Ideas in the Wild: How Jim Rushton is Helping Business Leaders Seize the Opportunity that Analytics Present

Decision-makers can’t get enough from data. The problem is, most leaders only use data to reaffirm the obvious information — and their companies are suffering because of it. Executives interested in getting to scalable, insight-driven business decisions are not sure where to start. Who should lead such a program? Will it be worth the effort? […]

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Decision-makers can’t get enough from data. The problem is, most leaders only use data to reaffirm the obvious information — and their companies are suffering because of it.

Executives interested in getting to scalable, insight-driven business decisions are not sure where to start. Who should lead such a program? Will it be worth the effort?

The good news is that, yes, underneath that surface-level data lies a treasure trove of useful information, and with the right approach you can get to it. With business analytics, you can have the competitive advantage you’ve been missing.

Jim Rushton wrote Guaranteed Analytics: A Prescriptive Approach to Monetizing All Your Data to help business leaders move past the obvious about the “stars” and “dogs” of their business and dive into where the true money — and competitive advantage — lies. This is a book about identifying the opportunity analytics present, building an insight-focused culture, and unlocking the stories behind the numbers. I recently caught up with Jim to see what inspired him to write the book, his favorite actionable idea, and how he’s applied that idea to his own work.

What happened that made you decide to write the book? What was the exact moment when you realized these ideas needed to get out there?

Analytics work each and every time. There’s no questioning the business value of insights that weren’t previously known. And when action is taken, these insights drive hard financial returns.

Yet when I looked around, I saw one failed project after another in the marketplace and I read magazine articles announcing the dismal success rates of analytics and business intelligence efforts. I knew it could be better because we had a 100% success rate with our clients.

So, I sat down and did some research on what was causing failures and found there were common overlaps in almost every situation I came across. I then thought about what tactics we utilized to avoid those typical pitfalls. Understanding the gap analysis, or “delta” between the actions that drove success and failure, is what allowed me to codify how to guarantee success with these elusive projects. The findings I uncovered all made sense, which I knew was a sign I was onto something (as I don’t believe in magic beans). People just weren’t aware or didn’t know how to utilize and manage the correct approaches and tactics to their benefit. That was the genesis for the prescriptive approach that is laid out in this book.

What’s your favorite specific, actionable idea in the book?

It’s the incessant focus on what will be your changed business action. This is particularly important because almost every step in a project is cost/expense:

  • Time spent strategizing and planning is a cost
  • Capturing and storing data is a cost
  • Selecting and implementing tools (e.g. query and visualization tools) is a cost
  • Analyzing information and looking for insights is a cost

All these costs keep summing up and ROI cannot be captured until there is a changed business action. So, the big takeaway is to think about what business decision will be made differently and what action does that involve? Here’s an example. Say you run a hotel chain and are trying to figure out how to better leverage your email campaigns. These approaches are all costs:

  • Discussing with the other managers different approaches and ideas.
  • Sending your data analyst to capture all the past year’s email campaigns and results.
  • Having your IT guy spin up a Data Mart in which to store all this data and implementing a powerful Business Intelligence tool on top.
  • Asking your PhD in statistics Data Scientist to mine this treasure trove of information.

Until you change an action — improving the offer, editing the audience, introducing new products — ROI can’t occur. However, once that action is changed, money is capturable.

Let’s say that an insight was uncovered that two of your email prospecting rent lists were getting great reservation responses but with unusually high last minute cancellations. You decide to not use those two lists and instead focus attention on the other prospect lists. This would produce both reduced expense (lower prospect rental list costs) and increased revenue (last minute room cancellation avoidance). That’s the changed action that drives a financial return.

What’s a story of how you’ve applied this lesson in your own life? What has this lesson done for you?

One of our customers, an electricity retailer, had a customer with an unpaid bill that was 63 days overdue. The standard process was clear: call to threaten them with service interruption and then terminate service if the outstanding bill is not paid within 7 days.

But, we sifted through all the information and created the possibility of a changed business decision and subsequent different action. We did not dispute the data (since data is always fact) that a bill was 63 days overdue for a Pizza Hut location.

But we did produce some new information: this Pizza Hut location was owned by the same successful entrepreneur as nine other locations. In others words, what you were incorrectly calling customers were actually just billing accounts. And this information led to a previously unconsidered insight: “If nine of the ten locations/accounts are paid in full, is this customer, the entrepreneur, really a financial deadbeat or, instead, do we perhaps have a billing issue?”

The changed action: “Do not call and threaten a very high volume customer. Instead call and ask how everything is going and if they are receiving all of their bills on-time.”

The result was incredible. Instead of incurring the expense of a call to threaten a non-paying “account” that could have ended up in ten accounts churning out from poor customer service, the expense was used to increase customer service, improve revenue capture, and reduce the risk of future customer churn/erosion. It was a win-win for all parties involved.

For more advice on making the most of your analytics, you can find Guaranteed Analytics: A Prescriptive Approach to Monetizing All Your Data on Amazon.

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