A Guide to Implementing the Theory of
That “P” Word – Paradigm
What about that “P” word – paradigm? This is a word that we haven’t seen very much of in the previous pages. What could be the reason for avoiding such a common word? Well, maybe, because it is just such a common word – in business. And maybe also because it has lost its real meaning – in business.
We have used words such as; mental models, views or maps of reality, schemata, insights, intuitions, hunches, beliefs, and perceptions, but these are all personal entities. A paradigm describes a common view of reality shared amongst a great number of people. To further understand the real meaning of the word however, we must return to the origins of the term, to science.
Thomas Kuhn coined the word “paradigm” to explain how people who study the natural sciences could, as a group of individuals, work independently upon a problem and yet maintain general agreement about the nature of problem they are working on. In contrast many of the social sciences are in a “pre-paradigm” stage of “schools” where various groups of independent practitioners can’t even agree upon the nature of the problem that they are investigating. Kuhn wrote (1);
“ ... I was struck by the number and extent of overt disagreements between social scientists about the nature of legitimate scientific problems and methods. Both history and acquaintance made me doubt that practitioners of the natural sciences posses firmer or more permanent answers to such questions than their colleagues in social science. Yet, somehow, the practice of astronomy, physics, chemistry, or biology normally fails to evoke the controversies over fundamentals that today often seem endemic among, say, psychologists or sociologists. Attempting to discover the source of that difference led me to recognise the role in scientific research of what I have since called ‘paradigms.’ These I take to be universally recognized scientific achievements that for a time provide model problems and solutions to a community of practitioners.”
The existence of pre-paradigm “schools” is, of itself, not a problem, it is simply recognition of a certain stage or state. All of the scientific disciplines had pre-paradigm stages, some extending back into pre-history. These stages are a necessary part of the development of a paradigm. Competing schools exist until a problem is sufficiently well defined that it becomes the dominant shared view of the participants. In business at the moment the best illustration of a pre-paradigm stage is probably strategy where, currently, there are some 10 different schools of thought (2).
Schools arise because; “In the absence of a paradigm or some candidate for paradigm, all of the facts that could possibly pertain to the development of a given science are likely to seem equally relevant (1).”
In business applications the pre-paradigm schools that exist today within strategy, and perhaps also sales and marketing, are exceptions. Much of current business is conducted in accordance with widespread, strongly held, and internally consistent views. Many would argue that these represent paradigms. Indeed, we will argue here that there are at present two concurrent paradigms afoot. We have essentially done as much in the pages on strategic advantage and the OODA Loop, although we have so far continued to call these concurrent ideas “approaches.” Let’s now use the criteria of Kuhn, the originator of the concept of paradigms, to test the “fitness” of these approaches to his description of a paradigm.
And let’s add that, although there are two paradigms afoot at the current time, they are essentially mutually exclusive. The newer paradigm may have built upon the older pre-existing paradigm as we shall see, but unless a person is of “two minds” we can not hold on to more than one paradigm at one time. Moreover, paradigms are not whims or fashions, they are held dearly and given up reluctantly, and once given up they are not revisited. If you had a “paradigm change” this morning then it probably wasn’t a paradigm at all.
When people talk about “having to give up” or “overcome” so many paradigms, then they are confusing the detail of the interpretation that arises as a consequence of a paradigm with the paradigm itself. They are confusing policies with paradigms.
A paradigm is characterized by achievements that are “sufficiently unprecedented to attract an enduring group of adherents away from competing modes of … activity.” While at the same time it is “sufficiently open-ended to leave all sorts of problems for the redefined group of practitioners to resolve.” Kuhn considers that achievements that share these two characteristics should be referred to as paradigms. Furthermore he recognized that a group of adherents can “agree in their identification of a paradigm without agreeing on, or even attempting to produce a full interpretation or rationalization of it. Lack of a standard interpretation or of an agreed reduction to rules will not prevent a paradigm from guiding research (1).”
Before we delve any further into investigating the fitness of our differing approaches as paradigms, it is important to remember that we as individuals can not hold multiple paradigms at once. This website is written from the point of view of one of the approaches – the new approach; therefore it is sometimes difficult to completely argue for all aspects of the older and preceding approach.
In the introduction we presented a simple matrix that served to combine two key concepts, the concept of complexity and the concept of optimization.
From this simple matrix we deduced two diametrically opposed approaches. We have consistently used these two approaches to frame, and to reframe, our view of our organizations. The two approaches are;
(1) Reductionist/local optima approach.
(2) Systemic/global optimum approach.
We have been able to consistently use these two approaches, these two views, these two lenses, to classify and to sort the various business methodologies that we have examined in these pages. Let’s now collate all the different activities that we have examined (plus a few more from project management for good measure) and put them in a table sorted against the two approaches.
Let’s draw the table.
Surprisingly, when we do this we find that there are not only the two end-member approaches; but that there are also a number of methodologies that seem to be transitional between the two. The transitional methodologies might be described as having a strong leaning towards a systemic approach but still retaining vestigial reductionist parts. The transitional methodologies are enigmatic; we might “feel” as though they ought to be systemic and yet we “know” that they are not. And while we may “know” that they are not systemic, we may not know why they are not systemic. As we develop and tighten our definitions of what is systemic and what is not, we will be able to better understand this transitional class as well.
We have characterized our two approaches in terms of the methodologies that they embrace over a number of different aspects of organizational activity. We know which methodologies are characteristic of the reductionist approach and we know which methodologies are characteristic of the systemic approach. We are almost ready then to test our two end-member approaches for “fitness” as paradigms. It would be useful first, however, to remind ourselves of some the developmental sequences that we inferred in earlier pages. Let’s do that.
