Toward More

Creative Variance Analysis

As we urge every CEO and business owner to do, we compare actual results with the projections the client made at the beginning of the year, whether it’s a formal budget with staff accountability or not, and we ensure a discussion with management follows. Even without staff accountability, there is value in management learning what differed from what they had estimated only a few months ago, and looking beyond the basics for answers that will drive better results. Here’s a short example of that interaction with a current client, a product distribution and service company. 

The monthly results were published. Revenue fell short but the bottom line beat the profit projection. Then we compared key elements as a percentage of total revenues, and that revealed that Gross Profit Margin (GPM) was 51% vs. the projection of 44%, each measured against their respective revenue projections. That was the lion’s share of the profit improvement, and it turned a mediocre projection into a solid gain. We saw that a dollar of sales cost them less than they thought it would. Let’s go further.

We next calculated the percentage of revenue of each element of the Cost of Goods Sold (again, against their respective revenue numbers, so that the anticipated relationships are preserved). 

Their labor provided to customers is their most profitable offering, and it’s an essential part of every sale, so we looked there first. The percent of revenue projected was 12%. Actual percent of revenue achieved? 12%. Clearly, this was not the contributor we were looking for. 

Next, the parts and components that are typically part of every sale came in 2% under the projection. No one recalled any comparison between vendor invoiced costs and the client’s price list to see if a price increase differential was the reason, so some homework to be done there. 

Then we got to equipment – the largest dollar category but the least flexible in price due to supplier controls. Turns out their equipment sales cost 5% less as a percentage of sales than forecasted. That’s a big number. Why did that happen? Product mix? Price list revisions? Missed budget (always a possibility)? More homework was needed to check that out, but we felt pretty good that the resulting research would give us information that would enable us to do a couple of things better:

  1. Compare our price lists with vendor invoice costs to see if we are keeping up with passing cost increase through to our customers, or over-compensating, 

  2. Help our marketing and sales teams drive their efforts in optimally profitable versions of the sales plan, with new information, and

  3. If needed, help to improve our forecasting accuracy with more real data. 

This is more analytical than the traditional budget variance analysis, which looks at dollar differences by line item and stops there. It's a bit more homework, but it’s also more useful in driving management actions than analysis based on dollar variances alone. Better data, better analysis, better results.