How to compete—and triumph—as a data-centric organization
"Data is the new oil" is one of many buzz phrases used today to denote the importance of creating data-driven companies. In the 2019 annual executive survey conducted by New Vantage Partners (haas.org/ nvp-survey), 77 percent of executives say that adoption of data initiatives continues to represent a challenge for their organization. Respondents clearly say that technology isn't the problem, people and process are. So, what's going on?
While leaders want to build a "science-type" organization that uses operational data to create forward-looking strategies and decisions, the reality is most organizations tend to be a "story-type" or "stats-type" organization. In a story-type organization, work is based on celebrating one-off wins and is typically reactive. A stats-type organization has data but tends to be fragmented, with data often used in a backward-looking way to justify or explain decisions.
Since graduating from Haas, I've had the privilege of running global organizations with over 400 team members. Reflecting on my own experience and many bouts of failure, I've learned three lessons I wish I knew back then. These lessons would have helped me make the transition from a story-type to a stats-type to a science-type organization much easier.
Most organizations have data in many systems but often the way it's used is inconsistent. For example, one department may consider their key metric to be time to respond to customer questions and another may use overall satisfaction. The challenge is not which is the right answer but how to create a basket of key metrics applicable across the organization. Leaders also need to ensure that these metrics are being calculated and used consistently and that they are visible to everyone via organizational dashboards.
Department heads typically review data, but team members may not understand how it's connected to their work. To ensure data are converted into actions, I always ask, Is this what we expect to happen? What can we do to improve after looking at this data? Then, use the data for setting individual goals. In a previous organization, as we started to set goals, we realized that individual team members did not have the ability to own the outcomes as they were dependent on other teams. We unpacked clear metrics that worked for the team and through this process were able to make data more relevant to individual work and connect it back to top-line objectives.
At the leadership level, impact is often linked to truly moving the needle, as in, "increased customer facing time by X percent." But driving big impact requires time, and most teams want to know their work is meaningful today and connected to their career aspirations. Consistent communication about progress is important but not sufficient. Leaders need to celebrate key milestones publicly and reward team members for smaller outcomes. Themed awards given quarterly that balance both effort and outcomes have the greatest impact on driving successful change in understanding that data-driven is the way to individual and team success.
The transition to a science-type organization requires more than an investment in technology. Leaders must build new organizational habits for all team members. Apart from discipline, leaders need to engage with their teams to understand their motivations and connect their goals with data. Building the muscles to pivot to a data-centric organization may take time, but the ultimate reward is being able to make forward-looking strategic decisions rapidly.
Dutta Satadip, MBA 09, is a thought leader, keynote speaker, and tech industry veteran who specializes in customer strategy and scaling operations. He is the global head of customer operations at Pinterest and previously worked at Google as the director of customer success. He has a multidisciplinary leadership background leading operations, marketing, product management, and engineering teams. He often speaks at major conferences and contributes to publications like Harvard Business Review.