In earlier pages on accounting for change, production, and quality we constructed summary diagrams which, in addition to classifying various methodologies according to our two end-member approaches, also showed developmental relationships between the methodologies (or at least a broad interpretation of the developmental relationships). The developmental sequence is indicated by arrows. The arrows don’t show duration, but the relative positions do imply priority. We can use these diagrams as guides to test against some of the key characteristics of paradigms.
Let’s start with manufacturing process/production planning and control methodologies.
The reductionist/local optima approach is well represented; firstly by the family of material requirements planning (mrp), manufacturing resource planning (MRP II) and enterprise-wide planning (EPR). Secondly, it is represented by “reversions” from more systemic but nevertheless transitional approaches. The reversions are World Class Manufacturing and Lean Production.
The transitional class is composed of the Ford Production System and the Toyota Production System. Both methodologies are mass production systems and while both are paced or synchronized to the slowest step in the line, safety is distributed evenly throughout the system. The advancement of the Toyota system over the Ford system is that although safety is spread throughout both, the Toyota system seeks to substantially reduce it by increased quality throughout the process.
Drum-buffer-rope is the only truly systemic/global optimum approach. It is both fully synchronized, and contains reduced safety aggregated in the few key places where it maximally protects the whole system.
Let’s re-examine accounting methodologies in a similar fashion.
The reductionist/local optima approach is represented by the suite of; cost accounting, activity-based costing, and the balanced scorecard. Each seeks to measure almost everything, almost everywhere, most of the time. The balanced scorecard takes this principle further and applies it to non-accounting areas as well.
The transitional methodologies are variable costing and throughput accounting. Both seek to make finer and truer distinctions between variable expenses and period expenses; but both have their roots in cost allocation.
The systemic/global optimum approach is represented by the relatively new field of constraints accounting. Constraints accounting, for the first time, essentially subordinates the financial information system to the strategic constraints of the system and thus it is a truly systemic approach.
What then of the third and final set of methodologies that we investigated – quality planning and control?
The reductionist/local optima approach is represented by kaizen, total quality management (TQM) and six sigma. However, it is a little difficult to untangle the priority between kaizen and total quality management. From a North American perspective we might consider that total quality management developed out of kaizen, although from a Japanese perspective the opposite might equally be true. It is not so important; both are strongly reductionist and six sigma is the latest development out of this line of thinking.
Deming’s system of profound knowledge developed out of the much earlier work on statistical process control and is transitional. It still uses Pareto analysis to distinguish the areas to focus upon and Pareto analysis assumes independence between parts in the system. Thus it does not fully recognize dependency. Nor does the approach recognize the vast inequivalence between different parts of the system or process.
Stein’s TQM II is the only systemic/global optimum approach. It recognizes dependency and inequivalence and thus uses the focusing process to determine what is important and what is not. There is, however, a strong antecedent that the toolset is built upon – TQM.
Thus, we now have some broad understanding of the priority and developmental sequence of some of the most important methodologies that we have addressed in these pages. We are now in a position to better evaluate their suitability as paradigms.
Kuhn subdivided paradigm-based science into periods of relative stability which he called “normal science” and periods of change or scientific revolution. Let’s start at the start with “discovery,” then work through aspects of “normal science” that occur after acceptance of discovery, and then finally let’s examine something of the resistance of an older paradigm to the challenges of a newer paradigm.
"Discovery commences with the awareness of anomaly, i.e., with the recognition that nature has somehow violated the paradigm-induced expectations that govern normal science. It then continues with a more or less extended exploration of the area of anomaly (1).”
It is much easier to start here with the systemic/global optimum approach because discovery of the reductionist/local optima approach most probably has its roots in the Enlightenment movement of late 17th and 18th Century Europe. We need to ask first; what evidence of anomaly does the systemic/global optimum approach produce in comparison with the reductionist/local optima approach? Secondly we must ask; how does the systemic/global optimum approach violate the expectations of reductionist/local optima approach?
Let’s confine ourselves to consider just two critical points at the moment, one from production planning and control and one from accounting. From production planning and control the anomaly is that by identifying and protecting one or just a few critical points in a process we can substantially increase the output and decrease the total lead time. From accounting the anomaly is that even without an increase in output, we can substantially increase the total profit by considering just 2 things; product throughput (product contribution margin excluding direct labor) per unit processing time at the critical point in the process and the total operating expense (including direct labor) for the process.
How does this cause the systemic/global optimum approach to violate the expectations of the reductionist/local optima approach? In terms of planning and control it violates expectations that everything everywhere must be scheduled by instead writing a schedule for just one or a few entities, the constraint and any control points. It violates expectations that the process rate is some sum of the process rates of the various stages in that the rate of the constraint only, determines the rate of the whole process. It violates expectations of having sufficient safety distributed amongst all points in the process in that less total safety placed in front of a few key points will result in greater system safety. It violates expectations in that the non-constraints do not require scheduling, that they do and should hold more capacity than that of the constraint, and that they are the main determinant of total work-in-process and therefore lead time.
In terms of accounting the systemic/global optimum approach violates the expectations of the reductionist/local optima approach that total profit is the sum of individual product profits. Instead total profit is determined by the sum of the throughput per unit time on the constraint in the process. The systemic/global optimum approach violates the expectations of reductionist/local optima approach that operating expense (including direct labor) can be allocated to individual products. Rather expenses are aggregated to each process level. The systemic/global optimum approach violates expectations of reductionist/local optima approach that operating expense (period cost/expense) is accrued throughout the process. Rather operating expense is largely determined by the non-constraints.
By examining just these two aspects, production planning and control and accounting, we can say that we have positive evidence that the systemic/global optimum approach produces unexpected and anomalous results. The systemic/global optimum approach violates expectations brought about by the reductionist/local optima approach. We can infer then that the reductionist/local optima approach is a paradigm. If the reductionist/local optima approach wasn’t a paradigm, we shouldn’t care about the anomaly and we would have no expectations to violate.
