Theory of Constraints

The theory of constraints (TOC) is a management paradigm that views any manageable system as being limited in achieving more of its goals by a very small number of constraints. There is always at least one constraint, and TOC uses a focusing process to identify the constraint and restructure the rest of the organization around it. TOC adopts the common idiom “a chain is no stronger than its weakest link.” This means that processes, organizations, etc., are vulnerable because the weakest person or part can always damage or break them or at least adversely affect the outcome.

History

The theory of constraints (TOC) is an overall management philosophy introduced by Eliyahu M. Goldratt in his 1984 book titled The Goal, that is geared to help organizations continually achieve their goals. Goldratt adopted the concept with his book Critical Chain, published 1997. The concept was extended to TOC with respectively titled publication in 1999.An earlier propagator of the concept was Wolfgang Mewes in Germany with publications on power-oriented management theory (Machtorientierte Führungstheorie, 1963) and following with his Energo-Kybernetic System (EKS, 1971), later renamed Engpasskonzentrierte Strategi.e. as a more advanced theory of bottlenecks. The publications of Wolfgang Mewes are marketed through the FAZ Verlag, publishing house of the German newspaper Frankfurter Allgemeine Zeitung. However, the paradigm Theory of constraints was first used by Goldratt.

Key Assumption

The underlying premise of theory of constraints is that organizations can be measured and controlled by variations on three measures: throughput, operational expense, and inventory. Throughput is the rate at which the system generates money through sales. Inventory is all the money that the system has invested in purchasing things which it intends to sell. Operational expense is all the money the system spends in order to turn inventory into throughput. Before the goal itself can be reached, necessary conditions must first be met. These typically include safety, quality, legal obligations, etc. For most businesses, the goal itself is to make money. However, for many organizations and non-profit businesses, making money is a necessary condition for pursuing the goal. Whether it is the goal or a necessary condition, understanding how to make sound financial decisions based on throughput, inventory, and operating expense is a critical requirement. It is an important segment of Theory of Constraints

The five focusing steps

Theory of constraints is based on the premise that the rate of goal achievement by a goal- oriented system (i.e., the system’s throughput) is limited by at least one constraint. The argument by ad absurdum is as follows: If there was nothing preventing a system from achieving higher throughput (i.e., more goal units in a unit of time), its throughput would be infinite — which is impossible in a real-life system. Only by increasing flow through the constraint can overall throughput be increased. Assuming the goal of a system has been articulated and its measurements defined, the steps are:

• Identify the system’s constraint(s) (that which prevents the organization from obtaining more of the goal in a unit of time)
• Decide how to exploit the system’s constraint(s) (how to get the most out of the constraint)
• Subordinate everything else to the above decision (align the whole system or organization to support the decision made above)
• Elevate the system’s constraint(s) (make other major changes needed to increase the constraint’s capacity)
• Warning! If in the previous steps a constraint has been broken, go back to step 1, but do not allow inertia to cause a system’s constraint.

The goal of a commercial organization is: “Make more money now and in the future”, and its measurements are given by throughput accounting as: throughput, inventory, and operating expenses. The five focusing steps aim to ensure ongoing improvement efforts are centered on the organization’s constraint(s). In the TOC literature, this is referred to as the process of ongoing improvement (POOGI). It is an important segment of Theory of Constraints

These focusing steps are the key steps to developing the specific applications mentioned below.

Constraints: A constraint is anything that prevents the system from achieving its goal. There are many ways that constraints can show up, but a core principle within TOC is that there are not tens or hundreds of constraints. There is at least one but at most only a few in any given system. Constraints can be internal or external to the system. An internal constraint is in evidence when the market demands more from the system than it can deliver. If this is the case, then the focus of the organization should be on discovering that constraint and following the five focusing steps to open it up (and potentially remove it). An external constraint exists when the system can produce more than the market will bear. If this is the case, then the organization should focus on mechanisms to create more demand for its products or services.

