What exactly is a data-driven organization?

Understanding what makes a data-driven business is essential for any company wishing to remain relevant over the next decade.

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The use of data by organizations to improve the efficiency of their operations and drive innovation is nothing new. Since the early 20th century, companies have been applying “scientific” management techniques to get more from their assets, both physical and human. However, the last decade has seen the rise of new tools and techniques as well as new sources and forms of data that are changing the landscape for business planning and innovation.

Analysts at Forrester Research have identified a new type of organization, the insights-driven business, which they claim are growing at an average of more than 30% annually and are on track to earn $1.8 trillion by 2021. Similar research from other consulting firms highlights the emergence of firms that are dominating their sectors as well as creating new markets by generating actionable insights through data collection and analytics.

For business leaders, a key question is what are the defining characteristics of data-driven businesses and what can companies do to catch up with the leaders?

Embedding a data culture

At the heart of any data-driven organization is the internal culture of the business with respect to the way it views and acts upon data. This has to come from the top and permeate down through the business. Research shows that treating data as a resource only relevant to specific parts of a firm for the creation of reports or strategic planning will limit the potential for developing insights that can feed into innovation and new product development.

A recent interview with the CEO of rapidly growing ecommerce start-up ShopRunner highlights the importance of a top-down approach to building a data culture. This starts with their recruitment process where they ask interviewees, “How have you used data in the past to make decisions?”

Research from McKinsey supports the notion that engaging in data analytics for its own sake is not going to move the needle. At the heart of all this activity needs to be the objective of making better decisions. This requires data to be made available to everyone in the organisation who needs it as well as the tools to analyse it. Evidence from global businesses such as Boeing and Maersk show that when employees have better access to data then new ideas will emerge and operating improvements made.

Improving data literacy

Of course, without the right training and access to tools, it is foolish to expect employees who are not data scientists to derive insights from data. This is where a data literate workforce is vital to unleash the creativity that lies untapped in many organizations. According to Gartner, a Chief Data Officer (CDO) may be the best person to manage this process and they believe that by the end of this year, 80% of organizations will be implementing data literacy programs. We are entering a new era of competition that is similar to that experienced by businesses in the 1980s when the personal computing revolution required massive training initiatives to bring an analogue workforce into the digital age. Computing technologies are now pervasive and embedded in virtually all organizations. Firms that train their employees to better manage and analyse the data flowing through their machines will have the edge over competitors that don’t.

The challenge for incumbents

In the personal computing revolution of the 1980s, larger established businesses often had an advantage as they could draw on better financial resources to buy and install expensive hardware and software. Today, computing technologies have become commoditized and are readily available to even the smallest company. Similarly, data has never been so pervasive, often from freely available public sources.

While larger companies can often draw on massive sets of operational data, they may lack the culture and dexterity to take meaningful and rapid action on the basis of that data. Start-ups and new entrants that build business models directly on the back of data are frequently able to outmanoeuvre industry incumbents. The challenge of changing company cultures and increasing the data literacy of the workforce comes to the fore amongst large businesses in these scenarios. The rise of increasingly accessible AI and ML applications and solutions will only hasten this trend.

Data, data everywhere

In 1987, the economist Robert Solow famously quipped that, "You can see the computer age everywhere but in the productivity statistics.” He was pointing to the fact that despite several decades of massive investments in computing technologies, the average productivity of most developed economies had not risen in any significant way.

It is possible, of course, that a similar pattern may emerge with the rise of data-driven organizations; simply having access to more data may not improve national productivity. The Harvard Business Review recently reported on research that showed slow progress amongst large US corporations in implementing data-driven strategies. This is despite large investments by the same companies in the technologies and resources to facilitate such developments.

However, any company concluding from this research that not investing in creating a data-driven culture might be a sensible approach would be making a grave mistake. Like it or not, the firms taking market leadership positions over the next decade will be those using data in creative and innovative ways to drive their innovation programs and out-perform their competitors.

Just as no corporation could resist the rise of the computer or the internet and survive for very long, no business will be able to ignore embedding data at the heart of their operations and remain profitable.

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