Impact of more than one Constraint - 5

Alan Barnard (at the 2006 TOC-ICO conference) asked the question whether the simple Throughput per Constraint Unit rule is valid with 2 (or more) overloaded resources. Alan used Eli Goldratt’s P-Q thought experiment for his discussion. His question is important because it is common to see businesses reduce ‘excess’ capacities to balance (or almost balance) capacities. The practice often results in two) or more concurrent constraints or ‘almost’ constraints. Since 2006 I have observed several factories that wonder why their output collapses below the theoretical capacity of their (almost) balanced lines.

I plan to show that that the Throughput per Constraint Unit rule continues to be valid using the same P-Q thought experiment. I also want to discuss this result in relation to the real World – how should companies manage resource capacities.

I would like readers to follow Eli Goldratt’s recommendation that they solve the problems – before I provide the solution and before my discussion of results. The learning experience will be greater and readers should be better able to discuss and critique my conclusions. If you are familiar with the thought experiment you can jump to the second part of this article.

The key part of the article comes at the end when the solution used in the P-Q thought experiment is discussed in relation to REALITY. The thought experiment should not lead managers to an easy solution. The tool is useful but requires thought and care.

 

Reality

 

As Eli Schragenheim[1] says, “The problem is not mathematical, the problem is the assumption reality is linear.” AND, a second problem is the assumption that “reality is deterministic”.

 

The real World is of course quite different from our thought experiment. In a real situation, customers will not allow their suppliers to dictate what they buy. Customers will not wait to buy Q because we want to make sure all the P demand has fulfilled (the original P-Q experiment). In reality we are unlikely to ever achieve the optimum. This is especially so when you consider that a business does not sell just 2 products, but more likely in the hundreds if not thousands of products. So forget about ever reaching the optimum.

 

BUT, is it still possible to move sales in the direction of better constraint utilisation?

 

In a real example, a business protects their engineering constraint by favouring the sale of standard products requiring no engineering. Their second favourite products are those that require only a small amount of engineering. Their annual sales have always been, and still are, limited by engineering. However, since their sales focus has changed the maximum possible annual sales have increased and, in turn, the business has become more profitable. Added sales are realised without the need for added to operating expenses. All that happened is sales of those items that do not need (much) of the constraint have increased significantly – without creating a new second (interactive) constraint.

 

Another example of using the Throughput per Constraint Unit as a tool to help decide what to sell is the Aramid fibre business (Kevlar®, Twaron®, Technora® are examples of brand names). A wide variety of aramids are produced with different structures and different fibre strengths (different decitex or weight per 10’000meters). Not only do many different varieties exist; aramids are also used in many different applications like sailcloth, ropes, filtration, tires, brakes, protective clothing (bullet proof vests) and more. Prices will vary from application to application and, of course, the price per unit of weight varies according to the decitex of the product. Since the various applications are so different, the sales and marketing organisation is divided into profit centres – each competing for supply. All this would be no problem until the factory is sold out and product must be allocated to customers.

 

A business can allocate fairly – give everyone the same relative amount less than they need; a difficult thing to do since clients catch on quickly and will order more to protect their business. The aramid supplier can also look at his product line and favour those products with the highest Throughput per Constraint Unit. (There is a fair chance that the most favourable or unfavourable products are not those with the highest or lowest margins.) He can also use the situation to target those customers that pay the lowest price in terms of Throughput per Constraint Unit and raise prices in those markets; higher prices tend to reduce demand or the client realises that, higher prices are justified.

 

The sales organisation needs to know the situation in relation to Throughput per Constraint Unit. They cannot switch away from clients and markets or raise prices as easily as I write this, but they can have a tool to help decide what they should do; where they should focus their sales and pricing efforts for greatest benefit.

 

Throughput per Constraint Unit is a tool to help decide what to do. Other considerations are part of the decision – including things like the importance of certain clients. When multiple profit centres are involved the tool can help resolve which of the profit centres should get preferential supply.

 

Eli Schragenheims work to develop a decision support system may well become the tool for business managers to use. (see footnote.)

 

Conclusions

 

1. The simple Throughput per constraint unit does not always work, so be very careful (think carefully) when you believe you should be using it.
2. The 5 focusing steps remain an excellent guide to manage a business. They do not absolve management from some critical thinking about how to approach initiatives to increase sales or to improvement operations.
3. Many companies, by trying to balance capacity for cost reasons, will often leave a lot of money on the table. Judging how much money is left on the table is not an easy task. It is easier to decide to have just one constraint and to decide where the constraint should be. The lost sales, Throughput and profit due to balanced capacity can far outweigh the additional cost for just one constraint or even the additional cost to move the constraint into the market.
4. Throughput and the impact of decisions on Throughput should take precedence over thinking about and taking actions to manage (reduce) inventories and/or cost. (A business is here to make money, not to save cost. If you want to save cost, do not start a business!) BTW – that Throughput should take precedence does not mean inventories and operating expense are unimportant.
5. To think about what to sell (what to favour when selling) is a discussion that involves most of a business. Finance and controlling should lead the discussion. Sales and production are key participants. The managing director should probably also participate – after all some pretty key decisions will be proposed and made during such a discussion. To do this, scenarios must be built based on experience, knowledge and intuition about the constraining elements and the direction and opportunities in market demand. Such scenarios can be built and compared (see Eli Schragenheim’s work with his DSTOC software).
6. So far the sales and operations planning process was not mentioned in the article; but this process, if it exists in the company, is a good place for such discussions. A good place as long as the appropriate participants are present, as S&OP design says they should be.

 

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[1] Below are 3 article titles in relation to Eli Schragenheims thinking and his work in the area. They are found on his blog (https://elischragenheim.com/) that is well worth reading. Look for the following article titles: 1.) The Non-Linear Behavior of the Cost of Capacity; 2.) Is it really an opportunity? and 3.) The TOC Key Decisions Support (DSTOC).

After the portage around one of the waterfalls on the Manicougan River. ca. 1958 

Impact of more than one Constraint -2

Solving the P – Q Experiment

Alan Barnard (at the 2006 TOC-ICO conference) asked the question whether the simple Throughput per Constraint Unit rule is valid with 2 (or more) overloaded resources. Alan used Eli Goldratt’s P-Q thought experiment for his discussion. His question is important because it is common to see businesses reduce ‘excess’ capacities to balance (or almost balance) capacities. The practice often results in two) or more concurrent constraints or ‘almost’ constraints. Since 2006 I have observed several factories that wonder why their output collapses below the theoretical capacity of their (almost) balanced lines.

I plan to show that that the Throughput per Constraint Unit rule continues to be valid using the same P-Q thought experiment. I also want to discuss this result in relation to the real World – how should companies manage resource capacities.

