Continuing from last issue, the second definition of "model" that seems to apply to accounting is "a system of postulates, data, and inferences presented as a mathematical description of an entity or state of affairs; also: a computer simulation based on such a system." In this case we use the relationships such as cost of goods sold to revenue to predict the effect of, say, changes in energy prices (vary the cost of goods sold by $X and see what happens to profit).
It is trivial to say, but the most accurate model in the world is not the same as the real rubber and steel machine, just as the most complete spreadsheet with all the relationships is not the business. The second part of this might not be a nice thing to say, but the best accounting in the world is crude when compared to the complexity of even a moderate-sized business. The complexity of a large business is truly beyond comprehension.
Accuracy is important in a model. Decisions based on faulty assumptions can be wasteful, dangerous or just plain stupid.
This relationship of the accuracy of the model and its usefulness is well known to the accounting profession. Generally Accepted Accounting Principles insure that accounting decisions represent the actual business being reported upon. We are vitally concerned with how we can impact the business when we sense that it is going the wrong direction, and the model answers some of those questions.
No accounting system (even SAP) can answer even relatively simple questions about maintenance. The answer to even a basic question like, "Should this spare part be held in inventory even if it hasn't been used for five years?" is beyond accounting systems.
As any maintenance manager knows, the answer is related to the criticality of the equipment the part is used on, probability of failure, the kinds and effectiveness of PM and PdM being done, the part availability and lead time, the cost of downtime, and even the condition of the industry (try getting tires for big haul trucks with the current mining boom). The accounting systems lack the data to help make these basic decisions. Few accountants have the time or temperament to build the expertise to make these maintenance decisions themselves (without maintenance expertise as an input).
This is where hubris comes in. People may be ignorant of their ignorance and prideful about it. They argue something must be done and the model says cutting the inventory is the answer. The numbers on the spreadsheet look better once the inventory is cut. Problem solved, and score another victory for the system.
The problem is that the accounting system lacks the granularity to identify the consequence of that decision in terms of downtime, loss of productivity, loss of morale and loss of customer service. Without specific feedback the accounting profession cannot learn. In fact, the learners from these decisions are the maintenance professionals who have to still run the fleet or business without the ability to get parts. They are the ones that have to face the music six or 12 months later when the critical spare is needed and it is not available.
This is not to say that maintenance folks need to be given a blank check. In fact, the reason accountants come into the picture in the first place is because of the accounting ignorance of the majority of the maintenance profession. That ignorance results in excessive waste and lost efficiency, which alerted the accountants in the first place. In this we need to step up to the plate and learn the language and how to look at and manipulate the models. The best decisions have both the fleet knowledge and the accounting knowledge behind them.