Tesla Motors is a good example of a fast-growing company who acknowledge that the more you scale, the larger volumes of data you need to analyze and translate into forecastable results, new business opportunities, and manageable solutions. Boryana Dineva, Tesla's Head of HRIS & Analytics, who spoke at the Data Visualization Summit in San Francisco, believes that when a company grows as fast as Tesla, they must be capable of visualizing this process in order to control the quality of it. Since 2011, the company has grown 1,700%, having internally expanded to over 11,500 employees globally. Visualizing workforce trends has therefore been imperative during this ongoing phase of hyper-growth.
Even though data viz tools allow for more structured and engaging interpretations of data, there must be a clear understanding of what an HR department wants to learn from this data. In order to be efficient, organizations who operate internationally, for example, need to acknowledge that there are cultural, legislative, and other unique features across different countries that they must comply with, and that's one of the reasons Tesla is trying to make data a foundation of HR. To do this, the company has been testing various approaches and experimenting with ideas until they got it right. At present, Tesla is trying to make all their HR resources - benefits, training, recruiting, compensation, and employee relations - data-driven. However, they found that implementation of these practices is not always easy and varies from one HR unit to another.
Before deploying data viz tools, Boryana discovered that many HR specialists didn't expect to work with numbers and graphs in the first place. She admitted that it wasn't much of a problem to make an HR Compensation unit data passionate, because they had already been working with numbers, but with others, it was tricky. In that case, Boryana says: 'It's vital to come up with a solution that can fulfil the purpose and sell the value.' Too often HR departments don't realize how much data they already have on hand, therefore they don't use it, and miss out on an opportunity to increase their productivity levels and hit targets.
At Tesla, they found that one way to encourage HR to work with data viz was to break up data into samples. If a company introduces a complex transformation all at once, employees quickly start feeling uncomfortable and intimidated. Instead, Boryana suggests introducing and testing data viz concepts step by step, not forgetting to regularly ask for feedback: Do people find it interesting and useful? Is there anything unclear about it? She explained that as confidence grows and benefits become more visible, there is an increase of interest in new tools.
One of the most important things to remember about data visualization is that it's there to simplify processes and improve understanding of data and not overcomplicate it. The choice of data viz tools may vary in each business case, but from Tesla's experience, there is no such thing as the essential data viz package, with Boryana believing: 'Use whatever solves your problem.'