Let’s examine then, another aspect of Kuhn’s argument.
“The success of a paradigm ... is at the start largely a promise of success discoverable in selected and still incomplete examples. Normal science consists in the actualization of that promise, an actualization achieved by extending the knowledge of those facts that the paradigm displays as particularly revealing, but increasing the extent of the match between those facts and the paradigm's predictions, and by further articulation of the paradigm itself.
Few people who are not actually practitioners of a mature science realize how much mop-up work of this sort a paradigm leaves to be done or quite how fascinating such work can prove to be in the execution. And these points need to be understood. Mopping-up operations are what engage most scientists throughout their careers. They constitute what I am here calling normal science. Closely examined, whether historically or in the contemporary laboratory, that enterprise seems an attempt to force nature into the preformed and relatively inflexible box that the paradigm supplies. No part of the aim of normal science is to call forth new sorts of phenomena; indeed those that will not fit the box are often not seen at all. Nor do scientists normally aim to invent new theories, and they are often intolerant of those invented by others. Instead, normal scientific research is directed to the articulation of those phenomena and theories that the paradigm already supplies (1).”
Once again it is more difficult to examine the normal science phase of the reductionist/local optima approach than it is to examine the more recent systemic/global optima approach. However given that caveat let’s attempt both. Do we see an extension of the reductionist/local optima approach, and do we see further articulation of the approach itself? Let’s confine ourselves once again to production planning and control and to accounting. In production planning and control the first automated systems were material requirements planning systems – “small” mrp. This allowed the automation and compression of hitherto complex and time consuming manual planning methods in the growing numbers of larger and more mechanized job and batch shops. Based upon the success in material supply the approach was then extended to manufacturing resource planning – “big” MRP and MRP II. In turn, based upon the success of that in shop floor planning, it was extended to supporting functions such as sales and ordering to become enterprise resource planning or ERP. The initial promise of mrp was extended and further articulated until it encompassed the whole business planning function.
If we look at accounting we must start with cost accounting which successfully used direct labor to allocate overhead costs and thus determine product costs. But we need also to be aware of a distinction, we need to step back for a moment, back to a time before mass production; back to a time when costing a “job” in shop was more important than costing a product in a repetitive process. The accounting systems of the railroads found their way into the steel companies that supplied the railroads and from the steel companies to Fredrick Taylor. “The system that Taylor absorbed …, made into his own, and altered to suit his clients, was one he would apply at company after company. It gave you, monthly, a statement of expenses, broken down by jobs labeled by letters and numbers and, later, by a special mnemonic system. It applied overhead not only to wages but to each machine, with time spent on the job the basis for its proportion of the overhead (3).” Prior to accrual cost accounting, overhead allocation was interested in jobs not products. It was a management system. “Many historians mistakenly associate the overhead allocation methods of these early mechanical engineers with the overhead application procedures used by twentieth-century financial accountants. …modern financial accountants require cost accounting to value inventory for financial reporting (4).” This is a financial system.
Given this distinction, the acceptance of more modern cost allocation was maintained even as direct labor became less important and was then further articulated in the development of activity-based accounting which could use cost drivers other than direct labor alone. The acceptance of activity-based accounting has led in-turn to an even broader application – the balanced scorecard approach. Each of these is both an extension of the reductionist/local optima approach and a further articulation of that approach.
The further development and articulation of the reductionist planning and control and accounting methodologies suggests that the reductionist/local optima approach is indeed a paradigm. How about the systemic/global optimum approach then? Do we also see an extension of this approach and do we see further articulation of the approach within the various methodologies? Let’s examine this, again using production planning and control and accounting.
The production planning and control the methodology is drum-buffer-rope. Drum-buffer-rope was originally applied to linear make-to-order situations but was further developed and articulated to apply equally to divergent/convergent flows and also make-to-stock environments. More recently we have seen the development of simplified drum-buffer-rope and the method has also been extended to “project” type production or manufacturing (5).
Accounting presents more of a challenge in that the systemic methodology, constraints accounting, is so new to the public domain that we can’t really evaluate it yet – although we can argue that the development of constraints accounting is nothing less than direct evidence of a further and on-going articulation of the whole approach.
Both approaches show evidence of intolerance of other theories. Paradoxically we see this in the work of Schonberger (6) who helped to introduced Japanese manufacturing techniques to North American. Even though he was a proponent of kanban for logistical scheduling to replace mrp, he considered that MRP II was still superior for “major event” scheduling. The resistance of the reductionist/local optima accounting methods to new theories invented by others is well documented in other sources (7).
Such reaction is not unique to the reductionist/local optima approach. It is equally evident in the systemic/global optimum approach. Anecdotally at least, it appears that until quite recently, other “competing” theories were barely mentioned by active Theory of Constraint proponents. Until recently acknowledgement of Senge’s work, or of Lean Production, or of Six Sigma for instance did not occur within the context of Theory of Constraints. As an example; even though we can see allusions to Theory of Constraints in the World Class Manufacturing literature (8) we do not see World Class Manufacturing mentioned in the Theory of Constraints literature. And we should add that the allusion to Theory of Constraints was a subtle broadside at that. Hopefully as we tighten the definition of the driver of the systemic/global optimum approach some of the reluctance to acknowledge these methods can be viewed as due to their “impure” and transitional nature. But we haven’t reached the point in this discussion that we can do that yet.
What we are seeing in the production planning and control part of the reductionist/local optima approach and the systemic/global optimum approach are the mopping-up operations of normal science – the extension and further articulation of the approach and apparent resistance to other ideas. This suggests that both the reductionist/local optimum approach and the systemic/global optimum approach are much more than just approaches; they are indeed paradigms.
