Decision Support Systems (DSS)

By Avraham Mordoch and Eli Schragenheim

How can the new fast development of technology effectively help organizations to achieve more of their goal?  The vast majority of the new technologies have a considerable impact on IT (Information Technology departments), which causes huge pressure on the workload of the IT people in most organizations that need to keep themselves frequently updated, causing headache to top management and lack of focus instead of helping them to move the organization forward.

But, the potential of the new power of computerization, including methodologies like Big Data, Artificial Intelligence (AI) and the Internet of Things (IoT), could also be used cleverly to improve the effectiveness of management by leading the organization to a secure and successful growth of its activity.

On one hand the new technologies allow getting more data, which is also more accurate than ever before.  That data, when properly analyzed with focus on what is truly meaningful, could serve managers in analyzing the current state of the business, its weaknesses and could lead to new ideas of how to improve the bottom line.

This article offers new ways to use the recent technology to allow management to get beneficial support in evaluating new ideas or prepare for expected changes coming from elsewhere.  We have chosen to focus on manufacturing organizations, which face the threat and the potential benefits, of digitization of the manufacturing shop-floor, considered to be the fourth industrial revolution, and thus gained the title of Industry 4.0.  The threat is being pushed to enormous expenses without gaining any business benefits. The capabilities of the new technology could assist a dramatic improvement in the way tactical and strategic moves are evaluated.  The point, though, is that in order to materialize the benefits some management paradigms have to be challenged and replaced with common-sense paradigms that utilize the new capabilities to support decisions.

Viewing the current types of software systems supporting manufacturing organizations, these systems can be classified into four types:

  1. MES (Manufacturing Execution Systems). This type of systems is focused on the very short term and aims at providing operators and production management with the most updated state of the flow of raw materials all the way to the finished goods inventory.  It allows handling priorities, fast fixation of problems and achieving efficient utilization of the equipment.  MES collects data and organize it in a way that can be easily viewed by middle operational managers. Scada systems, for example, are a subset of MES systems
  2. ERP (Enterprise Resource Planning). We include in this class also the CRM (Customer Relationship Management) systems. This class consists of a suite of integrated applications that the manufacturing organization can use to plan operations and collect, store, manage, and interpret data from different business activities. What integrates all the various part of the ERP class of systems is one database of all the key transactions, of the financial and the material, that have been recorded or are planned to be done in the short to medium-term.  The main function of this type of systems is planning the basic operations required to deliver the firm orders, while also record the transactions and institute order and the systemization of all the data related to the main processes in the organization. ERP and CRM systems are mainly data systems with some crude planning functionality. When information is defined as the answer to the question asked (Goldratt, The Haystack Syndrome) ERP and CRM supply answers to the most frequent and simple questions, like what needs to be done in order to deliver a customer order. SAP, Oracle or Dynamics 365 are just a few examples of ERP systems
  3. BI (Business Intelligent). The objective of the BI programs is to display high level information for top management, providing a picture of the current situation, and possibly pointing to certain observed trends.  The power of the BI technologies is to be able to collect relevant data elements from various databases. Internal data is mixed with data that is collected from the Internet and used to create graphs and charts for management to be aware of what’s going on within their organization and how it compares to what’s going on in the market and with their competitors.  The Key Performance Indicators (KPIs) are supported by BI making them clear to top management.  This gives the background to management to evaluate ‘what to change?’  But, it does not provide the tools to ‘what to change to?’, definitely not to ‘how to cause the change?’.  In other words, BI supports decisions by pointing to required areas, but it does not support specific decisions.
  4. Decision Support Systems (DSS). While the title of DSS was raised already in the 80s of the previous century, the true capability of actually supporting decisions has been achieved only recently. Every management decision is considering a change to the current state.  Every significant decision is also exposed to considerable uncertainty.  So, the key capability of a DSS is to be able to direct the managers to various alternatives to the considered decisions and present the possible ramifications of these changes.  We can divide this level of DSS into two parts:
    1. Supporting routine decisions done by experts, so less experienced people can take them, or even let the computer make this decision.  These types of computerized programs are based on Artificial Intelligence new technologies and create a variety of expert systems that support such decisions.
    2.  Supporting more significant tactical and strategic decisions by providing the decision makers with the holistic analysis of the potential financial and other ramifications of the decisions.  These are systems that support business organizational decision-making including decisions that consider unstructured or semi-structured potential opportunities that are exposed to significant uncertain situations. The assessment should consider the short term as well as the long term. A DSS must “understand” the cause and effect relationships between the different functions of the organization. These systems should allow a direct interaction between the human decision-maker(s) and the computerized algorithm.  The objective, given the amount of uncertainty and lack of full precise information, is to present the decision-makers with a full picture of what MIGHT happen, for good and for worse, as the result of the decision(s).

The above four classifications are not clear-cut and there are systems that cross the lines between them.

On top of that there is often an interaction, even a loop, between the above types of systems. The ERP consumes data accumulated by the MES and accordingly creates work orders that feed MES system.  The ERP database has a major role for the BI system showing the current state and the ERP and BI data are input into the DSS programs.

Interestingly enough the effort a manufacturing organization needs to make to implement these systems is especially significant when implementing an MES system, since there is a need to overcome cultural objections, including the antagonism that one finds in organizations with no established culture to report what has been done. When this initial infrastructure is laid down, it is a bit easier to implement and properly use the ERP system and by far easier to continues to climb the ladder and implement Expert Systems and the higher level of DSSs. So, the effort is reduced going up the ladder through the four types of systems,  but the benefits from the implementations is increased and there are very significant benefits when the top management, the C-level managers, are using a DSS for solving the crucial dilemmas they may have.

We have to take into account that manufacturing organizations are both complex and exposed to significant uncertainties. Still the C-level managers have to make tough decisions like:

  • Should the company offer packages of its existing products for a reduced price?
  • Should the company accept small orders for customized products for a not-too-high markup?
  • Should the company expand the product-mix with additional product family (or families)?
  • Should the company save considerable cost by shrinking its resources, as well as stopping the production of products with very low demand?
  • Should the company go on massive advertizing campaign?
  • Should the company participate in a big tender, quoting a moderate price, knowing that winning might affect the good delivery performance of the regular orders?
  • Should the company invest in opening a new export market?
  • Should the company invest in a new production-line when the market seems to go up, but some people believe this upward trend is going to stop?

These decisions lie outside the comfort zone of the decision makers, because of the obvious risk and having much less past experience with such situations.  The decisions are risky not just from the perspective of the organization, but also from the perspective of the personal risk of the decision maker, who ties himself/herself to the success or failure of the initiative.

The above risks force conservative decisions whenever the needed decision is beyond the known comfort zone. Lack of proper support for a holistic analysis blocks many organizations from achieving the true potential of the organization.

There are two big obstacles for any DSS to tackle the above decisions and many others: One such obstacle is expressing the intuition of the people close to the relevant area to play its role in the analysis.  Even when the situation is beyond the comfort zone of the decision-maker, it is still valuable as the people involved always know something that is more than nothing.  While lack of good precise relevant data is a constant issue, analyzing what MIGHT happen is a valid possibility, which yields a focused picture of the actual risk.

The second obstacle is being able to evaluate the proposed decision when it is added to everything else the organization is doing or committed to do.  This requires deep understanding of the rules behind the flow of materials, products, orders and financial transactions, including the various dependencies in Operations and in Sales.  This leads to the massive calculations, checking the state of capacity, materials and cash.

The DSS program needs to “simulate” the top-level dilemmas (like the examples above) and come up with the predicted financial results.  It has to make it easy to run a variety of ‘what-if’ scenarios and compare the results.  In the end, it has to display the predicted results for, at least, two different scenarios:  one that is based on reasonable conservative assessments and the other on reasonable optimistic one.  The range of the end results means the reasonable result should fall anywhere in between the extreme sides of the range.  The decisions should never be done automatically by the system – it needs constant intervention by the decision maker looking for better alternatives and use human judgment to make the final decision.

Generally speaking there could be two main ways to accomplish an effective support for decisions:

  1. Being able to carry a mass of calculations, based on good cause-and-effect rules, which describe the materials and capacity requirements for every product sold as well as the impact on the revenues and cost. This way is described in detail by the book Throughput Economics, written by Eli Schragenheim, Henry Camp and Rocco Surace.
  2. Using a powerful computerized simulator that closely follows the flow rules, and records revenues, truly variable expenses and the cost of capacity as an integral part of the simulation. The uncertainty has to be input into the simulator’s critical parameters to provide the possible range of the results.

The mass calculations way is more visible to the decision-makers, as the calculations are all straightforward and the added-value of the computer is the ability to carry such mass  calculations.  This means the decision makers fully understand the assumptions that are at the core of the calculations.

