In the previous article we explained what the Theory of Constraints (TOC) is, and we reviewed its history. In this article we will go into more detail exposing the essential TOC concepts for their application in the supply chain. In a later article, we will focus on production, as well as the similarities and differences between TOC and Lean Manufacturing. Throughput is an essential concept in the theory of constraints and represents the rate at which the system produces money through sales or, expressed another way, it is the money that enters the company thanks to net sales after deducting expenses. variables. We can see it as the added value that is created.
In addition to throughput, there are two other variables to consider: Inventory and Operating Expense.
Inventory can be defined as the money that has been invested in the system to buy what you are trying to sell, although in the context of TOC here we would also include equipment, real estate, etc. That is, inventory represents money currently within the system.
Operating costs or Operating Expense, abbreviated as OPEX, is all the money that must be injected into the system to convert inventory into throughput. In general, it refers to fixed costs (rent, salaries, etc.).
Considering that the goal of every company is to obtain greater benefits, there will be three ways to improve its performance: increase throughput, reduce inventory or reduce operating costs.
The Theory of Constraints is a philosophy of continuous improvement, which implies also thinking in the long term. And in the long term, reducing inventory and operating costs has a more marked limit (after all, these variables can never be negative), while throughput conceptually has no limits.
With this in mind, the most successful modern management philosophies have been migrating from the old models, where priority was given to “cost reduction”, towards models that give the highest priority to increasing throughput, as one more bet. safe in the long term. Improvements in production processes and in the supply chain that allow us to reduce inventories are important in TOC, not because of cost reduction, but because this leads to an ability to improve sales and, with it, to increase the throughput. When Eliyahu Goldratt was asked in an interview how he would sum up the theory of constraints in one sentence, he replied that he could do it in one word: “Focus”.
Focusing is one of the keys to TOC: focusing even more than with the usual 80/20 rule. In fact, the Pareto principle in a system of dependent variables is closer to a behavior of 99/1. This reflects that, in a system that acts like a chain where its performance is limited by its weakest link (the constraint), there will only be one link that is the weakest and that a small part of the system has a high impact on performance. final score.
When the system constraint is a relatively easy to objectively identify bottleneck (for example, a physical constraint such as a machine or warehouse space), the five focusing steps can be applied:
- Identify the restrictions or bottlenecks of the system.
- Decide how to exploit those restrictions.
- Subordinate all decisions according to the exploitation of the restrictions.
- Elevate restrictions.
- If after following the previous steps a restriction is no longer restricted, repeat the process from step 1, trying not to get carried away by inertia. That is, adopt a philosophy of continuous improvement.
Devoting resources to optimizing the parts of the business that are not the constraint of the system (they are not the weakest link) will not have a substantial impact on overall performance.
Conversely, when the system bottleneck is correctly identified, focusing efforts on its optimization provides the fastest path to a noticeable improvement in overall results and lays the foundation for growth. Exploiting the constraint means making the most of the resource that represents the bottleneck.
For example, if the restriction of the system is a specific machine in the production plant, it will be necessary to ensure that said machine always works at its full capacity. Keep in mind that the performance achieved in the constraint will have a great impact on the overall results of the company.
As another example, if the bottleneck in a warehouse is picking, then it will be necessary to ensure that picking operations are carried out at the maximum performance that the order preparation system in use allows. For example, optimizing slotting or choosing another picking strategy (by zones, by batches, etc.).
It is important to make the most of the capacity of the resource that is a limitation, before going directly to invest in new equipment, that is, not to jump directly to step 4. This will allow you to start improving results faster and help you make better decisions later when investing in new equipment and technologies. The third step in the five focusing steps is to track or synchronize all non-constraint resources to the rate of the system constraint.
Resources that are not a constraint have, by definition, more capacity than the bottleneck resource. But it is important not to produce at a much higher rate than the constraint can process to avoid excess WIP (work-in-process) inventory, higher costs in maintenance tasks, etc.
For example, in a production plant where the bottleneck is a specific machine, it will be necessary to ensure that said machine always has work to do, that is, that at its entrance there is always raw material or WIP inventory to process and that there is no Defective materials arrive. The system par excellence of the theory of limitations applied to production is the Drum-Buffer-Rope. In the example of a warehouse, the typical bottleneck could be order fulfillment. Then, the increased capacity of the other resources should be used to ensure that replenishment tasks always keep merchandise on the pick shelves and that purchase orders are processed quickly. Excess capacity from resources not used for order picking can then be used for other important tasks, such as reverse logistics. Once the capacity of the resource that represents the constraint of the system has reached maximum capacity, then it is time to raise it by investing in more equipment or technology.
For example, in a warehouse with manual picking racks where order preparation is the bottleneck, after exploiting the resource through slotting optimization, the maximum possible performance could have been achieved. It would then be time to increase the resource by incorporating the ATOX Technological Solutions light-guided system for semi-automatic picking with pick-to-light operations, combining it with the intelligent roller transport system, minimizing the movements of picking operators. This would also allow efficient application of other picking strategies such as zone picking and batch picking.
