Title: Managing data as an asset: An interview with the CEO of Informatica
As CEO of Informatica—one of the world’s largest providers of cloud-based services for managing data across multiple environments, supporting analytics programs, and achieving compliance with data regulations—Anil Chakravarthy sees how companies in every industry use data to make better business decisions. What distinguishes the most successful businesses, in his view, is that they have developed the ability to manage data as an asset across the whole enterprise. That ability depends on certain supporting elements: a strong technical foundation, mechanisms to govern the handling of data, and employee accountability for managing data well. In this interview with McKinsey partner Roger Roberts, Chakravarthy explains why these elements matter and offers examples of how they have helped companies use data in support of their business objectives. An edited version of his remarks follows.
McKinsey: In your experience running a data-management company, how do businesses use data to create value consistently?
Anil Chakravarthy: The most value comes from being able to collect and correlate information from different kinds of systems. For example, a major oil company that we work with historically used traditional data models and databases to determine things like the profitability of an oil well. They would start by collecting data about an oil well. What are my costs? How much production do I have? Then they could ask, If the oil price hits X, will this oil well be productive or not? That was a traditional way of doing an analysis on an oil well.
Now through IoT [the Internet of Things], they have a lot more data on actual productivity in terms of things like output and maintenance status. And they’re correlating that data. So now they develop predictive analyses that identify the most efficiently run or most effectively run oil wells, or the most profitable oil wells. Then they can make real-time decisions.
We see this in industry after industry. It’s being able to take the data that a company traditionally had, which dealt with things like profitability, cost, expense, et cetera, and combine it with more IoT-based data on efficiency, maintenance, status, and so on.