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Guidance and results for the data-rich, yet information-poor.

Predictive Analytics Can Tackle Quirky Questions, Too

MMsGoogle recently used predictive analytics to answer an unusual question, according to The Washington Post. Are employees eating too many M&Ms, and, if so, how can we alter their behavior without removing the M&Ms entirely?

It may seem like a trivial question. But as it turns out, Google was able to cut employee calorie consumption by 3.1 million in just 7 weeks, leading to happier, healthier employees.

How did they do it? They asked a good question before digging into data to find the answer.

What if the company kept the chocolates hidden in opaque containers but prominently displayed dried figs, pistachios, and other healthful snacks in glass jars? The results: in the New York Office alone, employees consumed 3.1 million fewer calories from M&Ms over seven weeks. That’s a decrease of nine vending-machine size packages of M&Ms for each of the office’s 2000 employees.

The titan of Internet data is taking its own medicine, using the data analysis that has helped the company produce $55 billion in revenue each year to improve the morale and productivity of its 40,000 employees. Many tech companies offer perks such as free snacks or cafeteria food. But at Google, almost every benefit is broken down into crunch-able, profitable or geographic data, including salaries, the lengths of maternity leave, the size of the plates used at the food bar or even the squishy goal of workplace happiness.

What are your business problems and goals? Predictive analytics can help, so long as you launch your business intelligence program in a way that meets those objectives.

Getting the results you want takes training, whether you are targeting M&Ms, fraud reduction, or cost-cutting. Real business intelligence requires a real strategy. Register today for the free webinar that will help you build yours.

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