In the first week of September 2018, electric vehicle major Tesla was rocked by a series of unusual events that culminated in a not-so-happy ending for the pioneering carmaker. First, a couple of C-suite executives announced their resignations. Second, a video surfaced online showing CEO Elon Musk smoking marijuana while recording a podcast. Tesla’s stock took a massive beating and plunged over 11% within a week.
Less than two months later, however, a more positive incident went largely unnoticed. The company turned its first profit in two years, riding on the Model 3’s popularity. Tesla made $311 million, more than in any other quarter in the company’s history. In reaction to this news, Tesla’s stock soared over 9% on a single day. The genesis of this second event was Musk’s announcement in April 2018 that he would manufacture Model 3 cars round the clock to meet the company’s production target.
When this proclamation was made, engineers at alternative data company Thasos began to watch. Thasos “circled Tesla’s 370 acres in Fremont, California, on an online map, creating a digital corral to isolate smartphone location signals that emanated from within”. Thasos, which leases databases of trillions of geographic coordinates collected by smartphone apps, set its computers to find the pings created at Tesla’s factory, and shared the data with its hedge-fund clients, showing the overnight shift swelled 30% from June to October.
Thasos utilized a new model—generating data from smartphone location tags—to demonstrate that Tesla was adding more firepower to its workforce with the intent to meet its promised production targets. After scrubbing the data to eliminate personal information, Thasos shared it with hedge funds, helping them in their decision-making process.
The jury is out on whether such data is beneficial to traders, and concerns over privacy violations obviously remain. While regulations will likely catch up, the truth is that we live in a data-rich world, and such experiments will become commonplace. The real question is: How much of the decision-making process in your organization today is influenced by real-time data?
IBM’s report, 10 Key Marketing Trends For 2017, pointed out that over 90% of the data in existence had been created in the past two years. With IoT, 5G and other technological advancements, this growth in data will accelerate. Given this reality, it is increasingly important for executives to be comfortable with data and seek out new sources of information, such as the one provided by Thasos. Here are three levers to lead in the data-driven age:
Develop an insights-driven mindset
In her book Powerful, ex-Netflix executive Patty McCord points out that while the decision to develop the blockbuster House of Cards series was in part informed by data about the show’s star being popular with Netflix’s viewers, it was also dependent on ace director David Fincher’s vision for the show. The head of content at Netflix stresses that insights from data analysis complement his team’s decision making, but certainly don’t dictate it. Put differently, an insights-driven mindset is all about developing a unique point of view by connecting the dots of data, personal experience and intuition, and using each one of those to arrive at an informed decision.
(Re)framing the problem
Asking the right questions and democratizing data can improve efficiency. An example is Unilever’s partnership with Microsoft to enable AI-assisted decision making for its various business functions. In the past, Unilever had IT experts or business analysts comb through data. Now, with the help of Microsoft’s tools, it is able to put data—and Unilever has collected a lot of it over the years—in the hands of employees who need it to make forecasts, efficiently and accurately. This is reframing the problem—it’s not only about looking back and learning from the past, but also using data to proactively learn in the present and to predict the future.
As leaders begin to get comfortable with data, it is essential for them to communicate complex situations in a simplified manner so that others within and outside the organization can comprehend, respond and contribute to the ongoing changes.
Storytelling as a tool allows leaders to do this—analyse, synthesize and communicate data-driven decisions effectively to those around them for the best results.
The data-driven transformation of diverse corporations ranging from FMCG to airlines is already underway. As the world around us reshapes itself into this new reality, how will you adapt and respond?
Rajiv Jayaraman is the founder and CEO of learning and assessments platform KNOLSKAPE, and the author of Clearing the Digital Blur.
Subramanian Kalpathi is senior director at KNOLSKAPE and the author of The Millennials: Exploring the World of the Largest Living Generation.