If, for example, the restriction of a warehouse is the physical space and the metal racks are already being used to their maximum capacity, then the resource can be raised, taking advantage of the space at height through mezzanines and elevated walkways. In the pallet racking area, you can opt for racking systems that eliminate the need for aisles between pallets, such as the radio shuttle system, live racking, push-back racking, etc. Once the constraint on the system is raised and its performance improves, it may no longer be the weakest link. Then, the bottleneck will be in another resource.
The changes made to the previous restriction to improve it may have entailed new forms of management, new company policies, new technologies, etc. But then focusing on a new constraint may require a new way of managing the system and you need to avoid inertia making previously established policies a barrier and becoming a constraint itself. Therefore, you have to go back to step 1 and repeat the entire process completely, thus following a philosophy of continuous improvement. Despite the fact that the Theory of Constraints (TOC) has the word “theory” in its name, Eliyahu Goldratt developed it with a clearly practical focus, adapting common reasoning tools in the hard sciences to apply them to science “ soft” such as production management, supply chain management, marketing, etc.
When system constraints are not physical (for example, behavior patterns, outdated management philosophies, lack of information, internal communication problems, etc.) it is more difficult to identify them and instead of the five-step targeting system, it is The TOC Thinking Process is more useful.
The TOC Thinking Process is a set of cause-effect logical reasoning tools that help in a methodical way to answer the questions:
- What to change? (What to change?)
- What to change to? (Towards what change?)
- How to cause the change? (How to provoke the change?)
Goldratt said that while the first two questions were technical, the last one, how to bring about change, was mainly psychological, because of the resistance to change that will always have to be dealt with.
The TOC reasoning process begins by analyzing the symptoms that show that the company is not achieving the desired performance. With the help of a current reality tree, it is determined what needs to be changed in the system. Later, through evaporating clouds, a clearer understanding of what problems are causing the conflicts is acquired. This helps to get to the root of the problems, question the assumptions and misconceptions on which the current operation of the system was based, and ask what can be changed to evaporate the conflicts.
Through a future reality tree, the ideas reached in the previous steps are taken and it is ensured that the change that will be created will effectively solve the root problems and not cause new ones. Through a prerequisite tree, the obstacles that will be encountered during the implementation of the change and how to overcome them are determined. Finally, using a transition tree, a detailed step-by-step implementation plan is created.
All this makes it possible to design a path of change solidly based on logical reasoning, which will help to overcome resistance to change. One of the main tools of the TOC thinking process is the evaporating cloud.
An evaporation cloud helps determine a conflict. For example, in a warehouse, the objective is, as in any company, to obtain greater profits both in the short and long term. To do this, it is proposed, on the one hand, to reduce inventory. At the same time, on the other hand, it is proposed to maintain higher inventory levels to protect sales and, therefore, protect throughput. Clearly, this creates a conflict between reducing and increasing inventory. Eliyahu Goldratt said that when two ideas conflict, there is a simpler one that does not conflict. You just have to find it.
Frequently, conflicts arise because we base our reasoning on starting assumptions that we consider unchangeable when, in reality, they are not. A historical example of this can be found going back to the 50s, when Toyota needed to improve its production. Back then, Ford’s mass production was the dominant system in the West, but in Japan at the time the car market was smaller and more diversified. Those responsible for Toyota considered that, instead of producing in large batches as in Ford, they should manufacture in smaller batches, switching more frequently between the production of some models and others of the product, thus being able to respond more quickly to real demand. . This was the seed for the now internationally renowned Toyota Production System (Toyota Production System or TPS). But a conflict arose: the configuration time.
In the 50s, the configuration times of the production lines to go from manufacturing product A to product B were high and, therefore, in order for the unit cost to compensate, large batches were manufactured. Profitably manufacturing in small batches seemed impossible. But Toyota officials (particularly Taiichi Ohno, considered the father of TPS) questioned that assumption: why should setup times be assumed to be high? And so, they began a trajectory of improvements, not without encountering strong resistance to change, until they managed to reduce configuration times. With this approach, the conflict of manufacturing in small batches evaporated and gave rise to a pull production system, which decades later would become popular in the West as Lean manufacturing and just-in-time.
Returning to our example of the warehouse, the conflict is created because we assume that we have to have large amounts of inventory based on medium-term predictions to protect sales, that is, following a push system and being the main cause of the effect whip. But demand forecasts, no matter how sophisticated the systems used, will not be able to give accurate answers weeks in advance. The theory of restrictions applied to the supply chain then proposes a pull system, that is, governed by demand, and based on a replenishment at points of sale carried out more frequently and regularly, and this approach should be propagated. up through the entire supply chain. This makes it possible to reduce inventory and reduce the terms to which demand predictions must be applied, so they will be more reliable, thus contributing to reducing variability. In this article we have discussed throughput, five-step targeting, and the theory of constraints reasoning process. In the next article in this series we will discuss the theory of production constraints, talking about the Drum-Buffer-Rope or DBR system and exposing the similarities and differences between TOC and Lean Manufacturing.