If your analytics results aren’t what you hoped, maybe the fault isn’t in the “stars” — and you can do something about it.

“Aligning the stars” to produce fabulous analytical results is extraordinarily difficult for most organizations. It requires a combination of skilled data scientists, complex technology, and quality data from robust information systems. Each of these elements demands considerable expertise. For every successful story we hear about, I suspect that we do not hear about many, many unsuccessful analytics initiatives.

What’s worse, just producing these analytical results still isn’t enough. For organizations to gain business value from analytics, managers must turn the analytical results into action — the organization must be able to consume analytical results, not just produce them. Consuming analytical results is a growing problem for organizations. Organizations that build the expertise to produce stellar analytical results, also create a sizable gap between their ability to produce these results and their ability to consume them.

This analytics gap can be narrowed from two directions: by producing analytical results that are easier to consume, or by improving capabilities to consume them.

Many organizations are providing guidance to data scientists on how to make results easier for managers to digest: storytelling, for example, is now becoming a standard part of analytics training curricula. At the same time, data scientists are using increasingly complex and sophisticated techniques. The net effect is that efforts to make analytical results easier to use is not keeping pace with the growing complexity of analytics.

Furthermore, a wide range of analytical techniques are becoming commoditized. While it is unlikely that organizations will completely lose their ability to differentiate themselves with analytics, there is still considerable potential to differentiate by building up their ability to consume analytics.

As an example, Angela Kelly was educated in library science. But as she advanced in her career as a research analyst — emphasis on research, not analysis — she saw an opportunity to apply analytics techniques in her work. Angela started teaching herself through books and online courses in statistics, and found them helpful. But she also believed she needed more hands-on discussion and guidance.

With the support and tuition reimbursement of her employer, a private equity company based in Boston, she enrolled in a part-time MBA program with an emphasis on analytics. She initially considered becoming a data scientist, but realized that it was not a good fit with her interests and would squander her business background. But by building her analytical skills, she thinks she’ll improve her work performance and her prospects. Even just a few classes “helped me begin to grasp the power, limitations and real use cases of analytics,” she says.

Angela’s story highlights how both the individual and the organization can make important contributions to improving a company’s ability to consume analytics.

Individuals, for example, can develop their own skills through formal education, ad hoc courses, and background reading. There is no lack of material; instead, the volume of material available can be overwhelming. Additionally, tools and technologies rarely require investment of substantial money to experiment with. Practice datasets are plentiful. Each addition an individual’s analytical foundation can improve his or her ability to consume analytics.

Organizations can also support improvements in consumption abilities. Tuition reimbursement or allocation of time to experiment can certainly help. Small, low-stakes test projects can provide opportunities to gain experience. Centers of Excellence offer examples and resources that can be particularly helpful because they are organization specific, reduce the overwhelming amount of material, and help people take initial steps. Our forthcoming report, The Talent Dividend, details many ways that organizations are working to develop their analytical skills, particularly through augmenting skills in existing employees.

However, despite both individual and organizational efforts, it is likely impossible to align consumption abilities with production abilities. Production will likely outpace consumption. As a result, managers will need to become comfortable consuming complex analytics. Our recent article, “Minding the Analytics Gap”, offers five ways for managers to increase their comfort: (1) bolstering their knowledge base; (2) building off their prior analytical experiences; (3) creating analytical options; (4) capitalizing on their domain knowledge; and (5) using their background to recognize the limitations of analytical models.

1 Comment On: Once You Align the Analytical Stars, What’s Next?

  • Nik Zafri Abdul Majid | April 2, 2015

    In any organization, all data acquired for analysis should come from the periodical evaluation, monitoring and surveillance of effectiveness of any type of system.

    The methodology of analysis chosen is also equally important.

    The data need to be classified into as many perspectives as we can in order to gain a clear picture of overall effectiveness and whether there are still flaws in the system.

    Then most important is “What are you going to do about it?” (besides the ‘good figures?’ reflected – what about the ‘bad ones’?)

    Only then, there should be some Improvement Plan in order to avoid future problems.

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