Using computerized simulation better fits complex situations, either within the production-floor, or with complicated dependencies within the sales.  For instance, simulating different flow rules, like batch sizing and different prioritization, are much more effective than mere calculations that have to rely on assumptions regarding the effectiveness of the flow rules.  On the other hand, the user has to inquire deeply to validate that the internal parameters of such simulation are in line with reality in order to trust the results.

Both ways have to start with a good representation of the current state as a reference according to which all the changes are compared to.  For a simulation it means creating a ‘digital twin’ that seems to come up with the current performance of the organization.

A computerized system that produces reliable reference or a digital twin, and is able to introduce variety of changes and compare the results to the reference, while also depicts the potential impact of uncertainty and lack of accurate data, deserves to be called a decision-support-system (DSS). Such a system will reduce significantly the risk in taking top-level decisions and will also reduce procrastination that is usually found whenever ‘hard decisions’ are evaluated.  This would help significantly to put the company ahead of the competition.

The first few true DSSs to appear in the market will enjoy a “Blue Ocean Strategy” compared to the “Red Ocean” which is typically the current situation in systems supporting manufacturing organizations.

Preparing for a recession

By Rudi Burkhard and Eli Schragenheim

Recession is an external threat that no organization has the power to stop or even delay.  A recession starts when enough people (those that influence the economy) expect it to happen soon and they start to take action to protect themselves from its impact. These may be actions by politicians, central banks or a major financial scandal that accelerate peoples’ decisions to take action.

What should a company do when recession is a close possibility?

A recession pushes most managers out of their comfort zone.  Managers’ intuition about markets’ direction dives and their fear level surges.  Every organization suffers the reaction of clients and suppliers to the coming recession. The first blow (actions) to sales are often much bigger than the actual real decline of the economy.  The knee jerk reaction is to reduce inventories; suppliers are the first to feel these reactions, sometimes even over-reaction, to the recession’s threats.

It takes time to understand the actual impact of a recession. Until that time hysteria and limited intuition frequently cause major mistakes. Managers also do not have good intuition about a recession’s impact on real physical demand. They often do not understand what really takes place in the economy.

Common practice is to cut cost. Warning: This common practice takes management’s focus away from the one parameter they must not hurt: sales!  To survive a recession a company must, as much as possible, protect sales revenue. We don’t claim that reducing cost is not important or critical to survival, but managers should carefully analyze their situation to ensure they do not disrupt their sales more than the recession  does. They must be careful to not make the recession’s damage worse.

Estimate the impact of a possible X% sales decline

Throughput Accounting, and more recently Throughput Economics, lead to a clear set of data and information that together estimate the range of valid probable results from such a macro-economic event.   Using these two tools, and the related knowledge, can lead to a much better perspective on how a recession might cause damage to the company’s future.

Two financial parameters are of special importance:

  1. Total Throughput (T), revenues minus totally variable costs (TVC).
  2. Total operating expense (OE) – all the money spent to maintain the necessary capacities of resources (space, equipment, manpower and even cash).

Comment:  The TOC goal measurements include also the money that is captured within the organization, called ‘Investment’ or just ‘I’.  While it is one of the key measurements it seems that to evaluate the potential impact of a recession the part of Investment that is important, is inventory, which is a natural candidate to reduce.

Interested readers are referred to the Theory of Constraints materials on Throughput Accounting, like Thomas Corbett book Throughput Accounting, and the more recent Throughput Economics by Schragenheim, Camp and Surace. These resources explain how the concepts they introduce give much better insights into the current and future financial state of a company.

Throughput is the cash inflow from sales (minus the cost of materials).  OE is the cash outflow to maintain the necessary capacity required to stay in business. Cash inflow includes depreciation of the investment in capacity.  Sufficient capacity is required to support the two key flows:

  1. The Flow of Value, focusing on the current flow of products and services to clients. This flow encompasses the entire chain from purchase orders to suppliers to product delivery to clients and finally payment collection.
  2. The Flow of Initiatives to improve (increase) the Flow of Value. This flow contains all improvement projects and new idea evaluations for products and processes.

A cost cut reduces capacities; for instance, by stopping all overtime, special shifts and temporary workers production capacity is reduced.  Depending on local regulations the company could also consider lay-offs and/or short workweeks.  Understanding the impact of these actions on sales volumes is critical for the survival of the organization.  Companies should use careful prioritization to prevent from cutting capacities that ensure the Flow of Value is maintained. An unavoidable and longer-lasting decrease in demand makes such cuts possible, as long as delivery lead-times and reliability to remaining clients are not negatively impacted.

Practically this means that when cutting capacity, the cost required to maintain capacity, should be considered mainly for resources required to support the Flow of Initiatives, rather than resources required to maintain the Flow of Value.  Proper consideration reduces the threat to future prosperity by the delay or cancellation of flow initiatives.  This implies that some of the luxuries management gives itself are valid potential cost reductions. Every organization may have capacity that supports the Flow of Value in an indirect way or maybe does not support it at all.  Such capacities with a questionable direct contribution to the business are the natural and sensible candidates to be cut in a recession.

In practice this means considering the short-term benefit from cost cuts vs. the longer-term benefits that will stem from the Flow of Initiatives. Cutting cost that stops or slows the Flow of Initiatives threatens future prosperity and creates opportunities for competitors.  Sometimes the short-term survival dictates having to give up future opportunities, but extra care is needed for that.

The two categories of actions necessary to keep a company safe, even truly successful, over the longer term are:

  1. Predict the possible range of the financial impact in order to correctly choose the resources that must remain to provide a good enough financial (cash flow) performance during the recession and enough to best support growth once the recession recedes.
  2. Improve Operations to a level so that reaction to market demand changes are faster than any competition. By this the company gains a clear, even decisive, competitive edge. Rapid identification of the products less impacted by the recession is one example how improved operations can be used to gain an advantage over competitors. A recession presents opportunities to capture more market demand; demand that until the recession has been served by competitors. A recession ‘forces’ clients and their suppliers to reduce inventory, which in turn requires a faster response to supply smaller quantities.  The supplier able to respond faster with smaller quantities (replenish his clients at a higher frequency) than the competition gains a decisive advantage.  Spare capacity should be used to accelerate response times, and to keep low stocks of finished goods to maximize the competitive advantage.

Major points to realize when predicting the depth and duration are:

Operating Expense behavior is not linear:  it is impossible to reduce the capacity by the exact predicted decrease in sales. Most resources come in sizable increments. Cutting capacity is possible only in amounts different from that required by the decrease in sales.

Can we make reliable estimates of the extent of reduced demand? Can we make reliable estimates of the extent of price reductions? We cannot!

All decisions are based on forecasts that are mostly intuitive, sometimes quantitative or a combination.  Forecasts are always based on the past with assumptions on how past behavior will change.  Management practice of treating forecasts as deterministic is the core problem behind erratic decisions over demand. A single number will never be reality – the best we can do is estimate a range and prepare to respond quickly as reality becomes clearer.  A valid way is to define a range from the conservative to the optimistic assessment. Both estimates should be reasonable; put aside possible results with a very low probability.

Thus, it is possible to estimate the reasonable range of the impact of the recession on a specific market and then check the extreme predictions to decide what, how much and where to cut cost and how much stock is absolutely necessary.  Note, you need to check both extremes, not just the conservative side. The optimistic side gives you what you might lose if you just consider the worst case.  As the recession’s impact can be quite different for different businesses and for different countries or regions the responsibility of the management of every company is to estimate the reasonable range of change in their specific market.  Estimating a range is easier (not “easy”, just easier) than predicting a single number. The company can discern reasonable estimates of how bad the situation might become and what can be done about it. The company should also consider what it can achieve if it maintains the required level of resources to obtain the best outcome of the recession.  This is the Throughput Economics process to obtain vital and relevant information that support superior decisions and results.

Both the conservative and the optimistic assessments lead to actions.  The job of management is to make the decisions that, even when they are based on the wrong side of the estimates, the damage is limited, while the potential gains are high.

Probably all managers realize that in their market final consumer behavior is critical.  Consumers dictate demand.  Consumers’ demand impacts all players in a supply or value chain. For some value chains or positions in the value chain the recession’s impact may be somewhat delayed.  It is essential that B2B organizations extend their evaluation beyond their immediate clients. In order to predict the evolution of demand they must evaluate what is likely to happen to the demand all along the chain starting from the final consumer.  Suppliers to retail organizations might suffer a very high drop in sales at the beginning of the recession.  However, the real drop in sales to the end consumers is usually much smaller.  Nevertheless the retailers decide to reduce inventories.  For suppliers this means demand is likely to return back quite soon. Understanding clients and their clients’ business well is an essential capability for every organization in a value chain. This capability is not only critical in a recession – it is always a critical competency to understand clients’ needs even better than they do!

How do streamlined operations win in the market during recession?

