In part 1 of these series I discussed the concept of Naive Intervention as a response to purely human need of causal narratives, while no such thing exists outside our brain. In part 2 I discussed the priority of survival over efficiency in our intuitive responses to events.

In part 3, I want to conclude my essay with a discussion about the similarities of illusions of managing a business with processes and illusionary investment theories. In both cases intellectuals use claims of unproven hypothetical benefits to justify acts of naive intervention.

Let me add once more that I am not referring to process management in manufacturing where the benefits of repeatable and solid processes are obvious, but to industries where service and customer interaction is the product. A lot can be learned from manufacturing, but you can’t turn the people who service your customers into robots or monkeys.

Less information about the more important thing makes decisions safer.

Investment theories use mathematical models to predict for example the future value of a stock, broadly based on the Efficient Market Hypothesis. I discussed in part 1 and 2 that it is arrogant to pretend that the vagaries of the business world and economy can be predicted by a few formulas. Similarly, Business Process Management uses symbols to express a model of how processes should provide a certain value in the future. Apart from a functional syntax, there is not even a definition what the true meaning of these symbols is. They express logic that does not exist in business interactions outside process management theory. It is an unproven assumption that BPMN models can actually express business interactions or even more important can represent what a business wants to deliver in value. The appealing simplicity of process graphs is understandable but their use is actually naive.

As a further point I propose, that deciding in a larger business ‘which processes to optimize how’ is similar to deciding into which stocks to invest on the stock market. Why? Because they follow the same investment principles, require a similar risk assessment and therefore will be exposed to similar fallacies. You buy a stock at a current market price and you take a risk of it going up or down. You might buy a future from a partner who guarantees you a stock at a certain price at some future date. Both parties take a risk in doing so. That risk estimation defines the risk premium. You ‘buy’ a better process through its implementation and maintenance cost. For that it provides a return in reduced costs or improved value. There is a slight difference in that you can’t sell the process to someone else, but some process outsourcers actually try to do so. The main return of stock is not its dividend but the price difference between purchase and sale. Overall that does not matter in a future value consideration. It is the return that counts regardless of how it is achieved. The risk is the uncertainty how much return the ‘process stock’ I invested in will deliver. With processes I am even less sure what the purchase price is as the implementation costs are upfront purely assumptions, as are the expected returns in terms of savings or improvements. More information about past process implementations does not help me at all in that consideration.

I thus suggest that a BPM process implementation could too be measured by an ALPHA (how much better are you doing than the average) and a BETA (average return on the market). Alpha makes BPM worthwhile, beta doesn’t. But how can we calculate these numbers in terms of the return of a process? It is really difficult. For that simple reason the main selling point of BPM in the past has been cost reduction. Firing people is a simplistic short-term cost benefit that any idiot can understand. But that does not automatically turn a BPM investment into long-term benefits and it does not make it a competitive measure. Cost reduction is a naive intervention performed by clueless management. An important point is that there are limits to cost reduction. There are only three reasons for the suggested increase in efficiency in industrial production and they are not related to managerial skill or BPM. It is miniaturization in electronics, automation in manufacturing and outsourcing to cheap third world countries. These reasons are running out of room to move. In the long run it is much harder to make money by lowering cost than by spending money to improve quality.

Apple has driven up perceived value and changed the world.

Others merely drove down cost in a spiral to extinction. Apple made customers pay a pleasure premium over the cost of the product simply because they offered a unique emotional benefit. The problem is that the pleasure is not a simple measurable quantity at all, and neither is displeasure from a cheaper, but lower quality product. BPM should thus be about improving perceived quality and not about reducing costs.

Because customer perceived value cannot be determined by a model or guaranteed by certain processes, all decisions in this arena must be based on intuition and not on probabilistic prediction. It cannot take you out of BETA territory. So the question is: how could we capture reality and make things better by performing to the real-time perception of value by the customer. Quality in the definition of current BPM methodology conforms to some abstract, usually measurable spec of a deliverable when the real thing is the emotional reaction of a real person only! Therefore we simply can’t predict or measure the true outcome of processes. We thus need to focus on creating enough potential for perceived value.

The prediction that a particular process will instill a certain perceived value reeks of ignorance. Even probabilities such as coin throws in the physical world are influenced by chains of uncertainties. By the law of large numbers, coin throws are utterly predictable in the average, but that won’t tell you what the next coin throw will show. Customers are further influenced by emotional people interactions rather than a platonic, theoretical perfection. In the real world where things are chaotic, small variations in starting conditions produce substantial variation in the causal chain. Probability chains in people interactions can’t be calculated at all. Emotional, intuitive response to a customer is the only real world measure to influence perceived value and thus true outcome. Only people who care are able to deliver such value. Process management’s ONLY real world benefit can be achieved by improving how people interact effectively, including how to make that interaction more efficient by not losing incidental information or missing goals. A hard-coded flow doesn’t do that.

There is however no point in asking people what they want, where they want to go or where they will be tomorrow. Like you they don’t know. They only know what they want when they had the experience of getting it. Even if there is a statistical distribution of people reacting to that physical outcome with different emotional perceptions, like with coin throws that does in no way predict an individual reaction. Which simply means that at best ALL your process management efforts will be no more than the BETA – you will never go beyond average. There is no potential upside. You are wasting your money. Simply do nothing. It’s cheaper.

BPM experts use the same approach as economists – simply ignore complexity!

The standard process flow assumes that only a minor variation around the mean will take place in the future. The radically naive assumption of BPM is that the variations of a process outcome will only be the same risk of diffusion of past observed variations by which the variation in perceived value is (like in stock markets) related to the square root of time.

Variations in processes must however be considered in three ways: variations of the outcome over time and the variation across different processes, and third the unpredictable outside influences that move the outcomes of all variations away from their starting values. From what I have seen, the consequences of that are not understood by most BPM experts. They do not even consider it but assume that a governance structure will take care of those problems. But as I pointed out previously, governance does not actually align the process with changes in context, it just demands more governance to enforce previously defined processes. The common practice of standardizing processes is proof of that and it assumes that if the principle outcome is the same then clearly the process and cost leading to it should be the same. The standard process is the holy grail.

That one can come to the same endpoint from many starting points and through different paths produces a huge potential gap between the true cost and the perceived value across all process variations and all process starting points. The problem is that these processes work with implied parameters, meaning that some common performance indicator is construed to be relevant across quite disparate processes. The optimal process must be the cheapest one and therefore if we apply it across all customers and across the whole business then it must also be good for the whole business and also good for the future. That in effect is idiocy!

Just because you averaged out indicators that does not mean that all your processes will perform at average. Cutting cost this way carries the risk that some processes may be quite out of line and your numbers can still look good in average. There are no risk distribution profiles you could use. Some processes may experience huge volatility in outcome over time and some may simply not work at all. Your models won’t tell you and the glorious BPM dashboards are no more than fairytales. The only one to tell you is your customer! If you now say that you are doing customer satsifaction surveys they might again give you an averaged-out indication much too late, but it won’t tell which part of what process is the culprit. Big-Data-like analysis on processes just produce more stasticial noise about less important numbers. The problem is that a singular bad experience in your customer’s perception can wipe out your great process performance over the years. Emotions do not average out over the years and across processes. They are REAL and NOW and they make the customer switch in a cinch.

