Traditionally, accounting systems have focused on the rear-view mirror, capturing information about economic transactions that have occurred. Now, however, digital data can point to future economic exchanges. Al Bhimani writes that, if accountants are to retain their usefulness, rather than recording retrospective insights, they must report on predictive insights based on data analysis that is much wider than what accounting information systems have been set up to do.
The relationship currently evolving between digital technologies and financial information is the biggest transformation in the history of business decision-making. When businesses were adopting computer technologies last century, innovations in accounting emerged. Tools such as target cost management, activity-based costing, cost of quality reports, and the balanced scorecard started to be advocated by financial managers, scholars, and consultants to help managers steer increasingly complex business environments. The focus was on new metrics and indicators. The evolution of digitalisation today is entirely different: it enables decision-makers to visualise what they could not have conceptualised or understood about their business. Digitalisation means more data that can help enterprises think up novel products, new services, and operational innovations. But to achieve this, financial intelligence producers must face up to the need for change.
Data that is considered important is not what it used to be. Three trends are ongoing. First, accounting systems capture information about economic transactions that have occurred, but digital data can point to economic exchanges to come. The finance professional needs to veer toward reporting predictive insights based on data analysis that is much wider than what accounting information systems have been set up to do. Business decision-makers require pointers to what’s coming, not recapitulations of where they’ve been. If accountants are to retain their usefulness, they will need to learn to read the signs and directions which digital data reveal.
Second, accountants must consider how digital data are sourced because this will change their work. For instance, some digital technologies are becoming part of products as ID tags and IoT devices. This turns products into data gathering devices themselves instead of just products trailed by financial information capture. Accountants will need to unravel new insights from information emitted by products which are themselves becoming information systems. Likewise, blockchain applications can provide assurance of transactional legitimacy while also recording transactions. This is altering the raison d’etre of audits.
Third, with new data forms come new responsibilities. Accounting professionals cannot be disengaged from data concerns such as ethics and transparency requirements, and data privacy regulations. And they must understand novel workforce patterns. Within ten years, two-thirds of employees will be millennials or Generation Z (people born in the mid-90s). There is a mismatch if they are to use accounting and control systems which were designed over three decades ago. Millennials and Generation Z-ers have different views on what good information should look like. If they favour more open communication, uphold different ethical priorities, and like direct engagement with customers, then financial controls which prioritise more conventional priorities will have to catch up.
Greater women participation, especially at more senior levels, brings different sensitivities, proclivities, and value creation ideas to enterprises. Their information needs will deviate from established norms. Additionally, digitalisation makes machines more involved in human-less decision-making. This crowds out the need for specific information formats and reporting since machines, unlike human decision-makers, do not need information that is pre-structured in specific ways. Accountants will have to learn to accommodate to different information user needs.
Digitalisation is creating a multitude of novel challenges for the finance function which must force a re-think of what the interface between digitalisation and financial management should look like. Of relevance is that as organisations become more reliant on digital technologies, the traditional ways in which accounting has brought quantified measures and calculated metrics to the management table needs to be questioned. Data-driven management in a world profuse with data no doubt has a continued role to play. But more than ever, numbers should not trump qualitative insight. Decision-making today requires more rather than less qualitative input from accountants when businesses go digital. Digitalisation enhances the possibilities for numerical analysis, but this must be viewed as a call for more rather than less qualitative input.
- This blog post expresses the views of its author(s), and do not necessarily represent those of LSE Business Review or the London School of Economics.
- Featured image by geralt, under a Pixabay licence
- When you leave a comment, you’re agreeing to our Comment Policy
When the author says “The finance professional needs to veer toward reporting predictive insights based on data analysis that is much wider than what accounting information systems have been set up to do”, I totally agree. In fact the computation of expected credit loss as per IFRS 9 is also a case in point. ECL is based on predictive model and it has proved to be extremely useful in identifying any upcoming crisis as the macro economic data with a multivariate regression would have already unravelled this.