Let’s press on.
“during the period when the paradigm is successful, the profession will have solved problems that its members could scarcely have imagined and would never have undertaken without the commitment to the paradigm. And at least part of that achievement always proves to be permanent (1).”
For the moment let’s examine just the more recent systemic/global optimum approach with respect to these comments. Theory of Constraints began as a manufacturing “thing.” It could have stopped right there and if it had, it would still have been a very valuable contribution. But it didn’t. We have to ask ourselves why it didn’t stop there.
The answer, in-part, comes from one of the earlier quotes – there was a promise of success discoverable in selected and still incomplete examples. And the answer, in-part, comes from a commitment to the new paradigm. The surety that something that worked for one aspect of a process here might work for another aspect of a different process over there. Thus commitment to the paradigm has allowed the development of not just a production application, but also a project management application. Moreover, not just single project environments but also multi-project environments as well, and process/project environments. Commitment to the paradigm has allowed the development of applications in supply chain, both raw material supply, and finished goods. Within supply chain It has also enabled the development of applications that are not just linear but convergent/divergent as well. It is commitment to the paradigm that allows these digressions to occur with some surety that the problem will be better illuminated by the paradigm.
Within the reductionist/local optimum approach an excellent example comes to us by way of project management. And although we are not specifically addressing project management, the example is too good to miss. Everybody knows about Gantt charts, right? And nearly every commerce student can tell you that they were developed in the ship building industry, right? Gantt was involved in speeding ship production through the Emergency Fleet Corporation – in 1917. But where did he train? He was Fredrick Taylor’s assistant from 1887 to 1893 and disciple thereafter (9). Gantt’s commitment to standardization and documentation within the reductionist/local optima approach learnt at Midvale Steel found its way into project management during the First World War.
This commitment of both the systemic/global optimum approach and the reductionist/local optimum approach tells us that these are more than just approaches; they are paradigms. However, commitment to a paradigm invariably brings about resistance.
“The source of resistance is the assurance that the older paradigm will ultimately solve all its problems, that nature can be shoved into the box the paradigm provides. Inevitably, at times of revolution, that assurance seems stubborn and pigheaded as indeed it sometimes becomes. But it is also something more. That same assurance is what makes normal or puzzle-solving science possible. And it is only through normal science that the professional community of scientists succeeds, first, in exploiting the potential scope and precision of the older paradigm and, then, in isolating the difficulty through the study of which a new paradigm may emerge (1).”
Do we see resistance to reductionist/local optimum approach? Sure, if you fully subscribe to the systemic/global optimum approach. The insistence on cost allocation by reductionist/local optima practitioners is seen as resistance by the systemic/global optimum practitioners. The assurance that reductionist/cost allocation is correct has seen a suite of increasingly more complex approaches; cost accounting, activity-based costing, and now the balanced scorecard. We see the same occurrence in the reductionist suite from mrp to MRP II to ERP and thence to isolated and imported elements of just-in-time as practiced in either World Class manufacturing or Lean production.
Without doubt these reductionist methodologies, both manual and automated, are directly responsible for a great deal of the increase in industrial productivity from the 1900’s to around the mid-1970’s. At some point around this time however difficulties began to become better known in both accounting (10) and production planning (11), still the assurance that had allowed the reductionist methodologies to succeed in the first place now began to look stubborn and pigheaded – at least to those who were aware that a new discovery had been made.
That brings us a full circle. It brings us back to where we started; awareness of anomaly. But now we can be certain that our two approaches are paradigms. Let’s summarize our findings so far.
There are two distinct approaches apparent in guiding business decisions today; they are the older reductionist/local optima approach and the newer systemic/global optimum approach. They represent concurrent, mutually exclusive, and internally consistent views that have been developed and articulated over a wide range of business activities. If we test them against the criteria that Kuhn used to describe the development of paradigms in science then we are left with the inescapable conclusion that both approaches are widely shared and strongly held concepts. They are both, indeed, paradigms.
We can now be quite sure that our end-member approaches are indeed paradigms. Thus the reductionist/local optima approach is a paradigm, and the systemic/global optimum approach is a paradigm. But these terms – reductionist/local optima and systemic/global optimum – are just descriptive names. We have used them throughout these pages to avoid introducing bias by referring to older more common names. What then are the more common names? Let’s draw a generic diagram along the lines of the ones above and see.
The older reductionist/local optima paradigm has been characterized by Corbett as scientific management (12). Scientific management was the development of Frederick Winslow Taylor and his associates; it dominated North American, European, and Asian industrial thought in the early to mid-1900’s (13). Scientific management as a discipline today is probably not so well known outside specialist circles, although the term “time and motion studies” is known anecdotally by most people. One of the major thrusts of this movement still abounds – the standardization of work procedures – and although this no longer necessarily means improvement, it is still the heart of a number of approaches such as ISO 9000 and its derivatives (if not in its fundamental formulation then certainly in the execution). Scientific management is the epitome of reductionist thinking, men as machines at the dawn of the machine age.
Scientific management didn’t really disappear. Rather, as we have mentioned on the page on measurements, it “morphed” into operations research – a wholly more respectable endeavor because it required large, expensive, and complicated computers. However at the heart of operations research is the desire to reduce the problem to its fundamental reductionist parts.
Let’s consider the transitional methodologies. Here we have placed systems thinking. Previously, in the individual methodologies we used; the Ford production system, Toyota production system, variable costing, throughput accounting, statistical process control, and the system of profound knowledge. All but the last of these are application specific. Systems thinking, in contrast, is closer to an overarching methodology and this is the reason for including it here as the representative for transitional methodologies.
