Scott Nelson is the president and chief digital officer of Tamarack Technology. He is an expert in technology strategy and development including AI and automation as well as an industry expert in equipment finance. Nelson leads the company’s efforts to expand its impact on the industry through innovation using new technologies and digital transformation strategies. In his dual role at Tamarack, Nelson is responsible for the company’s vision and strategic planning as well as business operations across professional services and Tamarack’s suite of AI products. He has more than 30 years of strategic technology development, deployment and design thinking experience working with both entrepreneurs and Fortune 500 companies.
While it is too early to define the new normal, one thing we can say for sure is that the rule “past performance does not guarantee future returns” has never been more true. Scott Nelson explores how real-time data can reflect a customer’s current financial health and reduce uncertainty about the future.
“We need to understand risk better.”
“Originations are up. My worry is our existing customers’ business health.”
“We have to decrease our distance from customers.”
Risk managers’ plates are full. These recent comments from lessor leaders regarding today’s economic environment in equipment finance showcase the uncertainty within the industry about how COVID-19 has changed how we live our lives and how we run our businesses.
While it is too early to define the new normal, one thing we can say for sure is that the rule “past performance does not guarantee future returns” has never been more true. In my opinion, COVID demonstrated that our society was not ready to use real-time data in public policy and healthcare decisions to manage uncertainty and risk. Now the question is whether our businesses and industry colleagues in equipment finance are ready.
Uncertainty Feels Like Risk, But It Is Not
The seminal work on risk versus uncertainty in business, Risk, Uncertainty, and Profit published in 1921 by Frank H. Knight, defines risk and uncertainty as follows:
Risk is present when future events occur with measurable probability.
Uncertainty is present when the likelihood of future events is indefinite or incalculable.
By definition they are different, but by consequence they are the same. Traditional project management teaches that risk can be managed but uncertainty cannot, it must be removed through process. Risk managers drive to a probable consequence based on previous experience, minimizing the bad or optimizing the good. But when uncertainty is treated as risk, the consequences can be unknown and unbounded. Think about how often uncertainty was treated as risk during the COVID19 crisis, i.e. a path was chosen as if the probabilities and severity of consequences were known. As a result, the consequences were realized, not managed. COVID-19 is a novel virus so using process or past experience to remove uncertainties did not apply, but economic and social misfortune were made a certain by decisions treating health uncertainty as a known risk. When uncertainty is not mitigated, unintended — often dire — consequences are realized.
The first step in any innovation process is understanding “why?”
“Why are we uncertain about how our customers will behave?”
“Why are we uncertain about the health of our customers’ business?”
“Why can’t we trust our traditional risk management methods?
The answer is simple: everything we know about our customers financially is historic and we are no longer sure if a customer’s business strengths, behaviors or models will help them in the post-COVID economy. We converted past financial behavior and performance to “measurable probabilities” of future behavior and performance. But those probabilities are no longer valid. A coin flip is no longer a 50/50 proposition.
Ironically, even though we understand “past performance does not predict future returns” we basically live by the contrary. Credit scores measure past payment behavior and we expect those scores to predict future behavior. P&Ls measure past profitability but not future cash flows. Balance sheets indicate financial health at a point in time rather than forecast future enterprise resilience. By changing the “norm,” COVID has made this methodology anachronistic. The rule now is “Past financial behavior is not relevant to future financial behavior.” We remain uncertain.
Reduce Uncertainty to Better Manage Consequences
Two bits of good news. Today there is an entire ecosystem of technology built to reduce uncertainty. The industrial world is undergoing its fourth generational transformation led by data, data from equipment — the Internet of Things (IoT). Industrial operational leaders have long used control loops and asset monitoring fed by data to run their processes. They have models for how both equipment and operations work that include conditional events thereby mitigating uncertainties. The rate and amount of data has grown so fast with the IoT that they must now automate the aggregation and analysis of data. In return this “big data” allows them to deploy machine learning (ML) and artificial intelligence (AI) to deliver new levels of performance and create new, time-based value propositions.
IoT adopters remove uncertainty with live, operational data and then manage risks by adapting in real-time. They can predict outcomes — productivity, margin, equipment health — with data streams feeding models derived from databases. Image how easily one could remove the uncertainty of “if, when and where” people return to soft-serve ice cream parlors, thereby driving demand for soft-serve machines if every soft-serve machine across the country reported use every day. Data analysis is a statistical science and statistics convert uncertainty to risk.
The second bit of good news is the financial opportunity. Knight’s treatise on risk and uncertainty also teaches that uncertainty is the source of profit. Profit is the reward for an entity’s awareness of uncertainty and good judgment in dealing with it. If all we had were risk, said Knight, then buyers and sellers would practice economic efficiency and eliminate profit — costs would equal gains. Those with good judgment can use new types of data to convert uncertainty to advantage and profit.
We must decrease our distance from customers.
Most customers lease equipment for one purpose: to generate revenue. Today, that equipment generates data that helps operators reduce uncertainty and manage operational risks proactively. We have uncertainty about how our customers will perform financially post-COVID. But if equipment is used to generate revenue and equipment generates data, then that equipment data can mitigate financial uncertainty. Data transforms uncertainty into risk. Risk can be managed.
Business leaders and risk managers alike must transition from backward-looking methods and experiences to real-time, operational data if they are to get closer to customers and survive post-COVID uncertainty. Data streams put anyone sitting anywhere “on-site, in real-time.” Getting closer to customers reduces the uncertainty of the relationship, it increases empathy, and it informs how customers are adapting to the “new norm.”
Much of what we understand and believe about financial behavior and business models is now suspect. But the right data, real-time data, can tell us what is happening and even what is going to happen — we can reduce uncertainty. The evolving truth is that “capital provides access to data and data protects capital.”
Financial risk management must become a function of operational data to survive in the uncertainty of the post-COVID economy.
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