Antifragile – A favorable assymetry of winning options!

Antifragility (allowing gain from disorder) applied to processes enables more options to win than to lose in a favorable asymmetry and no amount of risk assessment or future value assumptions can do better than that. It basically means to play it safe in the large and allow for the potential upside in the small and not vice-versa by cutting costs across all processes. This is not the same as trying to standardize 80% of a process, as you still have the same problem within them. The other 20% have no upside potential at all and remain part of the average. It is more important to not lose that one customer (which is the first step to lose your business) than to have a large cost saving potential that could however bankrupt you. If you chose to not service a particular customer segment then that is a different thing alltogether. To become efficient is secondary to becoming effective or safe! If you choose a process that offers more options it is more likely to satisfy the customer even if you are less sure about the future costs and the future outcomes. More options means more antifragility and more potential for upsides. As long as we have a bottom line of process performance we keep them all reasonably happy and where possible we excel!

The same is true for your staff that ought to perform these processes. It is their caring attitude that is the only thing between a customer staying or leaving. This age of highly educated individuals demands a change in thinking. We must acknowledge that they collaborate as social networks of autonomous individuals. Studies show that only security, autonomy and appreciation keeps them in their jobs. Managing a business by individual performance is utterly futile. Averaging out these individual performance numbers tells you nothing about how your business is doing. It is the people network that makes the individuals produce value and not a process straightjacket. The quality of their outcomes is proportional to the quality of the relationships they entertain. An executive does not manage individuals, he is just a node in a network of people with some stronger ties. It is well understood that it is the weak ties (Granovetter) that make the network tick!

The difference between humans and animals lies in the ability to thoughtfully collaborate. Purposeful collaboration (=business) has an explosive upside, an additive capability that leads to evolutionary emergence of new stuff. All you need to do is to create collaborative environments such as the Apple Appstore that a connects developers (musicians) and users (audience) or a system like ACM that empowers the various departments and their internal and external customers to collaborate freely. Your processes become antifragile — they benefit from the disorder!

Let me close with a summary of various snippets and conclusions from ‘Antifragile’:

MBAs love strategic planning but there is no evidence that it works, rather the opposite. Don’t invest in business plans but in people. You don’t need a plan, but goals and an environment that enables people to collaborate towards them.

Everything theoretical in business and economy has been exposed as pseudo-sience. Evidence of absence is not absence of evidence — meaning that even if you can’t see it, it can still be there. Good news tend to be absent from past data but that does not mean that these are bad news. Empirical evidence therefore misses positives and underestimates overall benefits leading to the conclusion that something must be done. There is little evidence of good things that came from doing nothing.

The true question for a better future is not what we must add but what we can remove from our over-technologized world. Make it simpler but not by adding rules but by removing complexity. For cooking we still use the same tools as they used 300 years ago, just slightly improved to be non-stick or easier to clean. An iPad and most tablet computers are so appealing because they do not require technological knowledge to be used and they remind us mostly on how we used to work before we started to use computers. A two-year old can use them without being able to read or needing to be taught. Likewise, I propose that ACM is a return from the rigidity of BPM to the simplicity of people collaborating with content in the context of a case folder.  There were no processes but each performer basically knew what to do with the piece of content. ACM further adds guidance, context and auditing. While simplification is good, BPM flowdiagrams are an oversimplification.

Governance required to do BPM does not simplify — it complicates by means of rules. The most hindrance in developing human capital is the soccer-mom as per E.O. Wilson (enforcing structure that keeps kids from experimenting and adventuring) and formal education or HR programs. According to Nietzsche, not all that is unintelligible to humans is necessarily unintelligent. Nietzsche saw two forces in us: the Appolonian (measured, balanced and reasonable) and the Dyonisian (visceral, wild and untamed) or as the Asians called it, Yin and Yang. For progress we need both.

Nietzsche rather than Joseph Schumpeter first spoke of creative destruction. It is the wild and untamed in us that will destroy what the measured and reasonable set up as boundaries. If you are an executive then you should be using both forces wisely. The larger and higher the walls of rules that we create are, the harder and more profound will the earthquake be that takes them down. Looking at what is going on in economy and politics, it may be unavoidable there.

In Part 1 of this series I covered the problem that humans grossly overestimate our human rational capability and the power of non-emotional narrative in the form of theories and models. In this post on risk assessment and decision making I continue to quote freely from Taleb’s and Derman’s books.

We are demanding that the risks that we take are calculable.

While that is reasonably possible in the physical world, it is impossible in complex systems. Because our world is inherently unpredictable, human decision making does not utilize such rational and logical functionality but emotional weighting of available information from experience (Gigerenzer, Damasio, et.al.).

Most certainly you come to your decisions the same way:

  1. What can we know? -> How valid and plausible FEELS our input?
  2. What can we understand? -> How do we FEEL about the potentials (options and outcomes)?
  3. What can we influence? -> Do we FEEL capable of changing the course of things happening?

Our human ability to make decisions is thus not linked to reason as is mostly assumed. Russell Ackoff – who was a leading systems thinker – and others tried to structure that into the DIKW pyramid. Data, information, knowledge and wisdom are gained in that sequence to allow us to decide wisely. Ackoff preferred the concept of ‘understanding’ rather than wisdom in his explanations. I think because wisdom is clearly not about being logical or rational. Systems thinkers also consider themselves as overly rational and reasonable. That in itself can become a fallacy too. Many system thinkers build model illusions they then take for the reality. A true system thinker is foremost humble about his lack of knowledge.

Theories are right when they work (i.e. QED Quantum Electrodynamics is accurate to 12 digits) while models require explanation and verification. Just like an MRI scan doesn’t show a human’s emotions, an utility function like in the Efficient Market Hypothesis will not model a human’s buying decisions even if it seems statistically correct. Due to the individually acting agents of a complex adaptive system there is no such thing as predictable cause and effect in economics, finance and business.

More data is not automatically better!

Coming back to less is more or to remove what is wrong from part 1, we are entertaining another huge fallacy with Big Data. To come to good decisions you must REMOVE superfluous data until you retain the bare essentials that will keep you alive. Looking at everything through the illusion of Big Data analytics will most likely hide the real dangers in the noise. Daily changes in revenues or stock prices are no indicator where the economy or business is truly going. All they do is to provide an emotional background noise for people’s decisions. Obvious decisions require just a SINGLE good reason and not many and they don’t need statistical trends. Trends may be interrupted at any time by emotionally relevant news. So statistics are an observation but provide nothing for a prediction. They might actually do the opposite.

In the 80′s Time Magazine published an article that predicted that the then-current trend of diminishing oil prices would continue for some time and lead to prices way below $10 a barrel. This article caused OPEC to take notice and in an emergency meeting they decided to introduce strict export quotas for all member countries. While in my mind that makes OPEC is an illegal price fixing cartel there is in fact not much we or anyone can do it about except not to buy oil. As a consequence oil prices have been rising to its current levels ever since and most changes to the trends had little rational explanation up front. It was the observation of a trend with a naive model prediction that actually caused its reversal.

In practice, good decisions thus come from bad experience only!

