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Operationalizing Analytics for a Fortune 100

Operationalizing Analytics for a Fortune 100

Avishek Singh
By Avishek Singh
July 14, 2015

“Big data is not about the data” – said Gary King (Professor of Government at Harvard University focusing on quantitative methods) at the Institute of Quantitative Social Science, Harvard University.  While data is plentiful and easy to collect these days, the real value lies in its intelligence. One of the quicker and effective ways to generate meaningful insights from numbers is to know how to look at numbers. This is what Gary King meant when he uttered those famous lines in 2013.

With every passing day, the existing Business Intelligence tools keep getting more powerful, while another handful of them are launched. However, tools are just means to an end, and the end here is the ability to summarize performance and deep-dive into problem areas as soon as possible. The most common question every organization asks is “How do I start to leverage the data”. They have data, and people to invest in analytics. Today, they spend hundreds of hours extracting data and organizing them into bland reports that by the time they are ready to use it has already become obsolete and inefficient.

Let me give you an example. A global fortune 500 company was generating about 300 reports every month. This was just one department in one of the many divisions within this multinational. Different teams within the same department were pulling same data and reporting in different formats, and by the time the report was available 95% of this information was redundant.  We observed that 80% of team’s time was spent in digging and harmonizing data.

To solve this big problem, advanced Business Review solution was offered. One of the striking features of this solution was that it was developed entirely on MS-Excel. This meant no more license fees for expensive and fancy BI tools. It meant even someone remotely associated with analytics could consume these toolkits. It meant that one standard software (already available on everyone’s system) could enable a revolution in terms of how one looks at one’s business. Another centerpiece to this project was our ability to quickly refresh the solution whenever new data arrived. Within a couple of hours of arrival, the updated reviews were available to the managers.

The solution was inspired from 4Ps of marketing. The focus was on how the brand/product/category performed in terms of Products, Price, Place and Promotions. It focused on two levels of analysis- : the big picture view of multiple categories and manufacturers, and the drill down ability to pinpoint causality right up to smallest product level. Within six months, we had developed and launched a beta version of this solution across the division.

The big picture view was provided by a set of three executive level toolkits (combination of Excel and PowerPoint tools), typically used by the top management to see how the entire portfolio had performed in different markets vis-à-vis the competitors.  Category level analysis was facilitated by a further set of five toolkits. Specific toolkits were dedicated to assess and analyze performance across parameters like sales, promotion, pricing, distribution and new product launches. Collaboration with the organization was instrumental in developing a standard framework that could be scaled across all products/brands/categories across the globe.

Not only did we simplify and standardize the reports, we made sure that client could spend all their time in analyzing the numbers from day 1. Over 100 man hours were saved in just one functional department. Qualitative impact in terms of better analysis and faster decision making was the icing on the cake. Needless to say, the project was a massive success. What followed was a mad frenzy to quickly scale up the solution across all divisions and geographies. Its impact can be gauged from the fact that we implemented this solution across four other geographies within six months of the beta launch.

This project was a perfect demonstration of how even a simple task like standardized business review solution can make a huge difference to the ability of leveraging data. The buzz around Big Data does not only mean creating complex mathematical models, it also means simplifying the mess.



About the author:

Avishek has done his PGDM from K J Somaiya Institute of Management Studies & Research and is curently working on Big Data & Visualization for a major CPG client at Fractal Analytics.

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