In fact, we must further address systems thinking here because throughout this site we have treated systems thinking as synonymous with systemism and yet now we have chosen to treat it as if it were not. Systems thinking is somewhat paradoxical because it uses both simple and fundamental archetypes and yet it is still detail and data intensive. Systems thinking is transitional with its roots in the reductionist paradigm – most probably via operations research. The underlying assumption is that everything in the model and all of the data is of equivalent significance.
Senge illustrates the paradox well; “… the art of systems thinking lies in seeing through complexity to the underlying structures generating change. Systems thinking does not mean ignoring complexity. Rather it means organizing complexity into a coherent story that illuminates the causes of problems and how they can be remedied in enduring ways (14).”
We could sum this up as follows;
Dynamic complexity – isn’t
Dynamic complexity isn’t complex if we know how to locate and exploit the leverage points – the physical or policy constraints that keep us from our goal. In effect, knowledge of the constraints allows us to “see through” the apparent complexity. However, locating and exploiting the constraints is, of itself, insufficient. There is something else that we must know about, but we will have to leave that until we determine the fundamental driver for the systemic paradigm.
What then of the systemic/global optima paradigm? We hardly need to say that this is currently characterized by Goldratt’s Theory of Constraints. And let’s suggest that currently there is no other cohabitant methodology or approach that occupies this position. Again the reason will become clearer when we examine the driver for the systemic paradigm.
Scientific management, operations research, systems thinking, theory of constraints; are blanket terms for management philosophies within (and in-between) our two paradigms – but what then are the core underlying drivers that allow us to make this determination? What is it that underlies both scientific management and operations research that makes them reductionist? What is it that underlies Theory of Constraints that makes it systemic – and yet precludes systems thinking from the same paradigm?
Time to delve a little deeper.
What is the fundamental driver that underlies the world of scientific management? What is the fundamental driver that unites the reductionist manufacturing/process planning and control systems, accounting, quality, and project management methodologies that we have listed?
Could it be cost as in Goldratt’s description of the “cost world?” For Goldratt the cost world is pre-occupied with operating expense and independence (15). Certainly independence looks like a fundamental driver, but is cost? It seems unlikely that cost can be the fundamental driver for the paradigm. We know this from the measurements page; too often even while using cost as our guide we have to revert to “cost + intuition.” We know only too well that we let our intuition override the driver; therefore cost can not be the basis of the paradigm.
Let’s return then to independence. Could this be the fundamental driver for scientific management? Indirectly maybe, but probably not directly. Too few people have a conscious awareness of dependency and independency (statisticians excepted). Robert Kanigel gives us a clue to the real driver in the title of his biography of Taylor; “The One Best Way: Frederick Winslow Taylor and the enigma of efficiency (13).” It is that last word that is the clue – efficiency.
The fundamental driver for scientific management (and operations research and systems thinking) is efficiency. An efficiency focus coupled with assumed independence leads to local optimization everywhere. Goldratt of course was less equivocal; he simply called it “efficiency syndrome.”
Sometimes it is difficult to imagine how pervasive the concept of efficiency is. Steam engines – the very machine that powered the industrial revolution – are inefficient didn’t you know. At the onset of dieselization of the North American railroads steam locomotives were derided as thermally inefficient compared to diesel and yet it is only within the last decade that the largest diesel-electric locomotives have reached the same horsepower as the steam locomotives they replaced 60 years ago. Yes they were thermally inefficient – but stunningly effective.
Do you remember when radios didn’t have transistors but rather they had valves (or tubes) instead. Thermionic valves are inefficient too didn’t you know. Yet today very simple single-ended triode stereo amplifiers coupled to complimentary speakers are redefining high fidelity audio. Yes they are inefficient if wasting a few watts is a matter of concern – but they are also stunningly effective.
The concept of efficiency is so pervasive that it infiltrates almost everything that we do. Yet we make the error of equating efficiency with effectiveness. They are not the same thing.
The driver for the reductionist paradigm can be summarized in just one word then;
What then is the driver of the systemic/global optimum approach? Let’s have a look.
What is the fundamental driver that underlies the world of Theory of Constraints? What is the driver that unites the systemic drum-buffer-rope, critical chain, replenishment, and constraints accounting methodologies?
Could it be throughput as in Goldratt’s “throughput world?” For Goldratt the throughput world is pre-occupied with throughput and dependency (15). Certainly dependency looks like a fundamental driver, but is throughput? Throughput serves to focus on the open-ended potential for revenue generation rather than the closed-end approach of reducing existing costs against static revenue. However the financial measure of throughput is too close to the physical measure of output, and few businesses would fail to strive to increase their output. Thus, it seems unlikely that throughput is the basis of the paradigm, if that were so we would fail to have a differentiation and a differentiation surely exists.
Let’s return then to dependence. Could this be the fundamental driver for Theory of Constraints? Indirectly maybe, but probably not directly. An awareness of dependency arises whenever our span of control or sphere of influence is increased from a local to a more global perspective. We have certainly stressed that re-framing the situation from local to global is important – but it is insufficient. Local and global optima don’t represent mutually exclusive endpoints; they represent a sliding scale, a continuum, from one extreme to the other. It doesn’t seem so difficult to reframe from one extreme to the other, given the right circumstance it is almost automatic, therefore this can’t be driver of the paradigm. If it was there would be no difficulty and difficulty surely exists.
There is another aspect of dependence that we have touched upon. It is a unique perspective brought about by the Theory of Constraints through the recognition of the existence of a singular constraint within a process. There can only be one constraint in any one process under consideration, all other parts must be non-constraints. We must maximally exploit the constraint – no one doubts this. But in a system of interrelated dependencies we must also maximally subordinate everything else. This is the fundamental driver of Theory of Constraints in particular; and true systemic approaches in general.
