Expertise and Experience in Process Management

I have often discussions with experts in all walks of life and business. Experts come in many flavors, with many titles, certificates, and acronyms to their name. They usually come with a lack of experience too. In my diction expertise and experience are not the same. In process management experts sell methodology and practice. A boilerplate template and the necessary bureaucracy which most certainly won’t increase agility.

Yes, we do need people who are very knowledgable about one thing. For pure research it does make sense to have theoretical scientists who study to expand the theory. I proud myself to be a generalist and to know a lot about a lot. I learn from expert knowledge but always apply it in the real world. I learned a lot more from failure. Because I do large changes in small steps, most failures are small too and corrections are easy and affordable. The lessons are however ‚priceless‘.

Over the years I came to the conclusion that nothing stands for itself. In Quantum physics all theories have to stand up to a cosmological proof of how the universe evolved. Quantum physics changes your understanding of spontaneity and causality. Everything is connected. There are in fact no segregated fields of science and those we use are purely artificial. There is also no border between science, philosophy and art. There can’t be one without the others. They make each other better. I am one in this opinion with Edward O. Wilson, a magnificent biologist. He wrote the most amazing book called ‚Consilience‘ in which he calls for an end of scientific segregation.

What can be gained from looking over the edge of your plate rather than just deeper down Alice’s rabbit hole? I found that there is but one purpose in life and that is to improve my life by improving the lives of those around me, most of all my family, friends and colleagues. To do so does not require expertise of any kind. It needs experience and humble acceptance. It needs the ability to come to good decisions about things that have potential. Looking for guaranteed outcomes through a rigid procedure means to invite huge failures.

These days experts proclaim all sorts of do’s and don’ts that ignore the larger picture. They use shortsighted logic that targets one symptom, just like in medical treatments. That one blood value is out of a theoretical optimal range and it has to be corrected regardless of the reason why it is what it is and what the potential downsides of the treatment are. I wrote a three post series on naive intervention. Many did agree with me but still fail to see their own naïveté. Naive intervention happens in all complex systems such as the human body, a family, the economy or our climate. Shortsighted expert ignorance is the order of the day.

I find that most things are better left alone to allow natural dynamics. If at all, actions should be targeted at myself and not at others. Absolute control over our environment is an illusion and I do not mean a factory or lab. But take for example airplane crashes. Yes, we do fare better when we guide and share experience rather than being a control freak. As they say, it is better to teach people to feed themselves than to feed them.

Einstein was one of those who said: ‚Only the ignorant are certain‘ and that is the core problem with most experts. While I am steadfast in my intuitive beliefs and principles honed by experience and failure, I still leave a lot of room for being wrong and learning. While I oppose the ignorant naive activists with fervor, I still know that they make me better because there can be no progress without dissent and disagreement. Where all agree or are forced to agree, the future ends.

Logic would say that it is crazy for a 60 year old guy who is generally expected to be retiring soon, to buy a hyper-tuned 600 horsepower hatchback and compete with five to ten other crazy guys on a mixed tarmac and gravel race track in a world championship series? I ignore logic because the experience makes me a better person. I have a coach to teach me, but in the end I have to validate my learning. My coach Patrik Sandell is a world class racer himself and not a physics professor.

Cars and their drivers on a race track represent a dynamic, chaotic system that disregards control and predictability. The competitive element makes it however a valid comparison to doing business. The physics are secondary, but the drivers and teams are the key element. There are great drivers and dedicated team managers who lack the social skills that could make them successful in the long run. If I yell at my mechanics that might be as bad as a driving error. Even the regulatory frameworks put in place by FIA,  fail to achieve too often the desired effect as in everyday business and politics. Regulation produces rule beating and bypass actions that often cause the opposite of what is intended.

