It’s common knowledge that data can separate the winners from the losers in business. According to McKinsey, companies that treat their data as a corporate asset grow revenues five times faster on average than companies that don’t. But it’s one thing to want to be a data-first business and quite another to actually build a robust and sustainable data culture which helps you get there.

A data culture is when everyone in the company is switched on to the potential of data. They use it, understand its potential and its limits, and embrace the notion that data enables rather than blocks progress. But this culture doesn’t develop by just saying you have it. Building a data culture is hard work, and ultimately most drivers come down to three key areas: people, strategy, and technology.

People

A strong data culture isn’t something that will appear overnight. It needs to be led from the top.

Rather than relying on gut instinct, business leaders and managers need to ask their teams to provide data to back up their decisions and recommendations. (As a smart leader once said: “Bring me data and I’ll consider it; bring me an opinion and we’ll go with mine.”) They need to encourage the use of data and provide the opportunities for individuals to further develop their understanding, skills, and capabilities involving data. Communication is key to this, and every email, meeting or presentation is an opportunity to share data-driven insights on performance, promote data-driven wins, and recognise data-driven employees.

Increasingly we’re seeing organisations employing a chief data officer to help enable this. The chief data officer can act as a steward within the business, focusing on long term strategy and planning and keeping the team up to date on new tools, techniques, and resources to help them make the most of the data they have. The officer can then work alongside data champions within each part of the business to increase data literacy and help drive change throughout the organisation.

Strategy

Establishing how you’re going to implement each stage of your data strategy is important. Leaders must not only look at the broad strokes of the decision to go data-first, but also address important data security and privacy questions too. How will data be stored? Who will be able to access the data and what permissions will they have? Deciding how transparent to make new processes is also important, and who will be able to provide feedback and initiate change. Fundamental to all this are what underlying technology platforms you decide to use. Making sure the least technologically savvy person is comfortable using the chosen systems will be the deciding vote of whether you’ve created a winning data culture.

Having a clear strategy that lays out answers to the key questions (how, what, when, where and why) should create a positive environment for a data-first organisation to thrive. Think about how the new strategy affects different teams, from the data scientists to marketing to HR. Everyone needs to understand why you’re implementing the strategy, why now, and what’s their role. It’s important that everyone has a baseline understanding of why data is important and what skills they’re going to need, use, and develop. How will a data-first strategy help them personally progress as well as improve the business as a whole? What training will the company offer to employees to make a data culture more than just a written manifesto?

Technology

Without data we wouldn’t have technology and without technology we wouldn’t have data. But for a data culture to thrive, organisations need to make sure that they invest in tools that will support data-driven results both now and in the future. The first part of doing this is removing silos.

It doesn’t matter how big or small your company is, there will be silos. A recent study from Skyhigh Networks found that the average enterprise has 91 cloud services in the marketing department alone, and 96 per cent of these are not connected to each other or anything else. So how can teams make data-driven decisions if the data they want to use is in disparate systems? By integrating all of the silos, you’re providing a complete, holistic, accurate view of the data across the business, ultimately enabling teams to make data-driven decisions with the whole picture in mind, instead of isolated pockets of disconnected information.

Machine learning can also help drive a data culture. By employing machine learning programs, businesses can enable teams to focus more time on understanding and utilising data to help make decisions, leaving machines to focus on the mundane repetitive tasks getting the data to a stage where it can be useful. Machine learning lets your organisation learn from data, identify patterns, and make recommendations, all automated with minimal human intervention, such that your team can quickly turn insights into action.

Evolving data culture

Ultimately if everyone in the organisation understands at a very top line level how data can help your business, then you’re already half way there. By supporting this with a defined, easily understandable data-first strategy and the right technology, you’ll be on track to creating a great data culture.

♣♣♣

Notes:

  • The post gives the views of its author(s), not the position of LSE Business Review or the London School of Economics.
  • Featured image credit: Photo by rawpixel on Unsplash
  • When you leave a comment, you’re agreeing to our Comment Policy.

Gaurav Dhillon is the chairman and chief executive officer of SnapLogic, overseeing the company’s strategy, operations, financing and partnerships. Dhillon is an experienced builder of technology companies. He advocates the use of simpler, faster, and more economic ways to integrate data and applications to improve decision-making and outcomes. As the co-founder and former chief executive of Informatica, he guided it through a successful initial public offering and global expansion to become a market leader.