While the article “How to Pick a Business Partner” in the current issue of Analytics magazine is aimed at selecting a good analytics partner, it provides excellent guidance for any organization seeking to realize value from analytics regardless of whether the capabilities are built internally or sourced externally.

All 10 of the factors identified in the article contribute to maximizing value from analytics, but four stand out in my experience as the most critical.  Unfortunately, these factors are often overlooked as companies rush to get on the big data and analytics bandwagon by focusing investment primarily on technology solutions.

First, fact-based decision-making is ultimately driven by company culture, not technology or quantitative analysis.  Investment in big data infrastructure and data scientists will not deliver the appropriate return if the organization isn’t culturally prepared to act on the resulting business insights.  Developing this culture of data-driven decision-making (what the article calls “analytics DNA”) throughout the organization is often the most difficult part of realizing value from big data and analytics.

Second, analytic capability requires an interdisciplinary approach.  Business, math, technology, and behavioral science are among the key disciplines noted in the article.  Not only does an organization need to source all of these components, but it must also bring them together in a way that fosters synthesis of the various disciplines.  Facilitating this synthesis requires very specialized leadership, which is perhaps the most difficult ingredient to find.

Third, the entire analytic lifecycle must occur to realize business value.  The article describes this as creation, translation, and consumption of analytics.  Any analytics program which doesn’t focus on all three of these stages will ultimately fail to realize maximum value.  If building analytic capability is seen primarily as a technology project to enable creation, for example, the business results of the initiative will likely be a disappointment.

Fourth, the convergence of cross-industry experience is critical to realize maximum value from analytics.  While it is reasonable for an organization to seek out analytic resources with experience in its particular industry, an outside perspective can mitigate group-think and industry bias in the search for innovative insight.  After all, simply doing what everybody else in your industry is doing doesn’t create competitive advantage.  So, in developing its analytic capability, an organization should give strong consideration to resources with cross-industry experience.

I highly recommend reading the entire article in Analytics magazine and thinking about the key factors as important considerations for any analytics program.  Also, the entire digital magazine from the folks at INFORMS is excellent, and I believe it is offered to non-members via free registration.

Please add a comment and share your thoughts and experience on key factors in realizing value from analytics.


 


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