Learning to race teaches me to be humble and pushes me to become better in everything. It forces me to stay physically fit, rebuild my reflexes and ability for split-second judgment. Every time I take another few tenths of a second off my lap time, I have learned — something. Being fast is not about driving like a nutcase but rather truly about teamwork — and actually economics. Any unnecessary correction or movement of steering wheel, tires or car wastes energy and reduces momentum. It is not about being in perfect control but giving up control just enough to let the system take care of things by itself. I guide it, nudge it, correct it and the least amount will make me the fastest. Just as in life and business …

Driving fast is therefore mostly about efficiency, but not about who uses the minimum amount of fuel as in the over-regulated Formula One. Which are the least amount of actions that take me to the target in the shortest time. Sounds familiar? But try to code a race in a flow-diagram! I do train for example in a simulator, but not to find out what the perfect process is, but simply to produce the repetitive motor action that automates the driving skill. I then train on an ice track that is much more slippery to learn how to apply that skill in the real world. When racing time comes everything is different in each heat despite driving the same laps about 20 times. The track, the weather, the other drivers, my car, and my emotional state they all represent parameter input that changes the process in a chaotic system.

The inert momentum of the car is something that you need to get a feel for intuitively as you have no time to think and apply logic. Like in business there is simply no way to gather the information in time, process it, apply the logic and then perform a correction. It is all much too late and too often oversimplified logic. You have to feel it that when you apply a corrective action one way, momentum will swing it to the opposite. You see race drivers move the steering wheel in short left and right movements because that way they can react faster and avoid large changes in momentum. Like in a fighter plane you give up stability as a trade off. One intentionally destabilizes the car to make it more agile and responsive by using what is called a lift-off (from the throttle) into a Scandinavian flick. You do illogical things such as being at full throttle into a tight corner while breaking hard. Breaking harder before the apex allows you to accelerate faster out of the corner. Not logical at all until you gain the experience.

All processes in your business are the same chaotic structures. If you try to make them predictable then you kill the agility. The goals are stable and the outcomes remains desirable but the path of actions is different each time. The hardest part is to unlearn our demand for control and stability. Like in an aerobatic plane it is the instability that gives you agility. Not more control and more bureaucracy and more monitoring as suggested by process experts. In dynamic situations you need to empower people to act, just like a race driver needs to have power at the wheels at all times as otherwise he simply spins out. They need be allowed to react intuitively to something unexpected to be efficient and fast. That is totally illogical to experts, but it is a simple fact of life.

Many business or process experts are like the ‘couch experts’ in racing. They will make all sorts of comments about a race driver or business skills, but they have nowhere close the ability to do it any better because they never tried it and do not have the balls to try. I propose that many consulting firms just fill a market space where weak management structures in large corporations require external consultants to take decisions for a management team that is too afraid to take them. The best consultants have however the experience and have run a business themselves. Anyone else you can simply ignore …

No matter if you see it or you don’t. Real life happens at the race track.

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Posted in Adaptive Case Management, Adaptive Process

The Holstee Manifesto – This is Your Life!

You may or may not have seen it before, but this is one the most shared pieces of text on the Internet.

It began when a group of friends tried to create a definition of what a successful life meant to them and once it was in print it became an icon. The Washington Post called it the next ‘JUST DO IT.’

The Holster Manifesto - This is Your Life!

The Holster Manifesto – This is Your Life!


Here is a video version:

Why am I having this on a blog the discusses mostly information technology and process management? I think it would be obvious, because the manifesto so clearly describes the same human values that not only I consider to be more important for success than a perfect process illusion.

Success in business, from the shortest interaction with a customer to a very profitable year is achieved by focusing on the right thing – PEOPLE! All other forms of success are short-lived illusions.


Posted in Uncategorized

Will knowledge work be the only way to stay employed?

The above question appeared a few days ago on prompted by a post that suggested as much. I propose however that the perspectives are rather shortsighted. I do not even see BPM as the employee-eating monster as some seem to think, but simply as a consequence of other much more problematic causes. Anyway, from a worker perspective it is obviously better to have more knowledge and to be better educated. But the danger is that even knowledge work might not be good enough to keep you in the workforce. Just look at the number of unemployed university graduates.