I would like readers to follow Eli Goldratt’s recommendation that they solve the problems – before I provide the solution and before my discussion of results. The learning experience will be greater and readers should be better able to discuss and critique my conclusions. If you are familiar with the thought experiment you can jump to the second part of this article.

The key part of the article comes at the end when the solution used in the P-Q thought experiment is discussed in relation to REALITY. The thought experiment should not lead managers to an easy solution. The tool is useful but requires thought and care.

Most of us ‘solve’ the problem without much thinking. It’s like a simple arithmetic problem from grade school. From groups we usually get quite number of ‘wrong’ answers – some from arithmetic mistakes, some from faulty thinking. Below you will find the answers from inadequate thinking and the explanation for the ‘right’ solution.

Attempt 1:

Many do not check whether or not my factory has sufficient capacity to produce all the Ps and Qs. They do not identify the constraint. These people, barring arithmetic errors come up with the answer shown below – 1500€ profit per week. That would be nice, but why would I ask a consultant for help? The constraint makes it impossible to earn 1500€.

So, let’s find the “Find the constraint!”

The table below identifies it.

Clearly the B machine cannot produce all of the necessary components for both P and Q. We need to decide how many Ps and how many Qs we can produce (the optimal mix) to maximise profit. B is the constraint and, in this case, also a bottleneck.

Attempt 2

Those that found the bottleneck usually ask things like ‘Can we buy another machine?’ or ‘Can we use overtime?’ For the purpose of the experiment no additional machine and no overtime is possible. The job is to maximise profit within the given parameters. To expand capacity by either overtime or adding a machine would mean we jump questions 2 and 3 of the 5 focusing steps.

Step 2 of the 5 steps is to decide how to exploit the constraint (our bottleneck). Most people, from high school students to CEOs, will check at least some of the following to see which product is the more profitable and should be favoured by the constraint:

1. Which product has the higher price?  Q (100 vs. 90€ for P)
2. Which product has the higher contribution margin (Throughput[1])?  Q (60 vs. 45€ for P)
3. Which product requires the least amount of effort to produce it?  Q (50 vs. 60 minutes of effort per unit of P)

Based on these 3 checks it looks like Q is the better choice. Most people choose Q as the more profitable product. We should, therefore, produce all the Q (50) and fill our bottleneck’s capacity with P sales.

If we sell 50Q we consume 1500 minutes of B capacity (2, 15 minute operations multiplied by 50 units of Q). We have 900 minutes of B capacity left – enough to produce 60 P units. The table below shows our result.

Not so good! Despite using commonly practiced checks for product profitability we generate a loss. Is this the best we can do? Might there a better way to decide what we should produce?

We did not apply the second of the 5 focusing steps correctly. The 3 checks we made had nothing to do with deciding how to exploit the bottleneck machine B. Maybe we should ask: How long does it take B to create 1 € of Throughput? How many minutes of B do each of our 2 products P & Q to require produce 1€ of Throughput?

• Q Throughput is 60€ per unit. It takes 30 minutes to produce this Throughput. Producing Q our resource B delivers 2 Euros of Throughput every minute. It takes 30 sec. of B’s time to produce 1€.
• P Throughput is 45€ per unit. It takes 15 minutes to produce these Euros. Producing P our resource B delivers 3 Euros every minute; it takes only 20 sec. to produce 1€ with P.

Shouldn’t our decision be to produce the product that delivers the greatest number of €s per unit of time available at B (the constraint; the limiting factor for Throughput)? (Alternatively shouldn’t the decision be to produce that product with which B delivers 1€ in the least amount of time?) If yes, then our decision must be to produce 100 P and 30 Q (100 P consume 1500min of B capacity, leaving 900min for Q. Since one Q requires 30min of B capacity only 30 can be produced). The table below shows the result.

 

It looks like we have found a nice rule to determine what we should sell when a bottleneck exists. Throughput per constraint unit will tell us which product to favour – bearing in mind that our customers and our markets may not allow us to reach the theoretical maximum.

During Alan Barnard's presentation in 2006 he raised the question whether this nice simple rule (deciding based on Throughput per Constraint Unit) always works. He introduced a second constraint (at D) and asked how much we can produce now that two constraints are active at the same time. Is our simple rule still valid? If not, can we adapt the rule so that (sales) managers continue to have something simple on which to base their preferred product mix? The next post will show the P Q thought experiment modified for a second constraint at D.

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Chateau Frontenac, Québec City,  May 1954, 

[1] Throughput = the rate at which we make money = sales less totally variable cost (usually just materials).

The CEO’s Mission; The CEO’s Concerns

The CEO’s mission is to make sure his enterprise is ever flourishing. The criterion for ever-flourishing companies is to grow and be profitable far into the future, to always satisfy their customers and, achieve and maintain both satisfying and secure jobs for their employees.

The CEO mission is easy to define but it is an extremely challenging target. What should CEOs concern themselves with in order to achieve this very ambitious target?

Make Money Now and More in the Future

What is the key factor that blocks a CEO’s business from making more money? What might the core problem be that leads a newspaper like the Guardian to write t

hat senior executive remuneration is absurdly high and that many of those chosen for top jobs are ‘mediocre’?

A lack of intelligence cannot be the core problem – almost all senior executives are very smart. Their results or their performance may be mediocre, but intelligence, they do not lack. So, what blocks their performance, and what blocks their companies from achieving more of their targets? 

What is a CEO’s mission?

Whatever vision, mission or goal an organisation (a business) has, it cannot pursue it without sufficient money. Cash flow, profit and return on investment now and more in the future are essential for any enterprise to flourish. It is obvious this necessary condition must be fulfilled, along with satisfying customers and ensuring satisfying and secure jobs for employees. What is not so easy is to fulfil are all three necessary conditions at the same time, forever. To fulfil them is, however, the mission of every CEO and his management team.

Initially my focus will be on the first necessary condition for success – to ensure growing cash flow, profit and return on investment. (If a CEO can generate enough cash flow, profit and ROI, without alienating his team, he will have the means to pursue the other two necessary conditions.) To focus on the bottom line a CEO must first be dissatisfied with his company’s current levels of cash flow, profit and return on investment (independent of the glowing reports found in the annual report).     

What blocks Businesses from making more Money?

(Now and in the Future)

The core of this CEO problem and for almost all businesses is an, apparently, wrong assumption about what a business is. On the one hand all managers know that a business is a system of interdependent departments, divisions and groups. On the other hand many policies, reports and key performance indicators (KPIs) are aimed at one department or division at a time; most policies, reports and KPIs focus on the decisions and actions of one or at best just a few departments. The way a business is managed is therefore at the local level; as though departments and divisions are independent of each other – the actions of one, it is implicitly assumed, does not affect the performance of another. Every manager and department is asked to focus on his local environment to improve it. Local optimisation is the rule; global optimisation, unfortunately, is not.

