This article was first published in the February/March 2020 International edition of
Accounting and Business magazine.

Analytics is one of the hottest topics in finance today because of its potential to generate powerful insights that can transform how businesses operate.

With CFOs often taking the lead on the analytics agenda, the finance function has the opportunity to reinforce its role as strategic partner to the C-suite by helping to embed the use of the technology more broadly across the organisation.

Much of the current interest in analytics centres on its capacity to drive efficiencies, improve budgeting, planning and forecasting processes, and enhance risk management. Yet, as ACCA’s recent Accounting for the Future conference ( highlighted, analytics can also help businesses to perform better across a wide range of other operational areas, including product development, customer service, fraud detection and regulatory compliance.

Looking backwards and forwards

According to research by ACCA to be published later this year, the two types of analytics most commonly undertaken by organisations at present are descriptive analytics and diagnostic analytics. Descriptive analytics focuses on what happened in the past, while diagnostic analytics zeroes in on why it happened.

Nevertheless, the most successful businesses going forward will also use predictive analytics and prescriptive analytics. As its name suggests, predictive analytics is used to predict the likelihood of an event happening in the future. Prescriptive analytics is concerned with preparing for a particular event or to prevent that event from ever taking place.

Finance professionals can use these tools to help improve the overall performance of their organisation, from both a financial and a non-financial perspective. The tools facilitate faster and better decision-making across different business functions. In future, they are also likely to integrate external data, such as information on customer purchasing habits, and unstructured data, such as call centre recorded scripts.

While analytics presents many opportunities, adoption of the technology does not come without challenges. ACCA’s report, which is based on a survey of members, will indicate that most of the challenges relate to skills and data.

Lack of knowledge of technologies and solutions is the single biggest obstacle for finance teams looking to use analytics. The second-biggest challenge comes from data that exists in poor formats. Other hindrances include finding staff with data analytics skills, acquiring data from other departments and teams in the organisation, and the analysis of unstructured data.

‘The foundation of analytics is good enterprise-wide data,’ Simon Driscoll, practice lead for data and intelligence at IT services provider NTT Data UK, told the Accounting for the Future conference. Finance functions will only be able to use analytics tools to their full potential once their organisations have embraced the idea that data is a corporate asset and have implemented strategies to use it effectively. This means gathering trustworthy data from across the enterprise and storing it in usable, standardised formats. It also entails converting unstructured data into structured data.

Rise of the chief performance officer

Analytics tools effectively present finance with the opportunity to ‘create a single version of the truth’ that the entire organisation can work from. This truth will be derived from both financial and operational data, internal and external data, and structured and unstructured data. The role of the CFO, as the person responsible for delivering this truth, is likely to evolve into a broader role over time: that of chief performance officer.

For these developments to occur, organisations will need to abandon siloed ways of working, and functions will need to share information with each other. Finance professionals will also have to work hard at developing soft skills such as communication, influencing and storytelling, alongside harder technical skills relating to data analysis and interrogation.

Why do soft skills matter so much? Because finance professionals will need to persuade their peers in other functions to buy in to the use of analytics tools and to act on the insights they generate. These insights may well contradict long cherished beliefs and business practices. Any analytics implementation will invariably involve a considerable amount of culture change in an organisation. For it to be effective, people must first learn to trust the data that informs analytics tools; then they must learn to trust the outcomes of those tools and be willing to base their decision-making on them.

Ultimately, analytics cannot simply be something the finance function does; it has to be an enterprise-wide endeavour. Nevertheless, finance can take the lead in embracing the technology and helping the rest of the organisation to understand its vital role in driving future business success.

Sally Percy, journalist


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Biggest analytics challenges for finance teams

Lack of knowledge of existing technologies and solutions 40%
Data in poor formats 39%
Access to the right skills for analysing data 37%
Poor interdepartmental data sharing 34%
Analysing unstructured data 32%
Establishing a data-driven culture 30%
Too much data to deal with 29%
Integrating data technologies into existing tech landscape 28%
Access to the relevant data 28%
Identifying which data to collect and which data to use 26%
Unclear data ownership and governance structure in place 23%
No central data strategy 23%
Legal issues in relation to data access 16%
Executing business decisions from data insights provided 16%
No company leadership buy-in to data analytics 11%
Not sure 2%