Focus and Leverage Part 319

In my last posting I said we would now discuss Goldratt’s second step, exploitation.  Here’s where applying the tools of Lean and/or Six Sigma come into play as well as some common sense things to do first.  The fact of the matter is that since the system constraint controls the throughput of any process, any minute reduced or gained is a positive thing in terms of process throughput.  Before we look at how we might use Lean and/or Six Sigma to exploit the constraint, let’s look at some simple, common sense changes that can be made to the process that are essentially free.  Again we turn to Steven Bragg’s book for some ideas.  As I said in my previous posting, all of the concepts presented in this posting apply to all process types.  As such, we will consider their application to both a manufacturing process and a healthcare process.  Let’s take a look at our 4-step process we introduced earlier.

 

 

1. Cover break time.  Bragg tells us that when employees stop a constrained resource to take a break or lunch, the company will suffer lost throughput that could have been generated if the constrained resource hadn’t been stopped.  In this process we had identified Step 3 as the bottleneck operation requiring 90 minutes to complete work.  Let’s assume that this was a 2-shift operation which means that we have 16 hours, or 960 minutes (i.e. 16 hours x 60 minutes/hour = 960 minutes) of capacity on the constraint.  If it takes 90 minutes to treat a patient or produce a product, then in 960 minutes, assuming no downtime, we could process 10.66666 parts or patients in the two shifts of operation.  What does this number look like if we don’t relieve the constraint during breaks and lunch?  Assuming the operator gets two, fifteen minute breaks and one 30 minute lunch period on each shift, then theoretically we would lose 120 minutes of constraint time per day in a 2-shift operation.  This leaves only 960-120 = 840 minutes of constraint time.  This translates into 9.333 parts produced or patients treated in the same 2-shift operation.  So by not relieving the constraint operation during breaks and lunches, we lose 1.33 parts/patients of capacity each day.
2. Avoid downtime during shift changes.  It’s quite common in many organizations to actually shut down operations during the changing of shifts to allow out-going operators to “clean-up” their operations and for in-coming operators to review the schedule and attend meetings.  Let’s assume that this changeover of shifts accounts for 30 minutes (i.e. 15 minutes each for out-going and in-coming operators) of downtime at the constraint.  Bragg tells us that by having overlapping shifts, this downtime disappears.  The total loss of throughput due to shift-changes is then, 30 minutes or 0.3333 patients or parts.  Adding these first two ideas together, we are now up to 1.6666 parts/patients of lost throughput.
3. Off-load incidental work from the constraint.  Suppose a constraint operator is required to “clean-up” his/her work station or stage products/patients or fill out paperwork or even perform simple maintenance functions.  All of these operations could be performed by a non-constraint operator rather than the constraint operator.  Let’s assume that the sum total of these activities add up to 30 minutes of non-productive constraint time for two shifts of operation.  Once again, this 30 minutes accounts for an additional 0.3333 parts/patients bringing our cumulative total up to 2 parts/patients of lost throughput.

Bragg lists other ways to “exploit” the system constraint such as performing preventive maintenance on off-shifts, but the three listed above represent some of the more common ways to increase the output of the constraint without spending any money at all.  Think about it, we have just increased the throughput of the constraint by 2 parts/patients per day which translates into 10 per week or roughly 500 more parts/patients per year without spending any money.  If the revenue we receive for each part/patient was say, $300, then the total revenue gained would be $150,000 per year.  And since it didn’t cost us anything to implement these simple, common sense ideas, this new revenue flows directly to the bottom line!  The point is, look for the simple ways first to reduce the time on the constraint.  Once these simple changes are made, we can then use our knowledge of the tools of Lean and/or Six Sigma to help us reduce time on the constraint even more.

 

So far we have been discussing constraints as though they were physical in nature, but there are also constraints that are being caused by specific policies in place that negatively impact our ability to increase throughput.  Appropriately these types of constraints are referred to as policy constraints.  A policy is any rule, regulation, or procedure that dictates how our system is operated.  For example, suppose there is a policy that overtime will not be used.  Because non-constraints have excess capacity, there is no negative impact on their ability to process products or patients, but what about the impact of this policy on the constraint operation?  This one-size-fits-all policy could have a severe impact on the organization’s ability to produce a product or deliver a service.  In my next posting we will discuss policy constraints and how they can negatively impact throughput.

 

Bob Sproull