The World is not quite so black and white. Most business is managed by some sort of a compromise – a bit of global optimisation and a bit of local optimisation. I believe local optimisation is, in fact, the way most businesses operate most of the time. Are such compromises the right way to operate? What is the cost of compromise to the bottom line? To begin to find out the cost of these compromises, what does the dilemma or conflict, the reason for compromise, actually look like? 

It is probably safe to assume that CEOs, and his managers, want to lead their company to become an ever flourishing one, now and even more so in the future.

To achieve this the CEO needs, on the one hand, a set of simple policies and key performance indicators (KPIs) to guide all levels of managers and employees to make good decisions for their division, department or area – the manager’s area or responsibility and expertise. These departments must be competent effective and efficient in what they do – be it production, research and development, sales or any other function. The CEO needs departments that all do an excellent job in their area of responsibility – he expects them to optimise locally. This side of the conflict is usually managers’ focus. 

On the other hand departments are interdependent. To deliver the desired bottom line result they must work together in an aligned and coordinated way. It is very easy for any department to take a decision that on the surface seems to make a lot of sense but, when the decided action is taken, damage to another department’s performance is the consequence. Whenever this happens the company’s bottom line is at risk – actually the bottom line usually suffers. Instead the CEO needs all departments to optimise in a way that does not damage those few factors (production capacity, or market demand for the company’s products, …) that limit the bottom line. The CEO not only needs his department managers to keep the bottom line in mind, but he needs them to act in a way that optimizes the bottom line. He needs his department managers to be an integral part of the company’s global optimization.

Departments should therefore optimize both locally and globally, at the same time. To do this will certainly trigger conflicts within and between departments depending on how each individual department or division is measured.  On the surface it’s an easy decision to optimize globally – the rule would be to, “always do what is good for the company as a whole”. Under the surface, within all the departments, the situation is as clear as mud! How can a manager somewhere within the company have enough knowledge and insight into the workings of the company to always be in a position to take the right decision? ERP systems may have the necessary data within them; the necessary information is not generated and does not reach the managers that need it.

The following diagram describes the conflict:

 As described above both needs are valid; for the company it is important that both are fulfilled.

The wants are in conflict. It is apparent both wants cannot easily be achieved concurrently. The Wants are in conflict but that should not be the situation because both the Wants are there to fulfil an important valid need.

 

What are my assumptions for the reasons the two Wants are in conflict? There are several and you may find more:

1. Very often top management’s KPIs are in conflict with local department or divisional KPIs.
2. In most companies managers at the local level do not have the necessary information to be able to make the right decisions for the company as a whole. Usually the information available to them is only about their immediate environment.
3. ERP systems, despite the huge amounts of data they contain, do not supply the necessary information for managers at all levels to take the right decisions for the company as a whole.
4. In many companies policies, rules, culture and organisation structures exist that lead to conflict situations between departments.

These 4 are possible explanations for the CEO’s problem (or conflict) over global vs. local optimisation. 4 Examples may illustrate the situation better.

1.     Top management’s KPIs are in conflict with local KPIs:

Top management KPIs are things like cash flow, profit, ROI coupled with things like the per cent of sales and profit that comes from the last 3 years’ new product introductions. On the other hand at the local level departments like R&D or production have efficiency or cost reduction KPIs. Efficiency or cost KPIs will usually cause managers to make sure all    resources are all working productively. The consequence of efficiency as a goal is often factory overload (very high work-in-process levels) leading to both high inventory levels and shortages (because switching between products lowers efficiency) and ultimately damage to CEO KPIs. Inventory levels, profits, cash flow and return on investment are all impacted negatively.

In R&D the need for efficiency causes managers to launch too many projects in an effort to keep everyone busy (and ‘effective’). The consequence, as shown by Little’s law, is both a loss of capacity and of speed. Both losses impact hurt the CEO’s bottom line.

The graphic to the right illustrates the situation. Many (most) companies operate in the pink ‘common practice’ area and suffer the consequences in longer lead-times, reduced capacity and as a result of these 2 effects poor due date performance. The problem stems from KPIs, like efficiency, which cause departments[1] to overload their resources as the graphic shows.

The impact of lost sales due to overloading production can be enormous. By moving from too much WIP to the sweet spot a company can produce additional volumes without adding any cost. If this added production could be sold the impact to the bottom line is sales less (just) materials cost – a major incremental benefit. Just 10% more sales increases a 6% bottom line to about 11% (assuming materials are 50% of sales). This is huge!

It is part of the CEOs mission to make sure local KPIs (that he and his management team set or agree to) do not damage his (and the company’s) KPIs!

2.     Local Managers do not have access to the Right Information!

Aramid fibres are used in many applications from tire reinforcement, to reinforcement for optical glass fibres, to sailcloth, ropes, filtration and more applications. Fibres such as Aramids are produced in many different fibre diameters (the unit of measure is decitex – the grams of fibre per 10’000m). In the factory the limitation in terms of kilos produced depends either on the flow of polymer or the flow of fibre in the spinning process.

In the businesses concerned each application is a profit centre and all of them compete for product from the same factory. All have different profit margins based on calculated production costs and the market prices. If the factory is sold out –all of the profit centres will fight to get enough to meet their demand and fulfil their forecasts. But which of the profit centres should be favoured in order to maximise the overall business profit?

Should the fine decitex products that have much higher margins vs. the heavy decitex products be favoured? Is the profit margin the right criterion? If not, what is, and do the profit centres get the appropriate right guidance?

In this case all the managers have are profit margin and contribution (sales less materials cost) margins. But, when the factory is sold out, this is not enough. They need to know how effectively, in terms of the bottom line, the factory’s capacity is used; they need the contribution per machine hour (or, possibly, factory hour). This is the absolute margin earned by a product (or sale) per hour of the constraint machine (or factory). A fine decitex takes a long time to earn its margin while a heavy one earns it quickly. Without this sort of information the profit centres are likely to make the (common) error of preferentially selling the apparently high margin product that actually delivers less to the bottom line.

For the CEO to fulfil his mission he must make sure profit centres have the right information at the right time (a factory is not usually sold out all the time). His profit centre managers must be in the position to maximise the Throughput (the same as contribution used above) of the constraining element (for the company as a whole). To do this he needs those people with the capability to develop the necessary KPIs that truly align every profit centre with a CEO’s bottom line targets.