Types of (internal) constraints:

• Equipment: The way equipment is currently used limits the ability of the system to produce more salable goods/services.
• People: Lack of skilled people limits the system. Mental models held by people can cause behavior that becomes a constraint.
• Policy: A written or unwritten policy prevents the system from making more.

The concept of the constraint in Theory of Constraints is analogous to but differs from the constraint that shows up in mathematical optimization. In TOC, the constraint is used as a focusing mechanism for management of the system. In optimization, the constraint is written into the mathematical expressions to limit the scope of the solution

Breaking a constraint: If a constraint’s throughput capacity is elevated to the point where it is no longer the system’s limiting factor, this is said to “break” the constraint. The limiting factor is now some other part of the system, or may be external to the system (an external constraint). This is not to be confused with a breakdown.

Buffers: Buffers are used throughout the theory of constraints. They often result as part of the exploit and subordinate steps of the five focusing steps. Buffers are placed before the governing constraint, thus ensuring that the constraint is never starved. Buffers are also placed behind the constraint to prevent downstream failure from blocking the constraint’s output. Buffers used in this way protect the constraint from variations in the rest of the system and should allow for normal variation of processing time and the occasional upset (Murphy) before and behind the constraint.

Buffers can be a bank of physical objects before a work center, waiting to be processed by that work center. Buffers ultimately buy you time, as in the time before work reaches the constraint and are often verbalized as time buffers. There should always be enough (but not excessive) work in the time queue before the constraint and adequate offloading space behind the constraint. Buffers are not the small queue of work that sits before every work center in a Kanban system although it is similar if you regard the assembly line as the governing constraint.

A prerequisite in the theory is that with one constraint in the system, all other parts of the system must have sufficient capacity to keep up with the work at the constraint and to catch up if time was lost. In a balanced line, as espoused by Kanban, when one work center goes down for a period longer than the buffer allows, then the entire system must wait until that work center is restored. In a TOC system, the only situation where work is in danger is if the constraint is unable to process (either due to malfunction, sickness or a “hole” in the buffer – if something goes wrong that the time buffer cannot protect).Buffer management, therefore, represents a crucial attribute of the theory of constraints.

There are many ways to apply buffers, but the most often used is a visual system of designating the buffer in three colours: green (okay), yellow (caution) and red (action required). Creating this kind of visibility enables the system as a whole to align and thus subordinate to the need of the constraint in a holistic manner. This can also be done daily in a central operations room that is accessible to everybody.

Plant types: There are four primary types of plants in the TOC lexicon. Draw the flow of material from the bottom of a page to the top, and you get the four types. They specify the general flow of materials through a system, and they provide some hints about where to look for typical problems. The four types can be combined in many ways in larger facilities.

I-plant: Material flows in a sequence, such as in an assembly line. The primary work is done in a straight sequence of events (one-to-one). The constraint is the slowest operation.

A-plant: The general flow of material is many-to-one, such as in a plant where many sub-assemblies converge for a final assembly. The primary problem in A-plants is in synchronizing the converging lines so that each supplies the final assembly point at the right time.

V-plant: The general flow of material is one-to-many, such as a plant that takes one raw material and can make many final products. Classic examples are meat rendering plants or a steel manufacturer. The primary problem in V-plants is “robbing” where one operation (A) immediately after a diverging point “steals” materials meant for the other operation (B). Once the material has been processed by A, it cannot come back and be run through B without significant rework.

T-plant: The general flow is that of an I-plant (or has multiple lines), which then splits into many assemblies (many-to-many). Most manufactured parts are used in multiple assemblies and nearly all assemblies use multiple parts. Customized devices, such as computers, are good examples. T-plants suffer from both synchronization problems of A- plants (parts aren’t all available for an assembly) and the robbing problems of V-plants (one assembly steals parts that could have been used in another).

