Modern businesses run on data. From helping organizations to run more efficiently to creating new customer experiences and exploiting emerging technologies like artificial intelligence (AI), your enterprise needs to put data at the heart of its operational processes.
In a digital age, where companies succeed or fail due to their ability to draw insight from information, your organization must have a culture that allows people to feel confident with data. Three business leaders explain how you can create that culture.
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1. Make a plan for transformation
Sophie Gallay, global data and client IT director at French retailer Etam, said creating the right data culture involves three elements.
The first element is ensuring people in the business know how to use data in their day-to-day activities. “The most important part of my job isn’t dealing with data foundations and use cases, it’s supporting the business teams in understanding how they use this data in their processes,” she said.
Gallay told ZDNET that building comprehension of the importance of data requires a dedicated plan. “Culture is often the last point in the roadmap. Too often, it’s the cherry on the cake. People say, ‘If we have time and money, maybe we’ll do some training.’ But most of the time, you should start with culture,” she said.
“When you say you want your organization to be data-driven, it’s important not to focus too much on the ‘data’ part and focus more on the ‘driven’ part.”
Gallay said the second element is having data champions within line-of-business teams. “You can’t enforce cultural change from the IT team. Your organization needs representatives within the business teams and then your data culture needs to infuse almost organically,” she said. “Therefore, it’s important to choose the right champions. You then need to back these champions and ensure they have the right support in their business teams.”
Gallay said the third element is senior-level sponsorship. Business and digital leaders can’t force change — they need encouragement from their bosses.
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“The executive committee must support this data-led transformation and all the initiatives that go with it. If you have managers and directors who are not aligned, the transversal transformation won’t happen,” she said. “This senior-level backing is not purely about politics. It’s super-important to have the executive committee with you and to make sure they enforce your transformation in a top-down way through their dedicated business strategy.”
2. Develop minimum viable products
Richard Wazacz, CEO of foreign exchange specialist Travelex, said there’s a lot of talk in the IT industry about how companies can make the most of data lakes. He takes a different approach and prefers to build puddles.
“Start small, prove what you can do, build up confidence and maturity in your organization, and take on bigger and bigger problems,” he said. Wazacz told ZDNET that each data puddle should be associated with a specific business challenge. Once this solution is proven, you can move on to larger concerns.
“Get the confidence that your puddles are helping you,” he said. “There’s always a correlation and a way that one dataset can help you understand another. Then, in time, some of your ponds can be joined up to make small lakes and then you can create a bigger lake.”
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Wazacz said his approach is about developing minimum viable products (MVPs).
“Test, fail, learn,” he said. “Your puddles are your MVPs — create lots of puddles. Some puddles will dry up quickly because you were wrong. So, don’t build a lake straightaway — you will get it wrong and waste lots of money doing it.” This incremental approach helps people across the business see the value of information.
Rather than putting a data champion in every business function, Wazacz advised other business leaders to foster a realistic approach where you “prove the value of data through action.”
He said these proof points are important because the hardest part of building a data culture involves people, not technology.
“Identify a couple of colleagues in the business who have the competency and capability to play with puddles and make them valuable. Then you’ll find more people and there is a bit of osmosis,” he said. “People will say, ‘That puddle made that guy successful. Maybe I’ll try and build a small puddle.’ It’s an approach that takes time. If you try and waterboard everyone in data, and hope they’ll all love data, it never works.”
3. Use technology as an enabler
Nic Granger, director of corporate and CFO at North Sea Transition Authority (NSTA), said more people now understand the potential power of data.
“People hear about AI and machine learning, it sounds interesting, and they want to talk about it,” she said.
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However, this new awareness doesn’t mean a strong data culture is a given. Granger told ZDNET the finer details of data governance could be a turn-off for people excited about AI.
“If you talk about data management and records, it sounds like you’re talking about paper in a filing cabinet,” she said. “I think the important thing — and we do this on our side — is getting people across the organization to understand that you can’t do the fancy things that you want to do with AI and machine learning until you’ve sorted your house out on the data side.”
Granger told ZDNET her efforts to build a data culture are crucial to her digital strategy. Like other business leaders, she said systems and services are just one component of a data culture — and the key to success is your people.
“We start with people skills and culture because the technology isn’t going to be the solution to things — it’s an enabler to the solution,” she said. “So, having the right digital skills, the culture, and the right people in the team is the first pillar.”
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Granger said she’s worked hard to build the right data foundations, including creating an internal Digital Academy, which allows professionals to pick up digital skills and signposts the right places to learn. “If you want to learn Power BI, the Academy will point you towards the right courses,” she said.
While professionals hone their digital skills, Granger and her team identify areas where technology can be used to transform data access. “Some of the stuff we’ve been talking about includes creating a data warehouse in-house so that our colleagues in data analytics can access the right information to put together benchmarks and do some deep analytical work.”
