In the first week of September 2018, electric vehicle major Tesla was rocked by a series of unusual and bizarre 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. The result? Tesla’s stock took a massive beating and plunged over 11 percent within the span of a single week.

However, less than two months later, an incident that was much less peculiar and significantly more positive for Tesla went largely unnoticed on popular media. The company had turned its first profit in two years, riding on the Model 3’s popularity. Tesla had made $311 million, more than any in other quarter in the company’s history. In reaction to this news, Tesla’s stock soared over nine percent on a single day. The genesis of this second event had been triggered by an announcement by Elon Musk back in April 2018. Musk had vowed to manufacture Model 3 cars round the clock to meet the company's production target.

When this proclamation was made in April last year, the engineers at alternative data company Thasos began to watch. According to Thasos, “They 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 it. 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, then shared the data with its hedge-fund clients, showing the overnight shift swelled 30 percent from June to October.”

In other words, data company Thasos utilized a completely new model (generating data from smartphone location tags) to demonstrate that Tesla was adding more firepower into 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 may be out on whether such alternative data is ultimately beneficial to traders in predicting stock swings, 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 sooner than later. The real question is, as a leader, how much of your decision-making process today is influenced by real-time data?

Being comfortable with data

A few years ago, IBM released a report pointing out that over 90 percent of the data in existence has been created in the last two years alone. With the advent of IoT, 5G and other technological advancements, the growth in data will no doubt accelerate in the future. Given this reality, it is increasingly becoming important for leaders to not just become comfortable with data but also proactively seek out new sources of information, such as the one provided by Thasos.

At KNOLSKAPE, we have identified three crucial levers that can help leaders make sense of the data-driven age.

Lever one: Developing an insights-driven mindset

In her excellent 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 about David Fincher developing it.  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, intuition, etc., and using each one of those to arrive at an informed decision.

Lever two: (Re)framing the problem

Unilever has partnered with Microsoft to enable AI-assisted decision making for its various business functions. Jane Moran, the CIO of Unilever often checks with her team, “Why are we doing this?... At Unilever, our BI systems have primarily over the years focused very well on looking back in history. And how we have the enormous opportunity to predict the future.” In doing so, Moran is driving efficiency by asking the right questions and reframing the problem. The emergent solutions for Unilever will no doubt be implemented in partnership with AI.

Lever three: Storytelling

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 their organization can comprehend, respond and contribute to the many ongoing changes. Storytelling as a tool allows leaders to do precisely this – analyze, synthesize and communicate data-driven decisions effectively to those around them.

Like Unilever, Malaysian airline Air Asia has partnered with Google to integrate Google Cloud’s machine learning and AI into every aspect of its business. In doing so, group Chief Executive Tan Sri Tony Fernandes has begun the transformation of Air Asia into a travel technology company.

The data-driven transformation of major corporations ranging from FMCG to airlines is already underway. As the world around us reshapes itself into this new reality, how will you, as a leader adapt and respond?