… and luckily they don’t have to be our own experiences. Not clever thinking makes airplanes safer, but ugly and painful crashes. Even Fukushima was a valuable lesson to all PhD’s who design nuclear power plants and that in a country that created the word ‘Tsunami’. Intellectuals tend to focus on avoiding negative responses from fragility rather than recognizing their positive side-effects. That comes from working in theoretical lab environments that are however built to remove these outside influences!!! They tend to think that innovation comes from planning and an Harvard education rather than intuitive responses to bad experiences. In business, what nature and experienced people consider as a safety redundancy, MBAs purely see as inefficiency. Risk estimation and planning is just there to motivate people to take risks they DO NOT understand. But, not building a nuclear power plant is safer than building a theoretically safe one. Not buying a complex derivative is still a lot safer than buying one with an illusionary future value.

But there is no additional business in not doing something. So let’s give people a calculable risk and off we go. The calculated risk theoretically allows for higher risk premiums. People want to buy high-return, risky stocks with a calculated risk to make them less risky. Does no one see the paradox here? These are obviously not rational buying decisions! Yes, a well balanced portfolio might have the potential for a substantial upside on a small part of it with a smaller risk of loosing everything. But in the long run, if you rely on trends and statistics your return will be at best average with a substantial risk of loss as the system acts more volatile by everyone doing the same thing. If you DO NOT INVEST into risky stocks you might loose a little from inflation, but you will only lose if there is a big crash that takes everything down. As long as we believe we can calculate the risks of complex systems we are continuously increasing the risk of that total collapse.

In the long run it is a matter of survival!

Rationality and mathematics miss that past worst case events were at the time worse then all previous worst case events. Therefore decision making under uncertainty becomes even more relevant as we also have to consider matters of  survival. Fitness does not just mean to be just as strong as currently needed, but to be able to survive the next worst case. The notion of efficiency and optimization to improve profits is a naive rationalism that follows statistical theory and brings no other information than that it all fits under the Gauss curve. Survival issues are considered as too statistically rare to be of current relevance. As you make your business more efficient and more stable (by for example using BPM or outsourcing) you are unavoidably reducing its resilience by not being able to react continuously to changing external events.

But this is not just about business! Naive medical intervention (as recognized medical errors) kills several times more people than random car accidents. As cars crash frequently they get safer and safer continuously and people learn to avoid danger. Medical procedures do not change as fast as their use is highly regulated and their benefits are only considered in terms of statistical average. Additionally, the patients are given statistical information about risks to make an INFORMED decision. In reality doctors are misinforming patients by saying ‘This procedure is a calculable risk, so it is ok to take it.’ And if it fails it was not their decision. Some of that has to do with the practice of making money (lawyers and patients) through malpractice lawsuits. The immense cost and ineffectiveness of the American healthcare environment is largely caused by sortsighted gain of a few that misuse the naive intervention of the justice system.

Most medications are Naive Interventions with unknown risks.

Too many people who faught a supposedly heoric battle against cancer (like my sister in law) were in fact fighting to stay alive despite the medical treatment. Cancer treatment has only two treatment goals: tumor size and average survival after diagnosis. It does not take quality of life or time of survival without treatment into account! As we are diagnosing more (also less risky) cancers earlier the statistics do show more and longer survivors but to attribute that to treatment is a statistical lie. Someone who accepts the illness and doesn’t fight is branded a coward and quitter. How horribly arrogant and cruel can we become? When you know how treatment studies are performed (my late mother was a MD), then the pharmaceutical industry is not a life saver but purely a money printing press. And most of their grand discoveries (i.e. Penicillin and Viagra) were pure chance and not directed research! The combined side-effects of the many naive intervention medications (i.e. to lower cholesterol) that people are taking today are way beyond even being calculable!

You can get REALLY sick in LARGE hospitals where only antibiotics-resistant strains of bacteria survive. The constant antibiotics stress makes bacteria mutate to resistant variants while destroying our bacteriological microbiome with antibiotics makes us weaker. Many viral infections are treated with cure-all antibiotics while they only have a negative effect on bacteria in our microbiome. Treating children too early with antibiotics is now suspected to be a cause of the rise in allergies. Getting an infection is in fact healthy as it tunes the immune system to the changes in the environment. A natural birth and the immediate contact of the baby with the mother are so important because that transfers the most common bacteria from mother to child to jump-start the baby’s immune system. Without the constant stress of new bacteria we do not develop the ability to survive infections. Removing bacterial stress by too much hygiene is actually making us a lot less resilient. Most standard medical practice today completely ignores the long-term effect of treatments on our microbiome, making it largely naive intervention to suppress the apparent symptoms. Also a tumor is only a symptom. The real disease is a miscommunication between a body of cells and its biological context.

The hidden fragility of large systems with ‘industrial strength’ components.

A cat will survive a fall from ten feet unhurt, while an elephant most likely won’t. Because banks are so big, bailing them out, fixing prices or eliminating small scale speculation (similar to killing bacteria with disinfectants outside and antibiotics inside body) brings only illusionary stability until the crash. Suppressed volatility hides the truly existing risks until systems implode. In a complex adaptive system constant stress is not to be mistaken as overreacting to noise but must be understood as environmental tuning information.

What is claimed to be robust or ‘industrial strength’ is not, and it is also not the simple opposite of fragile. Robust will fail at some point as much as fragile, because all it offers is a tested strength to resist a well-known stress. ANTIFRAGILITY is a property of (complex adaptive) systems that improve when they are stressed. We need to re-learn that in a complex world the notion of a single logical cause or a predictable outcome of an action is suspect. The constant, random stress is information that aligns the small anti-fragile system with the changes in its environment. Large, apparently strong and efficient systems that have lost their ability to react to constant stresses are truly extremely fragile once the next large event happens or the system jitters. The true fragility of a system multiplies when most if its too-large entities are apparently robust – hence our financial system.

The same is true for projects. The larger the project the worse the outcome, unless the project is cut into many independently run elements. In too-large, too-rigid systems, variations never produce a positive effect but just worsen the situation as they produce more intervention to avoid them. Governments and global corporations completely underestimate non-linear convexity effects (see Jensen’s Inequality) with the multiplication of risks that come with size. The economy and businesses seem to become more and more efficient but the resulting fragility causes the outcomes of errors and/or events to be substantially worse.

Where is the evidence for anti-fragile benefits in Social systems?

Such evidence can only be found in real-world situations. Lab environments are not able to simulate real-world complexity. Simulating business processes is thus utter nonsense. In the Netherlands town of Drachten they removed all street signs in a traffic concept they call OpenSpace. As a result the traffic became a lot safer AND more efficient as pedestrians and drivers became more alert and active in participation. Less rules, more common sense. Good decisions are not about ‘knowing the future,’ predicting, calculating or enforcing outcomes but about creating an asymmetric potential of more positive opportunities versus less bad outcomes. Good decisions focus on survival or better ‘not biting the dust.’ Less people being hurt or killed is VERY efficient in the long run. Survival is more important than current profit. It makes no sense to be efficiently dead.

When however survival of ‘too-large-to-fail’ global corporations brings about the response to transfer their fragility to our economic system through bailouts or large loans then interventionism is no longer naive, it becomes outright stupid and ignorant!

It would be time to stop being so arrogant in pretending that we know it all and have it all under control. We obviously do not!

In Part 3, I will discuss the similarities of illusions in Investment Theory and Business Process Management.

