More is More: Why Layers of Data Matter

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Data is valuable, but data that you can accurately interpret and use to make better business decisions is priceless. For that reason, it’s important that stand-alone data be interpreted against other data points to provide a fuller picture of trends and behaviors. In other words, layers of data offer meaningful insights and context that solve business needs.

Layers Turn Isolated Data into Opportunities to Leverage

“Take the example of a company that has invested heavily in business intelligence software that organizes internal data. In an increasingly connected world, this company has not leveraged its data to its potential,” wrote Alissa Lorentz, vice-president of creative, marketing and design at Augify, in Wired.

“Why not? Because the company’s internal data is isolated from the rest of the data universe including news, social media, blogs and other relevant sources. What if you could join the dots between all these data sources and surface hidden connections?”

The key for race directors may be avoiding the tendency to place data from participants, past events, social media and other sources into silos. Rather, working to understand how those data points relate to each other and what the data is saying.

For example, learning how many participants are registering for your event each day is valuable. Taking that data and relating it to last year’s pace and where registrants are coming from is the context that allows race directors to identify even more potential registrants.

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Layers Answer the Question: What Story Is My Data Telling?

Layers of data turn random numbers into a story.

Seeing that your per-day registrants rose 30 percent yesterday doesn’t help you fill your race. A ton of new registrants in Southern California the day after a local running club mentioned your event in an email blast is a story with a who, a what and a why. That data (and the layers of context) might prompt you to reach out to that club for additional cross-promotion or to contact other running clubs for similar opportunities. The takeaway isn’t what your next move might be, but that you are enabled with information to make a move.

The data scientists responsible for interpreting raw data for told Harvard Business Review that their real job is simply storytelling.

“In short, we’re tasked with transforming data into directives,” wrote Jeff Bladt and Bob Filbin.

“Good analysis parses numerical outputs into an understanding of the organization. We ‘humanize’ the data by turning raw numbers into a story about our performance.”

Do you have access to data that tells a story about your event’s performance?