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.