‘Naive Intervention’ is a term used by Nassim Taleb (The Black Swan) in his recent book ‘Antifragile – Things that Gain from Disorder.’ Taleb explains that in business and economy progress comes from natural dynamics and not from naive intervention. He uses the term to describe management and political action that is based on theory rather than experience. Another book that asserts things I have said in the last ten years is ‘Models Behaving Badly – Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life.’ by Emanuel Derman whom I also quote widely here. This three-post series discusses why any approach that ignores real-world dynamics and complexity will eventually cause catastrophical failures. These books show that I am not alone with my opinions and proposals and that much of the BPM community is wearing blinders.

ACM has become an accepted way of guiding unstructured processes.

My conviction on these subjects are responsible for my work in the process management arena and particularly Adaptive Case Management. I have stepped away from discussing ACM as a software product because despite all the arguments to the opposite by Business Process Management ‘experts’, the functionality has become accepted as both standalone solution or as add-on feature of BPMS. What the BPM community has not yet understood is the concept of Goal Orientation. As a key element of ACM, I propose that it delivers embedded business governance that guides rather than controls.

Why is much of BPM still a form of Naive Intervention? The role of information technology is to improve the way a business can be managed. As an executive I look for tools that will not only control or reduce costs (MBA bean counting) but helps my business and therefore my employees to deliver customer value. While that requires a planning cycle to set goals, it is obvious that strategic planning methodologies as proposed by business consultants do not deliver. Only people who care deliver value. Economists and pseudo-scientific consultants overestimate the role of theoretical university knowledge in economy and business. They degrade the role of experience and intuition, which alone can help to deal with natural complexity. Interventionists won’t allow that goals can be reached and improvements can happen without (planning, command and control) intervention taking place. While ‘measure to manage’ makes sense to know where you are now and you are going, it is not the measurement that predicts or controls what will happen. CEO to accounting: ‘Our costs are too high.’

Steve Jobs was certainly not rational but simply followed his intuition. ‘Experts’ and Steve Ballmer laughed about his distrust of market research. It clearly shows that past or big data DO NOT predict the future. Why must the ‘right’ business decision or any other one for that matter be a rational and sensible exercise in logic and reason based on flawed data produced by illusionary models?

Not all science suffers from naive intervention.

What physicists do differently to economists is that they learn from nature. They observe and measure and then a hypotheses is turned into a theory and then a model. It works when it predicts. In economics and business naive interventionists build a model and then turn it into a religion. There is neither proof nor validation and at best there is anecdotal evidence. But economy is a social science and not physics. Social systems are dealt with through biology. Theories of economy must follow the same natural dynamics of complexity that drive all biological systems. A biologist like E.O. Wilson can teach us more about economy than any theoretical economist can. Wilson said that Karl Marx was right about Communism. Marx just applied it to the wrong species. It does work fine for ants!

The similarities of theoretical physics and economy lie only in their mathematical syntax but not in the semantics. In physics we can have if-then relations as theorems but there are no definite causal relationships in the complexity of economy or business. Economists present model illusions as the laws of economy and executives take rational methodologies as the principles of business. Mathematical or planning rigor does not turn fiction into fact. Intellectuals forget that any number they derive from economy or business by means of a mathematical model is not accurate or relevant but a snapshot abstraction that misrepresents the reality of the world. They most certainly won’t predict the future. At best they are self-fulfilling prophecies as long as people believe in them.

Why do we go wrong? We simply do not like uncertainty as it produces fear. Evolution does not need or provide narratives, but our human rationality wants explanations and predictions to reduce uncertainty. We create causal narratives despite the everyday evidence to the opposite: You don’t teach a child to walk by explaining the physics. The taste of food cannot be explained by chemical formulas. Cooking recipes (process flows) do not guarantee good taste! Despite all our models no one can tell you which way the stock market will go the next day. John Maynard Keynes: “Markets can stay irrational longer than you can stay solvent.” Keynes on the other hand believed strongly in naive political intervention through base lending rates and government spending. The question is how the ‘man at the controls’ would know which way to turn them.

‘In theory there is no difference between theory and practice, in practice there is.’ (Albert Einstein)

The difference lies in experiencing emotional aha-moments versus following a causal model theory. For knowledge gained without that personal experience it is easy to develop illusions about the causality of events taking place. Large systems make such emotional experiences impossible. BPM is a classical example as are the explanations why the stock market went a certain way. We have proof today that human decisions are purely emotional, while the Efficient Market Hypothesis (EMH) assumes that we decide rationally and while individuals err, the statistical average will be right. Nassim Taleb describes that the most successful traders had absolutely no idea about economics or the currencies they traded. They were not mathematically calculating or estimating the future as if-then-else chains but simply acting on guts. Given that EMH must be seen as the main cause of our current financial crisis, the so called Adaptive Market Hypothesis adds behavioral economics to EMH, by applying the principles of evolution to financial interactions. I doubt however that it will be better than human intuition.

As agents in the economy, our decisions weigh our desires to avoid pain and experience pleasure. That pleasure may have an altruistic motive or we might use reasoning to emotionally chose deferred pleasure or avoiding pain. That emotional component comes from personal experience and not from contemplating statistics. Dry science offers no such learning and if at all produces more uncertainty and thus fear. I can however learn from someone else’s emotional experience through emphatic narrative. We see other people and emphatically copy their behavior. We see us in their shoes. This is why true leaders lead by example and not through enforcement. Clearly our perception may be wrong or we may be misled, sometimes even intentionally. Look at political campaigns or the incredible promises of Ponzi scheme investment funds and you know what I mean. We are after all human and statistics won’t improve on that. Our gut tells us to stay away from things we cannot grasp.

There is no need for the RIGHT action, not even ANY action!

We are told by politicians, economists and business consultants that success or improvement needs rational directed action. What utter nonsense! Acts of commission are considered necessary and sometimes heroic, while acts of omission are considered dumb, lazy, ignorant and even signs of cowardice. You can succeed or be guilty by both action or inaction. That was already a core theme in my 2003 novel ‘Deity’. Interventionists forget that one can win just as much and with less risk by ‘not losing.’ Learning what NOT TO DO keeps us alive more than any book on ‘Ten steps to a safer (happier, prosperous) life.’ The greatest contribution to knowledge is to REMOVE what is wrong. A team is improved by removing the wrong people and it works a lot better than adding more better ones (see issues with size).

Weak leaders promote the concept of an ideal outcome that is however a fallacy of wrongly applying probability theory and expected value to complex adaptive systems and natural evolution. Communists and socialists use the emotion of envy to produce a narrative that claims that it is not ethical for one individual to have more. In social systems progress is however achieved by some doing intuitively better than others. Promoting equality is thus purely a matter of equal opportunity and not enforcing equal outcome! We know that communism failed because averaging outcome kills the natural dynamics needed for evolution to work. Survival of the fittest does however not mean the strongest and biggest, but the most adaptable to a changing environment.

But I am clearly not promoting to always do nothing, because we need to try something new to progress. However, following in others footsteps or executing model theories won’t take you anywhere new or interesting. To justify their existence, governments and executives promote the need to act and because they do not lead by example they write laws and prescribe work in a causal model illusion towards the (average) ideal.

Mathematical (Big Data) models will never beat our intuition.