The example talks to the need for sales to sell the right products to maximise Throughput. There are other situations that need proper clarification and better information for managers to take the right decisions.

In many (most?) instances managers of a department have no choice but to optimise locally; they simply do not have the necessary information and decision rules to operate any differently.

(Industry 4.0 is coming. Will it solve this problem? The potential exists but a big part of making Industry 4.0 a success is the necessary change to management practice.)

3.     ERP systems are no help; but they could be!

There are many examples of situations such as that described in the section above. The data necessary to generate the required information for the right decisions exists, to a large extent, within ERP systems. The necessary information could be made available but generally common practice prevents its generation. Is the view is not worth the climb? The example about misaligned KPIs should be powerful enough to at least indicate to CEOs that the potential is or can be huge. CEOs have the power to cause the necessary upgrades to their ERP systems and make the right information available for all those managers and employees that could make good use of it.

Employees will be a problem. For so long, their only option has been to optimise locally. They probably have (very) little aptitude and knowledge how to think about the company as a whole – let alone evaluate their local action’s impact on the company. Whenever I ask a manager about another part of the company I get either no answer or some sort of wild guess. Its very much like most of the World’s population that, despite the best efforts of the BBC, CNN and others, has no idea what its really like to live and work in other countries. The CEO’s job will be to get everyone into the new mind-set (or new paradigm); one that requires all of us to understand our roles for and our impacts on the company as a whole.

The concepts are not difficult to grasp – they are (just) common sense. Nevertheless managers at all levels will need coaching to get them over the hump so that they can always decide in favour of the company. Inertia is the barrier to rapid and sustainable change because once something is learned it becomes a paradigm and is then difficult to shift. Old paradigms must be shifted and not just by a little bit. CEO’s have it in their power to cause paradigm shifts – by leading the change together with their C-level colleagues. The C-level team’s leadership is key for the necessary change.

4.     Assumptions, Policies, Rules, KPIs, Culture, Structure

A CEO arrives in his job with experience, knowledge, a set of assumptions, and paradigms he acquired in his previous jobs. All of these are obstacles to change because paradigms are generally not questioned – there is simply not enough time in a day or month to question them all since a CEO has so many things that concern him. He is bombarded with problems and decisions from both internal and external sources – not to mention the various official duties he may have. A CEO solves, somehow, conflicts such as what products should be sold – to optimise production or to generate the highest sales volumes and margins. Often such problems are solved with a (less than optimal) compromise because both departments get half a win. In the end nobody is truly satisfied.

If a CEO solves such a problem in the way just described he is likely following an assumption about the importance of maintaining motivation; although I wonder how motivating such compromises really are since ‘in the end neither department can be satisfied’.

The important word is assumption. Based on what he knows the CEO has a collection of assumptions (or paradigms) that determine how he will behave. His paradigms are the necessary shortcut essential for him to manage given the stresses and volume of work he faces. Without them his job would, for time reasons, be impossible. With paradigms, especially if their validities are not questioned, his mission is just as impossible to achieve because many paradigms, if not wrong, are inadequate for his job. He cannot achieve his mission.

On his own a CEO cannot develop the appropriate policies and KPIs – he is too busy. He needs someone that understands the need for and how to get global optimisation. He must give this person the freedom and necessary time to craft both the new policies and the related KPIs. The management team and the company as a whole must review these KPIs – do they really support the company as a whole; do they give the correct guidance to all departments? Everyone should have the possibility to input from their different perspectives in order to test the new policies that should guide the company to optimise globally, and leave local department optimisation behind.

Products and Services are “Created Equal”

What our competitors and our company offer to customers is all about the same. In most cases not one of the competitors in our industry has a sufficient enough competitive advantage to gain market share or to realise better prices. All of us suffer declining prices as our customers take advantage of this situation. We all have no choice but to match ever-lower prices in order to maintain market share and contribution to our bottom line. More and more our focus is cost and efficiency. We are forced to reduce cost to survive with ever-thinner margins. More and more our ability to invest in the future through better (production) equipment and new products is compromised. Without a miracle we may soon be out of business.

This sounds dire. It is probably the truth in more industries than we think. Look at Apple and Samsung smartphones. Are they, in reality, much different one from the other? For the average user it probably makes no practical difference which smartphone he or she has. For most other industries the differences between products is probably even smaller than this example. Product differentiation is often not the key factor to gain market share. In most industries, if a product differentiation is achieved, competitors will almost always catch up very quickly.

How can your company achieve a decisive or (even better) several decisive competitive advantages so that your (the CEO) can achieve his mission – a truly ever-flourishing business? The answer must come from effectiveness, speed and reliability from the company’s key departments.

Finance, Key Performance Indicators and Policies

Cost Reduction

A consequence of the described situation is pressure on cost (by Finance). Clearly every bit of cost we can eliminate from our operating expenses will help improve the bottom line. True, if the cost reduction does not cause Throughput[2] (or sales) to decline. If Throughput declines the effect of a cost reduction can easily be negative – for every sale lost the corresponding Throughput (or contribution margin) will be lost from the bottom line. (A 5% turnover loss wipes out a 5% cost reduction for a typical company.)

Common practice favours cost reduction over the possible (but uncertain) impact on sales and Throughput. Maybe this is because we can define exactly the cost to be reduced (the advertising we stop, the people we fire etc.) while it is very difficult to predict the impact on sales and the reasons for this sales impact. Nevertheless Throughput is very real and somebody must make the judgement call of any decisions impact on Throughput and therefore on the bottom line.

We recommend companies to look at a contemplated decision’s impact in absolute numbers – sales, Throughput, operating expenses and profit. The CEO’s role and responsibility is to make sure Finance and the company’s managers evaluate their decisions based on the effect on Throughput, Operating Expenses and Investment, not just the impact on one department! Following this recommendation will tend to help a company maintain and even increase market share. It will help the company focus more on those things that do increase sales and market share. It does not diminish the importance of cost; it does increase the importance of Throughput and Inventory relative to cost.

Efficiency

All managers want to apply their resources efficiently. “A resource standing idle is a major waste”; so managers will try to make sure everyone is busy working on something (at least apparently) useful. Concurrently all employees will want to be busy – after all they are as aware of cost pressures as managers. If employees are not busy (not seen to be busy) then they feel their jobs are no longer secure.

The damaging consequence of everyone and every machine working “all of the time” is factories to fill up with work in process that will slow the production process down, make the factory unreliable and deteriorate quality. The chaos that reigns on the shop floor reduces a factory’s capacity and correspondingly increases unit costs – especially as sales are lost due to longer lead-times and greater unreliability.