The Theory of Constraints (TOC) for manufacturing and distribution companies is the ultimate Lean. TOC methods ensure excellent response times and/or product availability with the lowest possible amount of work in process (WIP).  These methods are the correct choice whether in a recession or not.  These methods also require the least amount of cash to finance inventory and operations.  This makes the potential for competitive advantage especially during a recession. During a recession everyone is under pressure to spend money much more carefully.  Every purchase, by an individual or by the organization, is thoroughly checked. Competition becomes fiercer than before opening the path to price competition (price wars). The other, often ignored, option is to compete using faster response and smaller quantities. Throughput Economics and Simplified-Drum-Buffer-Rope (SDBR) are combined to define your best strategy and tactics to deal with an arriving recession.  As inventories are flushed out of the system, once the original demand comes back the suppliers should be ready to deliver, with less inventory, the original demand plus the new demand achieved through fast response during the recession.  Constantly updated holistic information on the actual demand and its trends allows management to estimate when demand will start to rebound. This information is critical to decisions about the required capacity levels, which in turn determine cost and cash flow. The questions to answer are how strongly the company should protect current sales and to what extent should improvement projects continue to be implemented.

The Theory of Constraints (TOC) tools, particularly SDBR and Throughput Economics, support this route, combining operational and financial capabilities.  The idea is to limit the potential damage of a recession, gain competitive advantages and be ready when the economy rebounds to fully capitalize on the acquired competitive edge.

The devastating impact of the fear from uncertainty

Suppose you are the CEO of a manufacturing company and Ken, your VP of Operations, comes to you with the idea of offering fast-response options to clients for a nice markup in price. That means on top of delivering in four weeks for regular price to deliver in two weeks for 15% markup and in one week for 30%.  You ask Ken what Mia, the VP of Sales thinks of it, and he tells you she does not object, but also not fully support.  As long as you, the CEO, would support the idea she will cooperate.  A similar response comes from Ian, the CFO of the company.

There are two possible problems with the idea.  One is that Operations might be unable to respond to such fast deliveries, but Ken is confident Production can do it.  The second potential problem is that clients would refuse to pay the markup and still put pressure to get faster response.

Suppose you tell Ken the following: “Sounds interesting idea.  If you truly believe in it – go and do it.  Get the support of Mia and Ian and bring results.”

Is this “good leadership”?  The words “if you truly believe …” radiate that the full responsibility for a failure would fall on Ken, no matter what has caused the failure or the fact that any new move is exposed to considerable variability.  Would this pave the way to more people with creative ideas to bring them to management?  What do you think would happen to Ken if “his idea” fails to impact sales?

A manager who dares to raise a new idea for improving the performance of an organization faces two major fears.  The first is from being unable to meet the challenge and the responsibility and accountability that come with it.  The second fear, much more devastating, is from unjust criticism if the idea won’t work according to the prior expectations because of the significant inherent uncertainty.  Expectations are usually built according to optimistic forecast, even when the one who raised the idea took into account also the less optimistic results.  The unjust behavior of critics, who choose to ignore the uncertainty, is what eventually causes cold feet to most managers, preventing them from raise new ideas.

Think of the conflict of a coach of a top sport team before an ultra important game that has a key player after long break due to a bad injury:  should he use the player in the game?  On one hand that player could be the decisive factor for winning the game.  On the other hand, he might be injured again.  How would you judge the coach after the game?  By how much your judgment is influenced by the actual outcome?

A coach before a game has to take several critical decisions.  But, when one has a daring new idea simply ignoring the idea is a valid option.

Nassim Taleb is absolutely right saying that instead of trying to avoid uncertainty we should use uncertainty for our benefit.  However, you cannot just ignore the fear that any negative actual result would cause too high personal damage, much larger than the damage to the company from the specific idea.  The fear is intensified by knowing that many people, who might judge the outcomes of the idea, do not really understand the nature of uncertainty.  Then there is a concern that a “failure” would play a role in the power-game within the organization, causing damage to the person who came up with an idea that worked less well than expected.

Most people are afraid of variety of uncertain events.  One question is what do you do with the fear?  Most people delay critical decisions, which is the same as deciding to do nothing.  Others take the uncertain decisions fast in order to avoid the torment of the fear.  The use of superstition to handle uncertainty, and mainly to reduce the fear, is also widely spread.

As the reader has already realized, the focus of this article is not on individuals who make decisions for their own life, but on people who are making decisions on behalf of their organization.

One difference is that decision making on behalf of the organization should be based on rational analysis.  The business culture of organizations radiates the expectation for optimal decisions checking carefully the cost-benefit relationships.  People make their own decisions based mainly on emotions and then justify the decisions using rational arguments.  Organizations might have certain values based on the emotions of the owners, but the vast majority of the derived decisions are supposed to be the outcome of rational analysis.

Are they?  Can people have two different sets of behaviors when they need to take decisions?

The famous Goldatt’s saying “tell me how I’m measured and I’ll tell how I’ll behave” gives a clue to what could make a basic change in behavior between the work-place and all other environments a person interacts with.  Every organization sets certain expectations on its employees.  When continuing working for the organization counts, certainly when there is a wish to go up the ladder, fulfilling the expectations is of major impact.

People are not optimizers they are satisfycers”, said Prof. Herbert Simon, the Nobel Prize laureate (1978 in Economics).  ‘Satisfycer’ means trying to meet satisfactory criteria and once they are met the search for better alternatives stops.  If Prof. Simon is right and if the organization culture promotes the value of optimization, then organizations demand a different way of making decisions than what people do for themselves.

The critical and devastating conflict lies with making a decision for which the ramifications cannot be accurately determined.  This is the core problem with all decisions due to uncertainty and lack of relevant information.  When it seems possible that the ramifications of the decisions might be bad, but could also be great, then we have a “hard decision” on our hands.  Satisfycers would naturally make the decision based on evaluating the worst case and whether such an outcome could be tolerated as a key criterion.  At the same time the other criterion would be based on how good the ramifications could be.  Even though most people give much more weight for negative results, there are enough cases where people are ready to take a certain risk for the chance of gaining much more value.  Many times taking the risk is the right decision for the long term.  This is definitely true for organizations that could gain a lot by taking many decisions that their average gain is high, and the damage from losing is relatively small.  While there are organizations that operate like this all the time, like high-risk funds, the vast majority of the organizations behave as if the single-number forecast is what the future is going to be. In such a scenario failing to achieve the ‘target’ is due to incompetence of specific people, who are openly blamed for that.  This culture forces medium and high-level managers to protect themselves by aiming at lower business targets that they feel confident can be safely achieved.

The devastating damage of the fear of managers to raise new ideas is being stuck in the current state, and being exposed to the probability that the competition will learn how to handle uncertainty in a superior way that vastly reduces the fear.

This can be done by radiating to the organization’s employees that every forecast should be stated as a range rather than a single number.  When the formal analysis of any opportunity or new idea is analyzed by a team of managers from all the relevant functions checking two different scenarios, one based on conservative assessments and the other on reasonable optimistic one, then such a team decision is better protected from the unjust after-the-fact criticism.  Addressing uncertainty by estimated ranges and the creation of two reasonable extreme scenarios is a key element in Throughput Economics aimed at supporting much better decisions and opens the door for many new ideas.

The Value Generated by TOCICO


TOCICO as an independent and neutral organization of the TOC international community is at cross-road where its value to the community is, to my mind, very high, but it struggles with cash problems. For a non-profit organization the core problem is that generating value to customers does not always return enough revenues.

Of course, the duty of the management of any non-profit organization is to establish the necessary cash for generating the value.  Generally speaking there are three ways for non-profit organizations to raise cash.  Of course the combination of three sources is very common.

  • Sell the generated value in the same way as for-profit organizations. Membership fee is one way to sell value. Selling specific products or services is another way.
  • Be financed by the government or another large organization that provides a budget.
  • Donations by the various parties who appreciate the global value generated by the organization. Bill Gates comes to mind as an example of a billionaire who donates huge money to keep non-profit organizations effective.  Most of the performing-art organizations in the US are financed this way, on top of selling tickets.

Two general comments:

  1. Every non-profit organization is producing value that, from whatever reason, is difficult to sell commercially, and thus such an organization has to be careful to protect its goal from behaving according to profit considerations. Customers evaluate every purchase based on the perceived value of the specific product/service they buy, and not by the overall value generated by the non-profit organization.  Thus, the incoming revenues do not represent the true value of the organization.
  2. Every non-profit organization is constrained by cash. The underlining assumption is that the organization is able to generate more value when more cash is available.  While this assumption has to be checked in reality, it should drive management to exploit the money to generate as much value as possible; no matter how much cash that value brings back.  Eventually the budget of such an organization is spent on maintaining resources and it makes sense that the cash limitation creates a specific internal capacity constrained resource (CCR) that limits the Flow of Value, while the other resources have excess capacity in order to support the internal strategic constraint.

TOCICO was, and still is, financed by selling value, mainly the revenues from the annual conference, delivering the certification exams, and membership fees.

What is the value generated by TOCICO?  And for whom this value is significant?

