How to identify the constraint of a system? Part 5

This is part 5 of a series of posts about identifying the constraint of a system and time for wrapping up and a conclusion (of the series, not the topic!).

Newcomers to Theory of Constraints understand quite easily the concept of bottleneck but are frequently puzzled when looking for them in a real-life process. Furthermore, people have usually difficulties to distinguish bottlenecks or Capacity Constraint Resources from the system’s constraint. As only the latter controls the Throughput of the whole system, meaning it does control the system’s profitability, constraint hunters should better not mismatch the focusing point.

Through the examples in the previous posts, readers can understand that there is no such a thing like a simple trick, neither ready procedure to find the constraint, but a necessary and sometimes painstaking investigation process.

If you missed previous posts, you may check:

Some constraints can really be well hidden and remain elusive, leading analysts to be wrong when identifying it. Because of the growing number of standard and regulatory requirements, the constraint is more and more often found in the paperwork process, in quality assurance or information flow. And this is the wrong place for the constraint to be.

How to be sure the constraint is found?

With so many opportunities to mismatch the constraint, how can one be sure about having found the constraint? Well, by definition the constraint controls Throughput. Elevating the constraint is like opening a valve, the flow through the constraint increases. And as, also by definition, all other resources have excess capacity compared to the constraint, the flow should soon reach the process’ output. This enables the organization to ship more, to ship on time, take more orders and shorten time-to-cash.

For non-profit organizations, the Throughput is expressed in “Goal units”, meaning achieve more of what the organization exists for, like treating more patients for a medical center, providing more food to the homeless, etc.

Now this is quickly noticeable if the downstream process steps are waiting for supplies from the constraint, otherwise the flow from the constraint may take longer to reach the process’ end.

Be aware of the S curve and Valley of despair

As with many improvement initiative, the result may be delayed to a point that some stakeholders come to the conclusion it doesn’t work. Before getting trapped in this pitfall, the project manager or the leader should be aware of the frustration with the S curve.
When dealing with bigger projects rather than improvement activities, it’s not only the S curve the project manager and the sponsors should worry about, but also the “Valley of despair”. This valley is a low in morale following the excitement and expectations about the benefits that the new project will bring. The drop in morale comes when issues and bugs let the new solution appear worse than the old. The challenge for the leader is to get everyone as quick as possible through the valley of despair, accommodate the new way or system and eventually recognize the benefits.

Keep on alert once the constraint is found!

Now once the constraint is properly identified and the efforts to exploit and elevate it begin, the leaders should immediately take care of the consequences of releasing more “goal units” through the constraint.

  • First because the constraint will most probably move to another spot and again this can be anywhere in the process.
  • Second because upstream as well as downstream process steps may be taken by surprise. Upstreams by an increase of demand in order to supply and exploit the increased capacity. Downstream by the flushing of the work in progress that may propagate a significant wave of workload.
  • Third because management must anticipate any necessary action to sustain the flow at the new level, otherwise the success will only be sporadic and ultimately disappointing.

I recommend reading two other posts related to these warnings:

Conclusion

The search for the system’s constraint can be very simple and straightforward, but most often it is tricky and leads to identify wrongly some resources as culprits. It is no rocket science but needs investigation skills and rigor. Experience helps a lot and the good news is that taking care of constraints is never-ending, so experience may accumulate fast.

About the author, Chris HOHMANN

About the author, Chris HOHMANN

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How to identify the constraint of a system? Part 4

Since the publishing of early books on Theory of Constraints, the world grew more complex and the system’s constraint got more and more elusive. Globalization and extended supply chains give a constraint opportunity to settle literally anywhere in the world and extend its nature. It can be a physical transformation process in a supplier’s facility, it can be the way cargo is shipped from distant suppliers to the company, it can be the custom clearance process somewhere along the supply chain.

Walking a factory door to door may not suffice anymore to find the system’s constraint. The examples given in the part 1, 2 and 3 of this series of posts are simplified with regard to the reality of most companies.