The CEO’s role is to make sure work in process is never above the optimal range that ensures lead-times are low, production can deliver reliably on time and capacity is maximised. If a CEO is able to do this, his company will eventually gain sales and market share with little or no added cost. Share gains have the added benefit of weakening the competition. Good reliability and shorter lead-times also will result in less price pressure from the market. This advice (ensure the optimal level of work in process[3]) holds true for all areas of a business – not just production.

Efficiency is often measured based on tons/hour (steel); square meters per hour (films, paper; units per hour etc.) or, in the case of sales, the number of calls sales people make. In the good old days of X-Ray film production factories produced film large enough to X-Ray an entire thorax as well as tiny films for dentists to X-Ray your teeth. Factories measured production efficiency by the number of m² produced in a shift. Since film for dentists was (is) inefficient to produce, production supervisors would postpone dentistry film for the next shift or until someone started yelling very loudly! In steel factories thick steel plate is much more ‘efficient’ to produce (in tons/hour) than thin plates – so there is usually a surplus of thick and shortages of thin plates.

The CEO’s role is to make sure the load on a factory is limited to a maximum amount where production capability and lead-times are optimal, and there should be no more in stock than required for the near future. Production must not steal capacity from one product in order to produce too much of another. To produce more than immediately necessary might improve efficiency numbers, but it often steals capacity required for (much) more urgent and real demand.

Efficiency is important but only if sales and Throughput are not blocked and only at the constraint – the factor that limits the businesses capability to produce Throughput. If a business has plenty of production capacity, then it may be that the efficiency of the sales organisation should be improved. How can more orders and market share be gained? Sometimes (often?) sales people are hampered in their efforts by the factory’s drive for efficiency!  If a factory’s delivery performance in terms of lead-time and due date reliability is poor, no wonder sales have a hard time convincing customers to buy. Conversely, if all competitors’ performance is equally poor, then the one company that improves lead-time and due date performance significantly will almost certainly emerge as a winner. This company’s sales and margins will improve, at least until competitors catch up.

Engines of Disharmony

While I hope that all of the above might make sense to you, a lot of it is the opposite of common practice. In fact it is often the opposite of what managers and employees think is expected of them. In today’s business World there are constant pressures to improve – efficiencies must increase, costs must decline, inventories must be minimized, due date performance should be perfect and lead-times short. Almost everyone sees the conflicts between the first two (efficiency and cost) and the rest. People have no choice but to compromise. The 3 quotations in the box above indicate what many smart people think about the value of compromises.

In fact these diverging pressures lead to Goldratt’s  “engines of disharmony”. These “engines” are:

1. Not knowing my own required contribution to the goal or how my contribution will be measured and recognized.
2. Not knowing others’ contribution or how their contribution should be measured and recognized.
3. Organizational conflicts about which “rules” to use to best achieve organizational goal(s).
4. Individual conflicts due to unresolved gaps between responsibility and authority (e.g. resulting in firefighting).
5. Inertia or the fear of failure blocks necessary changes to achieve ongoing improvement.

Lets assume a manager (CEO) decides to implement the suggestions from above. Unless the reasons for the change are explained very well these engines are likely to be active and prevent the desired progress. If old rules are not modified correctly then despite good explanations the engines will be active – especially if many ‘old’ rules support the efficiency syndrome and pressures on cost. The rules need to change so that Throughput becomes the top priority (without making inventories and cost unimportant) not some unsatisfactory compromise between sales increases and cost reduction.

The engines of harmony the CEO and his company need to achieve are:

1. Employees know exactly how they should contribute and how their contribution will be measured and recognized.
2. Employees know exactly how others should contribute and how others’ contribution will be measured and recognized.
3. Systematically align “rules” with goal of the organization (replacing local/short term optima with global optima rules).
4. Systematically close gaps between responsibility and authority, using “firefighting conflicts” to trigger improvements.
5. Processes, skills and culture are improved continuously by exposing inconsistencies and challenging basic assumptions.

To create harmony in an organization will require a considerable amount of thought by the CEO and his management team. Changes such as those suggested will cause uncertainty and resistance. Employees will evaluate management’s actions In relation to their experience and their personal criteria. Resistance to the changes can be expected. This resistance is caused by employees’ evaluations about the proposed changes – including all the misunderstandings, all the experience they have from the past and how they evaluate the proposed changes in relation to their person (“what is in it for me”). To prepare for the change management might look at the situation from the 4 quadrants of (resistance to) change.

1. “The pot of gold” symbolizes the expected benefit (for everyone involved) the CEO and management see from the proposed change. (The company will become much more profitable with positive consequences for both employees and customers.)
2. “The crutches” symbolize the potential damage that may be the consequence of the proposed change.
3. “The mermaid” symbolizes what employees like about the current situation – it might simply be that they know exactly what to do in their job and as a result they are comfortable and do not want to change.
4. “The crocodile” symbolizes the consequences of not making the proposed change. If we do not make the changes then competition will … (All major automobile manufacturers see Tesla electric cars as a crocodile and consequently are developing their own electric cars.)

These four perspectives of a change are important in order to build acceptance throughout the company. The ‘inventor’ of the change (the CEO) is likely to be focused on the pot of gold and may ignore the other quadrants – except as they relate to him. The CEO must not forget that his managers and employees also have 4 perceptions of the change and these perceptions will not necessarily be the same as his.

Summary

Major opportunities exist for CEOs to fulfil their mission. Current common practice tends to block companies from realising this potential. CEOs and their managers need to move away from efficiency and cost focus everywhere, to a strong focus on Throughput first. If they do they will soon realise the powerful effect gaining Throughput can haves on their bottom line (not to forget the impact on cost and efficiency!).

Not only are their opportunities for CEOs to achieve their mission, tools exist to help them think about and design their successful change strategy and implementation tactics. The tools are useful frameworks to think about the many consequences and how both customers and employees will perceive them.

CEOs and companies that successfully implement the suggested changes should expected significant jumps in performance – not just a few percentage points, but double digit ones. (When implementing their change a CEO and his employees should record their expected outcomes, check their results against these and take appropriate action as a result of any deviation(s))

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[1] We mentioned production and R&D, however, the effect of too much work in process causes the same damage in other departments – sales often chases too many ‘skirts’ (potential customers) and, due to too much WIP, misses out with too many opportunities.

[2] Throughput = the rate at which we make money or Sales less Totally Variable Costs (usually just materials). Many times Throughput is called contribution margin. We use Throughput because contribution margin, can an often is, defined differently.

[3] The optimal level of work in process (WIP) cannot be determined deterministically – there are too many variables and too much uncertainty. Happily the peak area is relatively flat so a good enough guess at the level of WIP is the way to go. Just do not starve your resources with too little work. The risk of too little work for resources is small since a) only the constraint should be close to a full load and b) the efficiency paradigm will not disappear easily.

