Legendary Alabama coach Bear Bryant believed in defense:
“Offense sells tickets, but defense wins championships.”
Legendary boxer Jack Dempsey saw virtue in offense:
"The best defense is a good offense.”
Legendary analytics guru Thomas Davenport takes a more neutral stance in his Harvard Business Review article What’s your Data Strategy?
"The key is to balance offense and defense.”
Davenport goes on to say:
“Data defense is about minimizing downside risk, including ensuring compliance with regulations, using analytics to detect and limit fraud, …and ensuring the integrity of data flowing through a company’s internal systems.
...Data offense focuses on supporting business objectives such as increasing revenue, profitability, and customer satisfaction.
…The challenge for CDOs and the rest of the C-suite is to establish the appropriate trade-offs between defense and offense and to ensure the best balance in support of the company’s overall strategy.”
Balance is fine. But at Juice, we’re all about building data products. That’s an offensive data strategy (we’re with you Jack Dempsey, June Jones, Mike Leach, and Mike D’Antoni).
In practice, most organizations start from a defensive crouch. The relevant question is: when is it important that you shift to a more offensive data strategy?
Davenport shares a few indicators that suggest more data offense is warranted. For example, offensive strategies are often employed at organizations that operating in largely unregulated industry where customer analytics can differentiate. He also sees opportunity for offensive data strategies at that those organizations with decentralized IT environments and where “Multiple Versions of the Truth” are encouraged.
His HBR article even provides an evaluation tool to determine whether your organization has shifted its balance toward offense or defense, giving you a snapshot of where you’ve (organically) evolved. It doesn’t tell you where you should be.
When we think about the dozens of companies we’ve worked with who are launching data products, some common patterns emerge in terms of the characteristics of those organizations. Here are four categories where an offensive data strategy provides like a good fit:
Government, non-profit or public-service organizations
These organizations aren’t necessarily in the “competitive” markets that Davenport describes. Nevertheless, they are sitting on tons of valuable data that can shape conversations and influence the decisions of their constituents. We’ve worked with Chambers of Commerce, Universities, and State Departments of Education that are taking on offensive data strategies.
Data science startups
There are hundreds of start-ups who are building their businesses on offensive data strategies. These companies have mechanisms for collecting data across an industry and are adding value through predictive algorithms, identifying patterns, and ultimately helping their customers make smarter decisions. We’ve working with a couple healthcare start-ups who have proprietary methods for predicting performance of healthcare providers. This is deeply valuable information for health systems and employers, and a purely offensive strategy.
Consultants
We’ve seen a couple different offensive data strategies by consulting firms. First, if they are delivering a project with an analytical deliverable, why not make the deliverable a recurring data solution? Another approach by the most innovative consultants is to view data collection and data products as an opportunity to proactively identify problems for clients. An annual survey of customer brand awareness can be turned into an incisive discussion starter, spurring clients to pursue the next project.
Companies with dominant market shares
If you are a market leader, you may be collecting enough data from your customers to be able to provide benchmarking solutions. In some cases, this offensive strategy is core to the original purpose of the business (e.g. US News & World Report’s surveying of colleges). In other cases, the opportunity to create new data products can be a result of “data exhaust”.
If you find yourself wondering how your data might be turning into a revenue-generating or customer-differentiating solution, you should download our ebook Data Is the Bacon of Business: Lessons on Launching Data Products.