Another complexity is brought by the growing number of requirements of standards and regulations. A company wanting to count among the aeronautical industry makers has to comply to the AS 9100 (USA) / EN 9100 (Europe) / JISQ 9100 (Asia) standard. For the automotive industry the standard to comply to is ISO/TS 16949 (now IATF 16949). And those two examples are only standards for the quality management system.

Pharmaceutical industry, as some others, require a license to operate. In order to be awarded such a license and to keep it, the company must comply to all requirements, undergo periodic audits and keep record of anything happening along the manufacturing process. This industry is under constant scrutiny of government agencies, regulators, etc.

Therefore, the paperwork associated with products is impressive and requires a lot of resources in the dedicated processes, and as we will see, likely to host a system’s constraint!

Over time, layers of requirements accumulated. And what is a requirement if not a limitation of the way to execute, a constraint?

Quality assurance

Quality assurance (QA), according to wikipedia, comprises administrative and procedural activities implemented in a quality system so that requirements and goals for a product, service or activity will be fulfilled. It is the systematic measurement, comparison with a standard, monitoring of processes and an associated feedback loop that confers error prevention. This can be contrasted with quality control, which is focused on process output.

https://en.wikipedia.org/wiki/Quality_assurance

Anyone working with a Quality Assurance department soon realises that this department is more acting as a defense attorney for the company against regulatory or standardization agencies, and a watchdog internally than a support for improving quality by problem solving.

For obvious reasons, QA and Production must have a clear divide, as it would not be acceptable for the maker to assess and certify the quality of his own production. Their staff are also distinct. QA usually has a huge influence on decisions and can be very powerful, to the point that top executives have to accept QA decisions, especially when QA has to sign off the release of a batch or clear the allowance to ship.

QA activities are mainly administrative, with some lab testing. QA staff is “white collar”, working a typical 9 to 5, 5 days a week regardless of production. Some QA authorizations are mandatory for the physical batch to move to the next step in the process. Many productions run more than one shift, up to 24/7, while QA works 1 shift 5 days a week. As a result, the paperwork relative to production batches accumulate during the QA off-period and is later flushed during QA working time.

Now here comes the first problem. The difference of working time patterns send waves of workload through the system. It is not uncommon for some production batches to wait for QA clearance in front of a process or in a warehouse. This could give the impression that the bottleneck is in the next manufacturing processing step, but it is not.

In reality the bottleneck is in QA. It can be the plain process of reviewing of paperwork or some testing, measurement, analyses, etc. A trivial yet common bottleneck is the “qualified person”, the one or few ones entitled to sign off the documents. Those people, usually managers, are busy in meetings and other work and let the paperwork wait for them.

Note that QA activities are not always extensively described in the production task lists, do not always have allocated time and if they have, QA department is seldom challenged about the staff adhering to standard time neither to possibly reduce the duration by some improvements. This can lead to underestimate the impact of QA’s activities on the production lead time and “forget” to investigate this subject when searching for the bottleneck.

Dependence on third parties

With an ever growing number of requirements to fulfill and proofs, certificates and log files to keep ready in case of inspection, many specialized tests and measurements are farmed out to third parties. It makes sense, in particular if those activities are sporadic, the test equipment expensive and maintenance of skills and qualification for personnel mandatory.

Now this type of subcontracting bears the same risks than any other subcontracting: supplier’s reliability, capability, capacity, responsiveness, etc. and the relative loss of control of the flow as it is now dependent on a distinct organization. The system’s constraint may well be located then outside of the organization, and even beyond its sphere of influence!

Beware of the feeling of being in control when the third party operates in-house. I remember such a case where a specialized agency was doing penetrant inspection and magnetic crack detection in the company. While everything seemed under control, the external experts often failed to come as scheduled because they still were busy elsewhere or had sick leave. When they were in-house, they frequently lost a fair amount of their precious time moving parts around, a kind of activity not requiring their qualification but significantly reducing their availability for high-value added tasks. It turned out that this spot in the factory often was a bottleneck due to the lack of management’s attention.

