CFOs have long known that businesses aren’t using sound microeconomics when they make decisions…because individual business units within the company aren’t! This practice misrepresents the company’s financial health and reflects poorly on its gatekeeper, putting profitability in jeopardy.

But is it so important that shortcuts like using average costs should be eliminated in favor of real economics — in other words, knowing when variable costs occur? Or, is it like the saying originated by Cervantes in Don Quixote, “It will all come out in the wash?” On a monthly, quarterly, or annual basis, don’t costs average out anyway?

Not according to a Ventana Research study, which states:

“Decisions based on average costs can have unforeseen negative consequences on profitability.”¹

Without microeconomics incorporated into planning and decision-making tools, leaders cannot fully understand the financial impact of the decisions they’re making. As complexities increase, businesses are recognizing that the need to appropriately understand financial drivers is becoming not only more important, but crucial. It’s one of the reasons that companies are projected to triple the use of prescriptive analytics in the next several years. Simply put, it’s the only type of analytics that can handle the ever-growing number of variables, constraints, and cross-functional KPIs.

Without prescriptive analytics, however, decisions like whether to move production of one product to another part of the country usually fall back to inflexible spreadsheets and BI reporting, an approach used by 75% of companies today.¹ Other reasons that contribute to a company’s inaccurate financial planning include:

• Planning that starts from scratch — one that simulates an ideal scenario versus replicating the business as is today (creating the digital twin)
• Using a non-existent framework for financial modeling; this causes the use of assumed variables that affect decisions and rely on humans to think through every action that impacts or is impacted by decisions.
• Performing ad-hoc analysis, which fails to provide a basis on whether assumptions are correct versus ongoing planning systems, which are constantly measuring the plan against performance.
• Relying on siloed data interpretation that doesn’t represent the impact on the company as a whole. For example, transportation data that is specific to the transportation silo may not align with how the company views the overall financials.

The consequences of inadequate supply chain planning extend beyond internal actions, too.

What Micro-Economics Means to the Business Externally

Customers want the continuous assurance of receiving the best pricing, quality, customer service, and delivery for the company’s products. However, the real picture is that there are pockets of opportunities that will benefit customers and corporate stakeholders, which are often missed by using the average cost method in planning.

In Figure 1, the blue line shows the assumed, fixed labor costs, taking a linear, progressive path, beginning at $3 per unit. The red line shows that labor is actually more complex — shift labor is “semi-fixed” rather than fixed. A fixed rate for the shift becomes a variable as overtime is incurred (increased) or another shift is added, fixing the cost again until that shift runs out. Note: When the red line dips below the blue, Opportunity Values exist.

When the use of microeconomics is absent, accounting for the contribution margin is flawed — not captured is the difference between revenues received and the variable cost of production. Companies don’t have visibility into how much the real product costs contribute to the fixed costs. This reality prevents companies from adjusting margins and maintaining profitability.  

^¹”Supply Chain Planning with Prescriptive Analytics,” Ventana Research, 2018.