Finance departments need to think through their use of data for maximum impact.
By Andrea Chipman
The advent of big data over the past two decades, along with the broader data revolution, has, in theory, made it easier than ever for corporate finance chiefs to support their financial and business strategies and decision-making processes with a comprehensive evidence base.
A recent report by US-based analytics software developer SAS observed that “data is no longer a by-product of business processing — it’s a critical asset that enables processing and decision-making.”
Yet, not all data are created equal, and getting the most strategic use of data points requires an in-depth understanding of not only what is being measured, but why.
We spoke to several data analytics experts to find out how they advise clients to best use the resources available to them. They offered a number of key points to be aware of when formulating a data strategy.
Don’t just look backward. One of the biggest pitfalls for using data to support corporate strategy is the tendency of companies to concentrate on metrics relating to past sales or results, rather than looking toward the future.
“You need to think about data as a driver for behaviour going forward, rather than making decisions based on looking back,” says Richard Hilton, a London-based managing director of Europe, the Middle East, and Africa (EMEA) for Miller Heiman Group, a sales training, research, and technology consultancy.
If a company makes reductions in its client services team based on first-quarter results, rather than concentrating on forward-looking data, it might create a scenario where it is always a quarter behind, he adds.
Improving access to real-time data can help sharpen forecasting and ensure that companies are targeting the right opportunities, he says.
Understand what you are measuring. Data analytics has the ability to give companies an advantage over rivals by helping them understand their business better and make better decisions about how to harness that power, says Andrew Moyser, a partner at UK accountancy firm MHA MacIntyre Hudson.
But it is crucial to choose the correct data, which entails understanding the company’s goals in the first place.
“Have a clear vision of what you want the desired impact to be,” Moyser says. “Sometimes you can collect data and start analysing it, but not be sure why you are doing that. You need to make sure the data source is right.”
One example of an area where more targeted use of data can help improve business outcomes is the cost of sales, Hilton says.
“The reason cost of sales can be excessive and can feel excessive is the inability for an organisation to truly qualify [its sales targets],” Hilton says. “They can chase an opportunity for an inordinate amount of time, suggesting that they are chasing the wrong organisation.” Similarly, he adds, CFOs will often look just at the cost base, rather than at the potential upside of a sales opportunity.
Prioritise data quality. Clearly, the most effective data are those of the highest quality, and improvement in the quality of data can lead to a virtuous circle, Hilton says. In-depth data on different market segments can help CFOs understand a product mix at a more nuanced level and not make the most obvious conclusions.
“Sales may be dominant in one particular product, but thinking that that’s what the market wants might not be the right answer,” he says. “It may mean that profitability is higher and sellers may be oriented to that product. It’s not just sales, but marketing and client services that can be impacted [by data].”
Sales managers should be considering how data can provide value back to the seller. Consequently, the collection of information from sellers should be more than just an administrative task, Hilton says. If companies are able to use analytics to make data valuable, they “will get to the point that their quality of data will improve, sales will improve, and the quality of business forecasts will improve”.
Make it accessible. Companies should make it easier for people across the business to work with data, says James Eiloart, senior vice-president for EMEA of Seattle-based software analytics company Tableau.
“One point is getting the data and the ability to ask questions of that data into the hands of the people who understand it the best,” he says. “At a lot of companies, people who understand the business really well don’t understand technology, or, conversely, tech specialists don’t understand the nuances of the data.”
In particular, he adds, data should be accessible enough and the technology intuitive enough to enable employees across the organisation to use it to answer questions “on the fly” at meetings.
At its best, the ability to confidently access accurate data can contribute to rapid and insightful decision-making in a business.
“Organisations we’ve seen be really successful are data driven at the boardroom and run all the way down the organisation,” Eiloart adds.
Standardise your data. In addition to choosing the right data, it’s important to know how to collect them and how to format and understand them, says Moyser, adding, “Sometimes it’s understanding it graphically, sometimes it’s looking at granular data or key performance indicators, but there are lots of ways to look at that data.”
A number of software tools can make it easier to both pull together multiple, disparate datasets and support visual analytics or building of dashboards.
“If that flow stops because you need data specialists, you have broken the mental flow and damaged productivity,” Eiloart says. At the same time, he also cautions against the tendency of some organisations to wait until they have a full spectrum of data before starting the analytics process.
Software can help aggregate data, making it easier for corporate strategies to look forward, whether it involves analysing where customers are based and seeing that visually on a map or plotting what times of day sales are made and who made them in graphic form.
“There is a lot of different data out there,” Moyser observes. “The mistake many companies make is just looking at the accounting data and other things that drive the finances. Sometimes it might be useful to look at external data such as weather in a seasonal business or social media.”
Similarly, he adds, the most forward-looking companies will aim to collect data for future use, even if it isn’t useful at the moment.
“Sometimes you might know you want data on a certain part of the business, but you don’t have the historics, so you need to start collecting them now in order to have six months of data,” he adds.
Andrea Chipman is a freelance writer based in the UK.
This article was originally published in Financial Management magazine.