Digital Finance – Hanging on to the cutting edge

Digital is the perennial transformation buzzword in Finance. Whether it be controls enhancements in the 00’s, automation post-2008 or Artificial Intelligence and commercial analytics in recent years, Finance teams are continuously implementing ‘the next big thing’.

Despite this, many CFOs feel the rapid pace of technological change can make it feel like the needle never moves.

But this is no excuse to give up. Adopting new digital technologies is key to ensuring that organisations can continue to compete, and effectively meet business stakeholder demands. The challenge is to prioritise and focus on the highest-value areas, whilst acknowledging and putting in place a strategy to overcome the most common challenges.

So what high value outcomes Finance should focus on?

• Real-time actuals reporting – Automation and acceleration of close processes has been central to Finance transformation for the last decade, and stakeholder expectations regarding speed of turnaround for information and insights continue to increase. This is leading to a push for hyper-automation (progressing to automated judgement and process orchestration) in many Finance functions. As actuals and forecasts move closer to instantaneous production, traditional cycles will become increasingly less relevant.
• Self-service – Not all business users need handholding for every piece of financial information. Finance functions are automating activities ranging from report production to budget queries, allowing business teams to access the financial MI they require as and when they need it, freeing up Finance teams to focus on more complex analytics, insight and business partnering. The goal is to replace data in spreadsheets with visually rich, user-configurable dashboards that are fully accessible and easy to use.
• Enhanced forecasting, planning and business analytics – With substantial portions of traditional financial accounting processes already automated, the focus of technology vendors has shifted to supporting Finance experts to add value. Finance functions should look to analytics and AI tools that can help support decision making through rapid forecasting, scenario analysis, and provision of automated insight, that create better, faster insight for decision makers.

Despite many organisations having identified – and pursued – these priorities, implementing them is not easy. As a result, actual delivery is often delayed or deprioritised as stakeholders become frustrated with the time and cost to implement. In our experience, these are the most common blockers to change, and how Finance functions can overcome them:

• Securing funding for discretionary spend – Regulatory and statutory requirements will always trump technological enhancements when it comes to securing budget. As most of the current technological trends are perceived as ‘nice to have’, they often fall prey to funding cuts. Finance need to articulate a compelling case as to how new technologies can improve the bottom line to demonstrate return on investment and secure business sponsorship.
• Lack of digital skills – Finance’s skills needs are evolving fast, with emphasis shifting away from the traditional accountant towards data scientists and business analysts, a dramatic change for many organisations. Indeed, many finance leaders report a shortage of technology-based competencies in existing teams, and difficulty securing talent in the market. Teams should adopt a two-prong approach; identifying and sponsoring existing team members who can be upskilled in-house, and long-term recruiting in line with their anticipated mid-term need.
• Risk averse culture – The nature of traditional Finance work means an eye for accuracy in most areas is key. However new technologies are increasingly focused on directional and indicative analysis to support rapid decision making. Risk aversion and an obsession with precision can overcomplicate implementations and reduce value in BAU. Finance need to challenge themselves more thoroughly as to what constitutes ‘good enough’, and ensure perfect does not become the enemy of good.
• Poor data infrastructure – Every Finance function knows that no matter the front-end solution, being able to integrate the right data is often a huge programme of work itself. This is particularly acute for Finance, as input data comes from across all areas of the organisation, based on a variety of data models. Sadly, no silver bullet exists to solve these challenges. Whilst automation can make transforming and moving data between systems easier, the need to ensure robust manual inputs, change control database updates and apply good data governance cannot be skipped over. Finance teams must work closely with their CDO teams to ensure robust financial data governance is in place, and secure buy-in to remediate source data and move towards standardised data models wherever possible.

Rapid technological change coupled with the challenges listed above are daunting; but this does not mean CFOs should give up on digital.

What may feel like an eternal game of playing catch up is nevertheless still driving substantial progress., Furthermore, by taking the right actions now Finance leaders can help ease the implementation process in the future: focus on business benefit when securing funding, build a pipeline of talent ready to embrace digital, learn when good is good enough, and remediate data issues wherever possible.

The Finance teams that succeed in the coming years will be those that embrace continuous change; not those who shirk from it.