Last year, a move to remote working triggered a seismic shift in how businesses maintain operational productivity, particularly its finance segment. Digital processes became increasingly present with more finance departments leaning on AI’s power to make data-driven decisions and gain a sustained advantage.
Six months into 2021, digital transformation is still an ongoing, slow-moving process that hasn’t been fully embraced by CFOs. Traditional financial reporting solutions like the ever-present Excel still play a significant role in a world where cloud-based systems efficiently and at scale fulfill demands for speed and transparency in financial reporting.
In other words, businesses are lagging.
Long turnaround times when creating reports, no predictive insights, and potentially costly error-prone manual entry all add friction and processing time to what should be a largely automated operation. At least, in theory.
The reality is a bit different. To get ahead in this AI-led present and future, there needs to be an accelerated adoption of new technology across their entire organization. Here are two critical ways businesses can act now to not fall behind and grow faster.
Don’t ditch Excel - AI it
Excel has a lot of staying power. Microsoft was smart to listen to customer demands over the years and evolve the iconic software to support more functionality. Whether it’s for budgeting, forecasting, or analysis purposes, to name a few, Excel can rise up to the challenge.
However, this financial workhorse also has limits to what it can and can’t do well. Regardless of their size, businesses need to be able to automatically extract their financial data from multiple cloud sources and utilize more advanced data analytics. After three and a half decades of delighting financial executives, Excel is struggling to meet those norms.
A lot of data is fragmented and decentralized across various systems, and Excel is a largely siloed software. Despite the option to create automated reports and its role as a collection point for data from other systems, it can’t efficiently handle massive data sets. When you add the cut-and-paste input method and finite collaboration capabilities, it’s clear where and how the lags are happening.
With such a long and deeply embedded history of use, expecting finance teams to switch from Excel to another flashier solution will almost certainly disrupt the entire workflow. Plus, it’s inexpensive and relatively easy for novice users to pick up, at least when it comes to its basic functions.
Hence, integration with a financial planning and analysis (FP&A) provider makes the most sense.
Platforms such as DataRails are a great example of the best of both worlds merged together. They automate existing Excel-based processes by leveraging existing models and templates to generate a unified database. On one side, you have the accessibility, legacy report compatibility and versatility of Excel and on the other, all the advantages of a cloud-based database and online dashboard powered by AI algorithms.
“Unlike sales and marketing departments, the processes in finance departments have been pretty much stagnant in the past 30 years and are still being conducted manually with Excel,” said Didi Gurfinkel, founder and CEO of DataRails.
“That’s why we developed a technology that runs the Excel-based organizational processes in a transparent manner and completely automates the monthly and quarterly financial processes.”
For instance, period-end reporting is far easier when managed through system functions within familiar Excel spreadsheets. By relying on automated consolidation functions, there is a significant cut down on time spent extracting the company’s financial performance, as well as more accurate results at a lower cost and improved data control that allows for better decision-making.
Put differently, businesses get a predictive AI layer atop Excel, directly plugging in advanced capabilities. As the end result, CFOs get to stay in love with their spreadsheets and deliver more precise and understandable performance information to company stakeholders. At the same time, they’re retaining flexibility and adaptability to a changing environment.
Unify cross-organizational real-time data for comprehensive analysis
Automation is a major step in the broader AI adoption that also lends a hand to increased data visibility across the business. Handling multiple data sources in spreadsheets historically takes a great deal of time.
Without uniform access in real-time, the entire process is often poorly executed as financial reports tend to be incomplete and inaccurate, even irrelevant in some cases. As a result, they don’t contain decision‐useful information.
AI collects structured and unstructured spreadsheet data and turns it into a centralized database, essentially mashing together disparate data sources.
With its data centralized, a business can perform real-time allocation tracking, for example, in order to understand all the expenses that go into a specific business activity.
Some FP&A platforms can integrate with other mission-critical platforms such as CRM, ERP, and inventory management systems, housing all the financial data under one roof. In addition, platforms with Excel as a front-end interface can sync with virtually any tool capable of exporting data as a CSV file.
This not only broadens the options for CFOs in terms of data manipulation but also offers full-scale granularity and the ability to generate reports on the fly according to specific needs.
They can collect huge, diverse data sets in a more comprehensive manner and analyze them quickly. Thus, finance moves closer to standardization, where data is collected and updated on a routine basis, and most importantly - made readily available whenever the situation requires it with interactive and embeddable visualizations.
You can love it, hate it, or have a passive-aggressive love-hate relationship with it but the fact is, Excel is here to stay.
Another fact is that advanced financial planning and analysis tools are encroaching on its territory with their potent combo of database capabilities, deep analytics, and rich visual representations. This is especially pertinent to the latest generation of CFOs who may not have such strong ties to the legacy software as their older peers.
By introducing automation in the mix, Excel sheds the look of an inferior option and eliminates manual processes that present a roadblock to increased efficiency and accuracy in reporting.
Plus, for finance leaders looking to ease their way into more automation in their processes, this is arguably the best place to start: tedious, repetitive tasks where impact can be felt instantly. Automation solutions don’t have to be ones with massive disruption and investment impact. There is a place for AI-powered, Excel-driven financial reporting - but only if CFOs acknowledge the current limitations.
Ralph Tkatchuk, freelance data security consultant