So why in the world are naive, intellectual rationalists stuck on using communist-like intervention in a free market economy and capitalist business environment! It is the pretense of being in control. Using the same mathematical model for everyone equalizes the outcome while dramatically increasing the risk should the model assumptions be flawed. Our current problems are thus not caused by capitalist greed but by naive intervention into free markets.

True democracy and free markets cannot be ideal theoretical models, but they must be empirical approaches that allow natural dynamics. They do not average out failures and successes. They ought to produce the opportunity for substantial upsides while accepting some downside. Systems are not made safer by making the entities bigger and apparently more stable as these large entities become unmanageable and their dependencies uncontrollable. Any entity becomes a single point of system failure. Political intervention to save insolvent banks is only transferring the risk to the political system and thus the populace.

Why has the banling system not changed after the crisis? Clearly because the rotten apples were kept in the basket by government intervention. The continue to rot and spread rot as they did before. Why? Because of the complexity of financial links, politicians are now in a squeeze to act because they allowed both these large banks and their large transactions to pay for the huge debts required for their previous naive (political) interventions. The system is now inherently fragile as the model is utterly illusionary and thus false! Idealistic theories such as Communism or Efficent Market Hypothesis have limited upsides and only produce the negative potential of massive downsides through the ensuing complexity of more and more short-sighted interventions.

Our current form of neo-liberal capitalism is no longer a FREE market. Just look at the amount of rules and laws! Compliance has become a major problem further killing business dynamics. The USA and European Union are no longer democratic societies. Both are technocracies hyper-controlled by naive interventionists who have no clue about natural systems. Their downfall (and ours) are the size of entities that only SEEM to be more robust. That is so for countries, cities, political organizations, and global corporations, who are in fact all very fragile. The reason that these entities seem more robust is because they are made to look this way. Buying or selling a business contains perfect opportunities defining goodwill and write-offs that make the books look right. Global enterprises are not rated on the stock market by quality, value or even profit but by revenue, growth and how bold their deals are. Boards oust conservative CEOs who do not  push up the share price. CEOs are considered lacking in skill if they do not meet analyst expectations who have no clue what the business is doing. Does no one see how ridiculous all this is? Enforcing smaller entities and smaller transactions is the only way towards more natural dynamics in economy with less global risk. While the solution to this problem is in theory simple, in practice any kind of governance structure won’t reduce the amount of governance. Any problem will be approached by asking for more governance, a.k.a. ‘Naive Intervention’ creating more tension against the dynamcs of complexity. The only consequence is a crash that will dissolve these governance structures. Likewise, a business run by bean counters and interventionists on BPM processes won’t survive.

And that is not a model illusion but a simple lesson of history!

In Part 2, I will discuss that decision making under uncertainty is relevant for survival rather than efficiency.

Before I get into the actual HOW-TO part, let me reiterate another perspective as to why current BPM approaches and/or BPMS are so lacking. Rather than being upset about my critical observations, the BPM community should use the opportunity for discussion (TED: Dare to Disagree) and try to validate and prove BPM theory. Therefore I do not understand the lack of response after I provided a simple formula two years ago as to why flow-charted processes won’t deliver BPM benefits in a larger business. Not a single expert or vendor has brought forward a single counter-statement. Does that not make you wonder?

There is on the other hand a huge library of books, white papers, blogs and seminar programs of how to implement BPM in large corporations. They all boil down to a few key messages that are repeated over and over again with no more than anecdotal proof that any of this works. I am referring primarily to BPM methodology, but also to its eventual implementation via a BPMS of some kind. BPM should always be an enterprise effort, while BPMS are mostly localized projects. One can say that BPMS are managed by BPM governance.

Even with the best-of-breed BPMS, most large businesses struggle to identify current processes and model them towards some desired end-state. Users perceive BPMS to be restrictive and the offered participation in the governance as a smoke screen to hide that the ROI is mostly achieved through manpower reductions. Ultimately, vendors propose that the savings of small, local BPMS projects can simply be applied to the larger business.

To implement BPM successfully supposedly requires …

  • … an executive sponsor who will enforce the use of BPM.
  • … governance to avoid scope creep and increase business agility.
  • … first a culture change within the organization.
  • … to prove its return on investment in a short time.
  • … that BPM methodology is more important than BPM software.
  • … the ability for business endusers and stakeholders to create processes.
  • … BPM software that matches corporate needs and maturity level.
  • … stages of analyze as-is, model to-be, implement, monitor and improve.
  • … tools for: business strategy, process analysis and design or mining,
  • … flow-execution, rules, analytics, monitoring, content, and security.
  • … the integration with systems of record, Social, Mobile and Cloud.

Most people involved in BPM will not dispute those above requirements. They seem to be a common consensus. If all of them would be easily achievable I would have not much of an issue with them in principle. But that is not my main point. I propose that in the real world they are actually contradictory, because BPM and BPMS mean very different things. But then there is no way to sensibly do BPM without a BPMS …

The NINE Contradictions in BPM Implementation Principles.

  • If BPM would be capable of being business-driven then there is no need for executive enforcement.
  • If the implementation of processes would really happen through users there is no need for governance.
  • As business users can maybe draw a flow-diagram but can’t make it executable, the BPM stages are all performed by experts, actually reducing agility.
  • Both BPM methodology and BPMS ignore that users understand processes in terms of content and context and not in flow-diagrams.
  • To change business culture is a long term prospect and collides with short ROI time frames.
  • What kind of culture change should be necessary to motivate people to follow flow-diagrams all day.
  • To reduce scope creep and ensure ROI, governance limits end-user requirements and achievable quality.
  • A holistic BPM methodology is fragmented over different software products (BPMS, rules, events, content, integration) for implementation.
  • As the fragmentation requires governance, any change requires long-term planning and therefore reduces actual business agility.
  • If a BPMS is chosen to match current needs and maturity level then it has to be replaced frequently as the business matures.

I could go into a long explanation of why I see each of those contradictions, but for once I will try to keep my posts shorter and less philosophical. If you know how business and IT really works then you know that these contradictions are correct. But how come that no one has yet pointed those contradictions out? You will find ‘experts’ that speak about the ‘Triple Crown’ of BPM implementations, when they increase revenue, increase quality AND reduce costs, all at the same time!

Supposedly BPM – simply by following the methodology – is able to balance organizational assets and resources to provide differentiating services to the customer, ensuring maximum value at the lowest cost throughout the value chain. I want to evaluate that claim. Differentiation and individualization can increase perceived value, but cost money and need manpower to increase revenue and improve the bottom line. BPM is an investment in the future and ROI can only be long-term. But during implementation, BPM standardization freezes processes into average happy paths that then are very difficult to change because of the software fragmentation I pointed out above. There is actually no differentiation and individualization possible and it becomes much harder to do as it has to go through the governance cycle.

How To Think Big and Act Small in BPM

BPM methodology and BPMS implementation must go hand-in-hand or at least have the opportunity to do so. Adequate technology must support the BPM enterprise effort, even if it might only be used locally at first. BPM must think big, but BPMS must allow small scale perspectives on the business user level. Considering them separately is a huge mistake. While the adage of ‘Small is Beautiful’ has lost its luster it is still as valid. Even in Taichi Ohno’s Toyota Production System (the grandfather of LEAN) it was the worker cell on the factory floor that was responsible for quality and outcome and not the business strategy or a monitoring software. Methodology does not change your business; only people do.