The goal of TOCICO, to my mind, is to support the spread of TOC awareness, knowledge and successful implementation throughout the world. 

This goal could be especially valuable to four different market segments. Each one of the segments should be divided into two sub-segments:  those who are already familiar with TOC, and those who are not.  Generally speaking TOCICO faces only those who are somewhat familiar with TOC, like having read The Goal.  We need to find marketing ways to raise enough curiosity in TOC and then the value from TOCICO would become clear.  Here are the four segments:

  1. Management consultants. Many managers contemn consultants viewing them as people without deep understanding of the particular reality, while also not accountable for the results.  However, getting an external view-point, based on many other organizations, could be a major opportunity to identify flawed assumptions, which are typical for specific industries, and which any inside manager faces real difficulty to identify and challenge.  Such external view could bring to the table new opportunities that the competitors, being trapped by the same flawed assumptions, cannot recognize.  Certainly TOC develops the skills of consultants to quickly identify key problems and deduce the flawed assumptions behind those problems.
  2. Every manager in any organization. This is based on recognizing that understanding well the TOC insights significantly improves the managerial skills of every manager.  Most managers would gain immense value when they recognize the opportunity.  A possible negative branch for such managers is to announce their views too early and by that being viewed by others as zealots and even be forced to leave the organization.  So, understanding the perspectives of the other managers should be part of the TOC insights and education.  The focus here is on the personal value of the managers, assuming doing well their job would improve their self-satisfaction as well as their career.
  3. Organizations and corporations that are using TOC could get immense value by exposing the wide spectrum of the TOC knowledge to all the organization members. A more specific need of such a corporation is to get focused TOC knowledge and certification for their employees.  Corporations that just contemplate to implement TOC should, in the vast majority of the cases, look for TOC consultants to guide the implementation. TOCICO shouldn’t recommend one TOC consultant over another, but indirectly participating in the TOCICO conference, or watching videos and webinars presented by consultants could assist in the choice.
  4. Academics, both students and professors, who get access to important knowledge that is not a regular part of the current curriculum. Certainly the TOC insights could easily serve new worthy research topics.

TOC knowledge gives consultants significant advantage, no matter whether they use the name ‘TOC’ in their practice or not.  The ability to quickly identify the constraint / core-problem, use the TOC available insights for the direction of solutions plus the systematic use of cause-and-effect, are required capabilities for doing better job.  This is the highest value consultants can get.  Add to it the spread of TOC, which adds more relevant leads and opportunities.

Another value to consultants is the SHARING platform provided by TOCICO.  When you use ideas that are in conflict with the current paradigms, the internal discussions with other experienced consultants are of immense value.  TOCICO is a platform for such internal discussions to take place.

The value to corporations is especially interesting.  In most cases the initial TOC implementation is guided by consultants.  The managers that learn directly from the consultants might, mainly after the consulting company leave, get constant stream of value from TOCICO.  At this stage the corporation faces new needs.  One of them is to make sure all their employees know what they need to know to get the improved results.  New employees also need simple and effective training on the TOC basic knowledge to understand the new thinking behind the not-so-common procedures.  This might require guiding the employees to take the certification exams to prove their level of understanding.  In order to learn the materials TOCICO will launch several educational programs that cover the various certification areas.

Another need of corporations, which can be addressed by TOCICO, is answering the question what next to implement?  This means covering topics that have not been implemented by the organization at that time, like Throughput Economics and the use of Goldratt’s Six Questions for guiding the evaluation of new products/services.  The effective way to evaluate what additional TOC insights should be incorporated next is by participating in a TOCICO conference as well as viewing several videos and webinars offered by TOCICO.

Yet another need of corporations is getting external recognition of achievements.  When the implementation is done in one division it is valuable to radiate the excellence to the other divisions.  External recognition by TOCICO could create pressure on other divisions to achieve this kind of recognition.  Of course, the PR department of the organization could also use that public recognition of achievement to generate more value.

The products/services of TOCICO need expanding into education/training programs to provide more value to all its market segments.  In particular there is a need for training programs. The Alex Rogo program, announced in the 2019 TOCICO conference in Chicago, provides effective guidance for self-learning. Training programs for higher level people could be adjusted to the specific requirements of corporations.  Eventually TOCICO should be able to offer basic TOC education to any individual, or organization, all over the world in variety of languages.

In order to achieve the generation of new ongoing stream of value TOCICO needs to stabilize its financial state.  This means TOCICO needs the support of its members, both individuals and corporations.

My call is to everyone who appreciates the potential value to be generated by TOCICO to become a member and by that support the ongoing TOCICO activities.

Increasing the membership is a necessary condition. When it’d becomes wide enough it’ll also become sufficient, as there are enough great people who are willing to contribute their time to do voluntary work to generate that value.  The neutrality of TOCICO is an asset that is absolutely necessary for both the value and the willingness to volunteer.

Keep in mind the global value of TOCICO when you evaluate the cost versus its specific value.  Eventually any charge for products/services generates revenues that are needed for carrying the full value of TOCICO to the world.

A new book opens a new direction for making superior managerial decisions

Cover (1)

I have struggled with the insights for this book for almost twenty years.  While all the ideas are based on the current body of knowledge of the Theory of Constraints (TOC), they extend its applicability and usefulness.  TOC already has challenged the use of cost-per-unit and local performance measurements that have a huge negative impact on managerial decisions today.  Expanding the already well-advanced TOC BOK requires special care and self-checking every part in the chain of logic.  When Henry Camp and Rocco Surace joined me in the writing, including outlining the necessary direction of solution and adding their own perspectives, it was a huge and absolutely necessary help.

There is a basic difference between a book and a blog, as they serve different needs.  Short articles in the blog are focused on one insight and if the reader sees value in the insight, then more efforts are required to develop the generic insight into a practical process.  A book should encompass the development of several new insights and integrate them into a clear focused message that is valid both theoretically and practically.

What is the particular need for Throughput Economics?

We claim that good management decisions must be analyzed and supported in a very different way than is customary today.  Managers have huge responsibilities on their shoulders and they deserve a better method to consider the relevant and available information to generate the best possible picture of might happen when any significant decision is undertaken.

The simple fact is that the current (and long established) methods of cost accounting distort the decision-making process by presenting a flawed picture of expected profits or losses resulting from the decision.  Managers might intuitively sense the impact of the considered decision on the bottom-line and they are also aware that the quality of their intuition is questionable.  Fear of unjust criticism, once the results become clear, is another factor that impels managers to utilize well-accepted tools, even if they feel those very tools are flawed.  In order to change the way managers are making decisions there must be a comprehensive alternative procedure that is demonstrably superior.

While the insights of TOC contributed much to clarify the flaws of cost accounting tools for decision making, pinpointing the underlying flawed paradigm behind the concept of cost-per-unit, could be quite beneficial. The core mistaken assumption is treating the cost of maintaining capacity as if it were linear.   This is just wrong because capacity of most resources can only be purchased by certain amounts – in chunks, if you will.  For instance, if you are looking for space for your office you might have a few alternatives each with its own specific square footage.  Eventually, you choose the most convenient one that has more space than you actually need.  It is up to you to treat the extra space as a “waste” or as an opportunity that, when triggered by new market opportunities, you already have the space you will need.  This benefit is offset by paying more for a bigger space in the meantime.  The point is that it is unrealistic to expect to be able to purchase exactly the capacity required for the changing level of activity in your business.

The fact that most resources have excess capacity means that consuming the surplus capacity generates no additional cost.  However, once the practical limit of the available capacity is reached, then any optional capacity increase is typically quite expensive and the quantities in which more capacity can be quickly purchased are normally subject to certain minimums.  This characteristic of buying capacity is what makes it non-linear.  The rub is: to know whether an additional consumption of capacity required for a new opportunity is ‘free’ or expensive, you must consider all your capacity requirements – the proposed new needs on top of all current activities.  In other words, a global calculation has to be made to estimate the actual impact of implementing a new decision on total operating expenses.

The most important decisions undertaken by any organization concern sales or capacity.  Sales are the key factor for income and maintaining capacity is the crux of expenses that enable the organization to provide what it sells.  It was an ingenious idea of Goldratt to look for two distinct information categories that impact any new decision concerning sales or capacity:  Throughput (T) on one hand and Operating Expenses (OE) (and Investment (I)) on the other.  T focuses on the added-value generated by sales.  OE describes the cost of maintaining the required capacity.  While changes in T usually behave in a linear fashion, the true impact of a new move on OE, the expenses for maintaining capacity, must consider the non-linear behavior of OE.  This non-linear behavior is often a big surprise to the managerial intuition of whether the proposed move is positive or negative.

What clearly comes out from cost’s non-linear nature is the requirement to analyze any new potential deal, not just by its own specific details and definitely not by any ‘per-unit’ artificial measurement, but by simulating the new deal as an addition to the load of the current activity of the whole organization and then checking the impact on ∆T, ∆I and ∆OE.

