“It is a capital mistake to theorize before one has data”
Sherlock Holmes, A Scandal in Bohemia
What is a data culture?
When people think of ‘data’ they tend to think of something abstract and boring, but the truth is that if we frame data properly it can become interesting very quickly. Your kids’ A-level results, your annual salary or where your team sit in the table are all individual data points. When put in context, each gives us an interesting indicator about performance. If you can make it relevant, people can easily become fascinated by data.
Data driven organizations like Amazon and Microsoft have impressive technical infrastructures to make their data easily available and transparent, but they also have great data cultures. Decisions are not decided by authority, but by evidence. Employees are actively encouraged to experiment and innovate to create new insights. Most companies these days have plenty of data, relatively few are using it well. Some because of technical limitations but even more because of a lack of confidence and trust.
Why build a data culture?
Most companies now realize they need to be doing something with their data but a data strategy that covers the technology without addressing the cultural elements it will be defective.
During World War Two, it was over a year after the codebreakers at Bletchley Park began to crack the German Enigma consistently before the decoded intelligence was regularly used by military decision makers. Despite the huge expense and investment, and even with the obvious value of the information at a time of war, the traditional hierarchy of the military was a barrier to leveraging this key advantage. Thankfully this didn’t last, and by the end of the war however the nature of warfare to being ‘intelligence-lead’ had shifted decisively. We now find it hard to imagine warfare without intelligence and code-breaking and soon we may look back at business strategy in the same way.
Now as then, many organizations with impressive infrastructure are still flying effectively blind because their culture fails to emphasize the importance and advantages of data led decision making. Mark Twain once said a person who did not read had no advantage over a person who couldn’t; it’s the same for organizations and their data.
Where to start?
As with any shift in culture, to succeed takes time, persistence and leadership. Taking that as read, here are a few useful principles to focus on when attempting to start your organisation on that journey.
- Reframe your data. As we started by saying, most people think of data as dry or abstract. To engage people you have to put it in context that makes it relevant to them. Language is key, particularly coming from techies or analysts, who need to resist the urge to use jargon in their explanations and analyses. For the rest of your team, you can make it relevant by defining their objectives in terms of measurable data points whether it’s sales per meter squared, cost-per-hire or calls made. What gets measured, gets done.
- Encourage Experimentation. To start unlocking the untapped potential of your data you’ll need encourage at atmosphere of exploration and experimentation. At first most experiments probably won’t yield anything useful, but over time the benefits will naturally begin to accumulate. That is why rewarding the effort, rather than the outcome (at least initially) is important to foster an environment where people feel comfortable investing time where their efforts may not bear fruit.
- Embrace the Nerds. Whether the person is in a technical or non-technical role, they need some training. Analysts need to learn to use the relevant tools and techniques, Managers need to know the art of the possible and consumers of data need to be able to navigate efficiently and interpret the information they get correctly. Even relatively short or simple training rolled out by your IT teams can go a long way to making the data less intimidating and more transparent which is a crucial component of a good data culture.
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