Every business wants a ‘data culture’ — how do you make one stick?

What does enterprise-wide data culture look like? UK fintech Revolut maintains around 800 dashboards and runs around 100,000 SQL queries on a daily basis.
1 January 2021

Revolut leverages a data culture. Source: Shutterstock

Pretty much every business leader wants their organization to be ‘data-driven’ — and while it’s become a business buzzword, it’s really not a new concept. Since some of the oldest companies were formed (as we’d recognize them today), owners have sought to make the best decisions based on the market and business intelligence they have to hand.

In the digitized 21st century, we have so many means of gathering intelligence, and such an expanse of it, that identifying the data that matters to our businesses and utilizing it effectively to improve performance is the challenge.

The influx of information is so voluminous and complex that traditional analytics systems aren’t equipped to handle it and, according to a recent report by Seagate, 68% of data collected by businesses goes unleveraged. But if you don’t continuously respond to the demands of your customers, operational issues, or the conditions of the market, the company won’t stay afloat, or at least remain competitive, for long.

In fact, the strategic advantages of data management and analytics are such that it’s created new jobs and entire industries. From product development to production, distribution, marketing, and sales, data has become a key factor in many roles that previously depended on expertise and experience. And in the current pandemic, it’s providing certainty and confidence where usual bellwethers are lacking.

So, what’s stopping a culture of data analysis from taking root?

According to Mathias Golombek, CTO of Exasol, it stems from a combination of factors from the technology and infrastructure choices a company makes and the tools available to employees to internal politics and silos, where certain people hoard data.

But it also comes down to a lack of data literacy among every employee, who — if a business is to become data-driven — must be “proficient in working with, understanding, and communicating data effectively to help drive the business forward.”

Data literacy, Golombek said, is becoming an “essential skill” without which many of us won’t be doing our jobs to the best of our ability.

Data democratization

Exasol’s own data found that just 32% of data decision-makers said teams are able to extract the insights they need. Organizations often fail to realize they need to teach people to understand the value of data, he said.

The concept of “data democratization” gives employees at every level access to data insights that are relevant to their role, Golombek explained. This level of buy-in across an entire organization drives cultural change by turning data analytics into a day-to-day contributor to the business rather than a perceived business function.

As a result, employees make better-informed decisions and uncover new opportunities. Data democratization helps overcome resistance or misunderstanding of data analytics through active demonstration of its value.

Some 85% of organizations have claimed to be taking action to improve levels of data literacy within their business. “This reveals that businesses have a real appetite to help build data skills among their staff. The more exposure employees have to data, the quicker they can learn and contribute to the overall data culture and goal of becoming a data-driven organization,” said Golombek.

How do you democratize data within your business?

Data Centre of Excellence (CoE)

Firstly, you need to give employees the framework and support to integrate new tools and ways of thinking into their everyday work lives.

A Data Centre of Excellence (CoE) can offer this. Comprising supporting experts in the field of data analytics — often borrowing individuals from different departments as an interdisciplinary team — a CoE acts as a central pillar of data culture.

In the long run, the CoE will drive education around data and help employees to use the right data in the right way. As a result, decision-making improves across departments as reporting and analysis outputs become more reliable. Additionally, data teams will become more efficient in their data collection, refinement, consolidation, and delivery, and infrastructure teams can establish more advanced setups for the growing need for highly-performant data that can be accessed across the business.

Chief Data Officer (CDO)

Secondly, you can look to recruit a chief data officer (CDO) to shape and enact a data strategy that supports the data culture top-down. KPMG suggests that organizations with a CDO are twice as likely to have a clear digital strategy. The ongoing education of the organization’s workforce is a fundamental part of such a strategy.

The commitment of the CDO is to drive the business forward across the board, from revenue growth and advancing internal innovation to improving operational efficiency. Achieving these results relies on having the right skills in your people and triggering their imagination and innovative ideas. The CDO is one of the best-placed individuals to make knowledge of data an integral, normal part of the everyday life of an organization.

Even if you don’t employ a CDO, you will increasingly find you need someone— or a team of individuals— to drive initiatives with data and analytics in order to remain reactive and aware if it is going to keep pace with changing customer expectations, marketplace evolution and disruption, and the advancement of competitors.

The IT challenges to becoming data-driven

Getting buy-in from people in the business should be at the heart of a data strategy, but businesses must ensure IT infrastructure facilitates convenient enterprise-wide access when the data is needed.

When choosing the right deployment model organizations need to consider a variety of different factors. These include speed, cost, future requirements, and types of workload, such as prescriptive analytics, data science, and/or the data warehouse.

It’s important to make this decision after a data strategy is in place for businesses to fully evaluate whether on-premises or cloud is the right option for what they want to achieve.

“Often, flexibility is important for organizations, which means a flexible approach to cloud migration can be the most efficient,” Golombek said. “When you plan with choice in mind, organizations can manage sensitive workloads on-premises but also utilize the cloud, which is powerful when it comes to big volumes of data needing to get to big numbers of people in real-time.”

What does data culture look like in business? 

Just look at the surging, digital challengers disrupting established industries. UK fintech Revolut knows exactly how important data is to its success and reputation. The firm maintains around 800 dashboards and runs around 100,000 SQL queries on a daily basis across the organization.

Revolut can optimally analyze large datasets spanning several sources to assist in fraud detection, improving customer satisfaction and financial reporting. Queries that used to take hours are now completed in seconds, enabling self-serve data analytics for all employees across all business functions. This is despite data volumes increasing 20x over the past twelve months.

Behind this data culture is a mission to ensure everyone at Revolut has access to the data they need for their work, every day, in a simple and efficient manner. The data science teams uses the central database as a single point of truth, from which it can download real-time extracts and insights at any time.

This is just one example of a company that has built a culture of data literacy from the first instance, but it showcases the potential of making data analysis and intelligence central to the entire business and making it a day-to-day discipline.