The modern financial industry could not exist without digital technologies that would make our recent ancestors gasp in awe. It wasn’t so long ago, however, that the ships of commerce sailed on simpler waters. On these smoother seas, accountants and finance professionals didn’t have to concern themselves much with the latest technologies.
The basic mathematical and financial underpinnings of accounting haven’t changed much since the introduction of double-entry bookkeeping in the late thirteenth century. For that matter, the analog underpinnings of bookkeeping technology remained the same for hundreds of years, until the proliferation of mechanical adding machines in the mid-1800s and primitive punch-cards soon thereafter.
Even with these tools, which helped perform calculations and aggregate data to some extent, bookkeepers relied on paper ledgers to officially record debits and credits to revenue and expense accounts for nearly the entire history of the profession. It wasn’t until the advent of the desktop computer in the last half-century that the essential functions of accounting became digitized on a large scale.
While early adding machines gave accountants the ability to perform basic mathematical functions, their utility was limited by the machines’ lack of computer memory. Each computation was transactional and ephemeral. The invention of primitive paper punch-cards was the first practical attempt to somehow store data that could be later used by a machine, but their applications were very limited.
The landscape began to shift more dramatically in the 1970s, however, when finance and accounting began to be fundamentally transformed by digital technology. This shift was spearheaded by two big breakthroughs. The first was the introduction of accounting software that could be used on early personal computers at a fraction of the cost of previous custom software solutions that ran on giant mainframe computers and were too expensive and complex for all but the largest organizations. Perhaps equally as important was the introduction of the first spreadsheet software, VisiCalc, which enabled users to build financial models on computers.
The growth of the personal computer industry over the ensuing decade led to even greater proliferation of these tools. By the late 1980s, millions of businesses were using computers and accounting software every day. Forward-looking accountants suddenly had to have an eye on technological changes, which were starting to disrupt the field.
The next decade saw the birth of the Internet, which rocketed an already-fast-moving technological boom into the stratosphere. From isolated, single machines or primitive local area networks (LANs) used by larger businesses, the world transformed into a more interconnected and interdependent environment. As the internet evolved, accounting software moved into the cloud – along with all of its associated data. As the speed of internet connectivity grew, processing power increased, and more and more businesses and individuals started moving more of their operations to the internet, the amount of data and our ability to harness, manipulate and use that data grew exponentially, becoming faster and more efficient at a breakneck pace.
During the last decade, the same technological evolution that has fueled the change in finance and accounting has led to an explosive new field that transcends industrial boundaries: data science. The evolution from Frederick Taylor’s time and motion studies to today’s learning machines, which drive everything from forecasting to fraud detection, has been much faster than the transformation of the finance function. But now, along with so many other specializations, the two are moving in lockstep toward the future. Just as the advent of robotics disrupted the manufacturing industry, the arrival and continued expansion of robotic process automation, artificial intelligence, and machine learning is already fundamentally changing the nature of finance and accounting.
Resultantly, we stand now on the cusp of the next industrial revolution – one that is likely to be just as disruptive as the ones that preceded it. The difference now is the frequency with which new technologies fundamentally change the nature of our existence. A solid century separates the first two industrial revolutions of coal and steam power beginning in the 1760s to gasoline and the combustible engine in the late 1800s. Those represented the technology that drove our economies up until the 1960s, when nuclear power and electronics began to co-exist and replace much of what came out of the prior revolutions. The next revolution, however, came just a quarter century later with the introduction of the Internet, followed after just over a decade later by the explosion of smartphone technology and the “always connected” modern civilization.
And now here we are today, where portable computers powered by ever more powerful technology are ubiquitous to a degree that was nearly inconceivable at the turn of the millennium. In the connected world of the 2020s, all of society is inundated with the availability of data and increased computing power. The majority of the population is startlingly unaware of how many of their daily interactions are driven by highly sophisticated algorithms.
What does this mean for the finance function?
In the past, the finance department’s role was primarily that of a historical record keeper – a master of internal controls and compliance. While those responsibilities still fall under their purview, successful finance departments are now responsible for much more. As improvements in technology have made it easier to track and model all the data that is now available, finance has evolved to offer greater value than just keeping score.
Finance departments now produce complex predictive models, track company KPIs and metrics, and provide insight to strategic issues. It has become an expectation that modern finance departments are fueled by analytics and data science. The business intelligence that they provide is used to help companies make data-driven decisions, from the everyday and mundane to the monumental and existential.
This evolution represents an opportunity for businesses. It has taken place over several years, as the amount of available data has increased; and it’s made more and more sense for finance to be the junction point for adding value. With appropriate data, today’s finance departments are ideally situated to report on all aspects of a firm’s business, from providing cost-benefit analyses to measuring operational performance. In keeping with the role’s traditional and indispensable position as impartial observer, data-driven finance departments can report objectively and accurately on all aspects of the business. This new approach can eliminate the prejudgments that are typical when companies rely on self-reporting from departments or business units to assess their corporate health.
This same evolution brings good news for current finance employees. The tools and skills that make a good financial analyst lend themselves to success in data science, so it’s not a matter of replacing existing finance workers. It’s more a matter of upskilling the current team to make use of the new tools that are available. Most financial analysts worth their salt can run simple linear regressions and know how to de-seasonalize and trend data to make more accurate forecasts. Their math and stat backgrounds transition easily to more extensive use of data science. It’s a short walk from linear regression to polynomial regressions for more curved data, and then another quick jaunt around the corner to Lasso and ridge regression (some of data science’s “greatest hits”).
For finance professionals, the tricks of the trade have come a long way in recent years. Now teams can use tools like R Studio, Power BI, Tableau and Python to extract value from existing data. If current finance teams aren’t yet using those technologies, they need to make their adoption a priority. The resulting insights can fundamentally change—for the better—the companies that use them.
There’s an old-guard sentiment that busy finance teams don’t have time to learn or be distracted by these new skills. This argument doesn’t hold water. As more and more of the foundational work of finance is being automated, finance (like all industries) must evolve to find a foothold in the new landscape. Those who don’t will be left behind like Blockbuster, Kodak or any of the other famous companies that once ruled in the analog world. Today, software can automate nearly all finance functions, from expense management to accounts payable to accounts receivable to bank reconciliations to the financial close process. Finance teams should not fear these innovations; they should embrace them. Because these advances don’t have to mean headcount reductions and smaller teams. Instead, they can lead these same employees to a shift from mindless data entry and repetitive work to mindful tasks that add value to the organization.
The good news is that modern finance teams aren’t being asked to do more with less. They are being asked to do more with more. The opportunity for finance teams to bring value to the business has never been greater. By embracing new technologies, finance teams can build more and more ROI for the department. The tools and processes they develop to drive the transformational shift to data-driven organizations become a kind of internal intellectual property with real value to the senior management team, board, investors, and to the business as a whole.
The immortal Ferris Bueller once memorably observed: “Life moves pretty fast. If you don’t stop and look around once in a while, you could miss it.” The role of the finance function is moving pretty fast, too. The smart finance department is well advised to look closely at the rapid metamorphosis that is taking place all around us. Don’t miss it, and don’t miss out.
