Competing With Data & Analytics
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“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.