You doubt this? Run around the house/office/factory/farm a number of times – let’s say 100 times for good measure. This is an incredibly efficient use of your lungs and heart and muscles to name just 3 functions. So, why won’t you do it? Because you have subordinated those functions to the whole system that constitutes your body. At right at this moment your mind is busy reading this text. It is so inefficient, but hopefully significantly effective.
We can summarize the driver for the systemic paradigm with just 3 words;
We can not repeat the word too many times. Moreover, subordination is fractal. It occurs at all levels and across all disciplines. Vertically, we must subordinate non-constraints in a production process to the constraint. In turn we must subordinate the production process to the market if that is where the ultimate constraint lies. However, we might also subordinate some markets to the strategy if that is the constraint to the goal of the system. Horizontally, within an organization we must also subordinate disciplines such as measurements and finance and quality to the constraint and the goal of the system.
Now let’s return for a moment to systems thinking. Nowhere in the 5th Discipline will you find an equivalent concept of subordination. This is the most compelling reason for considering systems thinking as a transitional approach rather than as a systemic paradigm.
If subordination is so simple then how did we get into this mess? We answered that on the measurements page; we grew into it. Previously – prior to the industrial revolution – local optimization via local efficiency was a valid paradigm. With the on-set of serial production processes we moved from local to global optimization. Global optimization is still achieved by local efficiency in the one place that it counts – the constraints. This part of the older paradigm remains. However, now we must subordinate all of the other non-constraints and it is this additional feature that distinguishes the new paradigm. Let’s try and make the distinction;
Reductionism and efficiency is the paradigm of independent entities – our pre-industrial past.
Systemism and subordination is the paradigm of dependent entities – our industrial present.
As we moved from job shops to flow shops and from craft to mass production, the process became more and more dependent and more and more serial in nature. Thus subordination became more and more important but we still mostly use the older pre-existing paradigm of efficiency that arose in the previous craft era.
If you like; we as people have remained the same but our mode of operation has changed – changed significantly. We are still in the phase of catch-up, changing our behavior to match our mode of operation. There is a mismatch at present, a mismatch that many of us can’t see. A mismatch that maybe our previous experience and “training” precludes us from seeing.
We saw that forming a systemic or global perspective isn’t difficult for those at the top but it appeared that they were held-back by the legacy measurements of a previous era. In fact we found that determining the new fundamental measurement wasn’t enough. We also needed a focusing mechanism – our plan of attack, the 5 focusing steps. And the key to that focusing mechanism is the one new step – subordination. Subordination allows us to determine what is “doing the right thing” in all circumstances. Without subordination we haven’t moved on from the older paradigm.
As we will soon see; we hear and we think that we understand the true meaning of subordination, whereas actual implementation experience shows that most often we don’t understand the true meaning at all. First, however, let’s try to further distinguish the two paradigms by looking at the differences between them.
In the following table are some of the key concepts found in the reductionist and systemic paradigms. This table allows us to effectively compare and contrast the two paradigms; we are able to see the similarities and differences more clearly.
Let’s start at the start. What do we mean by reducible? Well, we could use a quote from Margaret Wheatley to explain this; “… machine imagery leads to the belief that studying the parts is the key to understanding the whole. Things are taken apart, dissected literally and figuratively (as we have done with business functions, academic disciplines, areas of specialization, human body parts), and then put back together without any significant loss. The assumption is that the more we know about the workings of each piece, the more we will learn about the whole (16)..” Reducibility means that the whole can be known from an understanding of the parts.
To help to understand irreducibility let’s use a later quote from Wheatley and Kellner-Rogers (17). “A system is an inseparable whole. It is not the sum of its parts. It is not greater than the sum of its parts. There is nothing to sum. There are no parts. The system is a new and different and unique contribution of its members and the world. To search backwards in time for the parts is to deny the self-transforming nature of systems. A system is knowable only as itself. It is irreducible. We can't disentangle the effects of so many relationships. The connections never end. They are impossible to understand by analysis.”
Independence, invariance, and equivalence of entities within the reductionist paradigm are strongly interrelated. By equivalence we mean that all parts of the whole have approximately equal relative capacity or ability. Although each part may be serially coupled to others they are independent by virtue of local safety or buffering of some kind and their individual output is considered to be their mean output with no allowance for statistical variation.
Dependence, variance, and inequivalence of entities within the systemic paradigm are also strongly interrelated. By inequivalence we mean that some entities of the whole have greater or lesser relative capacity or ability than others within the system. Although each entity may be serially coupled to others they are dependent whether buffered or not, and their individual output is variable within the bounds of statistical variation (and then some as well – things that go “bump” in the night).
It is important to take care to remember also that the terms “constraint” and “non-constraint” don’t occur in the reductionist paradigm at all. Combining our discussion of inequivalence and constraint or non-constraint, Schragenheim and Dettmer reminds us that; “What makes a constraint more critical to the organization is its relative weakness. What distinguishes a non-constraint is its relative strength, which enables it to be more flexible (18).” We are also reminded of the effects of inequivalence in other ways as well. For instance; “The level of inventory and operating expense is determined by the attributes of the non-constraints.” Whereas; “The throughput of the system is determined by its constraints (19).”
We mentioned buffering or safety. We might think of this directly as safety time in projects or processes, as safety goods in supply chain, and as waiting time/patients in healthcare. In the reductionist paradigm where everything is equivalent, so too should the safety be equivalent and thus spread locally, liberally, and therefore equally throughout the whole. In the systemic paradigm where entities are inequivalent, so too should the safety be inequivalent. The maximal safety is found at the location of the least equivalence thereby protecting the whole system.
Protecting the whole system is analogous to exploiting the whole system.
