind of questions, you are likely to benefit from their work (assuming basic levels of competence of course). This way, they can remain conversant with the analytics people, and a middle ground can be established so that insights from numbers can actually flow into business.

So here is the plug for this post – shortly I’ll be launching short (1-day) workshops for middle and senior level managers in analytics. Keep watching this space 🙂


Why MBAs do finance – a studs and fighters perspective

I don’t have sources here but enough people have cribbed that nowadays too many MBAs are going into finance, and banking, and not too many of them get into “real management” jobs, which is what the country/the world desires them to get into. I clearly remmeber a Mint column on this topic by Govind Sankaranarayanan. And that is surely not the exception. And I remember reading this article very recently (don’t know where) which says that the reason MBAs were taken into banking was to provide a business perspective to banking, and not to be hardcore finance people themselves.

Management roles can be broadly classified into two – functional management and coordination management (the latter is also known as “general” management). Functional management is more like “captaincy” – you essentially do similar work to what your team does, and you guide and direct them, and help them, and boss over them, and get paid a lot more for it. The best part of functional management is that you can outsource all the chutiya kaam to some underling. And there is enough “functional” interaction for you with your team in order to keep your mind fresh.

Coordination management, on the other hand is mostly about getting things done. You don’t necessarily need to have experrtise in what your team does, though some degree of comfort does help. Most of your work is in coordinating various things, talking to people, both inside the team and outside, both inside the company and outside, and making sure that things are done. No special studness is generally required for it – all it requires is to be able to follow standard operating procedures, and also to be able to get work done out of people.

Historically, functional managers have been “grown” from within the team. it is typically someone who was doing similar work at a lower level who gets promoted and hence takes on a leadership role. So in an engineering job, the functional manager is also an engineer. The sales manager is also typically a salesman. And so on.

Historically, MBAs have been generally staffed in “coordination management” roles. Typically these are multifunctional multiskilled areas for which it is not easy to pick someone from one of the existing departments, and hence MBAs are recruited. Historically, when people have talked about “management”, they have referred to this kind of a role.

So through my description above, and through your own observations in several places, you would have figured out that coordination management/general management is typically a fairly fighter process. It is about getting things done, about following processes, about delivering, etc.

This applies only to India – but there is a reasonably high “stud cutoff” that is required in order to get into the better B-schools in the country. This is because the dominant MBA entrance exam – CAT – is an uberstud exam (I would argue that it is even more stud than the JEE – which requires some preparation at least, and hence puts a reasonable fighter cutoff). So you have all these studs getting into IIMs, and then discovering that the typical general management job is too fighter and too less stud for them, and then looking for an escape route.

Finance provides that escape route. Finance provides that escape valve to all those MBAs who figure out that they may not do well in case they get into general management. Finance as it was in the last 5-10 years was reasonably stud. And thus attracted MBAs in reasonably large numbers.

The simple fact is that a large number of people who get into MBA won’t be able to fit into a general management kind of job. Hence there is no use of commentators cribbing about this fact.

If the IIMs decide that they would rather produce general managers rather than functional managers, they would do well to change admission requirements. To make admission less stud and more fighter. ISB, in that sense, seems to be doing a decent job – by having significantly lower stud cutoffs and putting more emphasis on work experience and other fighterly aspects. Hence, you are more likely to find an ISB alum going into general managementt as opposed to IIM alum.