Once the BPMS has been setup there must be no further process implementation stages. They alone kill the promised agility. Install it and let the business have a go. If they struggle, don’t enforce a useless standard but figure out with them what UI functions they will need to describe their processes intuitively by picking resources from library menus. Different business units will have different ideas about that. Forget process or UI standardization if you really want to empower the business. Standardization is only needed because implementing processes in flow-diagram BPMS is so expensive and the BPM governance is so slow.

I propose that the key aspects of implementing BPM successfully are quite different once someone understands the issues of social complexity, workplace psychology and people motivation. These define what weapons to choose and not revenue, quality and cost. They are consequences and outcomes, driven by people and can’t be enforced as immediate targets. Henry Ford said: “A business absolutely devoted to service will have only one worry about profits. They will be embarrassingly large.”

But how can one bring the larger organization together to work for commonly understood objectives, targets and goals and ensure that the customer perceived value is truly delivered? BPM methodologists tell me all the time that it really isn’t about flow-diagrams.

I propose that the following is needed to make BPM work:

  • Chose (buy, build or integrate) a homogeneous ‘System of Engagement’.
  • Create Top-Down transparency through a business-architectured value stream visible in the software.
  • Define budget responsible process owners and their outcomes and/or handovers. (Authority, goals and means)
  • Define with IT the ‘Language of Business (Process)’ that non-technical users can use to create processes.
  • Link with ‘Systems of Record’ and refine UI’s until the business units really want to use the system.
  • Define with process owners the targets for ‘bottom-up transparency’ that enables management reporting.
  • Let business units define how to execute and achieve the defined process goals and outcomes.
  • Business users collaborate freely to assemble resources (data, content, rules, forms, tasks) into goals. (NO UPFRONT DESIGN)
  • Successful goal-achieving work can be stored as templates and reused and still be modified for each execution. (=ADAPTIVE)
  • Motivate business users through autonomy, job security and recognition and forget monetary rewards.
  • Enable users and customers to vote and rate each aspect of the process in real-time.
  • Continuous improvement is enabled by user empowerment and the embedded project and program management.

Now clearly, I do not have any proof that this works as a BPM theory in itself. But the above (and thus concepts of ACM) is based on a broad set of accepted scientific knowledge about systems theory, complex adaptive systems, and behavorial economics. BPM/BPMS as currently promoted by huge advertizing budgets have NO scientific basis at all!

In the ‘Age of Complexity’, BPM methodology and ‘governance’ must be embedded in technology. The resilience required in this dynamic age can’t be achieved through a command and control attitude. Executives have to provide the perspectives and principles of the ‘Big’ while the people who actually do it, utilize their experience to execute and innovate in the ‘Small’.

The experiences of Mobile and social networks prove that technology is the enabler of change that brings them together.

A few weeks ago Keith Swenson asked me if our current age has been considered or named in the sense of a further step in our human evolution, much as it happened during The Enlightenment or The Age of Reason. I answered that I did not think so, but I spent some time on the subject and what it meant for the business world today. I came to the conclusion that while we are entering a new age, like in the 18th century there is substantial opposition against the progress of mind. I would even propose that many concepts of the Enlightenment have not reached business and IT management.

The Enlightement era started according to Bertrand Russel with the Protestant revolution against the Catholic church. Renè Descartes  started it in the scientific sense with his ‘Discourse on Method’. John Locke, Francis Bacon, Baruch Spinoza, Pierre Bayle and no less than Voltaire belong to the group that pushed the idea forward. It was however the German philosopher Immanuel Kant who made the term well known in 1784 through his essay: ‘Answering the Question: What is Enlightenment?’ He proposed that the roots of Enlightenment had been there since Horace and his book of Epistles who wrote in 20BC: ‘Sapere Aude – Dare To Know!’

Why did it take so long for ideas of The Enlightenment to spread?

It is quite obviously not only about the ideas and principles as such. Without the invention of the printing press the ideas of progress would have remained hidden from the eyes of the public. I propose that we are entering a similar new age as today it is Social networking that provides once again the infrastructure in which such progress can be pushed. Wikipedia, Google, Twitter and Facebook are a social canvas on which we paint a new picture of mankind for all to see who care. Whether it fosters movements like the Arab Spring (whatever the outcome will be initially) or allows Wikileaks to spread its information without control of governments, in the end all this would not happen without the Internet. Even simple blogging is a fast and immediate form of global sharing of knowledge that wasn’t there just ten years ago. It will eventually kill the copyright and IP laws that hold back progress, simply because they won’t remain enforceable. It will change the way the business world thinks and operates. But we are not there yet.

We now see the effects of true globalization.

Not in the sense that large enterprises raid third world countries in terms of manpower and natural resources, but in that the people of the world can communicate with anyone they want (with some limitations but still). It is not only the Internet but the huge step from a complex and expensive MS-Windows laptop computer to a powerful but simple, mobile smartphone. But imagine that without the low-cost manufacturing in Asia the Mobile revolution would have never happened. Add Cloud Computing to the formula and you have a completely different world economy than 20 years ago.

Small business have through Cloud computing now the same access to IT functionality that large businesses had exclusively before. They can be as efficient and still remain nimble and swift in markets that belonged to enterprises. The difficulty to run the huge conglomerates who thought that they are ‘too big too fail’, will eventually cause their downfall. They will simply be too difficult to control.

If there is one thing that seems to permeate all aspects of the change we see, it is the recognition of our lack of control. The likes of Nassim Taleb started a rethinking with ‘The Black Swan’. Many management experts are advising businesses to the need to think adaptively and lose the ‘command and control’ attitude. But there are counter-movements such as ‘Big-Data’ and Predictive Analytics’ that continue to sell a control illusion just like the one that was originally sold with BPM. But even one of its fathers – Michael Hammer – had turned back on that idea a few years later. His later words were less and less heard as he stopped to consider the control illusion feasible. On a positive note, Harvard Business Review printed an interview with Michael J. Mauboussin about ‘Embracing Complexity’.

I therefore call this era we are entering ‘The Age of Complexity.’

John Henry Holland and others started in the 80′s to discuss complex adaptive systems and emergence as the true creative forces of nature. His books tell the story better than I ever could:

  • 1975, Adaptation in Natural and Artificial Systems
  • 1995, Hidden Order: How Adaptation Builds Complexity
  • 1998, Emergence: From Chaos to Order

The overarching message is that there is no need for rigid control structures as the resonant interactions of forces evolve the least energy consuming operation. Structures that waste energy will simply fail in the evolutionary competition. Control creates counter-forces and wastes energy. The important elements are communication and alignment of goals. That too is the message and power of Social networks. We no longer need to fear complexity and try to avoid it, but we can make use of it. Those who do will sustain while the others will dwindle away. That large, complex systems are uncontrollable we can see with the European financial crisis.