Exploitation is the only word that is common to both groups. Common and yet its meaning is different. In the reductionist paradigm where everything is equivalent we should not be surprised to find that we must exploit each part equally. In the systemic paradigm where entities are inequivalent we should not be surprised to find that we must exploit each part inequally. In fact the English language does not allow us to say this. Thus maximal exploitation must be reserved, like maximal safety, for the least equivalent entities – the constraints in the system. The word we must use to describe the inequal exploitation of non-constraints is subordination.
Just as exploit is the only word common to both paradigms; subordinate is the only word unique to one of the paradigms. Subordination is unique to the systemic paradigm. Subordination as we know means doing what we should do and not doing what we shouldn’t do – according to the system’s perspective.
The fact that the word “exploit” occurs in both paradigms and the word “subordinate” only occurs in the more recent paradigm is hugely significant. Let’s have a look at this.
Even though exploit occurs in both the reductionist lexicon and the systemic lexicon, it has different meanings. Does that sound like a recipe for misunderstanding? Oh yes. Exploit in the reductionist lexicon means exploit everything everywhere and thereby optimize the system. Exploit in the systemic lexicon means exploit only the constraints and thereby optimize the system.
The word “exploit” is common to both paradigms and yet its application is distinctly different. This is the source of some of the confusion between reductionists who indeed think that they are operating in a systemic fashion and systemists who know that they are not. However, the word “subordinate” offers even more cause for confusion. There is no word for subordinate in the reductionist paradigm, the nearest word is sub-optimize and in the reductionist paradigm to sub-optimize a part is to sub-optimize the whole. It has a strong negative connotation.
Under the systemic paradigm, in order to optimize the system we must subordinate the non-constraints to the constraints. As the number of constraints is few, then the number of non-constraints is many, therefore most parts of the system are subordinated and this is optimal.
Under the reductionist paradigm, in order to optimize the system we must not subordinate anything. As there are no constraints, everything is viewed as important. Therefore, most parts of the system are not and should not be subordinated and this is optimal. Under this approach to subordinate at any time is to sub-optimize.
We must be very careful about using the word “sub-optimize,” it only has relevance in the reductionist paradigm. In the systemic paradigm we can not sub-optimize we can only subordinate. In a system, subordination is optimal.
We have talked about the cost world and its assumptions of independence and equivalence, but inequivalence is hinted at in the 80 to 20 rule – the Pareto principle. Essentially this says that 80% of the result in a system of independencies comes from 20% of the entities in the system – usually interpreted to mean that 80% of the income comes from 20% of the products. Another way to look at this is to say that by touching 20% of the system we can affect 80% of the system. This is a statement of a power rule. Let’s summarize it as follows;
Pareto Principle; the 80:20 rule – much of the output comes from a minority of the parts.
Now have you ever heard, anecdotally at least, of companies that sought to “get rid” of the remaining 80% of the products that give rise to just 20% of the income? They couldn’t do it could they? You have to have the remaining 80% of product base or client base or whatever to support the total system.
In the throughput world of dependency and inequivalence that we are talking about, the effect of inequivalence is much, much, greater than the 80:20 rule (13). Goldratt suggested a ratio of more than 99 to 1. Essentially this says that at least 99% of the result in a system of dependencies is determined by one or very few entities in the system. By touching just 1%, the right 1%, of the system we can affect the remaining 99%. This is a statement of dynamic complexity. Let’s summarize it as follows;
Goldratt’s Rule; the 99 to 1 ratio – almost all of the output is determined by one or a few parts.
The one or few parts are, of course, the constraints. For this rule to function properly we must ensure that the non-constraints do do the things that they should do and more importantly that they do not do the things that they shouldn’t do – in other words that they are fully subordinated. We, too, need the other 99% of the process base to support the total system.
Let’s consider for a moment that a paradigm is nothing more than an underlying dynamic to which we were previously blind to. Consider also for a moment that this new understanding of the underlying dynamic allows a whole “pile” of previously assembled detail to be described for the first time in elegant cause and effect (with no flying pig injections). Too often we are so close to the problem at hand that we mistake the detail complexity for the paradigm; it is not. It is the underlying dynamic that is the paradigm.
When the underlying dynamic of continental drift became established, then for the first time, several hundred years of geological observation (detail complexity) could be explained in elegant cause and effect. When the underlying dynamic of extraterrestrial impact became established, then for the first time, several hundred years of paleontological observation (detail complexity) could be explained in elegant cause and effect.
In our modern business structures too, the key to understanding the paradigm is in understanding the underlying dynamic. Let’s have a look then at the implications of our new found fundamental driver or dynamic – subordination.
Quality is a necessary condition (19). Maybe, then, timeliness is also a necessary condition – except that we don’t usually think of it as such. Both are a result of moving from craft to mass production – from multiple parallel operations to fewer large-scale serial operations. We have “caught up” in our understanding of quality but we still lag in our understanding of timeliness.
Quality is composed of two components; grade and variability. We verbalize grade as either high or low. We can illustrate this with two simple examples. A 1960’s VW beetle where quality is characterized by low grade and low variability, and a 1990’s Toyota Crown where quality is characterized by high grade and low variability. Both are arguably examples of very good quality. Shewhart defined quality as; "On target with minimum variance (20)." If we are to discuss quality we must discuss grade – the target – as well.
Quality is a necessary condition in modern serial production process brought about by product part dependencies and variability. In a craft system interrelated parts can be made-to-fit because they are made together in time and space. In mass production they must be made-to-tolerance because each part most likely will not be made at the same time or even in the same place.
Quality is a necessary condition rather than a goal because we only need to have a better level of quality than our competitors and one that our customer demands (or can be educated to want) in order to have a competitive advantage. Additional quality may not yield additional throughput for more than a small section of the market.
