Early in my career I was a Manager at a Teamsters Plant in Detroit working the second shift. It was obvious to me that some of the hi-low drivers were much more productive than others, but I needed proof. After the administrative staff left, I would sneak into the offices to use Lotus 1-2-3 on one of the computers in order to track the number of truckloads each hi-low driver completed during their shift. Using that data I was able to substantiate my claims about the underperformers and eventually improve the efficiency of the shipping department.
That is my earliest recollection of using a data analytic tool in the workplace. Microsoft Excel has since become somewhat of an industry standard for spreadsheets in the finance and consulting world. Other tools such as PowerBI, Tableau, and One Stream have significantly enhanced our ability to handle larger data sets.
However, until recently even the most sophisticated data analytics software solutions have been limited to analyzing discrete data sets. With the advent of Artificial Intelligence, data analytics has the potential to move beyond the known, finite world of computing into a one involving super-charged predictive analytics that allow for more informed, proactive business management.
As it relates to FINNEA Group’s financial and operational consulting, we are hesitant to hand over the keys to running a business to a computer. However, we do recognize the benefits of using AI to improve the accuracy of predictive analytics. That is why we have taken a measured approach to utilizing AI, focusing on “AI Enhanced” predictive analytics as opposed to “AI Driven” analytics.
For example, consider the rollout of electric vehicles in the United States. As an EV owner for nearly four years now, I am well aware of both the benefits and pitfalls of embracing a technology too early. (Just ask my wife about the time we were stuck on the side of the road in Grand Rapids!). One could easily make the argument that, at least in the US, we might have been better off transitioning to hybrid vehicles first, while waiting for the infrastructure (charging stations, power grid enhancements, etc.) to be put into place before pushing adoption of full EVs. Regardless of your stance on ICE, Hybrid, or EV, I think we can all agree that 100% electric vehicles don’t work for everyone.
This is why we are taking the approach of “dipping our toes in the water” as it relates to incorporating AI into our consulting engagements. Take for example a 13-week cash flow model, a typical engagement for our financial consulting practice. Rather than allowing AI to drive the analysis and make important business decisions, we are finding ways to incorporate AI on the back end of a 13-week model build in order to better analyze trends in payment terms and other assumptions built into the model by human beings. Only in this way are we comfortable exposing the risks of a new technology to something as important as the running of a business. Better decisions can be made with the ability to analyze thousands of transactions per second without the risk of AI “hallucinations” or other unsafe outcomes that can cause material damage to the business. Having the ability to turn AI on and off when needed allows our clients to avoid being “stuck at the side of the road” with their businesses.
To learn more about AI Enhanced Predictive Analytics or FINNEA Group’s financial planning and analysis services, please email Joe Novak at jnovak@finneagroup.com or visit our website at finneagroup.com.