It will be some time until the current army of control freaks will fall off the duty roster as they retire. They demand predictability and certainty when such is impossible. They propose that one can build and manage a theoretical economy and business model theory. Thus I want to call for the help of another Austrian-born thinker, Sir Karl Raimund Popper (1902-1994), who proposed to change classical observationalist scientific method in favor of empirical falsification. That is well accepted today. But many in business and IT aren’t aware what that actually means. It means that only a theory that provides methods for falsification is a valid one. It does however also mean that the theory that is the least probable (containing the highest information content that can be tested) is the most preferable one. I see no such falsifiable content for Business Process Management. There is no BPM theory but only a faith in orthodox, justificationist management concepts – ‘so many can’t be wrong’. Thus I propose to apply the theory of complexity and embrace the potential of information technology. The most amazing part is that the theory of complexity is the most simple one to apply, as it uses existing natural concepts. John Nash discovered that the most successful collaborations in nature and economy are the ones where individuals act in way that is not just good for themselves but is also good for the family/group/company, despite the fact that we cannot predict or control what that individual does.

To embrace complexity also means to embrace technology.

I have already posted about the relationship between apparent simplicity and underlying complexity in information technology.  KEEP IT SIMPLE is good, but we must guard against oversimplification, which I consider the largest fallacy of current BPM practices. Rather than accepting a business and its markets to be complex adaptive systems it assumes WITHOUT PROOF that a work procedure will guarantee outcomes. It ignores the complexity of human interactions, chaotic starting conditions, uncontrollable events and the cost of control for a supposedly simpler procedure-flow that thus ought to be better. Without a technological advance that dumps the current fragmented IT world for a ‘System of Engagement’ the Age of Complexity will mean the end of those businesses who won’t have the necessary adaptability. It needs BOTH different management and different technology!

Immanuel Kant considered “Enlightenment as man’s emergence from his self-incurred immaturity, but not from a lack of understanding, but rather the lack of courage to use one’s reason, intellect, and wisdom without the guidance of another. Our fear of thinking for ourselves.” And that is why orthodox BPM that does not allow people to think for themselves has no place in the ‘Age of Complexity’. BPM must be about aligning goals in purposeful collaboration of reasonable and skilled intellects and not about command and control! BPM must be about empowering people to act as individuals.

The final straw is for me that the kind of thinking that orthodox BPM promotes in a business, kills the disagreement that allows a critical review as proposed by Popper. Margaret Heffernan explains how that works in this great TED-Talk.

So if you want to finally be enlightened: Dare To Know and Dare To Disagree!

For some time we have tried to come to a kind of ‘Standard Model’ of ACM. Because there are so many approaches to ACM this has not been achieved. Some of the difficulty is that despite being performer driven, knowledge work still requires a planning perspective and effort. In what way can this planning be supported and still remain adaptive?

Planning work is not modeling!

Modeling is abstraction. But what the business needs is real world processes, not models in abstract language. I have proposed before that a business focused terminology has to be defined that describes both data and functional elements in terms that everyday people can understand. Many seem to believe that my fairly far-reaching considerations have to do with my skeptic stance towards BPM and that ACM will replace it. That is not the case, while that’s what will happen eventually, but it may no longer be called ACM.

To move away from that emotional hurdle, let me start like this: even if we look at it from the perspective that ACM only covers some subset of work (processes or not) that a company performs, then it still has to be aligned with the overall business strategy and operational plans, correct? Is there any work that should be kind of performed disregarding company objectives and management guidance? Clearly not. Much like documents we can dump work that is not linked to a process and in fact goal: WHY do we do it?

Now, if you give someone a rigid process, someone else has already thought about (in the governance bureaucracy doing process analysis) how to blend the business needs into the process flows. The performer just hammers happily away at his keyboard, ignorant to what the point of his work is. Great. Enter ACM and those poor sods, the so called knowledge workers. They are now expected to perform according to their knowledge of what the business or customers need to have at this point. In what way should that be less aligned with business strategy? Obviously they need to work towards it just the same, but unfortunately they are expected to do it kind of on the fly without strict step-by-step guidance. Mostly because of customers who are chaotic nitwits who can’t follow the process someone else considers to be ideal.

I propose that to achieve this, it is essential to create a top-down transparency of business objectives and targets for the value streams and the goals that process owners need to achieve. We define basically WHY we do what we ought to do and make it transparent to the performer. So the whole mumbo-jumbo of process optimization in the governance is suddenly a transparent exercise of everyone involved and it happens upfront before you even start to do the process. We still haven’t described any of the work, but we know WHY we should do WHAT for the customer. Knowledge workers are experts at the HOW and we tell them where to apply it and what the outcome of their work should be.

Knowledge Work: The only way is Up!

I have further proposed that the same concept is perfectly suited to be applied to change programmes, projects, plans, processes and cases? The higher you go in the hierarchy, the less flow-oriented work becomes. Adaptive management concepts can be applied at all hierarchy levels and on all time scales. Clearly, a project is not instantiated the same way fifty times, but the entities to describe a project are the same as to describe a process. We can spend a lot of time on abstract term definitions to describe the WHY, WHAT and HOW and we should, but in the end that term definition must be in business language. Regardless if they describe a project or a process. The entities and functions are the same.

One can have a very low-level conceptual definition that allows more flexibility but requires more knowledge by the user. Or you supply a limited functions set and with it a limitation in use. Some may be quite technical such as taxonomy, ontology, object, property, transaction, or assignments.  Properties might be used to identify (class), name (user) or link concepts together. Use that and you just lost the users!

It is important to use real world concepts such as activity, tasks, goals, documents, notes, times, business events or legal constraints. In terms of describing the work progression one can use events, decisions, calculations, rules, and conditions. Data types should be real world such as time, count, amount, and duration. For people we need skills, roles, hierarchy, and authority. To describe the environment that the user will interact with you have applications, processes, user interfaces, services, and forms. Keep it simple but unambiguous.

The main problem with the fundamental terms of ACM is that they have to be used ADAPTIVELY, meaning all elements must be open to change by the performer or basically anyone at any time. That does not mean to change the definition of the concepts itself. That is IT and architectural work. But in what way those concepts are assembled to represent knowledge work must be up to the business performer! While any kind of graphical editor is cute (flow or entity graphs) the whole point is to open the work descriptions of WHY, WHAT and HOW to business people: executives, management and performers. They want an intuitive, real-time representation of the ‘things’ that drive the business. Sounds easy, but really isn’t.

Goals, milestones, tasks and more …

Adaptive means that business people create the work tasks on the fly to achieve defined goals and can reuse those definitions in future when they want to work on those goals again. Goals ought to be linked to objectives and targets (KPIs and SLAs) to ensure that the business performs. BTW, ad-hoc tasks or allowing central changes that are immediately deployed to all processes DO NOT provide adaptive capability! That is still rigid, orthodox process management.

People tend to look at goals as milestones or sub-processes/cases. Keith Swenson recently suggested in a LinkedIn discussion that one can look at goals as tasks. Yes, one can but why should that make things simpler if it creates confusion? I propose that a goal in the sense of a business guideline is something quantitative, which does not have to be enumerable or measurable. Outcomes maybe quantifiable but still subjective. Operational targets are usually KPIs but they might still not be measurable. Service levels are typically measurable and enumerable as they are set up this way.

For projects a task could be used as a milestone but I propose to make it an explicit entity. A milestone is a time-line synchronization juncture and might be related to a goal, i.e. completion of all required tasks.  A milestone might be a decision point with or without a rule (i.e. once you reach runway speed V1 you must takeoff). It is still not a goal while you work towards it. I use the term objective for goals that are very abstract in the sense of a business strategy. ‘Increase revenue by 10%’ is an objective. Objectives are mostly achieved when the related targets, goals and rules are satisfied. But they can also be completely subjective and just checked off by the relevant person.