Timeliness, like quality, is composed of two components; the wait and uncertainty. We verbalize the wait as either sooner or later – shorter or longer. Two examples? Well, how about private and public service hospitalization. The private system is characterized by timeliness that is both sooner and more certain, the public system by timeliness that is both later and less certain. If we are to discuss timeliness we must discuss the wait as well as the uncertainly.
Timeliness is a necessary condition in modern serial production process brought about by process part dependencies and variability.
In a craft system batches of work, if indeed they exist, are small and the number of steps in the process is usually low and so timeliness is not a significant issue. In a mass production system, however, batches can be very large and the number of steps quiet considerable and therefore timeliness becomes much more significant. Timeliness is also a necessary condition rather than a goal because we only need to have a better level of timeliness than our competitors and one that our customer demands (or can be educated to want) in order to have a competitive advantage. Additional timeliness may not yield additional throughput for more than a small section of the market.
Let’s be careful to make a distinction between cycle time and timeliness. Let’s illustrate this with an classical serial system – an 1850’s tannery for book binding. In this process hides take about a year to tan to completion, this is effectively the cycle time – and for many people today this sounds horrendously long. However, it is possible to have multiple hides at each stage of the process so that the end stage is producing one hide per week or two hides per week – whatever is required. Thus we can be sure of that the wait for the next hide will short rather than long. The timeliness of this particular process is related to the production rate and its variability, not to the cycle time. Having said that; where by cycle time is affected by more than the simple production rate or duration, for instance because of rework or additional work arising from the length of waiting, then there is a case for treating the cycle time as a part of timeliness.
It is the dependent and variable nature of modern serial systems – our industrial present – that catapults quality and timeliness into the center stage. Of the two however; quality is much more tangible in nature and this helps to explain why quality has had an earlier and more pronounced profile than timeliness. Quality is a more obvious factor and probably the more important factor at first. There is no point in the rapid and timely production of sub-grade or highly variable output, however, once quality is no longer a defining issue then timeliness may become one if a competitor wishes to exploit it.
There is also a more subtle interaction here. Increasing product quality – that is closer to target with reduced variation causes increased timeliness. That is what just-in-time does. The continuous improvement in product quality through the process results in increased timeliness within the process. Thus improved timeliness is a direct consequence of improved quality.
The opposite, however, is not true. Timeliness does not have a direct consequence on quality. As we discussed on the Quality/TQM II page, quality in a Theory of Constraints application does improve, but indirectly, from knowledge of the affect of poor quality on the output of the constraint. Even if we forget the notion of Throughput for a minute, improving timeliness still does not directly affect quality. It does indirectly affect it through our prior knowledge that quality affects timeliness.
If you are still with me; then when we have a timeliness issue we may look at product or process quality issues in an effort to resolve the timeliness issue, however resolving the timeliness issue by itself (through reduced lead times or effective buffering for example) will not, of itself, improve product quality. This is a long way of getting around to the point that we should not be surprised that improvement in product quality has had better “press” until now than improvement in process timeliness. This says two things;
(1) Companies that seize the timeliness opportunity have a strategic advantage.
(2) We must still continue to address product quality issues at the same time.
As businesses have become more specialized, larger, more consolidated and integrated, and more efficient, the aspects of quality and timeliness have become more and more important. However, both quality and timeliness as competitive issues have been mostly “fought out” within the older reductionist paradigm. How much easier it would have been if they had been fought out within the newer systemic paradigm. Once again the organizations that understand the new paradigm can be much more successful in utilizing these two competitive pathways without suffering the diminishing returns of the old paradigm. Why is this? Let’s see.
Stein’s central message can be interpreted as; had subordination been better understood then quality improvement initiatives could have been much more rapid, focused, and successful than has been the case. Goldratt’s central message can be interpreted as; had subordination been better understood then timeliness and output initiatives could have been much more rapid, focused, and successful than has been the case. After all, subordination too, is a necessary condition. Additional levels of subordination beyond that which is sufficient for the system to meet its goal will not move the system any closer towards its goal. But first we must ensure that indeed we have reached sufficiency. Let’s show some provisional relationships.
As a necessary condition, subordination is more fundamental than either quality or timeliness. It is the precursor or driver of the other two. We need to understand subordination if we are to properly understand quality and timeliness. But let’s be careful. Let’s consider this as a provisional illustration. We will soon see why, we will return to it shortly.
If subordinating the non-constraints is a necessary condition, then so too is exploitation of the constraints a necessary condition. Both are necessary conditions for moving the system towards its goal. This raises an interesting point, sometimes we consider failure of a system to be due to the “wrong” goal having been chosen, when in fact failure is due to insufficient fulfillment of a necessary condition. This happens not only at a local level, such as with insufficient subordination, but also at a global level. We can illustrate this effect at a global level with the goals and necessary conditions common to businesses in the United States and Japan.
The goal of corporations in each country is often different, and we might be inclined to think that one is right and the other is wrong, but this only misleads us. It is the insufficient fulfillment of a differing necessary condition in each case that is really the cause the problem. It isn’t the differing goal. We need a separate page to do justice to this argument, you can find it here. Otherwise let’s continue on with our two necessary conditions – exploitation and subordination.
We need to ask ourselves to what extent does the reductionist paradigm carry over into Theory of Constraints? When most people are first introduced to the systemic paradigm of Theory of Constraints their reference environment, their total experience, and certainly their performance measures are likely to be firmly rooted within the reductionist paradigm. Let’s investigate this further.
We drew the diagram below on the process of change page to show that the absence of subordination was the critical difference between the two paradigms. However, in doing so we may in fact have sub-consciously reinforced that the presence of exploitation is the real issue – at least to those operating within the current reductionist paradigm. Think about it.