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Your Businesses Potential

Check yourself against these 5 criteria. If you are not well in the green on them you probably have significant potential for bottom line improvement.

Global vs. Local Optimisation

Experience has shown us that most businesses behave in a way that indicates they believe that optimizing all the components of a business will optimise the whole. In most businesses departments and functions are given goals to optimise their performance which, if managers want to progress, will pursued to the maximum of these manager’s ability. Unfortunately we know that this practice leads to conflicts between and among departments and functions. These conflicts are not open war; they simply result in most if not all functions and departments not meeting their targets and the business as a whole is certainly not optimised.So, where does your business stand on the scale between local optimisation (all departments seek to optimise their performance) and global optimisation (all departments seek to optimise the businesses performance? Rate yourself on a scale of 1 (local optimisation) to 10 (global optimisation).

Aligned Key Performance Indicators

Frequently we see Key Performance Indicators (KPIs) that give the organisation mixed signals. For instance: Production should on the one hand achieve the lowest cost position and on the other hand they should support sales by excellent due date performance and short lead-times. Since these are often incompatible production will favour whichever KPI is the bosses favourite. A similar situation for production is the need for lowest cost and the lowest possible inventory levels. Sales of course wants perfect due date performance and short lead times which conflicts with production’s need for lowest cost.Are your Key Performance Indicators aligned across all departments and functions? Or do your KPIs cause conflicting situations between and among departments and functions. Where do you stand on the scale? Please rate yourself.

Your Limiting Factor(s) (Constraints)

Experience has shown us that most businesses have not recognised their limiting factor or constraint. When we speak with a business we often hear about many constraints and constraints that move about from one resource to another.Systems thinking and the Theory of Constraints tell us that any system of interdependent entities (like a business) can only really have one constraint. In any case only a very few constraints are possible (just like a chain can have only 1 weakest link).Since most businesses have not identified their weakest link (the limiting factor or constraint) it is unlikely they will have decided how to get the most (for the bottom line) from this constraint. These businesses will almost certainly have not aligned the rest of their company to the way they want to exploit (get the most from) their weakest link. Such businesses are missing opportunities for profit! Your business may be different. Please rate your business on the scale according to how well the entire organisation is aligned to get the most from your limiting factor or constraint (which might be operations, sales, R&D…). Properly deciding how to you want to get the most from your limiting factor and aligning your organisation to that decision can be very beneficial to your bottom line.

Reliability

Many businesses are not as reliable as they could be – delivery performance (products or projects) is not near perfect or product availability in warehouses or shops leaves customers dissatisfied. Our experience indicates that businesses within an industry generally perform at more or less the same level of reliability. If the industry as a whole is relatively poor every company has a significant opportunity to gain market share.Please rate yourself on the scale. It runs from 50% due date reliability (On Time In Full) to 100%. The further away from 100% you are, the greater your potential.

Effectiveness

Effectiveness is defined as doing what is supposed to be done and NOT doing what should not be done. Work In Process (WIP) and inventory levels are an indication for Effectiveness. Too much WIP (and thus long lead-times) indicates that work-orders are released into production too soon or projects are released to the organisation too soon. The result is a chaotic environment with unclear priorities and long lead-times. Inventories in the supply chain are indications of the same problem and the practice of producing in large batches (usually due to pressures to reduce cost). Big production batches are likely to block capacity for items that are needed now while a significant part of these batches will not be required for many weeks and months.Please rate yourself on this last scale. This rating is a bit more difficult because some inventory to buffer for uncertainty and unreliability is essential. Zero-inventory is not a good idea – it will lead to poor customer service. Moving inventory to suppliers or customers is simply a question of ownership – it does not change the effectiveness question.

Summary

If you have rated yourself in the deep green for all of these, then you are very likely to be in a powerful position in your chosen markets. Your performance towards clients is excellent, your cost structure is in great shape and because of your reliability you are unlikely to be under much cost pressure. Your profitability will be more than acceptable.If you have rated yourself in the deep green and the results I expect (the above paragraph) are not evident there is a good chance you are fooling yourself with your rating. I would look at each scale again and think deeply about the reality within your company.If you have rated yourself somewhere in the yellow or even red, then your business has considerable scope for bottom line improvement – even if your business is doing well today.
If you would like to evaluate the size of your potential we have a one page Excel spread sheet with which you can evaluate the bottom line implications for your business. If you would like a copy send an email to csstw@bluewin.ch with your name, email and phone number and business address.

Black Swans in our Supply Chain V

 

Summary of the Book ‘The Black Swan” by Nassim Nicholas Taleb

1. "Black swans" are highly consequential but unlikely events that are easily explainable – but only in retrospect. 
   
2. Black swans have shaped the history of technology, science, business and culture.
   
3. As the world gets more connected, black swans are becoming more consequential.
   
4. The human mind is subject to numerous blind spots, illusions and biases.
   
5. One of the most pernicious biases is misusing standard statistical tools, such as the “bell curve,” that ignore black swans.
   
6. Other statistical tools, such as the "power-law distribution," are far better at modeling many important phenomena.
   
7. Expert advice is often useless.
   
8. Most forecasting is pseudoscience.
   
9. You can retrain yourself to overcome your cognitive biases and to appreciate randomness. But it's not easy. 
   
10. You can hedge against negative black swans while benefiting from positive ones.
    

Little’s Law (Cycle Time = WIP/Output (per unit of time))

Little’s Law should be well known in operations – but it seems to be ignored nevertheless. Two phenomena are active that cause many operations to perpetuate less than their best performance. The first is the  perceived need to keep all resources actively (hard) at work. If every resource is working hard, then costs factory seem to be lowest, but it will fill up with WIP. Double the WIP and production lead-time automatically doubles with it. Increasing lead-times is common practice in operations approaching capacity. As a factory reaches capacity promised lead-times become more and more difficult to meet so the solution is to contact customers to tell them lead-times have increased (a seemingly good tactic since we want to keep our promises reliably). The factory then has a longer lead-time to produce. However almost immediately the factory fills up with more WIP and even the new lead-times will be difficult to meet. It isn’t the lead-time; it’s the factory’s capability or capacity. (Increasing lead-times and consequentially also WIP heightens complexity in the factory – priorities become more and more unclear and schedules are changed more and more frequently.(

The new lead-time cannot be met because we have not actually increased capacity (by increasing lead-time and WIP we actually reduce capability) – so how can we produce more. The increased WIP in the system confirms the longer lead-time, adds to the confusion in the plant (priorities become less and less clear to personnel) and capacity is lost. The situation is aggravated by common practice in sales or marketing. What do you think is the better decision – cause sales to slow down their efforts in order to not overload the factory, maintain good lead-times and maintain delivery reliability; or maximize order intake no matter the situation in the factory? Somehow we will get through this seems to be the attitude; we must take advantage while we have demand from the market. (Won’t poor service eventually cause clients to go elsewhere?). What may not be recognised is that demand would still be high – clients have left only because of ‘crap’ service!