Does this idea seem frightening because so many numbers and variables are involves?  This is where the right kind of decision-support software can help us with the calculations.  The principles are simple and straight-forward, but making a huge number of calculations should be delegated to a computer, as long as we human beings dictate the logic.

The power of our book is going into the details of such a broad idea, without losing its inherent simplicity.  We present the holistic direction, while also covering enough details, to answer any doubt that might emerge.

In order to preserve the sensitive balance between the generic method and the tiny details, making sure nothing is lost in the process, we came up with several fictional cases where a management team needs to specifically analyze non-trivial new opportunities that could be great but might also be disastrous.  Unless the analysis is done comprehensively outcomes are practically impossible to predict.  I have already used these types of fictional cases to demonstrate the cause-and-effect behind generic principles in a previous book (Management Dilemmas).  In this book, the detailed fictional cases are of special importance.   Subsequent chapters refer to these cases and their intrinsic ideas in a more general way, explaining the processes from your perspective as an outside observer.  Our objective was to lead you to see the insights from both perspectives: the practical case where managers have to deal with a specific non-trivial decision and the higher-level world of defining the global process for dealing with a variety of such decisions.

Amazon, of course, sells and ships the book:  Throughput Economics by Eli Schragenheim, Henry Camp, and Rocco Surace

ISBN  978-0-367-03061-2 / Cat# 978-0-367-03061-2

If you need any help in purchasing the book write to me at:

Threat Control – not just cyber!

The TOC core insights are focused on improving the current business.  TOC contributed a lot to the first three parts of SWOT, strengths, weaknesses and opportunities.  What is left is to contribute to early identification and then developing the best way to deal with threats.  Handling threats is not so much about taking new initiatives to achieve more and more success.  It is about preventing the damage caused by unanticipated changes or events.  Threats could come from inside the organization, like a major flaw in one of the company’s products, or from outside, like the emergence of a disrupting technology.  TOC definitely has the tools to develop the processes for identifying emerging threats and coming with the right way to deal with them.

Last time I wrote about identifying threats was in 2015, but time brings new thoughts and new ways to express both the problem and the direction of solution.  The importance of the topic hardly needs any explanation; however it is still not a big enough topic for management.  Risk management covers only part of the potential threats, usually just for very big proposed moves.  My conclusion is that managers ignore problematic issues when they don’t see a clear solution.

There are few environments where considerable efforts are given to this topic.  Countries, and their army and police, have created special dedicated sub-organizations called ‘intelligence’ to identify well defined security threats.  While most organizations use various control mechanisms to face few specific anticipated threats, like alarm systems, basic data protection and accounting methods to spot unexplained money transfers, many other threats are not properly controlled.

The nature of every control mechanism is to identify a threat and either to warn against it or even take automatic steps to neutralize the risk.  My definition of ‘control mechanism’ is: “A reactive mechanism to handle uncertainty by monitoring information that points to a threatening situation and taking corrective actions accordingly.

While the topic does not appear in the TOC BOK, some TOC basic insights are relevant for developing the solution for a structured process that deals with identifying the emergence of threats. Another process is required for planning the actions to neutralize the threat, maybe even turn it into an opportunity.

Any such process is much better prepared when the threat is recognized a-priori as probable.  For instance, quality assurance of new products should include special checks to prevent launching a new product with a defect, which would force calling back all the sold units.  When a product is found to be dangerous the threat is too big to tolerate.  In less damaging cases the financial loss, as well as the damage to the future reputation, are still high. Yet, such a threat is still possible to almost any company.  Early identification, before the big damage is caused, is of major importance.

The key difficulty in identifying threats is that each threat is usually independent of other threats, so the variety of potential threats is wide.  It could be that the same policies and behaviors that have caused an internal threat would also cause more threats.  But the timing of each potential emerging threat could be far from each other. For example, distrust between top management and the employees might cause major quality issues leading to lawsuits. It could also cause leak of confidential information and also to high number of people leaving the organization robbing its core capabilities.  However, which threat would emerge first is exposed to very high variability.

It is important to distinguish between the need to identify emerging threats and dealing with them and the need to prevent the emergence of threats.  Once a threat is identified and dealt with then it’d be highly beneficial to analyze the root cause and find a way to prevent that kind of threats to appear in the future.

External threats are less dependent on the organization own actions, even though it could well be that management ignored early signals that the threat is developing.

Challenge no 1:  Early identification of emerging threats

Step 1:

Create a list of categories of anticipated threats.

The idea is that every category is characterized by similar signals, which could be deduced by cause-and-effect logic, which can be monitored by a dedicated control mechanism.  Buffer Management is such a control mechanism for identifying threats to the perfect delivery to the market.

Another example is identifying ‘hard-to-explain’ money transactions, which might signal illegal or unauthorized financial actions taken by certain employees.  Accounting techniques are used to quickly point to such suspicious transactions.  An important category of threats is build from temporary failures and losses that together could drive the organization to bankruptcy.  Thus, a financial buffer should be maintained, so penetration into the Red-Zone would trigger special care and intense search for bringing cash in.

Other categories should be created including their list of signals.  These include quality, employee-moral, and loss of reputation in the market, for instance by too low pace of innovative products and services.

Much less is done today on categories of external threats.  The one category of threats that is usually monitored is state of the direct competitors.  There are, at least, two other important categories that need constant monitoring:  Regulatory and economy moves that might impact specific markets and the emergence of quick rising competition.  The latter includes the rise of a disruption technology, the entry of a giant new competitor and a surprising change of taste of the market.

Step 2:

For each category a list of signals to be carefully monitored is built.

Each signal should predict in good enough confidence the emergence of a threat.  A signal is any effect that can be spotted in reality that by applying cause-and-effect analysis can be logically connected to the actual emergence of the threat.  Such a cause could be another effect caused by the threat or a cause of the threat.  A red-order is caused by a local delay, or a combination of several delays, which might cause the delay of the order.

When it comes to external threats my assumption is that signals can be found mainly on the news channels, social networks and on other Internet publications.  This makes it hard to identify the right signals out of the ocean of published reports.  So, focusing techniques are required to search for signals that anticipate that something is going to change.

Step 3:

Continual search for the signals requires a formal process for a periodical check of signals.

This process has to be defined and implemented, including nominating the responsible people.  Buffer Management is better used when the computerized system displays the sorted open orders according to their buffer status to all the relevant people.  An alarm system, used to warn from a fire threat or burglary, has to have a very clear and strong sound, making sure everybody is aware of what might happen.

Challenge no 2:  handling the emerging threats effectively

The idea behind any control mechanism is that once the flag, based on the signals received, is raised then there is already a certain set of guidelines what actions are required first.  When there is an internal threat the urgency to react ASAP is obvious.  Suppose there are signals that raise suspicions, but not full proof, that a certain employee has betrayed the trust of the organization.  A quick procedure has to be already in place with a well defined line of action to formally investigate the suspicion, not forgetting the presumption of innocence.   When the signals lead to a threat of a major defect in a new product then the sales of that product have to be discontinued for a while until the suspicion is proven wrong. When the suspicion is confirmed then a focused analysis has to be carried to decide what else to do.

External threats are tough to identify and even tougher to handle.  The search for signals that anticipate the emergence of threats is non-trivial.  The evaluation of the emerging threat and the alternative ways to deal with it would grossly benefit from logical cause-and-effect analysis.  This is where a more flexible process has to be established.

In previous posts I have already mentioned a possible use of an insight developed by all the Intelligence organizations:  the clever distinction between two different processes:

  1. Collecting relevant data, usually according to clear focusing guidelines.
  2. Research and analysis of the received data.

Of course, the output of the research and analysis process is given to the decision makers to decide upon the actions.  Such a generic structure seems useful for threat control.

Challenge no 3:  Facing unanticipated emergence of threats

How can threats we don’t anticipate be controlled?

We probably cannot prevent the first appearance of such a threat.  But, the actual damage of the first appearance might be limited.  In such a case the key point is to identify the new undesired event as a potential to something much more damaging.  In other words, to anticipate based on the first appearance the full amount of the threat.

The title of this article uses the example of a serious external threat called: cyber!  Until recently this threat was outside the paradigm of both individuals and organizations.  As the surprise of being hit by hackers, creating serious damage, started to become known, the need for a great cyber control has been established.  As implied, Threat Control is much wider and bigger than cyber.

An insight that could lead to build the capability of identifying emerging new threats when they are still relatively small is to understand the impact of a ‘surprise’.  Being surprised should be treated as a warning signal that we have been exposed to an invalid paradigm that ignores certain possibilities in our reality.  The practical way to recognize such a paradigm is by treating surprises as warning signals.  This learning exposes both the potential causes for the surprise and to other unanticipated results.  I suggest readers to refer back to my post entitled ‘Learning from Surprises’,

My conclusions are that Threat Control is an absolutely required formal mechanism for any organization.  It should be useful to stand on the shoulders of Dr. Goldratt, understanding the thinking tools he provided to us, and use them to build a practical process to make our organizations safer and more successful.

