• Nathaniel Spohn , General Manager of EMEA at Fivetran


• 14.09.2020 10:30 am
Business Intelligence

Business Intelligence (BI) tools are indispensable to modern financial operations. A recent Fivetran study conducted by Dimensional Research found that 98 percent of businesses are using BI solutions today, with finance teams being the second most reliant on them in their day-to-day operations, coming a close second only to data-obsessed marketing departments. What’s more, the research revealed that financial teams were in the pole position across the 500 organisations surveyed to be given access to BI tools in the year ahead.

It’s clear that as financial operations require ever faster and more precise data analytics, investments in BI will continue to rise. When done right, the value these tools deliver – from turning data into rapidly actionable insights to expediting data-driven decision-making – lead to streamlined business processes, customer-centric growth and a healthy bottom line.

The reality: Frustrated teams, wasted resources

The research did not stop there – in addition to tracking overall BI utilisation trends, Dimensional Research also investigated whether these tools were being used to their full potential or whether there was a danger that organisations were, at least to some extent, wasting their investments. 

Here, the answers are more mixed.

BI: Well-resourced but underutilised

More than two-thirds (68 percent) of the data analysts polled told researchers that, while they have ideas for driving more company profits, they lack the time to implement these more strategic initiatives. A key factor impacting their productivity is that the typical analyst spends just half their time on actual ‘analytics.’ The greatest drain on their productivity is the time they waste trying to access disparate data sets. This should be a relatively simple process, but can account for as much as a third of an analyst’s time alone.

Analysts voiced a number of other, inter-related frustrations. Nearly all (90 percent) complained that the data sources they need to do their jobs were sometimes unavailable, broken or only accessible on an intermittent basis. Unreliable data sources often lead to delays that have a wider impact on the overall business. Any lag in the process means analysts are required to generate reports and suggest decisions based on information that is out of date. 

Given the rapid change and upheaval that nearly every company has had to cope with during recent months because of Covid-19, it is hard to envisage aging financial data being used as the basis for accurate decisions. It’s worrying, therefore, that 86 percent of the respondents indicated they were sometimes forced to use ‘old’ data. Worse still, of these respondents, more than half admitted that their data was, on average, at least two months old. 

Furthermore, it only takes one data source to be unavailable for wider delays to occur, which is an important factor to consider as today’s analysts rely on many disparate data sources. Of those polled, the majority were juggling 11 or more different data sets, with 96 percent of firms drawing at least some of their information from cloud-based platforms. 

The survey also exposed another challenge around data schemas, which are the blueprints for how these data sources are constructed. With businesses continually changing their operational focus and constantly re-cutting their data in order to uncover new efficiencies and opportunities, these schemas are in perpetual flux, with more and more data sets added all the time. While this improves the accuracy of reporting and the decision-making process, for the analyst, these changes often equal more work and more delays. 60 percent of respondents report that schemas update on a monthly cycle. 

A lack of available engineering resources to support these updates compounds this problem. Data analysts are forced to take on tasks outside their job descriptions – and core expertise – in order to keep projects moving at the pace required by business leaders. For example, many find themselves creating financial reports in Excel because they cannot access the information they need via a dedicated dashboard. Others have had to code their own scripts in order to ingest new data streams.

Time for a rethink

While organisations are firmly committed to resourcing BI tools and the analyst teams that manage them, when you scratch below the surface, there are worrying signs that both the technology and the people with the necessary expertise to maximise its value are underutilised. Employing more experts may help – and is an approach some of the surveyed organisations intend to follow – but it won’t address the root problem that data can be hard to access, is often out of date, and hard to manage.

To drive more value from their investments, an organisation’s first priority should be to enable its existing analysts to spend more time ‘analysing’ and less time ‘finding.’ In practice, this means re-assessing their data pipelines to ensure they can extract data from multiple sources – including numerous cloud-based applications. This extraction must be in real-time, before the information is replicated, transformed and integrated into one coherent data set that can be instantly analysed and reported on.

This approach automates many of the mundane, peripheral tasks that today’s analysts are forced to do, updating schemas without the need for engineering intervention or creative work-arounds.

In short, businesses often have the right people and ambitions to make the best possible use of their financial data. Now they just need to find the tools required to unlock the value contained within this data.

Nathaniel Spohn is general manager of EMEA at automated data integration provider, Fivetran