AUTHORED BY DONALD C. GILLETTE, PH.D., DATA CONSULTANT @ GUIDEIT
Last week we declared, “If you don’t embrace the fact that your business’ greatest asset is your data, not what you manufacture, sell or any other revenue-generating exercise, you will not exist in five years. That’s right…five years”.
This week, I’m introducing a perspective on leveraging Big Data to create tangible asset value. In the world of Big Data, structure is undefined and management tools vary greatly across both open source and proprietary…each requiring a set of skills unique from the world of relational or hierarchical data. To appreciate the sheer mass of the word “big”, we are talking about daily feeds of 45 terabytes a day from some social media sites. Some of the users of this data have nick names like “Quants” and they use tools called Hadoop, MapReduce, GridGain, HPCC and Storm. It’s a crazy scene out there!
Ok, so the world of big data is a crazy scene. How do we dig in and extract value from it? In working with a customer recently, we set an objective to leverage Big Data to help launch a new consumer product. In the old days, we would assemble a survey team, form a focus group and make decisions based on a very small sample of opinions…hoping to launch the product with success. Today we access, analyze, and filter multiple data sources on people, geography, and buying patterns to understand the highest probability store locations for a successful launch. All these data sources exist in various electronic formats today and are available through delivery sources like Amazon Web Services (AWS) and others.
In our case, after processing one petabyte (1000 terabytes) of data we enabled the following business decisions…
- Focused our target launch areas to five zip codes where families have an average age of children from two to four years old with a good saturation of grocery stores and an above average median income
- Initiated a marketing campaign including social media centered on moms, TV media centered on cartoon shows
- Offered product placement incentives for stores focusing on the right shelf placement for moms and children.
While moms are the buyers, children are influencers when in the store. In this case, for this product, lower shelves showed a higher purchasing probability because of visibility for children to make the connection to the advertising and “help” mom make the decision to buy.
Conclusion? The dataset is now archived as a case study and the team is repeating this exercise in other regional geographic areas. Sales can now be compared between areas enabling more prudent and valuable business decisions. Leveraging Big Data delivered asset value by increasing profitability, not based on the product but rather on the use of data about the product. What stories can you share about leveraging Big Data? Post them or ask questions in the comments section.