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Dickeson--Conducting Job Pathology

March 1998
Recall Dr. Quincy, the television series pathologist? He conducted postmortem examinations of bodies of crime victims. I caught a rerun the other day of that old Jack Klugman series, and it triggered some thoughts about costing and printing—if you can imagine that!

When I talk about "job costing" with a printer, the usual response is, "Yeah, we've got a terrific estimating system." We have a tendency to equate job costs with cost estimating and often overlook perhaps the major value of a job costing system.

We should play Quincy with our cost accounting system. Dr. Quincy didn't try to predict when a given person would die or from what cause. He reacted to what had already occurred.

For a good cost accounting system, we have three data sets available:

A. Transaction job dollar costs (transactors)

  1. Paper and ink

  2. Buyouts

  3. Hourly work center rates


B. Predictive production standards (predictors)

  1. Job usage pounds of paper and ink

  2. Job hours required in production centers


C. Actual job performance results (actuals)

  1. Material pounds consumed on the job

  2. Production center hours applied


We constantly use these three data sets in job cost application to:

A. Estimate costs by multiplying transactors by predictors

B. Load and schedule our facilities using predictors

C. Purchase materials by using quantity predictors, or

D. Manage materials pick-lists derived from predictors.

We give only passing attention to multiplying actuals by transactors, to produce the reactionary perceivers. By neglect of actual job cost experience analysis, we are missing statistical guidance for the long-term success of the company.

Production standards as predictors are iffy at best. Production standards attempt to apply actuarial tables to job specifications in order to project what will happen. We try to apply actuarial experience tables to tell us which jobs will live and which will die.

No doctor can look at any person and predict life-span. So why do we constantly try to use actuaries to predict the life-span of a job? Chaos theory, where small variations in inputs cause major variations in output, frustrates application of specific job predictors. Scheduling, purchasing and materials management use their own variations of production standards based on their view of experience.

Cost estimating lives in a world of virtual reality, forcing decisions based on predictions from tables that are not intended for such usage. Actuaries can only look at groups like white male smokers, construction workers, homemakers, etc., and provide averages and ranges of life expectancy. All we can do with our predictors is provide averages and ranges of job performance expectancy.
 

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