Where Value Stream Mapping can help finding the constraint

These examples above show that the information flow or paperwork associated to the physical flow can have a significant influence on lead time and can even decide if the flow has to stop.

In such cases Value Stream Mapping (VSM) can help finding the constraint as it describes both physical and information flows on a single map. Note that some companies including Toyota refer to VSM as MIFA, the acronym of Material and Information Flow Analysis.

Without such a map to guide the investigations, people on shop floor may forget to mention (or are not even aware of) analyses, tests, approvals, paperwork review, etc. during interviews of gemba walks. Experienced practitioners will ask about these possibilities when inquiring in strong standard or regulation-constraint environments.

Where the Logical Thinking Process can help

When the system’s constraint remains elusive despite all the search with previously mentioned means, Theory of Constraints’ Thinking Processes or the Logical Thinking Process variant can help finding the culprit by analyzing the Undesirable Effects at system level.

This later approach is best suited for “complex problems” when the constraint is a managerial matter, conflicting objectives, inadequate policies, outdated rules or false assumptions, myths and beliefs.

To learn more about the Logical Thinking Process and the logic tools, see my dedicated pages, series and posts on this blog.

About the Author, Chris HOHMANN

About the Author, Chris HOHMANN

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How to identify the constraint of a system? Part 1

A very common question once people get familiar with Theory of Constraints and the notion of bottlenecks and constraints is how to find them in a process. Identifying the constraint is key as the constraint, by its nature, controls the performance of the whole system.

The trouble with examples given in textbooks or case studies is that they are rather simple compared to finding the constraint in real life. This difficulty grew over time as processes got more complex, adding new layers of rules, standards and regulations. This complexity grew to an extend that many constraints remain elusive to people searching them, leading many people to be wrong when identifying “their” constraint.

Facing this kind of difficulties, readers asked me if a formal procedure to identify the constraint exists. I am not aware of such a procedure and from my experience the search for the constraint is much more like a detective’s job requiring investigation skills than applying a recipe. Some common patterns and similarities may exist, but every organization has some specificities that make the search for the constraint a special case. Therefore intuition and experience are definitely of great help.

In this series of post, I propose to review such investigations, that may help readers to transpose in their own situation, and eventually try to wrap up guidelines to identify constraints.

The usual suspects

First let’s review common bottleneck resources, keeping in mind that being a bottleneck is not synonymous of being a constraint and, as a general rule, a constraint is (and should be) a resource too long or too expensive to get more of it, or put differently turn it in a non-constraint.

A constraint was long said to be a very expensive piece of machinery or equipment which is too expensive as an investment to afford another one for additional capacity or which is not currently available.

Big stamping machines or presses, painting booth, heat treatment, surface treatment or sophisticated machine tools made good candidates for being bottlenecks and ultimately constraints.

Bad news is that things evolved, as we will see, and even if those bulky expensive or scarce equipment still make good candidates for the constraint status, they are not always the constraint.

For instance, I worked in a engineer-to-order company designing and manufacturing heavy mechanical equipment. The heat treatment was said to be the constraint and was managed by-the-book as a constraint.

After a short diagnostic, it turned out that heat treatment was not the constraint. It wasn’t because the true constraint was elsewhere in the process and those heat treatment operations could be subcontracted nearby at short notice and reasonable price. The subcontracting gave sprint capacity and provided relief whenever necessary. So heat treatment, even with long cycle times, was nothing really scarce nor excessively expensive.

Why was the heat treatment mistakenly thought to be the constraint? Because literature on the subject point this kind of process as usually being a bottleneck (remember: not enough capacity with regard to average demand placed on it). If indeed the workload often exceeded the capacity, the heat treatment was not the constraint. Failing to understand the difference between bottleneck and constraint led to a wrong conclusion.

Where was the real constraint? In engineering department where equipment are designed: people with specific skills that are long to learn.

More usual suspects

Very slow processes are usually also good candidates as bottlenecks: drying, curing, maturation, chemical or biological reactions, etc.