In most factories it is possible to simply stop placing work-orders for half the current lead-time and then release orders with half the original lead-time. This tactic has only beneficial effects – shorter lead-times, less stock, improved reliability, more satisfied clients. Lead-time is cut in half, WIP is cut in half, the production rate actually increases because of less confusion over priorities and less re-scheduling by management; due date performance improves. The result is a Black Swan – at least a significant improvement. All these benefits lead to better customer service and eventually to more business – especially if competitors don’t do the same. (Check how difficult it is to convince your people to implement this (next Monday) and you will see the difficulty competitors will have to copy your competitive move! It will take a while!

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Black Swans in our Supply Chain IV

 

Summary of the Book ‘The Black Swan” by Nassim Nicholas Taleb

1. "Black swans" are highly consequential but unlikely events that are easily explainable – but only in retrospect. 
   
2. Black swans have shaped the history of technology, science, business and culture.
   
3. As the world gets more connected, black swans are becoming more consequential.
   
4. The human mind is subject to numerous blind spots, illusions and biases.
   
5. One of the most pernicious biases is misusing standard statistical tools, such as the “bell curve,” that ignore black swans.
   
6. Other statistical tools, such as the "power-law distribution," are far better at modeling many important phenomena.
   
7. Expert advice is often useless.
   
8. Most forecasting is pseudoscience.
   
9. You can retrain yourself to overcome your cognitive biases and to appreciate randomness. But it's not easy. 
   
10. You can hedge against negative black swans while benefiting from positive ones.

Frederick Winslow Taylor (The father of scientific management)

Taylor’s ideas appear to be rejected by business managers of today. Yet, even today, efficiency everywhere is the norm. A resource standing idle is still considered to be a major waste – by management and workers alike. Managers detest resources that are not producing – if they have nothing to do they will find them something to do! Workers are afraid to be idle because being not needed risks being fired – so workers make sure they always at least look as though they are busy.

Common practice is to not waste resources – everything should be working. On the other hand Pareto and Goldratt have shown that only 1 resource needs to be working flat out – the weakest link, the constraint, the bottleneck. If everyone must always be working just imagine how much inventory will pile up – the limiting factor will not be able to keep up. Fortunately space and the dictates of cash flow will prevent companies from going way too far. Nevertheless are they not going far beyond the necessary? Shouldn’t most resources be idle, at least part of the time? Shouldn’t most resources have spare capacity so that they can guarantee the limiting factor is in fact able to produce at 100%?

It seems Taylor's ideas are important – but only at the limiting factor – the constraint or the .1%. Traditional Taylorism cannot help us find a Black Swan – it will most likely prevent us from consciously seeking the Black Swan.

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Black Swans in our Supply Chain - III

 

Summary of the Book ‘The Black Swan” by Nassim Nicholas Taleb

1. "Black swans" are highly consequential but unlikely events that are easily explainable – but only in retrospect.

2. Black swans have shaped the history of technology, science, business and culture.

3. As the world gets more connected, black swans are becoming more consequential.

4. The human mind is subject to numerous blind spots, illusions and biases.

5. One of the most pernicious biases is misusing standard statistical tools, such as the “bell curve,” that ignore black swans.

6. Other statistical tools, such as the "power-law distribution," are far better at modeling many important phenomena.

7. Expert advice is often useless.

8. Most forecasting is pseudoscience.

9. You can retrain yourself to overcome your cognitive biases and to appreciate randomness. But it's not easy.

10. You can hedge against negative black swans while benefiting from positive ones.

Dr. Eliyahu M Goldratt – The Theory of Constraints; 5 Focusing Steps

Goldratt’s theory claims that every (business) system must have one (and only one) constraint or weakest link . If there are two or more entities with the same capacity the system becomes more and more chaotic – and capacity and reliability collapse. His conclusion is, for all practical purposes, the same as Pareto’s (the 99:1 second law). Using this insight Goldratt developed his 5 focusing steps (more than 20 years ago).

To use the 5 focusing steps it is important to preface them with two important (bullet( points:

• Determine the goal of the organisation (for a business this is likely to be to maximize profits – now and in the future).
• Determine how the organisation will measure its performance to know whether or not the goal is being achieved.

1. IDENTIFY the constraint (the single limiting factor) that prevents the organisation from achieving more of its goal.
2. DECIDE how to EXPLOIT the constraint – how will the company get the maximum from its limiting factor. Quite an important decision if the business wants to achieve more of its goal – more profit and higher returns. This decision is a (maybe the) major determinant of profits and profitability. If focus is in the wrong area (the one that shouts loudest for instance) the business will have a good chance of disappointing results.
3. SUBORDINATE everything else to the above decision! The only way we can get the most from the limiting factor is to make sure it is able to realize its potential. Policies such as local optimisation everywhere will certainly waste a limiting factor’s capacity. They will cause all local organisations (divisions, departments, groups, business areas) to act selfishly. The will optimize their own (little) area with a very high chance of causing the real constraint serious difficulties and thus reducing company profits. On top of this local areas may well get a bonus for excellent local optimization. 
   NB. The first 3 steps also prevent unnecessary investment in new equipment and human resources before the limiting factor is fully exploited. The company’s return on Investment improves through a much more effective use of resources – the limiting factor is never wasted and unnecessary investments are prevented. Proper exploitation costs your business nothing and benefits it enormously.
4. ELEVATE the constraint. Once the constraint is fully exploited and assuming it is still the constraint of the system then is the time to expand capacity. If exploit and subordinate have been implemented successfully financing an expansion will be no problem.
5. IF during any of the previous steps the constraint has been broken then go back to step 1. WARNING: Do NOT let your inertia become the system’s constraint! The warning is essential and will often be disregarded nevertheless. We love our paradigms and hang on to them for dear life – after all when we let go of a paradigm we are not sure how we should behave under which new one! We may even be unsure whether or not the chosen new paradigm is valid.

Could these 5 simple steps help you to generate your own Black Swan and amaze the business World? What you don’t know, yet, is the impact this kind of focus has. Nevertheless maybe we should learn to question (and often drop) our paradigms in order to develop new and better ones.

