The four building blocks of data excellence

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In the digital age, data is everywhere. Having large amounts of data is no longer an exception. According to Improven, what data excellence is really about is managing all this data well. According to Ramon van den Heuvel, partner at Improven, to have an integral focus on four areas.

Many organisations now know that there is a world of difference between having data and harnessing the value of data. Ramon van den Heuvel in practice, however, mostly sees organisations still struggling with how to extract the potential from data.

"Everyone now sees the importance of data-driven working, but actually doing it often turns out to be more difficult than thought," he indicates. "Organisations often implement a tool and think they can take a step in data maturity with it, but the basics are often not in order. "Getting the basics in order - that, then, is the credo for organisations that want to turn their data into value. But how do you do that? Van den Heuvel approaches this question from four key data themes: data governance, data quality, business intelligence & data science.

1: Data governance

First, data governance. "To achieve structural success with a data strategy, setting up data governance is indispensable," says Van den Heuvel. "Data governance ensures a better grip on the large amounts of data in the organisation."

"It involves understanding what data is out there and how it is secured so that it is accurate, reliable, secure and meaningful. It also ensures that data is used and processed ethically and in line with laws and regulations."

Ensuring this requires setting up processes, policies, standards, organisational structure and technologies in the right way, he explains. "Here, it is essential to include the organisational context as well, so that all these elements fit well with the organisation's ambition. In addition, to reduce the management burden, it is good to automate as much as possible."

2: Data quality

In addition to setting up data governance, it is important to pay sufficient attention to the quality of the data available in an organisation. Van den Heuvel: "Good data quality is prerequisite if an organisation wants to extract value from its data."

"Linking data from multiple sources can reveal relationships between cause and effect that may not have been known before."

He stresses that data quality is not an end in itself. "It is important that data is 'fit for purpose'. High-quality data reduces risks, lowers costs and improves organisational efficiency and productivity by eliminating the need to fix errors and making decisions based on correct data."

According to the partner, to ensure that the data is of the right quality, one of the important things to do is to establish kpi's so that data quality processes can be optimised and secured on that basis.

3: Business Intelligence

Through the establishment of data governance and a focus on data quality, the available data can ultimately be used to provide valuable insights that allow organisations to make the right decisions: business intelligence.

"With BI, business data is collected, analysed and reported in dashboards," Van den Heuvel explains. "Reporting focuses on what happened. Dashboards try to answer why something happened. Linking data from multiple sources can reveal relationships between cause and effect that may not have been known before."

Here, an important part of the added value also lies in the method of presentation. "Proper interaction and good design of visualisations are very important when designing dashboards."

4: Data Science

Finally, data science. While terms like business intelligence and data science may at first glance seem like different terms for roughly the same thing, Van den Heuvel emphasises that they do differ.

"Data science focuses more on future insights, making predictions as accurate as possible."

"Compared to business intelligence, data science focuses more on future insights, making predictions as accurate as possible. To do so, data scientists apply all kinds of programming skills, statistical expertise and sector and organisational knowledge," he explains. "In doing so, they use both structured and unstructured data."

Getting the value out of data

With the establishment of data governance, proper attention to data quality, the use of business intelligence and data science, you as an organisation are able to extract value from the available data, Van den Heuvel summarises.

"Having a data organisation in place including high-quality data management with reliable reports and insights offers many benefits," the partner states. "You can reduce management costs and risks, stay compliant and in control, increase productivity and make better decisions. In short: data can be used as a value-adding tool for the organisation."