Cause-and-effect as the ABC of practical logic

Outlining clearly the causality behind undesired-effects, and wondering what effects, desired or not, would be caused by the actions we take, have been an integral part of TOC from its start in the early 80s. In the early 90s several structured procedures were developed by Dr. Eli Goldratt, in the format of cause-and-effect trees, called the Thinking Processes.  I think it is time to experience the merits, but also the limitations, of using logical claims in the shape of ‘Effect A’ is causing ‘Effect B’, for managing organizations.

My bachelor degree was in Mathematics, which is the ultimate use of strict logic.  In our daily practice we use logic both to reveal the causes behind effects we experience and also for speculating what is going to happen if we take a certain action.  However, that use of logic is not easy; it is combined with a lot of emotions that confuse the strict logic.  Even when we do our best to stay within the logical directives we are faced with several obstacles.  One of them is being able to distinguish between assumptions about cause and effect and actual causality. We certainly have great difficulty with hidden assumptions, meaning not being fully aware that the causality is only assumed and not necessarily valid.

Reality is fuzzy and includes huge number of variables that have some impact.  In order to live in such reality we have to simplify the picture we have in our mind.  We do it by ignoring many variables, assuming their impact is too small to truly matter.  The choice of what we ignore is part of the basic assumptions behind our cause-and-effect logic.

To experience the value and the boundaries of applying cause and effect let’s check the following effort to understand a practical logical argument.

It seems straight-forward logic to claim:

If ‘We improve the availability of items on the shelf from 80% to 98%’ then ‘Sales will go up’.

Is this assertion always true?  Are there some missing conditions (insufficiencies) for the causality to be true?  Even if it is true can we deduce how much more sales will be generated?

The initial logical explanation is that the missing 20% items have demand that is not satisfied, thus sales are lost.  If those 20% would be available they will be sold according to their natural demand.

The claim is shown in a simple chart:

initial state

The right hand-side represents the original claim, then some more explanations on current lost sales that would not be lost now.  The oval shape says that the two causes act together.

Two different reservations to the above logic are:

Some customers might buy the same item somewhere else.”   And: ‘Customers might buy another item instead of the missing item.’  Both reservations aim at the causal arrow connecting unavailability of items to losing sales, from that effect, together with the improvement, to the resulting effect of ‘Sales go up”.

The two reservations highlight a clarity issue. The improvement cause is stated “We improve…”, but who are ‘we’?   It could be the management of the chain of stores, the local management of a particular store or a supplier of a family of items.  Each of them gives a different meaning to the current state and then has its own reservation to the claimed effect of “Sales go up”.  The supplier of certain products means ‘his products’ are available only in 80% of the time and customers who buy replacement products cause the supplier to lose sales. If the availability of the supplier products would go up, then those specific products will be sold more.

This is a non-trivial ‘clarity’ issue.   We first have to deal with the clarity reservation by making a choice.  I have chosen the perspective of the store, and now I have to relate to the causality reservation doubting whether unavailability of an item always causes loss of sales to the store.

When customers don’t find a specific item they might buy a similar item.  In this case the store does not lose the sale.  In other cases the clients might simply give up.  In some rare cases the client might walk out, which could mean other sales are lost as well.  So, we conclude that some sales are lost because of unavailability, but the direct loss of sales is less than the calculated average sales of that item in the period of time it is short.

So, the above logical claim seems valid, but its real impact could be low.  We like to go deeper into the question when is the loss of sales due to unavailability significant?

Is the loss of sales equal for all items?

There are two parameters that make a significant impact on the loss of sales for the store when an item is missing.  The first parameter is the average level of daily sales and the second is the level of loyalty of the clients to the brand/item.

Fast runners, when they are short, create considerable damage not just to the direct loss of sales, but also to the reputation of the store – meaning customers might look for a different store in the future.  The logical statement is: if ‘a fast runner is missing’ then ‘many customers are pissed off’ causing ‘some regular customers look for another store to make their purchasing’ causing ‘total sales go significantly down”.  I’ve added ‘significantly’ to make a mark about the total impact.

But, as ‘management are aware of the potential damage to the store from missing fast-runners’ then we expect the following effect to apply: ‘management is focused on maintaining the perfect availability of fast-runners’.

So, we can deduce that if ‘the current management is reasonably capable’ then ‘the missing items do not include fast runners’.  Of course, 20% of the items being short might still mean non-negligible amount of sales of medium and slow movers being lost.   The open question is how much and even more:  how the current level of shortages impacts the reputation of the store and through this the future sales?

So, we need to look deeper into the impact of the second parameter – loyalty to a specific brand/item.  The effect ‘some items are special for some clients’ causes the effect that ‘some customers develop loyalty to that item’. This effect causes ‘the probability that some customers refuse to buy a replacement is high’.  Thus, if ‘items with strong loyalty are frequently missing’ then ‘some customers try other stores’.  The effect of ‘items with strong loyalty are frequently missing’ also causes ‘our reputation for what we carry on the shelves goes down’, with clear impact on the future sales.

The difficulty with ‘loyalty of customers to the brand/item’ is that it is difficult to validate its power.  The true test for the strength of loyalty is when the item is short and checking whether the sales of alternative items go up or not.

One additional reservation from the basic claim that improving the availability of items on the shelf would increase sales:  it assumes that ‘most customers entering the store know exactly what they want to buy’.  If this effect is not valid, then what is important for the sales is that the shelf is full with items that have good enough demand.  The effect that some items planned to be on the shelf are missing, but other items, with equal chance of being sold, fill the space well, would not cause a clear impact on the sales.  The kind of items that people come to browse and then choose (‘when I see it I’ll know’) have to managed in a very different way than maintaining availability of specific items.  For such items it makes sense to replenish them with new items, unless a specific item seems such a hit that maybe keeping it available is beneficial giving the high desirability of clients.

The effect of ‘The store has many regular customers’ has an impact on the meaning of ‘availability’ on the incidental customer. A shop in a big airport serves mostly incidental clients, so unavailability of items doesn’t impact future sales.  When there are no regular customers, then there is no difference between items that the store does not hold and items that are short.  This is relatively a small issue.

There are many more conditions that we consider true without further thought: ‘we live in a free economy’, ‘there are many competing choices for most items’ and ‘there is enough middle-class customers that can afford buying variety of products’.  If we try to include all ‘sufficiency’ conditions we’ll never end up with anything useful.  On the other hand it also opens the way to major mistakes due to hidden assumptions about what not to include in the analysis.  One needs the intuition when to stop the logical analysis, recognizing also the validity of ‘never to say I know’ (an insight by Dr. Goldratt).  Another aspect is the impact of uncertainty:  there are no 100% cause and effect relationships.  But, causal relationships that are 90%, or more, valid are still highly valuable.

Eventually we get the following structure as a summary of the above arguments.  Not all the previous effects have been mentioned, which means some of the logical arrows require more details, but eventually this is the claim.

Sales go up

We still cannot determine how much the sales would go up, because it depends on the characteristics of the medium and slow runners:  how many of them have strong loyalty.  If we add to the initial effects also ‘The chain makes marketing efforts to radiate the message that the chain maintains very high availability at every store’ then the chain can expect a faster and stronger increase in its reputation and in its sales.

Was it worth to go through logical analysis? 

While we still have only a partial picture, it is probably better than a picture based just on intuition without any analysis.

Antifragile – strengths and boundaries from the TOC perspective

Antifragile is a term invented by Nassim Taleb as a major insight for dealing with uncertainty. It directs us to identify when and how uncertainties we have to live with can be handled in our favor, making us stronger, instead of reducing our quality of life. Taleb emphasizes the benefit we can get when the upside is very high while the downside is relatively small and easily tolerable. Actually there is a somewhat different way to turn uncertainty into a key positive factor: significantly increasing the chance for a big gain while reducing the chance for losing.  A generic message is that variability could be made positive and beneficial when you understand it well.

While it is obvious that the concept of antifragile is powerful, I have two reservations from it. One is that it is impossible to become fully antifragile.  We, human beings, are very fragile due to many uncertain causes that impact our life.  There is no way we can treat all of them in a way that gains from the variability.  For instance, there is always a risk of being killed by an act of terror, road accident or earth quake.   Organizations, small and big, are also fragile without any viable way to become antifragile from all potential threats. So, while looking for becoming antifragile from specific causes adds great value, it cannot be done to all sources of uncertainty.

The other reservation is that finding where we gain so much more from the upside, while we lose relatively little from the downside, still requires special care because the accumulation of too many small downsides might still kill us. Taleb brings several examples where small pains do not accumulate to a big pain, but this is not always the case, certainly not when we speak about money lost in one period of time.  So, there is a constant need to measure our current state before we take a gamble where the upside is much bigger than the downside.

