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In their excellent Shumpeter column, The Economist recently wrote about something that we at Mindtree have been championing for a while, and what they called “the unspoken secret of big data”*:the fact that small insights gained from data analytics can lead to significant returns either over time or when applied exponentially.

Incremental improvements based on data are the hallmark of online companies like Amazon and Google. Their approach is to experiment with many small changes, and to test them individually to see what works. Each successful experiment is then implemented rapidly. Over time, these small improvements add up to a big lead over the competition, even fundamentally changing how business is done.

For traditional retailers and CPG companies, such experiments have typically been difficult and expensive without the promise of big gains. Accordingly, managers used to look only for the big ideas and ignored small, incremental changes that they could not be sure of. But the economics of testing ideas has changed, and successful managers will embrace the ability to test and make small changes that help businesses get a little better each time at identifying the right customer, or personalizing offers for each interaction, or ensuring better product availability, or fine-tuning the customer experience to make it more mutually rewarding over time, every time.

Tools to Harness the Power of Data Are Available

The Economist column noted UPS as an example – that they analyze data about the routes their delivery drivers take each day, because they’ve determined that “cutting each route by just one mile would save it $50m in fuel and other costs a year.” In the retail industry, the column notes how discount retailer Big Lots increased furniture sales by 9% after using data analytics to come up with the most attractive in-store financing offer.

Simply stated, crunching mountains of data from retail points of sale, retail audits, consumer databases and so on, is no longer as laborious as it used to be. We have seen this first hand with our clients. Using store sell-in data from about a million stores, Mindtree has routinely nudged up on-shelf availability, reduced out of stock situations, and helped place more adjacent products on store shelves for a top consumer packaged goods firm.

All the data that companies have collected for years can now be instantly mined for insights that were out of reach until very recently. Platforms like SAP HANA can crunch petabytes of point-of-sale data in moments – something that used to take hours, days or weeks of effort and computing power. And because everything is so wired up these days, every little action can also be measured.

This means a manager’s hunch can be quickly tested and validated. A small experiment built on the basis of that insight can easily be compared to control data. Let’s say the idea proves to lead to a 0.5% improvement. It seems like a small amount, but if it can be implemented at a low cost, and if you can successfully accomplish five more similar experiments over the course of a year, it would all add up to a significant difference.

All of this helps set the direction for sales and marketing leadership, and improves productivity for the entire brand, marketing and field organizations. Moreover, with such insights available on demand, managers can start to use their time to think strategically, while leaving the grunt work of data crunching and modeling to computers and data scientists.

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