Data Hero

How to Be a Data Hero

Here’s what it takes to be a Data Hero.

  1. You start with the empirical evidence. That’s the normal, everyday stuff that’s happened and that’s been quantitatively documented over time.
  2. You take a strategic, level-headed look at it. For this you need careful analysis and skillful interpretation.
  3. Ultimately, and eventually, both you and your organization are empowered to achieve exceptional results.

Sounds pretty pie-in-the-sky, doesn’t it?

It doesn’t have to be. Which is why it’s useful, I think, to bring the idea of a “Data Hero” down to earth and look at real-world examples of this process in practice.

A few weeks ago we looked at a Data Hero example from the movie business. Today I’d like to focus on an example that’s also far outside the wine industry – cancer care, namely, and a team in Toronto that takes empirical evidence, analyzes and interprets it, and is ultimately empowered by the data to achieve exceptional results.

But let me be clear from the start.

Curing cancer? Apples.

Making and selling wine? Oranges.

They are vastly different things. The parallel I’m drawing here is only in the use and application of data.

Here’s what I mean, in the case of an organization called Cancer Quality Control of Ontario, or CQCO.

CQCO monitors and reports publicly on cancer system performance in the Ontario province. They measure how well the system is doing. They address gaps, identify areas of opportunity, and recommend tangible actions for improving quality.

Keywords here: monitors, performance, measures, gaps, opportunity, tangible actions, and quality.

As for results? How's this:

  • Highest quality care
  • Lowest cost
  • Consistent manner and delivery
  • Sets universal gold standard

Not bad, right?

All of that takes data, which is harnessed in order to move cancer, in many cases, from an acute disease to a chronic disease.

That’s an "apples" example of Data Heroes in action, and it offers a model that Enolytics can emulate as we work toward an "oranges" solutions within the wine industry. Start with the data. Analyze it carefully for actionable insights, tangible applications, and adjustments that make a difference. Achieve results for yourself and your organization.

At Enolytics we have the team and the resources to help. Please be in touch with any questions or ideas – I’d love to hear them.

Thank you for being interested --

How Do I Use My Data? Let a Data Hero Demonstrate.

Here’s something we hear a lot at Enolytics:

We think we’ve got some good data, and we’re pretty sure it’s valuable. We just don’t know what to DO with it.”

It’s a fair thing to say. That’s partly because there aren’t a ton of people in the wine industry who work with data, so talking about it (and familiarity with it) is far from common. It’s a fair thing to say, also, because each situation has a lot of moving parts – your data will be different than another company’s data and you will each need it to do different things in order to be useful for achieving your company’s individual goals.

So I’d like to spend a few moments in this space to share some stories of Data Heroes. They’re the people who defined a goal, accessed the right data sets, and asked the right questions of that data in order to derive the most useful insights that they could put into practice to achieve that goal.

Today’s Data Hero comes from the entertainment industry, where the production company behind the Godzilla movie used data to evaluate everything from the trailer to cast selection to the release date. The company is called Legendary Pictures and their analytics office is based in Boston, far away from Hollywood groupthink.

Here’s an important takeaway from the Godzilla case study: Legendary used the data before they filmed and launched the movie, so that they could be as confident as possible in its success. Much of the work we see with data in the wine industry comes after the fact, but that’s the difference between reactive or diagnostic analytics (when we look at what happened) and prescriptive analytics (when we look at what we can make happen).

Here are some additional takeaways from a Data Hero that took the prescriptive analytics approach:

  • Legendary combined both new and traditional data sources, such as social media engagement and hourly box office figures.
  • Legendary learned to spend fewer marketing dollars on hard core fans and more on “persuadable people.”
  • They used data to identify those “persuadable people” and, more importantly, they segmented those people into precisely defined cohorts and communicated messages targeted precisely to them. Cohorts consisted of as few as four people each.
  • Legendary engaged and listened to their audience, and crafted the movie’s trailer to align with the audience’s interests. In practical terms, that meant the trailer focused more on the leading actor and conspiracy theories (which the audience loved) and less on the monster and destruction (which the audience did not love).

The transfer of each of these takeaways to applications in the wine world is not only possible. It’s the way forward, and it's the shape of the model that Enolytics is building. Combining new and traditional data sources. Allotting marketing spend to “persuadable people." Defining precisely who those persuadable people are. And crafting communications specifically to them.

Do you know of some Data Hero cases in the wine industry? Please share them in the comments section or with us directly via email at cathy@enolytics.com.

Click here for more information on the Legendary Pictures case study.