Opinion: Do data scientists have what it takes to get to the top? Tim Barker, Chief Product Officer at DataSift, looks at the potential of the data scientist.
Data scientists are set to become some of the most influential people in marketing. Modern-day Da Vinci’s with a skill set spanning engineering to analytics, they can do what many can’t – make sense of reams of brand data and prove the effect of data-centric solutions on business challenges.
The pertinence of their expertise to marketing’s recent revival, driven largely by data, puts them in a strong position to take their data leadership one step further into company leadership. Their role is clearly important, but is it enough to propel a data scientist into the top job?
To consider this question, we need to first look at the attributes of both the data scientist and the company leader. The data polymath has three key specialities: commercial expertise – seeing opportunities within data; statistical expertise – creating models from data; and development – building and implementing algorithms. Combining the technical and commercial skills to work seamlessly across each area elevates them to a position of real importance within the business pyramid.
The company leader, by contrast, sees business from a holistic point of view – navigating the macro environment and understanding the micro components that make up the big picture, as well as operating from both the left and right sides of the brain.
The left-side dictates rational thought and behaviour and the right-side is the source of emotional responses. Great leaders access both sides equally and use their emotional capacity to manage the human element of business.
This isn’t to say that a data specialist can’t function from the right-brain, but with their propensity for logic and reason, it’s fair to assume that the left-side dominates their decision making. So whilst they are, without doubt, playing with increasing power, data scientists are not necessarily suitable CEOs.
In any case, leading a business through its ups and downs will not appeal to all data scientists. Rather than seeking out leadership positions, many will be content to work behind the scenes in marketing teams as instigators of key value-driving business changes.
Others may be happy to sit on a company board – and management would be wise to invite them to the position, as their insights can undoubtedly aid commercial survival.
There are also other avenues for data leadership to exist within business. Prominent data scientist Hilary Mason, founder of Fast Forward Labs and former chief scientist at Bitly, is recognised for advising U.S. companies from a high-level data-inspired position.
Following her example, data scientists can develop their own consulting nous and influence business managers to take actions based on data intelligence – hence leading without assuming full responsibility.
However they progress, one thing is clear – they will progress. The rise of the data scientist is happening in parallel with the rise of data’s commercial influence. Data based on consumer behaviour allows brands to reach them with stories and experiences that resonate profoundly, not just adequately. Data insights empower companies to identify market gaps and capitalise on them better than competitors.
The data scientist’s job is to blend a mastery of these insights with an in-depth understanding of a business and its industry. As we embrace a reality that is increasingly propped up by data, the polymath’s ability to understand this new-world currency makes them a respectable economic force.
But even as they forge new territory, data experts can’t rest on their laurels. Data science must continue to develop in line with the evolution of the wider marketing industry. Keeping an eye on developments and trends in the field and ensuring their skills match the latest requirements is critical to reinforcing the polymath’s place at the forefront of marketing, and ensuring their companies stay relevant. It’s easy to become complacent and use old data techniques for customer engagement.
For instance, many companies are stuck at the stage of ‘you bought XYZ, here are similar products’, when they could be investing in pushing the envelope further. A good data scientist will use the latest data-knowledge to develop sophisticated algorithms that take advantage of current customer insights and return strong business outcomes.
With their analytical minds and propensity for finding new ways to move forward, it’s likely that data scientists will make sure they are keeping pace with industry changes. But the attitude of companies that also has to change. Data is widely accessible and the time is right to support data gurus in taking businesses to the next level. It’s a matter of joining the uprising and finding the best ones for the journey.