People with specific skills (as we have seen), knowledge, abilities, expertise, etc. that cannot easily be hired can also become constraints. So are some raw materials that are rare or dependent on harvest, climate, embargo, shortage, etc.

In some areas it is difficult to find some qualified workforce like welders, forklift drivers or specialists in some trade, which makes them constraints even so their profession is not so scarce at a larger scale.

When the constraint is not obvious nor easy to find, its identification becomes a matter of investigation. Investigation will start in part 2.


About the author, Chris HOHMANN

About the author, Chris HOHMANN

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Why is the Logical Thinking Process so hard to sell?

This is probably the greatest frustration for Logical Thinking Process (LTP) fans: why don’t more people get interested in? Why is the Logical Thinking Process so hard to sell?

Please understand “sell” with the quotation marks, I mean promote, advertise, grow the community, attract participants to seminars and courses altogether.

This post is a reflection of mine and an invitation to other LTP savvy and practitioners to share (please use comments) their analysis and thoughts.

The first reason is the weird sounding proposal to learn how to think. I got this reply of course.

Most people are convinced they are able to thinking in a logical way and don’t see the point learning anything about it. Those knowledgeable about the Logical Thinking Process changed their minds acknowledging they believed they were thinking logically until they went through the humbling experience of the LTP.

Make a clear statement that is both rationally sound and without any ambiguity is one example of the “thinking qualities” so many believe to master naturally but don’t.

Guiding an audience through a chain of causes-and-effects with rock-solid logic and in a crystal clear way is another “gift” commonly thought innate.

From what I’ve seen, everybody going through a Logical Thinking Process training course gets a lesson, regardless of how brilliant a speaker the person already was.

The second reason is maybe the jargon. Theory of Constraints (ToC) is full of jargon, metaphors and poetic names that do not help getting into it without a true motivation.

Other business philosophies and methodologies have their own lingo. Lean for instance “requires” to accept Japanese words without being a serious obstacle for its spreading.

The difference I see between Lean’s Japanese words and ToC jargon is that Japanese words are accepted because most people understand them through their translation / transliteration only. To them, those words have no other meanings that can be misleading.

In the Logical Thinking Process, “Evaporating Cloud” most people (with sufficient command in English of course) try to understand the literal sense in the context but can’t.

The Evaporating Cloud makes sense once the metaphor is decoded. It would have been so much easier to call it a Conflict Resolution Diagram (a proposed and sometimes used alternate name), which it really is, first hand.

Explanation about the sticking to the Evaporating Cloud can be read in Lisa Scheinkopf’s book “Thinking for a Change: Putting the TOC Thinking Processes to Use

Besides poetry and metaphors, acronyms are just as numerous. Take “POOGI” that stands for Process Of OnGoing Improvement in ToC’s lingo. The already popular “Continuous Improvement” was obviously not good enough and led to craft a weird-sounding new acronym, requiring more explanations and learning.

Even some ToC and/or Logical Thinking Process aficionados don’t like all the jargon, it is now the language of the ToC community and its mastery the price to pay for any new comer.

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My blog’s third birthday

January 2014 – January 2017, my blog is now online for 3 years and counts 347 posts.

Thanks to all of you my audience is gently growing on this blog, as well as on my Youtube channel and on tweeter. All organic!

What is the most read here?

According to the stats, Constraint vs. bottleneck is the absolute winner, ahead of 3D Printing and Porter’s five forces ranking second.

Then comes a string of posts related to the Logical Thinking Process and the popular Goal Tree.

What’s on schedule for 2017?

Well I have a huge inventory of titles, topics, half-written posts on the various subjects I’d like to share: Lean Management, more about Logical Thinking Process and Theory of Constraints, my prospective survey about the future of manufacturing and much more.

I’ll try to post on a regular basis and bring some value-added content. You are welcome to give me feedback in the comments.

Hope to see you here!