Without a clear term definition for the business users which I see as part of the Business Architecture, there won’t be real world use of ACM or BPM. Most of all business people won’t be able to describe their work without that language of process that reduces ambiguity. In the end the business choses to use the terms they want, but they should not be restricted by the limitation of a system that doesn’t allow goal definitions.

A lot has been written about process maturity. The different approaches proposed have as highest rating the ‘Optimized Stage’ of maturity, where continuous process improvement is enabled by feedback and by applying innovative ideas in an agile manner. Sounds good, so what is the point of process maturity assessments? In my mind nothing else than to sell consultancy services. Assessing process maturity is a pointless exercise that only leads to adding more bureaucracy to an already lacking approach. How can one start doing process management without making goal orientation and continuous improvement their starting point? Much worse than not well-defined processes are processes that can’t be optimized – regardless of the reason. That is why we do process management in the first place. Allow me to use the Higgs boson to guide you to my proposal why there is no need for expensive and slow process governance if you do it right.

Processes do not exist

BPM experts promote that processes have an independent existence (somehow disconnected from the real world) and follow odd rules that they seemingly make up when they are bored. First of all – in the most natural sense – is a process defined as no more than observing a sequence of (inter)actions that as whole have the consequence of some outcome. The idea to make this observed process now mandatory to achieve the same outcome over and over again only works in controlled environments such as factories or laboratories. It is not applicable in the real world of complex adaptive systems. Process flows are an over-simplification by ‘experts’ who do not understand the system that they are messing with. Because processes are event/action patterns and not rigid flows, I applied for a pattern-driven process mining patent in 1997, which I recently was awarded. But one can’t even start observing patterns effectively without a priori modeling. Yes, patterns can be seen without meaningful models, but then we need a long time to identify meaning – i.e. how a child learns for many years. One can’t model a flow of activity without the relevant capabilities (business objectives) that first need data or content models to make any sense. The illusion truly is in assuming predictability and controllability of a sequence of actions standalone – in my mind a consequence of human arrogance and pseudo-expertize!

The prediction of the Higgs Boson in the Standard Model

I have used quantum physical similes for explaining the above before and I would like to add another one here in honor of those who measured the Higgs mechanism on July 4th at the LHC. The Higgs boson has not been discovered or found as many say, but an energy signature was measured after several hundred trillions of particle collisions that can be interpreted to fit the predictions of the Standard Model for the Higgs boson with acceptable probability. In the real world hundreds of trillions of times the same process is being executed to smash protons into each other and only a few thousands times we can identify patterns that we can ‘probably approximately’ match with the model. That is the real world of processes and human interactions are no different. While the model requires (predicts?) the Higgs mechanism to be valid it can not predict the outcome of processes!

The Higgs Mechanism observed at the LHC at CERN.

A real-world process is defined by nothing else than some starting condition or event that causes (inter)actions that lead to some outcome (more about gauge theory later).

How does the above relate to process models?

There are many models that one can create related to processes. The most common and at the same time most misused one is the flow-diagram. Without a complete model of why and how people and resources interact towards what end, a flow-diagram is utterly point- and meaningless. Without having a business data model one cannot even observe the patterns that so many now start to rave about without knowing what it really means. And to make it all work the models that are being used for observation and analysis have to be aligned with the one used for execution!

Ideally a process definition to be used by people contains an explanation as to why that outcome is desirable. In the real world a process cannot be achieved by a declaration of a work sequence because the start and work conditions will be chaotic. The process must thus defined by which knowledge is required to achieve the goals. Knowledge is not data and not information and not contained in a predefined sequence. Knowledge is in the head of the performers (as experience patterns) who interpret the resources. Both contextual business data and statistical information (Big Data?) and work instructions are process resources and not knowledge.

It thus makes no sense to start a process management effort without explicitly defining what goals, outcomes and targets actually are because no one will know if the process that is being designed or already executed makes any sense. But once you define it it has to be measured and it has to be made transparent to everyone. Now you must be aware that no BPM system does that today. Yes, there are some BPM suites that have a monitoring component but what they measure is service levels and not process outcomes.

To be able to do so, the business has to define the capabilities in the value stream, the related targets and performance indicators and where in the organization the process owners will take responsibility. This is called a Business Architecture. It is actually irrelevant how the organizational structure relates to the value stream and capabilities. By defining end-to-end value stream processes this way, the goals and targets of each milestone become the handover definitions between organizational disconnected capabilities. Process owners who perform these processes are empowered to do them in any way as long as goals and targets are achieved. BPM vendors now use the term ‘empowerment’ when they let performers and customers participate in a rigid process for example via mobile or web. That is once again a very far-fetched use of the term, just as agile or adaptive for a complex governance bureaucracy.

Maturity implies self-sustaining independence for people

A company has process maturity when it no longer needs a huge bureaucracy to achieve its goals. A nanny-state government that writes laws about how to wipe your behind is not empowering its citizens but treats them like idiots. More rules and regulations do not make life and processes simpler because people don’t have to think, but overall it makes everything more complex. Compliance has become a major complexity problem for each and every corporation. Defining more rigid processes and rules makes it nearly impossible for people to use their knowledge and experience in fear of violating them. Any form of process rigidity kills the ability of people to engage the customer on a one-to-one basis and it also kills the creativity that drives innovation on any level. We live now a world in which knowing the rules (i.e. lawyers) is considered an act of being intelligent! Is this really where we want to go?

So starting to do BPM any other way than to define a top-down Business Architecture (which can be done for a single end-to-end process) and without using a goal-oriented, adaptive approach is doomed to fail. As much as you will hate to hear it, but if companies want to achieve process maturity, as a first step they will need to get rid of orthodox BPM software that lacks the embedded architecture capability needed for continuous improvement.

The Limits of Model Theory predictions (including processes)

So what can the measurement of the Higgs mechanism teach us? The only way we currently are able to predict anything in quantum physics is by applying so called gauge theories: an action integral which characterizes “allowable” physical situations according to the principle of least action. The observed system does not follow a single path whose action is stationary, but the behavior of the system depends on all permitted paths and the value of their action. The action corresponding to the various paths is used to calculate the path integral, that gives the probability amplitudes of the various outcomes.

The above means in layman terms that even on the lowest level of our universe there are no predictable processes! We find the most probable outcome by integrating over all possible ones. We cannot predict what the outcome will be but the principle of least action will take care of performing anything at the least expendable energy.

While we discovered in the 17th century that “light travels between two given points along the path of shortest time,” known as Fermat’s principle, our model theories do not explain how a photon/light wave knows which path it must fly to use the least amount of time (not in a straight line!) to its target. It just does!

I propose to empower people to allow them to follow Fermat’s principle as described by the words of Pierre Louis Maupertuis: “The laws of movement and of rest deduced from this principle being precisely the same as those observed in nature, we can admire the application of it to all phenomena. The movement of animals, the vegetative growth of plants … are only its consequences; and the spectacle of the universe becomes so much the grander, so much more beautiful, the worthier of its Author, when one knows that a small number of laws, most wisely established, suffice for all movements (and thus processes – MJP).”


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