Re: productivity standards (long)

From:Bert Dotson <amdj@duke.edu>

One must first ask the obvious questions: (1) what is the purpose of the 
standards? (2) how will they be used? (3) how will performance relative to 
the standards be measured?

There may be a number of purposes behind the decision to use some sort of 
standard that I am unaware of but in my experience they really come down to 
two. Standards are set up to measure laboratory performance or to measure 
individual performance. The first instance should be less controversial so 
I will tackle it first.

   Measuring laboratory performance can be used for cost accounting, 
setting staffing levels, benchmarking against peers/competitors or any 
combination. In these instances, it is very important that the standard be 
tied to some relatively universally acknowledged measurements or the data 
are meaningless.
   On this continent we have two such systems that are up-to-date and 
widely used and one that is hopelessly out-of-date and still frequently 
used. The two current standards are LMIP measurements from the CAP and 
Canadian workload measurement system. The hopeless one is the old CAP 
workload values that are still used by some but reflect none of the 
technological and market-place changes (automation, wider availability of 
ready-made reagents, shift from pathologist gross to technician or PA 
gross...) that have occurred over the past 10 years. The LMIP is a 
subscription system that carries a healthy price-tag but roughly measures 
the amount of output (slides) that can be expected from an average FTE over 
a period of time. This works out to about 1000 slides per FTE per month 
inclusive of a certain percentage of special stains etc. The Canadian 
system assigns a number of units of effort (minutes) to each technical 
task. The numbers of each task performed are then counted up and multiplied 
by the unit and you have an approximation of the level of effort required 
for a given lab. This system is much more versatile for cost accounting and 
for laboratories that perform a lot of specialty tests or have 
significantly different mix of workload from those in the LMIP (all 
research labs). The Canadian value to produce one finished H&E slide from 
one cut and blocked tissue (but not processed) is nine minutes.
   No system can be perfect and there will be justifiable variations from 
lab to lab. Canadian standards are based on actual time-studies in 
laboratories and contain small increments of overhead activities and 
step-function costs such as supervision and processor changing. Larger 
laboratories can perform better because they spread these activities over a 
larger specimen volume. LMIP is simply not suitable for research settings 
because it is based on actual clinical laboratories performance over longer 
time-spans (thus accounting for some fluctuations in daily workload). So as 
Tim Morken pointed out, these measures must be put into the context of the 
specific lab and its performance versus these measures over time. I 
disagree that simply looking at labor utilization versus workload may be 
used for staffing decisions because such a decision making process invites 
technicians and supervisors to "game" the system. Academia and the 
government are notorious havens for such "gaming behavior."

   The use of "standards" for assessing individual performance is a real 
problem. A government study (post office or census, I can't find the 
reference) in the '50s examined the performance of card punch operators 
when given various performance expectations. The study found that those 
that were given specific expectations in terms of the number of cards to be 
processed seldom reached the expectations (regardless of the actual number) 
and experienced significant stress when they did so. Those who were not 
given expectations soon surpassed the productivity of those that were and 
experienced no stress--go figure.
   If you must provide quantitative measures of employee productivity (as I 
must thanks to policies beyond my control) be VERY careful. From almost six 
years now of experience with this I can tell you there is no good way to do 
it. The best method I have used is a multivariable regression that allowed 
me to identify individuals whose presence in the lab significantly impacted 
total laboratory productivity. The powers that be found that method too 
complicated (they didn't understand it). Currently each individual keeps 
track of the number of blocks they cut and embed and these are monitored 
over long periods of time to control for differences in daily assignments 
and workloads. This is less than adequate but it does tend to give a more 
realistic picture and stifle some of the negative behaviors.
   I can provide a few pointers for those establishing a new system or 
modifying an old one:

Do Not set a standard "X blocks per hour." There is no way to properly 
monitor this unless you intend to stand over the techs with a stop watch 
and an abacus all the time. If you only monitor sometimes then performance 
when you monitor will be significantly different from when you don't. You 
will be measuring ability and not productivity. I disagree to some extent 
with the statement someone made that some techs are more talented. Many 
poor performing techs are capable of cutting at rates close to those of the 
better techs. They just don't.

Do Not count blocks over short periods of time (days or weeks). You do not 
have an unlimited supply of blocks. Those one person cuts are those another 
person doesn't. You will create block hogs.

Do have behavior and quality measures in addition to productivity. If 
productivity is the primary basis for deciding compensation or continued 
employment, poor quality and counter-productive behaviors will abound.

I've tried to be brief but given the amount of time I have wrestled with 
this issue it is difficult. And it is silly. Everyone in the lab knows who 
is not pulling their weight--just introduce peer evaluation and avoid all 
this busy work.

Bert Dotson



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