Can Data Drive Finance Departments?

Andy Botrill, VP EMEA of BlackLine, delves into the key questions that finance departments need to address in order to become truly data-driven.

Digital transformation: from buzzword to reality

Business’ biggest buzzword, digital transformation, has taken the technology world by storm. Despite being around since the 1990s, it has recently become a term that permeates almost every business strategy or vision for the future. Today, every technology provider claims it can enable digital transformation, and all well-informed CEOs are mandating it to drive their business forward.

The key to unlocking this business growth starts with technology’s second-biggest buzzword: data.

Barriers to a data-driven digital transformation

While data may be ‘the new oil’, an uncontrollable explosion of unrefined data doesn’t add any value to a business. You must be able to sort, process and examine data, view it from different angles and understand how to extract intelligent insights from it. To do this, having the right infrastructure in place is key. Indeed, large businesses in particular often struggle with legacy systems that aren’t designed to handle the volume of data we now produce and consume.

For finance departments, reliance on outdated technology is certainly part of the problem, but there are also other issues that need to be addressed. A recent BlackLine survey examining attitudes to financial data revealed that the C-suite’s top perceived challenge was that data was from too many sources and there was uncertainty over whether it was all being accounted for. Over a quarter of C-suite executives and finance professionals (28%) claimed that there were not enough automated controls and checks for the volume of data they had to deal with and that the process of collecting and processing the data was too complex (also 28%).

The key to unlocking this business growth starts with technology’s second-biggest buzzword: data.

So, what steps can finance professionals take to address these challenges? And what questions should finance departments ask as part of their quest to become truly data-driven?

Asses your data foundation

The vital first step for any transformation journey is to assess how far along the road you’ve already travelled. It might seem obvious that real-time access to accurate, reliable data – including financial data – can be used for strategic analysis and to create a competitive edge. But what may be less obvious is how damaging it can be to base this analysis on poor quality, unstructured or untrustworthy data.

According to BlackLine’s survey results, almost seven in 10 respondents believed that either they themselves or their CEO had made a significant business decision based on out-of-date or incorrect financial data. Not only can tapping into poor data compromise the decisions you make, but it can also seriously hamper your organisation’s ability to transform longer-term.

Is your data accurate?

With this in mind, the first question any organisation or department should consider is whether the data they do have is accurate. Is there real confidence in the precision of your data; can you be confident in the decisions you make from it? If there are inaccuracies, where are they coming from, and what processes or controls can you put in place to improve this?

The first question any organisation or department should consider is whether the data they do have is accurate.

In the finance department, clunky spreadsheets and outdated processes often leave finance teams in the dark until month-end, resulting in rushed work, manual workarounds and an increased risk of human error. By automating manual, predicable and repeatable processes, such as transaction matching or journal entries, data not only becomes more reliable but time is also freed up for more valuable work.

Is your data expansive and up-to-date?

Once you are comfortable that manual tasks have been automated, and are confident in the data being used to drive decisions, the next thing to consider is whether your data sets are expansive enough for intelligent analysis. Having a foundation of clean, relevant data is fantastic, but there must be enough of it to reliably answer pressing business questions.

At the same time, it’s vital to examine whether the data you do have access to is actually up-to-date. After all, why use data that is a month old to make decisions now? Continuous accounting, for example, which shifts the finance department from a monthly to a near real-time data cycle, makes it easier to deliver forward-looking, strategic insights that benefit the rest of the business.

Is today’s data ready for tomorrow’s demands?

Finally, finance departments need to ask whether the data foundations they are building today will be fit for purpose tomorrow. Much of this comes down to a question of trust: do you trust the processes you have in place to deliver data that is accurate, reliable, scalable and usable – not only now, but also in the long run?

Finance departments are bracing themselves for further technological disruption. A lack of trust in your data today not only has implications for human decision making, but it could also impact technology that learns from this data further down the line. While truly intelligent technology, like AI, may not be a reality for the finance department just yet, establishing its data integrity now will ensure it is ready for these advances when they do arise.


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