“Mores” Laws in Financial Accounting

Today’s blog is a guest post from Brian Sommer, Founder of TechVentive, and is a two-part series in our initiative at taking a deeper look at today’s tech-savvy CFO.

Ceteris paribus is a Latin phrase I learned in high school classes. It means “hold all other things constant”. The concept was great in solving math and physics problems. The real world, though, does not hold other things constant and that creates issues for accounting professionals.

In conflict with ceteris paribus are things like Moore’s Law—that axiom where Gordon Moore of Intel fame predicted a doubling of components on integrated circuits every year or two. What Moore’s Law did for semiconductors is also playing out in storage, processor speeds and other technology spaces. It’s also pushing down the cost of memory, storage, computing power, etc. And, the end result of this is that companies today can:

  • place super inexpensive technologies on all kinds of devices (e.g., the Internet of Things)
  • cost-effectively capture and analyze vast amounts of data
  • perform powerful modeling assessments in near real-time
  • pair large data sources with machine learning
  • harness third party and other data sources to spot fraudulent activity
  • etc.

What this creates is a set of additional More’s Laws for accounting professionals. These will deal with:

More data to peruse. This information will include information sourced from within and beyond the enterprise. Within the company, accounting pros will look at the firm’s already massive store of ‘dark’ data (i.e., big data sets they already possess but don’t currently utilize. Could an auditor spot potential fraud within the clues found in employee emails?). They’ll also look at third party data sources (e.g., social sentiment data and the clues it offers around future sales). The best plans/budgets/forecasts of firms will come from a mix of traditional and new, big data sources.

More analytical tools. These tools will NOT be Excel spreadsheets but of a rather different sort altogether. There will be data visualization tools (e.g., Tableau). There will be powerful, but easily accessible, statistical tools (just look at some of the items SAS Institute offers). There will be third party utilities that can parse massive volumes of data (e.g., look at what DataSift and GNIP can do to social media data!)./p>

More detail in their data. Data will come in more dimensions, from more sources (e.g., sensors, point of sale records, etc.) and with countless other attributes attached. New financial systems are now available to take advantage of an almost limitless number of slices of data. If your firm is still trying to jam too much into its already overload chart of accounts, then it’s time to look for new financial software.

More powerful and faster data parsing tools. Accounting pros will become more familiar with Hadoop and in-memory database technology and less so with other artifacts (e.g., spreadsheets, manual interfaces, paper reports/documents, etc.) of a constrained and bygone era. If ‘time is money’, then these new generation tools move companies closer to the real-time, big data world of today and tomorrow.

So, what does this mean for financial accounting professionals and their employers?

One of the key consequences is that the way Finance determines its value proposition to the rest of the business is fundamentally changing. Mere bookkeeping won’t suffice. As Finance groups modernize, they must adopt more integrated solutions as well as embrace machine learning technologies so that rote transaction processing is as automated as possible. What the business needs are more insightful analysts poring over data looking for opportunities and nipping potential risks in the bud as early as possible. That can’t happen when a Finance group is mired in reconciliations, spreadsheet debugging, and other low/no value added activities. Better outcomes are rarely possible via antiquated core financial accounting solutions.

Additionally, the modern Finance group is in possession of new skills. These professionals are capable of working with imprecise big data feeds (e.g., social media content), understand statistics in a commanding way and utilize tools other than ledgers and journals.

The tools that the modern Finance group possesses are starkly different from the tools that served Industrial Age firms well. Out are client-server systems with their limited reporting capabilities. In are solutions that can marry operational, financial and external big data. New views of the business, in near real-time, across a number of internal and external perspectives are what’s driving great businesses today.

The last consequence is a very real but scarce capability: Finance groups need cosmopolitan, risk-takers to implement these new solutions. Change is an uncomfortable thing for everyone. A lot of Finance organizations have spent decades creating this cozy set of systems and processes that fit like a well broke-in pair of shoes. Too many people would rather get a new pair of shoe laces for this worn out footwear. But, it is worn out and needs to be replaced. Competitors are, mark my words, replacing their financial accounting technology stack. They will have a finance organization that is capable of altering the dynamics of your industry. The question is do you have the team and enthusiasm to make such a change or are you willing to wait and see your firm/your role made obsolete? The ‘safe’ play today is to change. Only a fool sees safety in ignoring all of the change around them. Remember, ceteris paribus does not apply to financial technology or its users.