It seems as though the opposite should be true but the fact is that more often than not the simple solution requires in depth knowledge and a lot of hard work, while complexity is the child of laziness and ignorance.  How else can we explain the obsession with formulas and factors in management decision making?

Case in point:  A client that was presented with a request to invest in equipment that would reduce the set-up time of a machine, justified by multiplying the time saved by a fully loaded labor rate of \$150 or so.  The math is easy, to be sure.  Save 6 hours a week times 50 weeks a year times \$150 equals \$45,000 a year in annual ‘savings’.  It took all of about a minute to calculate the ‘savings’ using this standard cost based approach, and the \$150 per hour rate is backed up by reams of accounting allocation logic and data.  The problem is that, in spite of the two or more decimal point precision of the accounting math, the \$45,000 ‘savings’ figure is pure bovine scat (known more commonly by its acronym – ‘BS’).

Costs will change and the rate of flow might change; maybe by a lot more than \$45,000 a year, and maybe by a lot less.  But the probability of that number flowing to the bottom line in increased profits as a result of the investment is near zero.

The true economic impact of the investment have to do with a whole lot of things, direct labor cost and allocated overhead having very little to do with the matter.  Whether the machine is a constraint, or bottleneck, in the flow has a huge impact.  Whether increasing the available capacity as a result is part of it, but whether anyone in sales is in any way connected with the change and has a plan to sell the freed up capacity obviously makes all the difference in the world.

The real impact of the investment can only be measured in terms of cash – not based on some formula chock full of allocations and assumptions.  Nine times out of ten when measured in cash, the savings from such investments are a whole lot less than people think they are.  Cash is king – it is real money.  If all the same people are going to keep showing up for work after the investment is made, drawing the same paychecks, and there is not going to be a real increase in sales volumes, then the savings from that particular investment are pretty close to zero.

The complex allocation models accounting puts together are useless in assessing this and most other management decisions; and it is going to take a lot longer than 1 minute to figure out the math; and it is going to take a pretty in-depth knowledge of the business and a fair amount of leg work to figure out what will really happen once that set-up time is reduced.

EOQ  - lot sizing, Economic Order Quantity – is the most flagrant example.  With inputs pulled from the seat of accounting’s pants like average inventory holding cost per unit, and fixed order costs and set-up costs the resulting ‘optimum quantity’ is utter nonsense.  Without a logical lot sizing formula, however, MRP collapses like the proverbial house of cards, so because it would be great if MRP were accurate we have rationalized a very complicated formula in order to pretend it is accurate.  In truth, the right amount to buy or make is really, really complicated and it depends on a whole lot of things, and many of those things change every time we set out to buy or make stuff.

Good decisions require solid knowledge of reality.  They are driven by real money, rather than overhead allocations and silly accounting theories like ‘opportunity costs’.  And much of the input cannot be quantified in accounting terms and ultimately falls to management judgment driven by strategy.

Of course the true motivation for such heavy reliance on formulas and factors is so that accountants and managers far from the front lines, and largely ignorant of the realities of the business, can make decisions.  That will never work.  If the folks in the front office want good decisions they either have to get out onto the factory floors and sit in on the sales calls going face to face with real customers; or they should train the people in those decisions as to how cash actually flows and turn the decisions over to them.