Getting the Biggest Bang from Analytics Investments

Numerous research studies have validated the business value of predictive analytics.

According to a survey by Accenture of 600 director-level executives in the US and the UK, 57 percent are either “very satisfied” or “quite satisfied” with the results their organizations are achieving from analytics investments.

Determining Value

Still, how do you know whether your company is getting the biggest bang from its analytics? Well, by analyzing!

A good starting point is to determine how pervasive the use of analytics is across the enterprise. Research shows that the use of analytics by top-performing companies is exponentially higher than lessor performers.

Additionally, how is analytics being used within different functions? What is the adoption rate and the frequency of use, and how do those stats  compare to best-in-class companies in other industries as well as direct competitors?

Decision-makers can also use analytics to identify data-driven projects that generate the highest business returns based on results stored in project management systems as well as by conducting post-mortem reviews.

Measuring ROI

The results (e.g., cross-sell/upsell, price optimization) can be categorized and ranked to offer apples-to-apples comparisons by application.

Of course, ROI isn’t always measured in terms of direct changes in profits and revenue.

Companies that use big data analytics are not only twice as likely to be in the top quartile for financial performance within their respective industries, they’re also five times more likely to make decisions faster, according to a Bain & Company study of more than 400 companies around the world with revenues of at least $1 billion.

Meanwhile, companies that adopt data-driven decision-making achieve productivity that is five to six times higher than those who don’t, according to a study of 179 large companies conducted by MIT and the University of Pennsylvania’s Wharton School.

Companies that are able to make faster decisions are more likely to gain time-to-market advantages and other productivity benefits.