The focus of this article is on the impact of the concept of antifragile, and its related insights, on managing organizations. The post doesn’t deal with the personal impact or macroeconomics.  The objective is to learn how the generic insights lead to practical insights for organizations.

There are some interesting parallels between TOC and the general idea behind antifragile. Goldratt strived for focusing on directions where the outcomes are way beyond the inherent noise in the environment.  TOC uses several tools that look not just to be robust, but to use the uncertainty to achieve more and more from the goal.

A commercial organization is fragile, first of all, by its ability to finance the coming short-term activities. This defines a line where the accumulated short-term losses are allowed to reach before bankruptcy would be imminent. Losses and profits are accumulated by time periods and their fluctuations are relatively mild.  Sudden huge increases in profits are very rare in organizational activities.  It can happen when critical tests of new drugs or of revolutionary technologies take place then the success or failure has a very high and immediate impact.  As developing a new product usually involves long efforts over time, it means very substantial investment, so the downside is not small.  The gain could be much higher, even by a factor of 10, even 100, but such a big success must have been intended early in the process with only very low probability to succeed.  So, from the perspective of the organization the number of failures of such ambitious developments has to be limited, or it is a startup organization that takes failure to survive into account.

Where I disagree with Mr. Taleb is the assertion of unpredictability. The way Mr. Taleb states it is grossly misleading.  It is right we can never predict a sporadic event, and we can never be sure of success.  But, in many cases a careful analysis and certain actions raise the odds for success and reduce the odds of failure.

One of the favorite sayings of Dr. Goldratt, actually one of the ‘pillars of TOC’, is: “Never Say I Know”, which is somewhat similar to the unpredictability statement.  But Goldratt never meant that we know nothing, but that while we have a big impact on what we do, we should never assume we know everything. I agree with Taleb that companies that set for themselves specific numbers to reach in the future, sometimes for several years, shoot themselves in their foot in a special idiotic way.

Can I offer the notion of ‘limited predictability’ as something people, and certainly management of organizations, can employ? A more general statement is: “We always have only partial information and yet we have to make our moves based on it”.

There are ways to increase the probability of very big successes against failures and by that achieve the right convex graph of business growth while keeping reasonable robustness. The downside in case of failure could still be significant, but not big enough to threaten the existence of the organization.  One of the key tools of evaluating the potential value of new products/services/technology is the Goldratt Six Questions, which have appeared several times in my previous posts on this blog.  The Six Questions guide the organization to look for the elimination of several probable causes for failures, but, of course, not all of them.

Add to it Throughput Economics, a recent development of Throughput Accounting, which helps checking the short-term potential outcomes of various opportunities, including careful consideration of capacity. Throughput Economics is also the name of a new book by Schragenheim, Camp and Surace, expected to be published in May 2019, which goes to great detail on how to evaluate the possible range of impact on profit of ideas and the combined impact of several ideas, considering the limited predictability.

Buffers are usually used to protect commitments to the market. The initial objective is being robust in delivery orders on time and in full.  But, being able to meet commitments is an advantage against competitors who cannot and by that help the client to maintain robust supply.  So, actually the buffers serve to gain from the inherent uncertainty in the supply chain.

But, there are buffers that provide flexibility, which is an even stronger means to gain from uncertainty. For instance, capacity buffers, keeping options for quick temporary increase in capacity for additional cost, let the organization grab opportunities that without the buffer are lost.  Using multi-skilled people is a similar buffer with similar advantage.

So far we dealt with evaluating risky opportunities, with their potential big gains versus the potential failure, and try both to increase the gain and its probability to materialize. There is another side to existing fragility: dealing with threats that could shake, even kill, the organization.

Some threats are developed outside the organization, like sanctions on a country by other countries, a new competitor, or the emergence of a disruptive technology. But most threats are a direct outcome of the doings, or non-doings, of the organization.  So, they include stupid moves like buying another company and then finding out the purchased company has no value at all (it happened to Teva).  Most of the threats are relatively simple mistakes, flaws in the existing paradigms or missing elements in certain procedures that, together with a statistical fluke (or “black swan”) cause huge damage.

How can we deal with threats?

If management are aware of such a threat then putting a control mechanism that is capable not only of identifying when the threat is happening, but also suggests a way to deal with it, is the way to go. This handling of threats adds to the robustness of the organization, but not necessarily to its antifragility, unless new lessons are learned.

But, too many truly dangerous threats are not anticipated, and that leaves the organizations quite fragile. The antifragile way should be to have the courage to note a surprising signal, or event, and be able to analyze it in a way that will expose the flaw in the current paradigms or procedures.  When such lessons are learned this is definitely gaining from the uncertainty.  The initial impact is that the organization becomes stronger through the lessons learned.  An additional impact takes place when the organization learns to learn from experience, which makes it more antifragile than just robust.

A structured process of learning from one event, actually learning from experience, mostly from surprises, good or bad, was developed by me. The methodology is using some of Thinking Processes of TOC in a somewhat different form, but in general prior knowledge of TOC is not necessary.  The detailed description of the process appears as a white paper at:

The insights of Antifragility have to be coupled with another set of insights that are adjusted to managing organizations and have effective tools of making superior decisions under uncertainty. The TOC tools do exactly that.

Innovation as a double-edged sword

Innovation is one of few slogans that the current fashion on management adopts. The problem with every slogan is that it combines truth and utopia together.  Should every organization open a dedicated function for developing “innovation”?  I doubt.  This blog already touched upon various topics that belong to the generic term “innovative technology” like Industry 4.0, Big Data, Bitcoin and Blockchain.  Here I like to touch upon the generic need to be innovative, but also being aware of the risks.

It is obvious that without introducing something new the performance of the organization is going to get stuck. For many organizations staying at their current level of performance is good enough. However, this objective is under constant threat because a competitor might introduce something new and steal the market.  So, doing nothing innovative is risky as well. In some areas coming up with something new is quite common.  Sometimes the new element is significant and causes a long sequence of related changes, but many times the change is small and its impact is not truly felt.  Other business areas are considered ‘conservative’, meaning there is a clear tendency to stick to whatever seems working now.  In many areas, mainly conservative and semi-conservative, the culture is to watch the competition very closely and imitate every new move (not too many and not often) that a competitor implements.  We see it in the banking systems and in the airlines.  Even this culture of quick imitations is problematic when a new disruptive innovation appears from what is not considered “proper competition”.  A good example is the hotel business, now under the disruptive innovation of Airb&b.  The airlines experienced a similar innovative disruption when the low cost airlines appeared.

It is common to link innovation to technology. Listening to music went through several technological changes, from 78 records to LPs, to cassettes to CDs to MP3, each has disrupted the previous industry.  However, there are many innovations, including disruptive innovations, which are not depended on any new technology, like the previous examples of Airb&b and low cost flights, which use the available technology.  Technological companies actively look for introducing more and more features that are no longer defined as innovative.  After all what new feature, in the last 10 years, appeared in Microsoft Windows that deserves to be called innovative?

Non-technological innovations could have the same potential impact as new technology. Fixing flawed current paradigms, like batch policies, have been proven very effective by TOC users. Other options for innovations are offering a new payment scheme or coming up with a new way to order a service like Uber did.  Interesting question is whether the non-technological innovations are less risky than developing a new technology?  They usually require less heavy investment in R&D, but they are also more exposed to fast imitation.  The nice point when current flawed paradigms are challenged is that the competitors might be frightened by the idea to go against a well established paradigm.

It seems obvious to assume that innovation should be a chief ongoing concern of top management and board of directors. There are two critical objectives to include innovation within top management focus.  One is to find ways to grow the company and the other checking signals that a potential new disruptive innovation is emerging.  Such an identification should lead to analysis on how to face that threat, which is pretty difficult to do because of the impact of inertia.

There is an ongoing search for new innovations, but it is much more noticeable in the academy and with management consultants than with executives.   The following paper describes a typical academic research that depicts the key concerns of board members and innovation is not high in their list.

How come that so many directors do not see innovation as a major topic to focus on?

Let’s us investigate the meaning for an executive, or a director in the board, of evaluating an innovative idea. Somehow, many enthusiasts of innovation don’t bother to tell us about the (obvious) risks of innovations. But, experienced executives are well aware of the risks, actually they are tuned to even exaggerate the risks, unless the original idea is theirs.

On top of the risk of grand failure there should be another realization about any innovation: the novel idea, good and valuable as it may be, is far from being enough to ensure success.  Eventually there is a need for many complementary elements, in operations as well as in marketing, and most certainly in sales, to be part of the overall solution to make the innovation a commercial success. This means the chances of failure are truly high not just because the innovation itself does not work, but because of one missing necessary element for success.  The missing element could be is a significant negative consequence of the use of the innovative product/service.  This means a missing element in the solution that should have overcome that negative part of the use of the product.

Consider the very impressive past innovation of the Concorde aircraft – a jet plane that was twice as fast as any other jet plane. It flew from New-York to Paris in mere 3.5 hours.  The Concorde was in use for 27 years until its limitations, cost and much too high noise, have suppressed the innovation.  So, here is just one example for great innovation and a colossal failure due to two important negative sides of the specific product.

