5 steps to turn your company’s data into profit
Companies are gathering more and more data, but many are still struggling to turn that information into business outcomes. In the book Monetizing Your Data: A Guide to Turning Data into Profit-Driving Strategies and Solutions, published last month, analytics experts Andrew Roman Wells and Kathy Williams Chiang explain how enterprises can begin cashing in on their information by using analytics.
Wells, CEO of management consulting firm Aspirent, and Chiang, vice president of business insights at Wunderman Data Management, have each been practicing analytics for more than 20 years. While Chiang focused more on analytics, and Wells worked with business leaders on strategy, each observed that these two major processes were often disconnected within companies.
“Data scientists were churning through data trying to find insights, while the planning people had ideas and went to find the data to justify those ideas, instead of taking a more objective approach,” Chiang said. “We saw the opportunity to marry these two together so they become more synergistic and supportive—bringing objectivity to the planning side, and meaning and purpose to the data side. It shows how the quantitative and qualitative can be connected in the business environment.”
When they teamed up together for a project at a large hotel company, they found that the combination of their methods made for a new approach that links decision theory, data science, and agile analytics. Their methodology evolved over the course of several subsequent projects, and resulted in the book, Wells said.
“The old era of how you gathered requirements and put together analytical solutions for driving business value no longer works in the new era,” Wells said. “You have to change the conversation so that instead of wondering about the question, you’re trying to solve for the decision.”
Here are five steps outlined in Monetizing Your Data to help businesses use their data to get the biggest business impact.
The discovery phase involves focusing on the nature of the problems or opportunities the organization is facing, and trying to get a full sense of their business landscape to determine what actions and impact they are looking to achieve, Chiang said. This phase is interactive, and involves workshops and interviews to gather input from all users up front.
The discovery step also creates alignment for the project, Wells said. “It sets the foundation for understanding business objectives and drivers, and developing hypotheses we align [solutions] to so we know we’re solving a real-world problem,” Wells said. “It’s the launchpad for the rest of the project.”
This phase begins to structure the analytical problem a company is addressing, allowing staff to be more systematic about the problems they are trying to get to the root cause of, so that they can test hypotheses and develop actions around them, Chiang said.
