Before I introduce you to TA, I think it is appropriate to discuss some of the basics of TOC. TOC was developed by a Physicist from Israel named Dr. Eliyahu Goldratt in the 1980's and popularized in his classic book, The Goal. If you haven't read this book, I strongly recommend it. So just what is TOC and why should we be learning about it? Eli Schragenheim in his book, Management Dilemmas - The Theory of Constraints Approach to Problem Identification and Solutions tells us that his interpretation of TOC, the following three concepts are key assumptions in understanding the TOC philosophy:
- An organization has a goal to achieve
- An organization is more than the sum of its parts
- The performance of an organization is constrained by very few variables
One of the major problems I have with traditional Cost Accounting is that all individual parts of the organization must work to optimal performance. The measurement most used to determine whether this is occurring is the metric manpower efficiency. This metric teaches managers to maximize their output and if they do so, they will be considered successful. So what's wrong with that? Let's look at a few visuals to help understand why.
So here we see a simple four-step process where raw materials enter at Step 1, spend 30 minutes being processed and then passes the semi-finished part on to Step 2 for processing. After 45 minutes at Step 2 the part is passed on to Step 3 which requires 90 minutes to process before passing it on to Step 4. Upon completion at Step 4, the part exits this process as finished goods. So if your company is like many others and uses manpower efficiency as one of your primary performance metrics, every step in this process should be running at its full capacity. In other words, Step 1 produces parts at a rate of 1 every 30 minutes, Step 2, every 45 minutes, etc.
My question for you is, if you ran all process steps at its maximum capacity, what would be the impact or what would this process look like after 8 hours if every step was forced to run at maximum capacity?
Listed below each step in the above figure, assuming there was no down time, is the expected output running at full capacity after 8 hours. The individual boxes above each step are the number of semi-finished products at the end of 8 hours. In other words, the boxes represent the amount of accumulated WIP in this process at the end of 8 hours. As you can see, even though 16 parts were processed through Step 1, only 5 made it to the end as finished product.
So what would this process look like if it ran at max capacity after 3 days? the product would look like the following figure.
As you can see, the WIP continues to grow and eventually will overcome the process. Even though Step 1 processed 48 parts in three days, only 15 parts made it to finished goods. This is the impact of using efficiency as a performance metric, And when WIP grows, the ability to ship products on time is reduced dramatically. This is not an uncommon occurrence in companies being driven by traditional cost accounting.
So what is the answer to this problem? One thing that should be fairly obvious is that the only way to avoid this excessive WIP condition is to abandon the use of this performance metric. In other words, the only process step in this process that should be running at or near its capacity is Step 3, the constraint or bottleneck. In this process, all other steps should be processing parts at the rate of one part very 90 minutes. The other point is that the only way to improve the throughput of this process is to reduce the time required to process parts in Step 3. The inevitable conclusion is, the constraint controls the output of the process.
In my next posting, I will introduce Throughput Accounting which I believe all companies would benefit from.