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Individual and Tribal Behaviour

I have been a proponent of the Theory of Constraints (TOC) for many years now and still it is very difficult to ‘sell’ TOC to business people around the World – despite agreement that everything in TOC makes eminent sense. My friends in the TOC community experience the same things. That something new is a difficult sell is nothing new. Just read about the difficulties all sorts of inventors have had.

Confirmation Bias

Your personal experience should tell you that young liberal and open people are likely to believe that marijuana is harmless. You see them read or watch information about marijuana and retain only the positive (marijuana is not dangerous) parts of the presentation – even if the article or TV show is totally balanced for or against.

On the other hand the older, conservative (in relation to marijuana) less open person will do the exact opposite – he will retain only what confirms his existing views.

Both parties are exhibiting ‘confirmation bias’ – people everywhere seek out those things that confirm their preconception and tend to ignore contrary opinions, arguments and facts.

Look at your own behaviour. You and your partner have an argument about something. Try and notice how you respond to the facts, opinions and arguments put forward by others – which do you truly consider. D you really look at and logically think through the other positions? Or do you reject them quickly. What does it feel like when you suddenly realize your partner is correct – you are about to lose the argument?

As a proponent of the Theory of Constraints and as a human being I must behave in a similar way when confronted by other improvement methodologies. Lean, TPS and 6-Sigma experts must be similar, but they have a different bias.

In fact all of these improvement philosophies have a lot to offer, but this confirmation bias is getting in the way of progress and constructive discussion – at last many times.

The book “RISK The Science and Politics of Fear” by Dan Gardner discusses confirmation bias and many other topics of interest.

Tribes (Culture)

We are all members of tribes. I am a member of the TOC tribe; you might be a member of the Lean or 6-Sigma tribe. Within each tribe there are a series of (un-)spoken rules and expected behaviours. In the TOC community many of us look to Eli Goldratt for guidance (even if he wishes us to THINK on our own). Some try to emulate our leader. Some simply follow the generally accepted practices and thoughts of the community as a whole. As long as you conform you have the support of the community. If you don’t you run the risk of being ostracized by the group. This tribal behaviour means that many of us cannot accept Lean, 6-Sigma etc. We even have more explanations why these other methods are ‘wrong’ rather than looking for the good.

Other improvement methodologies probably react in similar ways – so it takes a very long time to get an integrated even more powerful toolset that incorporates the best from each. (Goldratt in his article ‘Standing on the Shoulders of Giants’ tries to show the way. However even this article must cause other tribes (other than the TOC tribe) to react less than positively.)

What we are experiencing is tribal behaviour – we are protecting our own community, our ideas etc. Given tribal behaviour and confirmation bias it is amazing that a coming together happens at all!

I would like to invite everyone that reads this to join the TLS group on Linkedin. TPS stands for Theory of Constraints, Lean and Six-Sigma. I would like to invite you all to join the TLS - TOC Lean & Six Sigma group in Linkedin. (I am a member, but not the group’s owner)

For more on tribal behavior read “Great Boss-Dead Boss” by Ray Immelman

The Challenge for ALL of Us

• How can we cause the various improvement methodology communities to integrate? How can we improve management processes far beyond where they are now? How can we foster real discussion and avoid confirmation bias?
• How can we create one CI (Continual Improvement) tribe that encompasses 6-Sigma, Lean, TOC and whatever else is out there or about to come on the scene?
• How can we speed up progress without the risk of embracing something truly wrong and risky?

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Black Swans in our Supply Chain - II

 

Summary of the Book ‘The Black Swan” by Nassim Nicholas Taleb

1. "Black swans" are highly consequential but unlikely events that are easily explainable – but only in retrospect.

2. Black swans have shaped the history of technology, science, business and culture.

3. As the world gets more connected, black swans are becoming more consequential.

4. The human mind is subject to numerous blind spots, illusions and biases.

5. One of the most pernicious biases is misusing standard statistical tools, such as the “bell curve,” that ignore black swans.

6. Other statistical tools, such as the "power-law distribution," are far better at modeling many important phenomena.

7. Expert advice is often useless.

8. Most forecasting is pseudoscience.

9. You can retrain yourself to overcome your cognitive biases and to appreciate randomness. But it's not easy.

10. You can hedge against negative black swans while benefiting from positive ones.

Pareto’s Law – The Law of the Vital Few and the Trivial Many

Pareto’s 80:20 rule is so well known to most people that it is part of the business (6-Sigma) gospel. This common knowledge is incomplete and leads the majority of business managers to very significant errors of judgement about what is important in the way they manage their resources. Correct application would simplify their business processes and help make significant bottom line improvement.

Pareto’s Law is valid if the population being studied is made up of independent entities. In systems of dependent entities the 80:20 rule does not hold. In such a system of interdependent entities (such as your business system) the rule is more like 99:1! Your focus should be on the one entity (and there can be only one) that limits, that prevents you from achieving more of your goal. I believe Pareto recognized this and postulated this second Pareto’s law along with the first.

The consequence is 1 operation, 1 resource or 1 division determines 99% of profit! When enough businesses realize this simple fact and learn how to use it to their advantage the World economy can experience a Black Swan and what a wonderful one! If you must focus on just one resource for bottom line improvement, would that not be a major simplification? (It is not quite as simple as I am making out, once you have the correct focus and know how to get the most from the limiting factor the rest of your organisation must be aligned to that. Everyone must support the decision how the business will get the most from its constraint.

Today every department or division is given marching orders – IMPROVE! Being good soldiers they all shout ‘YES SIR’ and do their best to improve the area they are responsible for. Since the 99:1 ratio holds, the result is inevitable – relative to the effort expended very little bottom line effect will be achieved. Oh yes, every manager can point to his improvements and as a result even get a bonus and/or a raise. But whatever most managers have done, 99% of it is a waste – at least for the time it takes for their part of the organisation to become the constraint.

In a business the first questions should be: “What should be our focal point? Where can we find the focal point? How will we deal with it? The focal point must be the limiting factor.

The next question must be: “How should the rest of our organisation behave to support the focal point?”

Could we be the source of a Black Swan? Could we trigger a Black Swan? If they are just random events the answer is NO! If someone (anyone) can discover a powerful leverage point – the limiting factor - and the way to exploit it then … why could WE not hatch a black swan?

A consequence, for you (a person within a large organisation) is you are probably not the limiting factor. Before you go looking for the limiting factor you need to recognize that the way management thinks is to get improvement everywhere. Your job is “make the boss aware of Pareto’s second rule.” Then a self-generated Black Swan becomes possible, even quite probable

Technorati Tags: 6-Sigma, Continual Improvement, Effectiveness, Efficiency, Goldratt, Risk Management, Theory of Constraints, TOC, Pareto, TQM