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Bill Dettmer and David Poveda share views about planning

David Poveda is a Colombia-based consultant, Owner and  Director of FLOWING Consultoria. David is well-known for his successful implementations of Theory of Constraints (ToC) and Lean-based solutions, and his expertise about Demand Driven MRP (DDMRP).

Just before the Logical Thinking Process training in Paris, in June 2016, he paid a visit to Marris Consulting and met Bill Dettmer. Both agreed to share thought about various subjects and in front of recording camcorder.

In this 10 minute video, David shares his views about planning techniques and somewhat surprisingly links ToC’s Thinking Processes to planning, especially Bill Dettmer’s Goal Tree .

According to David, the Thinking Processes should be called “the real planning processes“, because they are a complete planning and execution methodology. Bill is somewhat taken by surprise and explains the origins of his Logical Thinking Process (LTP) being in complex problem solving, but realizing with David’s inputs that changing what is done requires competent planning.

David goes on and explains that a Goal Tree is a planning tool for smaller projects as well, and many of David’s clients agree about not knowing how to plan. Therefore the LTP should be taught more widely.

We are all Lean now. What’s next?

Every once in a while, for nearly 30 years, the question arises: “what’s the next big thing after Lean?”, suggesting that the askers are done with Lean. We write July of 2016 and it seems that everybody is Lean now.

Many people have been repeatedly exposed to Lean methods and tools, have been involved in Lean workshops, kaizen events, sketched Value Stream Maps and identified wastes, sorted out, cleaned up and rearranged stuff 5S style.

They have seen improvements, celebrated the workshop’s success and were dismissed with a feeling of mission accomplished. Others didn’t see a clear outcome, noticeable improvement or a sustainable result and resumed their regular work.

Both may have a legit feeling of being done with Lean, the first because their objectives were met, the latter because Lean doesn’t work.

Almost everybody has heard about Lean, in good or bad, in manufacturing or administration, in hospitals or software development. Lean is a word that found its way into the business lingo, and hearing it often makes it familiar.

There is also the growing impatience as everything speeds up and the instant satisfaction sought by everyone becomes commonplace. Few people are able to commit to a very long and tedious journey towards excellence in the Lean way, most would prefer periodical quantum leaps. Just as they replace their smartphone from one model/generation to the next, keeping up with fashion or state-of-the-art technology.

Of course we are far from done with Lean and very very few companies I’ve visited can claim being Lean. Nevertheless I can understand the fading interest in Lean and the need to reinvigorate it with something new and effective.

Something new means something new to people they didn’t know about until now, not necessarily new per se. Effective means bringing positive results system-wide, not a local optimisation.

My advice would be to consider Throughput Accounting, Critical Chain Project Management and the Logical Thinking Process.

This is not about the next big thing AFTER Lean but the next big thing WITH Lean!

Throughput Accounting (TA) is not really accounting but rather a Throughput-based decision-making approach. In a nutshell, TA shifts focus from cost reduction to Throughput increase and optimization. Follow this link to know more.

Critical Chain Project Management (CCPM) revisits Critical Path Method, the prevalent project management method that failed so far to get developers and project teams to finish on time. CCPM makes sure that projects finish on time and that, thanks to continuous improvement Lean and CCPM style, project durations can be shortened in future.

Logical Thinking Process (LTP) copes with system-wide complex problems. It provides logical tools and methods to surface and neutralize false assumptions, beliefs, conflicting objectives and the like that hinders the organization achieving its goal.

Giving a try with any or all TA, CCPM and LTP, will reveal new potentials and focusing points for Lean to exploit them. Lean isn’t gone soon.


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My takeaways from throughput accounting, the book

I knew the author, Steven M. Bragg from his podcast series “Accounting Best Practices with Steven Bragg” before I came across his book “throughput accounting, a guide to constraint management” published by Wiley & sons, 2007.

Book presentation

The hard cover book has 178 pages, 10 chapters, easy to read in neat presentation and legible fonts, with numerous tables, graphs and illustrations to back up all the provided examples and case studies.
It claims to contain the tools needed to improve companies performance for accountants, financial analysts, production planners or production managers.

