If organizations are to improve transparency — to better anticipate the challenges of the future and to build stronger relationships of trust with the wider public — new and innovative approaches to accounting and reporting are likely needed.
More forward-looking, value-driven reporting
Nonfinancial data can help address this trust gap between current financial reporting and stakeholders’ expectations of reporting. An organization's ability to create long-term value is not always disclosed on balance sheets. Long-term value can grow out of an organization’s culture, intellectual assets, technology or infrastructure — all nonfinancial assets.
If stakeholders don’t have visibility of this value, their ability to make strategic decisions around business plans could be compromised. Likewise, if consumers can’t see how a business is behaving — for good or worse — they may not be inclined to trust it.
To close this gap between value and stakeholder oversight, organizations should get better at using all the data available to them, beyond financial data. This means deciding which nonfinancial data to measure, how to collect it and how to understand it.
Nonfinancial assets can include corporate culture, intellectual property, and key performance indicators (KPIs) of environment, social and governance (ESG). These and others are all potentially valuable nonfinancial assets that should be considered for inclusion in corporate reporting.
The space for smart technology
By its very nature, nonfinancial data is more ill-defined and more difficult to analyze using traditional tools and models, compared with traditional financial data. How do you factor customer loyalty, or corporate diversity, into earnings projections? How do you communicate this information to shareholders?
Forty-nine percent of survey respondents indicated that they actually spent more time gathering and processing data than they did analyzing it. If finance functions are to successfully implement a transformation of their function, to one that can incorporate nonfinancial data in their reporting, then a key part of that process will likely be the judicious application of smart technologies. These could include:
- Automation: Technologies, such as robotic process automation (RPA), free up human labor for more value-added tasks, such as defining and collecting nonfinancial data, or acting on insights derived by smart systems. Data then becomes a strategic asset rather than a burden that takes human capital away from high-value work. This work itself can involve more on-the-ground collection of nonfinancial KPIs or finding ways to communicate this information to the board.
- Artificial intelligence (AI): More advanced than RPA, AI can dig deep into complex sets of data and uncover value-driving insights. As data tools improve, they can move onto reading, managing and analyzing complex contracts and data, further liberating human talent. AI-enabled platforms and functions, such as biometrics and natural language processing software, can also help expand an organization’s ability to collect and make use of more diverse sources of nonfinancial data.
- Blockchain: By helping to secure reporting channels, blockchain can increase data transparency, and improve the speed and efficiency with which information can be communicated between functions and to external stakeholders. While no survey respondents indicated that blockchain was the most important technology in finance and reporting today, 24% of respondents think that it would be the most important technology in their role in the next five years. While blockchain is still considered less important than RPA (32%) and AI (44%), it is likely to become a central part of the reporting landscape.
Overcoming workforce and cultural barriers
Technology has significant potential to help organizations understand and deal with their financial and nonfinancial data. Thus, a more robust framework can be created for stakeholders — both internal and external — to engage with the organization.
Among the financial leaders surveyed, 72% said that AI alone will have a significant impact on how their function produces data-led insights, and 64% said that it had the ability to fundamentally disrupt the way finance and reporting are conducted.
However, there will likely be challenges to implementation of these technologies. As with any kind of digital transformation, security and data integrity will be concerns. Fifty-four percent of those surveyed mentioned concerns around data security as a major obstacle when implementing technology solutions in reporting and finance.
There are workforce and cultural issues as well, including the top-level leadership. Thirty percent of survey respondents cited a lack of buy-in from leadership and the board as an implementation challenge.
However, a larger problem is finding the right talent. In this EY survey, 41% of respondents said that a lack of relevant skills within the finance function was a major challenge.
Finance teams of the future will need the capabilities not just of traditional accountants, but of data scientists, analysts and statisticians. When asked, survey respondents indicated that the most important skill for prospective finance hires in the future is not going to be traditional accounting, which was ranked fifth. Instead, they said that it would be analytic capabilities.
Reporting teams may also altogether change the way they think about acquiring talent. Using third-party managed services may help give finance managers convenient, cost-efficient access to critical technical capabilities. Almost three-quarters of respondents indicated that such services would become a central part of their attempts to meet strategic priorities around the future of reporting.