Over the next 10 years, startups ability to operationalize their data will be the key determinant to their ultimate success.
So what are the most data driven companies doing today to operationalise their data. In our latest interview with Tom Tunguz, Partner at Redpoint, we discuss how the likes of Uber and AirBnB, the largest transport and lodging companies in the world, have had such success with no infrastructure.
According to Tunguz, it is simple, “they simply are the most efficient at operationalizing their data.” So what do these companies do to operationalize their data in the most effective way?
Structural Change
Companies that operationalize data most effectively change their internal structure to accommodate a data driven culture.
This can involve, as Tunguz states, “a separate data driven team,” like Social Capital and Facebook have created. However, structural change can also take place in a less formal manner, many change how they collaborate, how they make decisions and how they run meetings. The crucial element is a company’s ability to transition from using data as a historical record, to using data to drive future decisions.
It’s All About Supply
The development of functional data supply chains is crucial to operationalizing a business. This allows for the right insight to be sent to the right people at the right time. Despite the apparent simplicity of a spreadsheet, there is far greater complexity in their production.
Therefore, startups must ensure the data is synthesized and unified to create a an accurate view of the situation. As a result, Tunguz suggests, this will allow for the ‘development of an infrastructure that allows for instant access’ to the right data at the right time.
A Common Language
The most data driven companies develop an internal data dictionary for their employees. A data dictionary is a guideline for the common language of metrics used at the company. For example, sales and marketing teams often have very different interpretations of the term ‘lead’. This can create confusion, mistakes and a slowing of the funnel.
Consequently, as Tunguz highlights, “the development of robust data pipelines,” allows for the distribution of a universal language across the company.
Ultimately, the combination of bottoms up data literacy, robust data supply chains and a fundamental change to the internal structure of the company, are the reasons the most data driven companies have succeeded. So get your data together and get moving.