Analytics: the key towards intelligence gathering

Let’s start with the real legend, the story where ‘D’ came before ‘B’, a veil which unmasked one of the most bizarre truths in the history of retail industry. It happened long ago, when a retail giant was executing the promotional analysis for various brands of products available for sale at its stores. The technique employed was of market basket analysis where in patterns were observed for goods bought in tandem. This was substantiated with goods like Gin, which also resulted in simultaneous purchase of lemons or tonic. But what came as an utter surprise was the connection between Diapers and Beers. It was observed that on weekends, males bought diapers with beers between 6pm to 7pm. Though it’s quite surprising, but the rationale was that because packs of diapers were very large, the wife, who in most cases made the household purchases, left the diaper purchase to her husband; & being the end of the working week, the husband (& a father) also wanted to get some beer in for the weekend!!! Once known, the retailer stocked both the above products next to each other which resulted in enormous success, a quick sell-out; and the fathers who were earlier oblivious to buying beer started seeing the comfort in buying one along with diapers.

This evidently proves the significance of information & its extraction from galaxy of data available in every bit, not just in digital sense but across diverse realms & domains. What if the above analysis gets applied to huge variety of products, across various stores, amongst different demography’s, at different times and days of the year!! This gives rise to what we understand as data mining, strikingly different from data querying. There is no denying the fact that not every rule born out of such analysis shall be commendable, but nor would it be trivial enough to be ignored in a risky environment that exists today.

Analytics is the field to analyse, interpret and evolve the relationships between various variables, quantify them, to develop the support and confidence for business intelligence and effective decision making. With abundance of data available all around us, what is of crucial importance is the sensible information extraction. Querying can be referred to toiling with an idea and testing it based on hypothesis, but mining is to generate all ideas hidden somewhere in the banks of data before rejecting/accepting them by testing. The key is not to sit on a hump of data, but rather use it in the most meaningful manner.

Today, even with the most sophisticated systems and technologies, and risk covering methods, we are not able to having a cent percent determination coefficient where in all the variations in dependent variables gets explained by the explanatory ones. We’ve all come across the data used through credit cards to know the credit and transaction history of a user in order to rank him/her on the probability scale of committing a default in the future. Yet, the world faced the financial crises arising out of the mortgage industry. The organised retail in a country like ours though increasingly buoyant, still lingers with the procurement and sustenance issues for fruits & vegetables, and many other items. The list can be encumbered with examples from various walks of life, but the need of the hour is to use the vault of data in the most prudent manner to address the grave concerns.

Consider the application of analytics with the theory of ‘bottom of pyramid’ that can help in catering to customers from different strata of society, providing services and products as per the individual client’s characteristics & needs in the most efficient manner. The strength lies in delivering high-end products to niche customers on time while asking for a quick payment; and delivering the valued product to middle-class customer on a certain delay with the acceptance that there shall be a discount accrued to him (). This relieves an organisation from the cyclic variations, in contemplating the trends and organising the promotional patterns. How can this be made possible? Once the company has the relevant data to understand, analyse, and predict the behaviour of its customers, by incorporating intelligence based on analytics.

What remains to be understood is that a technique is not a solution to any problem, it’s just a method. The science of analytics is a solution enabler and not a solution in itself. To survive and thrive in a globalised and highly competitive world today, thought it is important to analyse data present globally that has both direct & indirect impact on your business, but what is more important is first to understand the need of such a tool in your domain of business for righteous results that can generate not just higher margins, but also reduces costs. Thus analytics acts as a catalyst to enable or rather complete a reaction; what is required independently is the input variables and the environment for outputs to get generated!!!