An exponential increase in business data, mixed with emerging analytics capabilities, has created a huge opportunity for finance to take center stage in the creation of the data-driven enterprise. Yet, against the backdrop of a global pandemic, a recent study by Harvard Business Review Analytic Services, sponsored by Workday, found a wide gap between finance leaders’ vision of the future and where the function really exists today.
While a vast proportion of finance executives believe instilling a culture of data-driven decision making is critical to the function’s future performance, only a slim majority said bringing such a culture to life is a high priority for senior leaders.
The global survey of 162 finance managers and senior executives reveals significant conflicts between finance executives’ aspirations and how they do their day-to-day work. A large majority state that the creation of a flexible data hub is critical to future performance, but most say they still rely on manual processes to collect and use their data. The report was emphatic in its finding that most finance teams have far to go on the road to data and analytics maturity.
Information explosion driving analysis paralysis
As the volume of both finance- and nonfinance-related data flowing through the business increases, the function’s ability to manage data and associated processes more effectively has never been more important. Ninety percent of respondents say the volume of data collected and used by the finance team has increased somewhat or significantly over the past two years.
Yet many finance leaders are struggling to process such huge volumes of data. The study found that the top three challenges for finance teams in handling data are accurately preparing, reconciling, and accessing high volumes of information (68%); integrating recent or real-time data into analyses (55%); and analyzing data, forming recommendations, and communicating them (52%.)
Data diversity requires emerging tools and technologies
As the role of the CFO broadens and the business requires a more real-time view, the finance function requires more analysis and a deeper understanding of business performance. The need for finance to use nonfinancial data from other areas of the business to drive strategic decision making across the enterprise also becomes increasingly crucial. In fact, nearly two-thirds of survey respondents say they make significant use of data from nonfinance departments to generate insights. In addition, 64% of respondents report that their teams use data from other parts of the organization to generate insights.
However, it was clear from the research that there’s work to do in embracing the tools and technologies to analyze diverse data types efficiently. The report found that only 37% say their teams assign a high or very high priority to leveraging a flexible data hub that can accommodate multiple data types, including data from different departments (16% marking it as a very high priority). Similarly, 49% of respondents rate investing in technology and tools to support analysis and data management as a high or very high priority for their teams (20% marking it as a very high priority).
Legacy technology and manual processes prevent progress
Given today’s technology capabilities, it seems unthinkable that more finance teams lean on manual processes to analyze their data than use data analytics tools to help inform their decisions. Yet more than three-quarters (77%) of respondents report relying a lot or a fair amount on labor-intensive manual processes to collect and use data, while a smaller majority (62%) use data analytics tools or platforms a lot or a fair amount to help inform finance decisions.
Most finance teams share their data-derived insights with senior company executives as well as with teams and executives elsewhere in the organization and transmit them using last century’s technologies. The vast majority (84%) say the finance team shares information and insights by emailing spreadsheets or slides to other teams. Regular meetings are the next most-used delivery medium (65%). Fifty-one percent share data via dashboards, and roughly a quarter (28%) use collaboration software or platforms other than dashboards.
Finance leaders: data confidence falls short
In previous articles, we looked at the attributes of a decision-ready organization, including the ability to have confidence in data. A majority of respondents are reasonably confident in the timeliness and accuracy of the data their finance team uses to support business decisions today, but much fewer are very confident. Fifty-nine percent rate their confidence in their data a 4 or 5 on a 5-point scale, with 14% rating their confidence a 5 and 45% rating it a 4. Forty-one percent are not confident, rating themselves a 3 or lower.
These challenges are not surprising given that, for most finance organizations, the use of artificial intelligence (AI) and machine learning/predictive analytics remains at the aspirational stage today. Less than a third (29%) of respondents rate their finance teams’ use of AI, machine learning, and/or predictive analytics in their day-to-day activities a 3, 4, or 5 on a 5-point usage scale, with 5 defined as employing these to a great extent. Thirty-three percent say their finance teams don’t use those technologies at all today.
The road ahead: A laser focus on aata
While there’s still much to do in building the data-driven enterprise, developing a data-driven culture in finance is clearly a key priority for senior executives. Nearly 9 in 10 (88%) respondents say fostering a data-driven culture in the finance function will be critical or very critical to the finance team’s future performance. A similar percentage (89%) says the use of analytics and data-driven decision making will be critical or very critical to future performance.
To do this effectively, finance leaders know they must prioritize their strategic investments, with a majority planning to invest heavily in their analytics capabilities. Over half (58%) of finance teams plan to adopt or increase their use of integrated planning, analytics, and forecasting systems to strengthen their analytics capabilities, and 53% plan to adopt or increase their use of a data analytics hub that consolidates financial and operational data. Four in 10 plan to adopt or increase their use of automated data collection and cleansing application programming interfaces to exchange data between different tools and/or allow for tighter data integration. And 36% plan to adopt or increase their use of a centralized accounting engine. A tiny number of respondents, only 5%, said they didn’t plan on adopting or increasing use of any digital tools within the next two years.
As innovation continues to bring new opportunities to the finance function, it’s perhaps unsurprising that execs predict the need to rapidly develop their teams’ AI and machine learning/predictive analytics capabilities. Seventy-two percent of respondents say their finance teams will use AI, machine learning, and/or predictive analytics to some or a great extent (3, 4, or 5 on a 5-point usage scale) in their day-to-day activities in the next three years. In terms of how much work there is to do, that percentage is a 43-point jump from where things stand today.
Finance leaders recognize they must shift their priorities and embrace new technologies if they are to successfully create the data-driven culture they need to be truly effective. Data will continue to flow, and the C-suite will look to finance to analyze and effectively join the dots across an increasingly diverse set of data. Time will tell if their ability to act meets their ambition, but CFOs and senior leaders have an opportunity to increase the strategic impact of finance across the enterprise.