• May 29, 2015

Mining Value From Hockey and Right-Hand Turns

By John Tomesco, Worldwide Business Intelligence Modernization Practice Lead, Applications & Data Management, Hewlett Packard Enterprise

How the Data-Driven and Agile Enterprise Transforms Mistakes into Big Ideas

A few years ago, a leading global logistics company discovered it could generate value if its drivers only made right turns. Left-hand turns dramatically increase idling time and reduce efficiency. By leveraging technology, data, and analytics, the organization developed the capability to generate right-hand-turn routes in minutes. The result? Packages were delivered faster while tens of millions of miles and millions of gallons of fuel were shaved from the delivery process.

It’s a potent example of how the data-driven and agile enterprise can transform by discovering issues, optimizing processes, and solving problems. But the key is to understand that it’s not about the data. It’s about the outcomes and the value.

Data-driven, agile organizations do a better job of extracting that value to understand issues—left-hand turns waste time and resources—and make better decisions—right-hand-turn routes lead to more efficient product delivery. They recognize that data is a strategic asset only if the maximum amount of value can be pulled from it. Data delivers information, which provides insight that should lead to action.

Unknown Unknowns

In the data-driven and agile enterprise, there is more free-form thinking and testing of hypotheses.

Challenges—both known and unknown—that beg action are piling up for the enterprise like never before. And so is the data: structured, unstructured, human, social, sensor, machine, environmental, and more. When you let the analytics do the driving, you identify issues and clearer paths to fixes faster.

I played hockey in college. When I came off the ice to the bench, our coach used to look me in the eyes and say, “Do you know you made a mistake? Because if you don’t, then we have two problems to overcome.”

Likewise, if an organization doesn’t realize it’s making a mistake (like excess inventory in one warehouse and not enough in another), then it has two problems—one of which will be continuing to face that inventory issue, for example, over and over.

Big Data, Big Value

Do you know what problems you’re trying to solve? Reducing costs? Mitigating risk? Accelerating revenue? Improving efficiencies? Traditionally, enterprises allow their thinking to be constrained by the structure of the information available to them. Totally old-school. And unproductive.

In the data-driven and agile enterprise, there is more free-form thinking and testing of hypotheses. More possibilities and motivation to make something happen. The organization leverages the data to develop a hypothesis through analytics and tests the implications. The clear and detailed view of the data might point to the shortest route to transform your customers’ experience, detect fraud, or even predict when the brakes in your company car might need replacing.

How do you get there? By changing the culture and aligning IT with business objectives. Focus on what the organization is trying to accomplish while utilizing Big Data analytics to understand and solve problems to generate value. Ground the data and your data analysts in the business outcomes.

It’s a challenging environment out there. Whom you provide products or services to and whom you compete with are changing in ways we never thought possible. To succeed, you have to develop a culture of testing and using Big Data and analytics in the search for new and different business models. If it isn’t broke, break it … and make it better. Let the data and analytics show you the way.