A Guide to Implementing the Theory of
Constraints (TOC) |
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How did you get on?
Did you get an answer? Many people decide to make everything required to
meet market demand. So let’s work
through that first. The results are
tabulated for convenience.
If we work through this step by step, then the first
step is to determine the contribution, or margin, or as we have called it
here – throughput. This is sales price
less material costs and for P this is 90 less 45 = $45. For Q it is 100 less 40 = $60. Thereafter, it is simply a matter of multiplying out
the margin by the number of units produced to the weekly throughput. The weekly throughput less the weekly
operating expense gives us a weekly net profit of $1500. Not bad at all. But let’s check things first. Let’s check that we have enough capacity to
undertake the supply that we committed to. In order to do this we must check that the total amount
of time required for each resource does not exceed the total amount of time
available. If you still have that
rough sketch of the process on paper now would be a good time to retrieve it. Let’s start with resource A. In order to make 100 units of P, resource A needs
100 times 15 minutes (raw material 1) and in order to make 50 units of Q,
resource A needs 50 times 10 minutes (raw material 3). A total of 2000 minutes out of the 2400
available to resource A. So from the
perspective of resource A, we can meet that commitment. Let’s move to resource B. In order to make 100 units of P, resource B needs
100 times 15 minutes (raw material 2) and in order to make 50 units of Q,
resource B needs 50 times 15 minutes (raw material 2) plus 50 times 15 minutes
(raw material 3). A total of 3000
minutes out of the 2400 available to resource B. Oops.
It seems that we have insufficient capacity on resource B to meet our
commitment. Let’s check C and D. Fortunately C only requires 1750 minutes (100 by 10 +
100 by 5 +50 by 5). D also only
requires 1750 minutes (100 by 15 + 50 by 5).
Let’s tabulate that data so that it is a little
clearer. The right-hand-most column is
the maximum available time, and the column to its left is the sum of the time
required for each resource to complete the commitment for units supplied of
both P and Q. The problem now seems to be one of how to best
maximize the capacity of resource B and still derive a good profit at the end
of the week. Because we have a
approached this problem from a cost point of view, then surely the best way
to maximize our process would be to chose the product that has the lowest
cost. If we do this in terms of raw material
cost, then the answer must be Q at $40 rather than P at $45. If we do this in terms of labor cost, then
the answer must also be Q at 50 minutes labor (10 + 30 + 5 + 5) rather than P
at 60 minutes (15 +15 +15 +15). As a reality check, let’s also see what the effect
of maximizing selling price and margin or throughput is. The maximum selling price also favors Q at
$100 rather than P at $90. The margin
also favors Q at $60 rather than P at $45. It would seem then that Q is the product to favor
and any spare capacity left over after meeting market demand can be used to
produce P. Let’s do the basic
calculation for this. We now want to produce 50 Q. For resource B this will require 50 times
15 minutes (raw material 2) and 50 times 15 minutes (raw material 3). A total of 1500 minutes is required for
product Q. This leaves 2400 – 1500 =
900 minutes for P. P takes 15 minutes
for resource B. Therefore we can make
900/15 = 60 units of P. Let’s tabulate
this new condition.
Well if your eye jumped to the bottom line like mine
did, you will see we are spilling red ink! How did that happen? We did everything that our experience told us would
be useful. We chose the lowest labor
cost, the lowest material cost, the highest sales price, and the highest
margin. And yet based upon these
rational decisions we seem to have driven our bottom line into the red. Let’s leave this problem for the moment and return to
the measurements page. Hopefully we
can find out what is wrong and return to this problem later. To return
to the previous press Alt key + left arrow.
(1) Goldratt,
E. M. (1990) The
haystack syndrome: sifting information out of the data ocean. North River Press, pp 72-78. This Webpage Copyright © 2003-2009 by Dr K. J.
Youngman |