It is not about workers having knowledge or not. In large corporations, employees have often a lot more knowledge than they are allowed to use for their jobs. Initiative is not necessarily a trait that current management concepts favor. It is more important to be compliant and to do what you are being told. And it gets worse when the management is following the BPM illusion. Supposedly, BPM frees people to do more important work but that is simply a ruse. People are not being trained to do more important work, they are being laid off. Oddly enough, Business Process Management (BPM) pundits are continuously trying to remodel, rebrand and rethink BPM with the most ridiculous ideas such as IoT, the Internet of Things. IoT happens mostly outside large businesses and thus BUSINESS Process Management has no relevance whatsoever. BPM won’t do anything to handle millions of sensor devices through simplistic process logic. Maybe some IoT analytics will provide input to a BPM system but IF, then the related human interaction will be more like ACM than process flows.

And in fact, most employment opportunities have little to do with knowledge. It is about money. People need more money to live than the businesses are able to pay. But it is not longer the greedy, capitalist fat cats that can be held responsible. Now it is governments and unions that are responsible. Yes, human work elements are being automated also outside manufacturing but not because it increases quality. Mostly because you can stop and reprogram a robot, but you can’t fire an employee. A simple historic fact of economic change.

BPM is however used for three reasons:

  1. managers don’t get that only employees who enjoy work increase customer service quality;
  2. labor laws and employment regulation that are meant to protect the workforce keeps them from being hired (see the temp industry); and
  3. the profit and share price motive of public companies.

BPM is an inhumane tool that is used to fufill the unethical requirements of all three. While BPM has advanced with ideas and means that go beyond rigid flowcharts (i.e. ACM) the above motivation and comparison to manufacturing remains rampant. BPM is the brainchild of naive interventionists who live in the illusion that things can be improved in human interaction through more control. But BPM will obviously do nothing to increase employment, or improve businesses, working conditions, customer service and human lives.


In this and many other discussions. the biggest issue of BPM at large (methodology, software and practice) remains its false analogy of manufacturing and customer service. The industrial age started when people were used as robots in assembly lines in manufacturing. It enabled scaling beyond the ability and skill of a single craftsman. The industrial age will end when all of that work will be done by robots. There will be a social impact but someone will need to design and build those robots that will execute work designed by people who know a lot more about how to design a product than any skilled craftsman in the past.

The information age started when humans were able to use computers to perform otherwise simple mathematical tasks at scale. What before needed 20 accountants, now just needed one and a programmer. While someone will need to design, code and maintain those applications there is the danger that the computing power is used beyond automation. The information age will end when all non-manufacturing work will be done by computers and they are used to control and manipulate everyone. It will however not end nicely but in upheaval, economic downturns and in the worst case wars.

Factory automation is not comparable to service automation through processes, because human interaction is not controllable through data mining, flow diagrams and decision trees. That is wrong in principle and the consequences on society and economy are very different. The challenges of the information age are also not comparable to the ones of the industrial age. The industrial age paid for itself and the loss of labor income was not a huge economic factor, partly as it happened gradually. The information age is however only affordable because most of its products are being built in countries with a labor force living at a substantially lower standard of life. That part of the change has already taken place.

A major issue will be education.

The workforce that was educated to perform simple manufacturing labor had to be retrained. And the young obviously don’t plan to work in a factory any longer. We are seeing a substantial increase in non-manufacturing jobs such as craftsmen and social or health services. The downturn of the farming industry is also not due to automation or process management. It is due to EU government meddling and the ability for companies such as Monsanto to patent gene sequences. EU farm subsidies kill the markets in Africa as they swamp them with low-quality EU rubbish. Monsanto kills farming in the Americas through patent litigation. Not greedy executives, BPM or automation but just really bad politics. While it does seem to keep farming jobs alive in Europe, the produce quality is truly appaling and doomed in the long run.