>Lisez-moi en français

The book starts head on by introducing the basics of Theory of Constraints (ToC) in an uncommon, and for me daring way: explaining very briefly the Drum-Buffer-Rope (DBR) logic, in chapter 1 (page 1!).

It is daring because it’s a shortcut putting DBR upfront when it’s usually presented to newbies (long) after explaining the bottleneck concept and the differences between traditional manufacturing, trying to run every resource at full utilisation rate, versus the ToC approach where “only” the bottleneck matters (this is another shortcut, but of mine…).

It goes on with presentation about the different types of constraints, not all being bottlenecks, discussing the nature of the constraint (page 5). The Throughput Accounting (TA) KPIs are presented page 7 and 8 before diving into the financial aspects of TA.

Chapter 2 is about Constraint Management in the factory, starting with how to locate the constraint and how to manage the constrained resource. The various hints are clearly targeting managers or readers keeping some distance from shopfloor as they give enough insight without being too detailed. No people will go through and get bored, the various hints are condensed within few lines, without giving up anything important.

Four pages deal with policy constraints, again something of interest for managers and readers that may have influence within their own organization to educate their colleagues about the drawbacks of some policies and hopefully change them. The importance of constraint buffer comes page 25 followed by the importance of proper batch sizes and machine setups.

Chapter 3 is about throughput (T) and traditional cost accounting concepts and starts with the emphasis on cost versus Throughput and goes on with all the consequences describing why traditional cost accounting – companies that means – is suffering from several problems.

This chapter is important for people not very familiar with accounting, especially in operations, because it explains some of the decisions that make no big sense when considered from operations point of view. It is also important for those familiar with traditional cost accounting for to understand the limitations and problems brought up by that approach.

Chapter 4 is about Throughput and Financial Analysis Scenarios and from page 59 to 86 take the readers through 14 different scenarios, from Low Price, High Volume Decision to Plant Closing Decision.

Chapter 5 is on Throughput in the Budgeting and Capital Budgeting Process, chapter 6 about  Throughput and Generally Accepted Accounting Principles and chapter 7 about Throughput and Control Systems.

Chapter 8 details Throughput and Performance Measurement and Reporting Systems, interesting because it links the operations’ reality to usable KPIs, e.g.

  • Ratio of Throughput to Constraint Time Consumption
  • Total Throughput Dollars Quoted in the Period
  • Constraint Utilization
  • Constraint Schedule Attainment
  • Manufacturing Productivity
  • Manufacturing Effectiveness
  • Order Cycle Time
  • Throughput Shipping Delay
    And more.

Chapter 9 is named Throughput and Accounting Management and addresses 12 decision areas among which: Throughput Analysis Priorities, The Inventory Build Concept, Investment Analysis, Price Formulation.

Finally chapter 10 presents 7 Throughput Case Studies each of them in a couple of pages.

My takeaways

The book is easy to read and to all concepts are easy to understand thanks to the simple ways the author puts them. Not being an accounting specialist at all, I always liked the simple, pragmatic and concise ways Steven Bragg explains accounting rules or practices. This book is not different.

Reading “throughput accounting, a guide to constraint management” reinforced both my knowledge and my interest in throughput accounting, as well as the conviction about throughput accounting being a powerful and crucial decision-making approach.

I’ve marked dozens of pages with sticky notes highlighting my points of interest and/or inspirations for posts on my blog, reinforcing my consulting approach, etc.

Throughput accounting

Almost all companies have their management heavily influenced by traditional cost accounting and most of them make ill-oriented decisions. With the book’s content help, it is easier to explain to CFOs and CEOs why their decisions are biased by false assumptions or outdated rules, something that can be quite shocking to them.

The book doesn’t come cheap, but as it explains, quit reasoning in terms of cost savings and consider how much (intellectual?) Throughput it can leverage.


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What is Throughput Accounting?

Throughput Accounting (TA) can be understood as a simplified accounting system based on Theory of Constraints (ToC) principles. TA makes growth-driven management and decision making simpler and understandable even for people not familiar with traditional accounting.

