Big data poses as many challenges as it does opportunities. While companies can capture, store, and index more information about their operations and their customers’ behavior than ever before, getting value out of that data remains a problem. Doing good analytics requires that companies collect information from multiple parts of the business and centralize it in a single repository. Once the data is stored, a team needs to create a multidisciplinary approach to analyze it, and, then, the team must share those results with various departments.
In response to the overarching role of analytics, some companies have responded by creating a new position in their C-suites — that of the Chief Analytics Officer. The CAO is responsible for figuring out how to collect the data, how to analyze it, and how to share that data. CAOs can either oversee a single analytics department that covers an entire company or can sit above multiple analytics teams organized on a department-by-department basis. In either case, CAOs are useful in organizations that meet the following four criteria:
- The organization must buy into the value of analytics from the top down. The corporate politics underlying cross-department analytics can make it hard for CAOs to succeed if CEOs are not their biggest supporters.
- Analytic systems must already be in place on a department-by-department level. When individual departments are also running their own analytic programs, they have both the data and the attitude that will help a CAO succeed on a company-wide basis.
- The company must already be using analytics in decision making. A CAO’s role is to improve the company’s analytic systems, not to create them where they don’t exist.
- Analytics talent must be taken seriously. When a company is nurturing its analytic talent, it is setting itself up for long-term success. A CAO can come in and build that success.