But there are other trends than to simply automate the hell out of everything. Those who are willing to deliver quality can do really well and it is not a step backwards. Mobile Cloud applications such as UBER create new work opportunities beyond the strictly regulated service industries. The Internet of Things will bring even more opportunities due to people empowerment but NOTHING in this arena has to do with what BPM has done, can do, will do or should do! It mirrors a new form of empowerment through technology that I have been proposing for large businesses since a long time. I have often named the Apple Appstore being such an empowering infrastructure. It IS ALREADY HAPPENING outside the businesses. Yes, these tools offer some well designed core processes to ensure smooth collaboration, but they do usually not restrict how the worker utilizes his skill. Most of all they offer a rating scheme that allows people to rate the quality of each service provider. Something that is for example strictly forbidden by unions for its union members in most countries. Add BPM and that together: You are being told what to do and no one cares if you do it well.


The problem is not technology and its opportunity for automation. BPM is just a consequence of poor management and bad government politics. The culprits are the people in government, the reality-disconnected business executives, and a financial and economic structure designed to keep both in place. I find it more than hypocritical to tell the corporate workforce: „We are gong to automate as much as possible everything that you could do and unless you find something to do that we can’t automate, you are out of a job.“

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Posted in Economy, Executives, Human Resources

The future is Machine Learning, not programs or processes.

I was once again voted the most outspoken BPM blogger on earth. Hey, why not the universe? But thanks for the mention. I won’t however waste my and your time on BPM predictions for next year and rather discuss the medium term future of process management in machine learning.

Machine Learning used to be called Artificial Intelligence and became popular when IBM’s Deep Blue won against Chess World Champion Kasparov in 1996. The victory wasn’t however a success of AI, but a result of Joel Benjamin’s game strategy and an ensuing Deep Blue bug, that led into a final draw and thus a win for IBM. And IBM did it again in 2011 with Watson which won the popular Jeopardy TV game show in a similar publicity stunt that has little relevance for machine learning. Jeopardy uses a single semantic structure for its question, so finding and structuring answers from a huge Internet database was not that hard. Watson had the hardest time with short questions that yielded too many probable answers. It used no intelligence whatsoever in providing answers.

1996: Kasparov is beaten by IBM's Deep Blue.

1996: Kasparov is beaten by IBM’s Deep Blue.

Why do I then say that the future of BPM is in this obscure AI arena? First, machine learning is not about beating humans at some task. And second, I see machine learning ideal for work that can’t be simply automated. My well-documented opposition in this blog to orthodox BPM is caused by the BPM expert illusion that a business and the economy are designed, rational structures of money and things that can be automated. In reality they are social interactions of people that can never be encoded in diagrams or algorithms. I have shown that machine learning can augment the human ability to understand complex situations and improve decision making and knowledge sharing.

To do so I turned my attention away from writing programs and processes many years ago. My research is into how humans learn and how that understanding can be used to create software that improves how people do business without the intent to replace them. For me the most important discovery was that humans do not use logic to make decisions but emotions (Damasio, 1993). Using logic requires correct data and perfect control which are both unattainable. Therefore humans developed the ability to come to decisions under uncertainty (Gigerenzer) using a wide variety of decision biases (Kahneman, Tversky). These aren’t however fallacies but very practical, simplified decision mechanisms. Many books on the subject focus on how wrong these biases can be in some situations. They ignore that logic-driven decisions are equally wrong in all other situations because the underlying data are wrong. Logic is only better in theory or in the closed shop of laboratory.

While machine learning collects past information to learn, it is a fact that the past never predicts the future. We can only identify general probability. Take a simple roulette wheel for exanple. But people are fascinated by predictions (see Astrology) and managers want certainty, which is however unattainable. Therefore they like buzzword driven hypes that suggest that if we collect and analyze more data about more things we will get better predictions to precode decisions for the future. It is mirrored in the ‚process mining‘ approach that assumes that collecting more data on more business processes makes them more predictable. That is in fact a misrepresenation of what ML can do.

