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Three analytics integration lessons from the sports data revolution

Three analytics integration lessons from the sports data revolution

You may not think of your organization as a sports team, but when it comes to data and analytics, there are more similarities than you might think. Those similarities can reveal how analytics, if effectively deployed, can lead to better decisions and more successful organizations.

According to Ben Shields, Senior Lecturer at MIT Sloan, executives can view sports as a petri dish for how their organizations can maximize the value of analytics. Although there are many lessons to be learned from the sports industry revolution, one especially valuable innovation is analytics integration—the ability of an executive to integrate an analytics program within the rest of the organization.

“It might be tempting to introduce an analytics program as a separate corporate function, one free to innovate and do things differently,” writes Shields in a recent article for MIT Sloan Management Review. “But while that might make things easier at the start, it will ultimately undermine the effectiveness of analytics, which needs to flow across organizational decision-making to provide its true value.” A better approach, he suggests, is to integrate from the beginning, even if your face pushback from analytics skeptics.

In his article, Sheilds explores three integration strategies that have been successful in the sports industry:

1: Practicing collaborative analysis
Analytically minded sports executives do not view analytics as the only thing that can chart the path forward to better decisions. An inclusive approach to information is key to integrating analytics throughout an organization. This means combining advanced quantitative metrics with other types of information, including qualitative analysis, unstructured data, and survey data, to inform the decision-making process. “Greater diversity of information and interpretation will lead to better decisions — and a permanent seat at the table for the analytics team,” writes Shields.

2: Establishing a Common Language
Analytics has its own language, which can be confusing or even intimidating to those outside the field. If insights aren’t fully understood by all stakeholders, they can go unused or unnoticed. “To maximize the potential of analytics, executives must establish a common language for their analytics program—one that is grounded in the organization’s goals, jargon free, and reinforced through immersive education.” In his article, Shields shares how the founder and director of applied sports science company P3 enables collaboration and “cross-talk” around analytics.

3. Deploying Accessible Technology
Driving the impact of data requires adopting analytics technologies and deploying them across an organization. Shields shares how the Kraft Group (owners of the New England Patriots football team) has invested in and built its own proprietary analytics technology capabilities to better engage customers through their behaviors at the stadium on game day and throughout the year via digital engagement or with partners. Regardless of industry, with analytics programs often requiring multiple technologies, being strategic about technology deployments is imperative. The chances of an analytics program’s success rise substantially if all key stakeholders have access to and can easily incorporate these tools into their daily work.

Fulfilling the promise of analytics takes more than sophisticated analytical methods and tools. It also requires creating the environment in which analytics is integrated across the organization. Read the complete article in MIT Sloan Management Review to learn how executing on these three strategies can help your analytics program become core to how your organization operates. Ben Shields also leads the two-day Executive Education program, Analytics Management: Business Lessons from the Sports Data Revolution. In this program, Shields provides insight into the sports industry’s “secret sauce” and helps executives apply it immediately to the development of their own analytics program.


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