When we think of some of the world’s most enigmatic leaders and entrepreneurs, there’s an enduring image – even a romanticism – of a person thoroughly in tune with their own intuition.

Intuition, gut feel, instinct – whatever you want to call it – has been feted as everything from a leadership secret to a human “superpower”.

Steve Jobs called it out in his 2005 commencement address at Stanford University. “Have the courage to follow your heart and intuition,” he counselled.

There are clear benefits in getting the balance right and in adopting what is essentially a two-speed approach to innovation, harnessing both intuition and data.

In Jobs’ case, his intuition bred innovations that would set Apple on a trajectory to become the world’s first trillion dollar business by market capitalisation.

But intuition is not the sole path to innovation. Big data and analytics is also an enabler of innovation. Data can help answer questions faster, understand customers better, validate intuitive responses and ultimately become a valuable input into the innovation process.

Yet, many executives say they struggle to get the balance between these different inputs to innovation right.

A study by the Smith School of Business found leaders were split on how to progress: “52 percent said they rely too much on data and analytics when making decisions and not enough on their intuition, while 41 percent indicated they rely on their intuition and experience more and not enough on data and analytics.”

Though they might lean more in one direction than the other, one of the positives to draw from this is that leaders don’t view intuitive and data-driven decision-making as being mutually exclusive. That’s important, because different approaches to innovation can yield different outcomes.

There are clear benefits in getting the balance right and in adopting what is essentially a two-speed approach to innovation, harnessing both intuition and data. One reason to do so is that leaders who traditionally lean more heavily on intuition might find opportunities and insights in their data that they wouldn’t otherwise have come to independently.

We often hear people refer to data as the ‘oil’ of the 21st Century. Invariably, what they mean by this is it’s a raw ingredient with many value-accretive uses. For example, oil as a raw material can be transformed to power cars or to create plastics. These finished products create new changes in society.

Data operates in a similar fashion. It’s a huge resource that we can ingest into a central place, cleanse, combine with other sources and process to create insight and value. It is an input used to transform the basic or rudimentary into something sophisticated, intelligent and differentiated.

It is frequently used to locate and address gaps in thinking. Conceivably, data might produce things that even the best entrepreneurs or leaders wouldn’t necessarily think of, or find more opportunities for value than were first recognised.

Data is also a useful validation mechanism. It can be used to check that a leader’s or team’s intuition or assumptions around a decision are, indeed, correct. Data can also be a powerful counter to self-doubt, which is often associated with entrepreneurship and innovation. As Psychology Today notes , “Rising levels of self-doubt can become crippling to an entrepreneur. It might even be these fears that keep people from making the leap to entrepreneurship”. Data can be a powerful way to defeat self-doubt by validating whether or not fears over a direction or decision are well-founded.

If data is to truly fulfil its promise as the raw input to create and sustain innovation, two things need to happen.

First, executives and workers need to prepare by increasing their data literacy and internal skills sets. If we expect data to support every decision a person in a business makes, we need to equip that person with the skills and confidence to make data work for them. Data must become part of the organisation’s fabric and workplace culture, with everyone speaking the same ‘language’.

Second, the technology needs to improve. Tableau, with its roots in university research, was founded with the goal of making it possible for people who know data best to be able to interrogate and view the data by themselves, instead of having to ask someone with technical skills to do it for them.

By itself, this is an innovation enabler for our customers, but even we can do more. For example, we recently introduced natural language processing, which is fast becoming an accepted way to interact with data and directly ask it questions and receive answers. Being able to converse with data like you would a person opens even more doors for innovation, since more people with more ideas can interact with the data, and more opportunities to innovate are likely to be found as a result.

Innovation happens in many different ways. It doesn’t makes sense to choose just one.

ABOUT FRANCOIS AJENSTAT//

Francois Ajenstat is Tableau Software’s chief product officer.