Big data has meant chief financial officers are investing in smart software which can increase their effectiveness and standing with the board.
The explosion of data in companies has left many chief financial officers (CFOs) struggling to manage the information. The result has been a surge in finance chiefs implementing business intelligence and analytics tools to help them address the issue. But these tools bring many challenges and opportunities that are forcing CFOs to redefine their data strategies, skills and mindset.
Gartner forecasts global revenue in the business intelligence and analytics software market to grow from $18.3 billion in 2017 to $22.8 billion in 2020. Most of this (79 per cent) comes from CFOs as finance is the department that most often invests in analytics, according to Deloitte Touche Tohmatsu.
David Anderson, UK strategy and operation finance leader at Deloitte, says: “The exponential growth in analytics technologies is hitting finance and they are struggling to make sense of it, forcing CFOs to change their data strategies. We don’t expect them to become technologists, but they do need to be more tech savvy, adaptable and risk loving; a completely different mindset and profile of individual.”
But Johanna Robinson, managing vice president of finance research at Gartner, says business intelligence and analytics will enhance CFOs’ positions in their companies if they can harness the tools effectively.
“Smarter business intelligence tools and analytics can improve profits by supporting better operational decisions, more accurate investment evaluations, and faster identification of emerging risks and opportunities,” she says.
“These tools also create opportunities for finance to provide more specialist decision support. To achieve this, they will shift strategies from standard data-cleansing towards so-called master data management (MDM),” says Ms Robinson.
Smarter business intelligence tools and analytics can improve profits by supporting better operational decisions, more accurate investment evaluations, and faster identification of emerging risks and opportunities
This is an approach that defines and manages critical data to provide a single point of reference. It also makes the data more “analytics friendly”, she says.
Many CFOs are yet to realise these benefits as they face a range of obstacles. One of the biggest is upgrading multiple outdated and inflexible data structures.
Nadim Ahmad transformation director reporting to the CFO, at British Land is leading a project to improve the organisation’s business intelligence and data analysis systems.
“CFOs should lead on business intelligence and analytics as they are already attuned to managing and reporting large data sets,” says Mr Ahmad. “Economic uncertainty increases pressure on CFOs to provide faster and more meaningful data. They will have to invest and innovate to do this, and they will need technical help.
“My role is to help drive operational efficiency through quicker access to data, with decisions made in real time.”
This usually involves implementing new software systems and updating existing ones.
Businesses are moving away from a single enterprise resource planning (ERP) solution – the common approach in the 1990s and 2000s – towards more bespoke, best of breed software solutions.
Mr Ahmad’s first task has been to establish the number of systems and data entry points, and the quality of the data, people and processes involved; and to look at how the data moves, and how easy it is to extract, standardise and enhance.
“These will all determine how good your business intelligence can be,” says Mr Ahmad. “Businesses tend to have multiple systems and data sets, some outdated and not logically arranged, which makes it hard to implement current technologies. But there are ways to address this. We are using MDM, which means improving data governance and handling; and improving validation, extraction, cleansing and standardisation processes. Also, there are smart business intelligence tools that can sit over existing architecture and pull out data for reports. You don’t have to use the source.”
Improving infrastructure will make it easier to attach more sophisticated technologies such as artificial intelligence (AI), machine learning and predictive and prescriptive analytics tools. These will enable executives to make real-time decisions and model what will happen and how the organisation should act much more rapidly, says Mr Ahmad.
Italian multinational energy company Enel is on a similar journey. It started its data transformation three years ago with a full migration to the cloud using virtual data storage “lakes”, one for each division plus another linking all the lakes. CFO Alberto de Paoli says this created the framework for more sophisticated tools and Enel plans to spend a further €5.4 billion on digitisation over the next three years.
Mr de Paoli says his focus is less on developing the technology, more on helping the company become data driven by changing culture and leading by example.
“The CFO, HR manager and ICT manager share this transformation objective,” he says. “One obstacle is that [each department thinks they own] their specific data set. My first step was to make my financial data available to everyone in the company.
“Another obstacle is identifying where an algorithm can make more accurate measurements and decisions than experienced managers, and convincing people to trust that.
“To help, we have hired many specialists in analytics. For example, we are launching a digitised report, which analyses over 1,000 financial control objectives each month, all available via voice recognition.
“We don’t impose this technology on divisions. Instead we show how beneficial it can be, trying to create a ‘wow’ and a ‘me too’ reaction.”
Katy Dinnis, CFO of Palladium, an Australian group that helps clients in 90 countries link commercial goals with social impact, says the data explosion has added complexity for CFOs, but it also gives them better insight into new markets and opportunities. More real-time data gives them more opportunity to drive strategy throughout the organisation.
Developing data networks that enhance decision-making is one area where Palladium helps its clients, from data collection to warehousing, forecasting and modelling, so it uses these strategies internally.
But Ms Dinnis says the biggest challenge is that Palladium operates a decentralised structure of in-country data systems with one accounting system across the world.
“My strategy has had to adapt because many of those 90 countries are emerging economies where data isn’t necessarily digitised,” she says. “Global data collection is one challenge, opening that data across our complex systems poses another. Bedding down our global ERP system has been a priority. The next phase is to build user-friendly business intelligence reporting, ensuring consistent data, which allows the organisation to build on our decentralised structure.”
This will be a tough test for the finance team. But Ms Dinnis believes that, as business intelligence and advanced analytics tools evolve, they can achieve it.