When we analyze the risk of a proposed innovative idea we have to include the personal risk to the director or manager who brought the idea and stands all the way behind it.  To be associated with a grand failure is something quite damaging to the career, and it is also not very nice to be remembered as the father of a colossal failure.

This is probably a more rational explanation to the fact that innovation is not at the top concerns of board directors than what the above article suggests. Of course, relatively young people, or executives who are close to retirement, might be more willing to take the chance.

One big question is how we can reduce the risks when an innovation carrying a big promise is put on the table. In other words, being able to do much better job in analyzing the future value of the innovation, and also plan the other parts that are required in order to significantly increase the chance of success.   Another element is to understand the potential damage of failure and how most of the damage can be saved.

‘Thinking out of the box’ is a common name for the kind of thinking that could be truly innovative. This gives a very positive image to such thinking where ‘sacred cows’ are slaughtered.  On one hand, in order to come up with a worthy innovative insight one has to challenge well rooted paradigms, but on the other hand just being out of the box does not guaranty new value while definitely mean high risk.

TOC offers several tools to conduct the analysis much better. First are Goldratt Six Questions, which guide a careful check from the perspective of the users, who could win from the innovation, leading also to the other parts that have to accompany the innovative idea.   Using the Future Reality Tree (FRT) to identify possible negative branches for the user could be useful.  Throughput Economics tools could be used to predict the range of possible impacts on the capacity levels and through this get a clue of the financial risk versus the potential financial gain.  The same tool of FRT could become truly powerful for inquiring the potential threat of a new innovation developed by another party.  We cannot afford to ignore innovation, but we need to be careful, thus developing the steps for a detailed analysis should get high priority.


The confusion over Blockchain

By Amir and Eli Schragenheim

Blockchain is often described as the technology that is going to change the world economy. In itself such a declaration makes it vital to dedicate a lot of time to learn the new technology and what value it can generate.  Blockchain is vital for the Bitcoin and similar crypto-currencies, but the claim of changing the economy looks far beyond the virtual money.  The direct connection between Blockchain and Bitcoin is causing a lot of confusion. While the Bitcoin is based on Blockchain technology, there might be a lot of other things to do with Blockchain as a technology by itself. Assessing the value of a new technology is open to wide speculations that add to the confusion.  For instance, Don Topscott says, among other predictions, that Blockchain would lead to the creation of a true sharing economy. A post on Bitcoin already appeared in this blog, (, where the biggest concern was that the exchange rate of the Bitcoin behaves in a too volatile way to be useful as a currency.  Let’s have a look on Blockchain as a new technology and inquire what the future value can be.

Let’s start with Goldratt’s Six Questions on assessing the value of a new technology. This is a great tool for guiding us to raise the right questions and look for possible answers:

  1. What is the power of the new technology?
  2. What current limitation or barrier does the new technology eliminate or vastly reduce?
  3. What are the current usage rules, patterns and behaviors that bypass the limitation?
  4. What rules, patterns and behaviors need to be changed to get the benefits of the new technology?
  5. What is the application of the new technology that will enable the above change without causing resistance?
  6. How to build, capitalize and sustain the business?

The power of the Blockchain technology

The simple answer to the first question (What is the power of the new technology) is being able to both execute financial transactions and (mainly) recording the information, being confirmed, in a way that is very safe.  The first part means transferring money from one digital account to another without the need of an intermediary.  However, the currency has to be one of the crypto-currencies and both sides need to maintain their digital wallets.  The technology checks that there is enough money in the wallet to make the transfer.

The second part of the power is keeping the safety of the information records that comprise the general ledger. This is the true unique feature of Blockchain.  Going into the general ledger already involves a certain level of checking and confirmation of many distributed computers.  In itself the recorded information is transparent to all (unless one codes it using the current available techniques). The unique part is that it is practically impossible, even for the involved parties, to change the information of the transaction.  If there is a mistake then a new transaction of correcting the previous one has to be executed and stored.

Coming now to the second question: what limitation is eliminated or vastly reduced by the new technology?

Blockchain experts claim that the current limitation of lack of trust between parties that hardly know each other is eliminated by Blockchain. Trade is problematic when the minimum trust isn’t maintained, thus governments force rules on trade.  The basic minimum trust means that when you pay the required price you have confidence that you are getting the merchandise you have paid for.  This is what governments try to control through regulations and laws. When it comes to exchanging value between entities in different countries maintaining the trust is problematic.

Is the limitation the need to use intermediaries? In most value exchange through the Internet we currently need, at the very least, two different intermediate parties – one that transfers the money and one that transfers the purchased value.  The intermediaries are, many times, slow and expensive.  Can Blockchain substitutes the shipping company? Is the essence of the value of Blockchain aims at lowering the cost of the value transfer?  If Blockchain would become effective in bypassing the banks then we might see a major improvement in the banks and substantial reduction of the cost.  When this takes place what would be then the limitation removed by Blockchain?

While Blockchain can directly supports the actual transfer of virtual money, it can only record the data about the physical transport of merchandise, unless the merchandise is digital. So, for buying music, ebooks, videos and other digital information it is possible to overcome the limitation of trust by Blockchain.  This is a unique market segment where Blockchain provides the necessary minimum trust for the value exchange.

We propose that the safety of the data is the key limitation that Blockchain is able to vastly reduce.

Is the current safety of the information on transactions, especially financial transactions, limited?

The irony is that the threat to our digital data is not that high today, but it is growing very fast. So, while people still feel relatively secure with their financial and intellectual data stored in the bank and in their computer or on the cloud, then in the not-too-far future this safety is likely to diminish substantially.

Let’s now evaluate the third question: how the security issues of value exchanges are done today?

First let’s focus on value exchange. Later, let’s review whether keeping very critical data safe would add substantial value.

What are the current generic difficulties of exchanging value? The first need is reaching an agreement between buyer and seller.  Does the seller truly own the specific merchandise the buyer is interested in?  The current practice is to buy only from businesses that have established their reputation – like digital stores that seemingly objective sites have recorded testimonies of satisfied buyers who purchased from those stores.  The more expensive the merchandise the more care the buyer needs to apply.

Credit-cards, banks, PayPal and the like play a major part in making money transfer relatively safe. Very large deals would use direct transfer between banks, and it is true that such a transfer, between different banks at different countries, takes today about three days and uses the cumbersome SWIFT system.  Credit card transaction might face the risk of giving away the credit card details, but there seem to be currently good enough protection, on top of the credit card companies taking certain responsibility and operating sophisticated machine learning algorithms to solve that.  As already mentioned we do not have any guaranty that in the near future all the current safety measures would not be violated by clever hackers.

Yet, there are two different major safety concerns from exchange of value. One is the identity of the site I’m communicating with for value exchange.  More and more fake sites appear that disguise as a known site.  This causes an increasing feeling of insecurity.  The other concern is that the seller would not follow the commitment to send the right goods on time.

The current generic practices regarding the safety of data lean heavily on the financial institutions using their most sophisticated solutions to protect the data. However, those institutions also become the desired targets for hackers.

Protecting our most important data, especially the identity of the person, the ownership of real-estate assets and medical records is of high value, requires using the best available protection means, and if a much better data protection technology appears then for such data it could bring a lot of value. Other data, which is much less critical, could use less expensive protective means.

The fourth question focuses on the detailed answer on how should Blockchain operate, and what other means are required to significantly improve the current situation regarding safety.

A solution based on Blockchain should come with procedures that, at the very least, follow a whole deal, from recording the basic intent to buy X for the price of Y, then initiate the money transfer, no matter whether it is a direct transfer or sending instructions to a financial institute to move dollars from the buyer account to the seller account.  Then the solution should record the shipment data of the goods until confirmation of acceptance.  The chain of confirmed data on transactions seems to be the minimum solution where the safety and objectivity provided by the Blockchain service (an intermediate!) yields significant added value to the current practices.

Such a service could also check the record of both the seller and the buyer: how many past deals were completed successfully, how many pending deals are open for relatively long time.  This is a much more powerful check than testimonials.  Fake accounts, without proven history, could be identified by that service, providing extra safety to deals.

Using such a service should have a cost associated with it, and we’re not sure it should be low. The users will have to decide whether to use it or stick to the current technologies depending on the perceived level of safety.

When such a service is launched, offering extra safe records of deals, then it could be extended to record keeping of ownerships and identities. In a world that is under growing threats to its digital records safety such a service is very valuable.  Will it cause a revolution in the economy?  We don’t think so.

As we don’t have, at the moment, a full Blockchain service there is no point in addressing the two last Goldratt questions.  Organizations that like to offer a service using Blockchain and complement it with the required additional elements would need to provide the full answer to the fourth question and then also answer the two final questions in order to build the full vision for the Blockchain technology to become viable.