Before you go on to read this blog in entirety, let me ensure that we are on same page on the very definition and boundaries of Analytics. To me analytics is a way of problem solving that relies predominantly on one thing – looking for repeatable, reliable and meaningful patterns in data to better understand the problem at hand – and hence developing a decision and action strategy, whose outcome is more predictable. I’m not getting into defining, or segmenting analytics itself into multiple types – that’s for another post.
If I may assume, in a rather non-analytical manner, that the hypothesis stated above that “Analytically driven decisions have more predictable outcomes” is true, then we have a solid case to ask the next question – “If Analytics is so important, should not all decisions be driven by analytics?” I’m convinced and I’m sure most of you are too, that corporations around the world already agree that analytics does deliver more predictable results and hence is critical for growth and sustainability.
It leads us to the next big question – “If Analytics is so important, or rather mandatory, then are organizations developing their analytical capability in the right manner? Are they performing various analysis in a manner that is consistent across time and space (read business functions)?” The answer, if not a resounding no, is at least a muted acceptance of lack of maturity from a vast majority of consumers of analytics.
Answer these to convince yourself – “Does your marketing team know what aspects of a product did the R&D team find important in the Conjoint Analysis they did two years ago?” Sample another one – “Does your analytics manager know the hypothesis tested by his/her predecessor and more importantly the ones he/she rejected?” Another one – “Are you sure the vendor you outsourced your analytics project to or for that matter your internal analytics team has done it in the right manner?”
Unfortunately while each individual project is done with great rigor and in most cases the end result is also great, the rigor, the process, the methodologies change from analyst to analyst and from analysis to analysis. This “adhocism” engenders uncertainty and a colossal waste of synergies across analyses.
It goes without saying that there is immense value in having a consistent way of performing various analyses across time and across functions. Some of the value adds that come to my mind immediately are, higher degree of reliability in results, consistency in interpretation of results by different functions, greater amount of cross learning owing to a common shared code of conduct and the availability of insights well post the project completion.
However the one single benefit that stand tall above rest is reduction in errors – given the magnitude of the decisions taken based on analysis, the cost of error could be very high.
Quoting an experience at Affine Analytics with campaign analysis project for a large internet company – Given the number of campaigns they run, the number of response models to be made was rather large (one for each “type” of campaign). Taking cognizance of scale and the need for repeatability, we first defined a framework or sorts (still keeping in mind the flexibility we need for individual models). Using this framework, we were able create huge efficiencies (40-50% reduction in model development time from 1st set of models to the third set) and also ensure error free delivery from the first model till the last one.
That said, there is a definite need to be wary of bureaucratizing processes. Overdone, it will end up stifling creativity, which is equally important in the development of analytics solutions. Organizations need to strike a fine balance between consistency and creativity by designing & following processes that are minimalistic in nature but comprehensive in assuring quality.
In my next post, I will start looking back at the analytical exercises I have been part of, primarily in the last two years at Affine, and see where process helped in making it more meaningful, reliable and robust. We will also briefly talk about aspects of Affine’s own analytical framework A4.
To end I quote John Updike : “Creativity is merely a plus name for regular activity. Any activity becomes creative when the doer cares about doing it right, or better”