For non-material systems, one can draw the flow of work or the flow of processes and arrive at similar basic structures. A project, for example is an A-shaped sequence of work, culminating in a deli Supply chain / logistics.

Application in Supply Chain Management

In general, the solution for supply chains is to create flow of inventory so as to ensure greater availability and to eliminate surpluses.

The TOC distribution solution is effective when used to address a single link in the supply chain and more so across the entire system, even if that system comprises many different companies. The purpose of the TOC distribution solution is to establish a decisive competitive edge based on extraordinary availability by dramatically reducing the damages caused when the flow of goods is interrupted by shortages and surpluses. This approach uses several new rules to protect availability with less inventory than is conventionally required. Before explaining these new rules, the term Replenishment Time must be defined. Replenishment Time (RT) is the sum of the delay, after the first consumption following a delivery, before an order is placed plus the delay after the order is placed until the ordered goods arrive at the ordering location.

• Inventory is held at an aggregation point(s) as close as possible to the source. This approach ensures smoothed demand at the aggregation point, requiring proportionally less inventory. The distribution centers holding the aggregated stock are able to ship goods downstream to the next link in the supply chain much more quickly than a make-to-order manufacturer can. Following this rule may result in a make-to-order manufacturer converting to make-to-stock. The inventory added at the aggregation point is significantly less than the inventory reduction downstream.
• In all stocking locations, initial inventory buffers are set which effectively create an upper limit of the inventory at that location. The buffer size is equal to the maximum expected consumption within the average RT, plus additional stock to protect in case a delivery is late. In other words, there is no advantage in holding more inventory in a location than the amount that might be consumed before more could be ordered and received. Typically, the sum of the on hand value of such buffers is 25–75% less than currently observed average inventory levels.
• Once buffers have been established, no replenishment orders are placed as long as the quantity inbounds (already ordered but not yet received) plus the quantity on hand is equal to or greater than the buffer size. Following this rule causes surplus inventory to be bled off as it is consumed.
• For any reason, when on hand plus inbound inventory is less than the buffer, orders are placed as soon as practical to increase the inbound inventory so that the relationship On Hand + Inbound = Buffer is maintained.
• To ensure buffers remain correctly sized even with changes in the rates of demand and replenishment, a simple recursive algorithm called Buffer Management is used. When the on hand inventory level is in the upper third of the buffer for a full RT, the buffer is reduced by one third (and don’t forget rule 3). Alternatively, when the on hand inventory is in the bottom one third of the buffer for too long, the buffer is increased by one third (and don’t forget rule
• The definition of – too long” may be changed depending on required service levels, however, a general rule of thumb is 20% of the RT. Moving buffers up more readily than down is supported by the usually greater damage caused by shortages as compared to the damage caused by surpluses.

Once inventory is managed as described above, continuous efforts should be undertaken to reduce RT, late deliveries, supplier minimum order quantities (both per SKU and per order) and customer order batching. Any improvements in these areas will automatically improve both availability and inventory turns, thanks to the adaptive nature of Buffer Management. A stocking location that manages inventory according to the TOC should help a non-TOC customer (downstream link in a supply chain, whether internal or external) manage their inventory according to the TOC process. This type of help can take the form of a vendor managed inventory (VMI). The TOC distribution link simply extends its buffer sizing and management techniques to its customers’ inventories. Doing so has the effect of smoothing the demand from the customer and reducing order sizes per SKU. VMI results in better availability and inventory turns for both supplier and customer.

More than that, the benefits to the non-TOC customers are sufficient to meet the purpose of capitalizing on the decisive competitive edge by giving the customer a powerful reason to be more loyal and give more business to the upstream link. When the end consumers buy more the whole supply chain sells more. One caveat should be considered. Initially and only temporarily, the supply chain or a specific link may sell less as the surplus inventory in the system is sold. However, the immediate sales lift due to improved availability is a countervailing factor. The current levels of surpluses and shortages make each case different.