Beyond simplifying, TA has a different approach compared to traditional accounting. The latter will focus on cost control (cost of goods sold) and minimizing the unit cost while TA strives to maximize profit.

Throughput Accounting sets the base for Throughput Analysis, helping to make decisions in the ToC way.

Simplifying accounting

Throughput Accounting will probably not replace GAAP in short nor medium term, but provides a limited set of simple KPIs, sufficient to:

  • Manage and make decisions in a growth-oriented and ToC way
  • Allow faster reporting and near to real-time figure-based management
  • Help people in operations to understand the basics of accounting
  • Set a common base for controllers and operations to discuss decisions, investments, etc.

Throughput Accounting uses 3 KPIs and 2 ratios:

Throughput (T)

Throughput, defined as the rate of producing goal units (usually money) and translates as revenue or sales minus totally variable expenses in accounting terms.

Totally variable expenses can be simplified to the cost of direct materials because labor is nowadays paid on a (relatively) fixed amount per time period, hence a constant expense to be considered as part of Operating Expenses.

Operating Expenses (OE)

Operating Expenses are all expenses, except the totally variable expenses previously mentioned in the calculation of throughput, required to run and maintain the system of production. Operating Expenses are considered fixed costs, even so they may have some variable cost characteristics.

Investments (I)

Investments, formerly call Inventories, is the amount of cash invested (formerly “tied”) into the system in order to turn as much of the Investments into Throughput as possible. This encompasses the stored raw material waiting to be transformed into sellable products as well as investments in capacities / capabilities to produce more units.

Net Profit (NP)

Net Profit is defined as Throughput minus Operating Expenses, or Sales – Total Variable Costs – Operating Expenses.

Return On Investment (ROI)

Return On Investment is the Net Profit compared to Investments (ROI = NP/I).

Drivers for achieving the Goal

Throughput Accounting offers a simplified way to identify and use the drivers to achieve the Goal, assuming the Goal is to make money now and in the future.

In a very simple way this can be summarized by the following picture which means strive to maximize Throughput while minimize the Operating Expenses and Investments.

ToC practitioners recognize that Throughput has no limit while Operating Expenses and Investments have limits beyond which no safe operations can be further envisioned.

The priority focus on improving T (focusing on the constraint exploitation) rather to go for all-out cost cutting explains the (usually) superior results when going the ToC way compared to unfocused improvements.

Throughput Accounting KPIs can be presented in a Dupont-inspired model in order to make the levers and consequences clear. (graphics to come)

Throughput Analysis

Beyond the simplification compared to traditional accounting, Throughput Accounting sets the base for Throughput Analysis, helping to make decisions in the ToC way.

Reminder: in a system with a capacity constraint, the Throughput is limited and controlled by the sole constraint. As the capacity is fully used and no spare is available to exploit, what goes through the constraint must be chosen wisely in order to make the best use of this very precious resource.

It becomes obvious then that utmost attention must be paid to maximize the passing of the highest profit generating products through the constraint. The decision making is then based on the Throughput per constraint minute rate. The higher the T/mn, the better.

Other decisions Throughput Analysis helps to make are about anything likely to alter the Throughput, Operating Expenses or investments. Basically, any incremental increase of OE and/or I should lead to an incremental increase of T.

Conversely any decrease of OE and/or I should NOT lead to an incremental decrease of T.


This post is partly inspired by the work of Steven Bragg. I recommend his blog and post about Troughput analysis http://www.accountingtools.com/throughput-analysis


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Schragenheim’s concise history of constraints

The definition of a constraint in Theory of Constraints (TOC) has varied as the corpus grew and matured. Still today it is confusing for newbies to sort out what is meant with “constraint”, depending how they got their basics in TOC.

Thanks to Eli Schragenheim, one of TOC’s founding fathers, and the related post on his blog, the reader can understand how and why the definition varied over time.

I strongly recommend to read Eli’s post: A concise history of constraints