Algorithms can be used to automate mechanical functionality in real-time in a factory, airplane or car. Take Google’s self-driving car for example, military drones or robotic assembly lines. Let’s not forget that they don’t take decisions on where to go and what to do when. They are surrounding-aware robots that follow a human given directive. That is not intelligent. Thus one can’t automate a business process or any complex human interaction the same way.

True innovation in process management won’t be delivered by rigid-process-minded ignoramuses, who fall for the illusion that correct decisions can be encoded. It will arrive in the arena of machine learning that will help humans to understand information to make better decisions.

What is machine learning and what is it not? And how far are we?

Marvin Minsky had 50 years ago a vision that computers would be as or more intelligent than humans fairly soon. He proposed the use of software called neural networks that mimicked human brains. However, a human brain does not work by itself, but is a complex construct of evolved brain matter, substantial inherited innate functionality and learned experiences of which many are only available through our bodily existence. Our experience of self is not a piece of code, but a biological function of our short-term memory and the connection to our body through our oldest part of the brain, the medulla which sits atop our spinal cord. Without our hormonal drives human intelligence and decision-making would not even develop. What makes us human are our bio-chemical emotions to feel fear, love and compassion. That is accepted science. Therefore a purely spiritual entity (our soul?) or logical function without body and body chemistry can’t feel either and thus won’t possess human-like intelligence. It won’t be able to take human-like decisions. But machine learning can provide benefits without the need for human-like intelligence. So in the last few years all large software companies have jumped on the machine learning bandwagon.

While IBM has no more to offer than publicity stunts, Facebook has no other interest than to utilize the private information of their 700 million users to make money. Facebook is using buzzword-speak ‘deep learning‘ to identify emotional content in text to improve its ad targeting through big data mining and prediction. Supposedly some of this is already used to reduce the Facebook news feed to an acceptable amount. My take? It isn’t working, much like Netflix movie suggestions or the product recommendations of Amazon. Why? Statistical distribution can’t judge my current emotional state!

But ML isn’t a ruse. It is real. Minsky’s neural networks are still being explored and improved for voice and image recognition and semantic, contextual mapping. These are important while low-end capabilities of the human brain for pattern recognition. Japanese, Canadian, and Stanford University researchers developed for example software to classify the sounds it was hearing into only a few vowel categories more than 80 percent of the time. Also face recognition is already extremely accurate today. Image classification is successfully used to recognize malignant forms of tumors for cancer treatment. In fact, voice recognition in Apple dictation in both iOS and OS X are extremely good in understanding spoken sentences. The hidden lesson is that Apple uses both a dictionary and a grammar library to correct the voice recognition. I have written much of this post using Apple dictation. The important progress in this area is the recognition of NEW common image features at a much higher success rate than humans can. But in all these approaches it is the human input that decides if the patterns are relevant or not. Man cooperates with machine, not machine replaces human intelligence.

So what is Google up to in machine learning?

The most publicized and successful Google venture in this domain is the self-driving car. A great example of how real-time data sensors in combination with a human-created world map (Google Maps obviously) allows a machine to interact safely and practically in a complex environment. Don’t forget that the car is not controlled by a BPM flow-diagram, but is totally event and context driven. So much for BPM and the ‘Internet of Things’ …

I dare to put Ray Kurzweil’s work at Google in the same category as IBM’s with similar illusions as Minsky. I have known Ray Kurzweil since the days he created the K250 synthesizer/sampler in 1984. It was the first successful attempt to emulate the complex sound of a grand piano. I was the proud owner of one in my musician days. It was inspired by a bet between Ray Kurzweil and Stevie Wonder over whether a synthesizer could sound like a real piano. It was awe-inspiring technology at the time and it too lead to predictions that performing musicians would become obsolete. It is obvious that this did not happen.

Kurzweil joined Google in 2013 to lead a project aimed at creating software capable of understanding text questions as well as humans can. The goal is to ask a question just as you would to another person and receive a fully reasoned answer, not just a list of links. Clearly this reminds of Siri and Wolfram Alpha and both have been at it for a while.

Kurzweil’s theory is that all functions in the neocortex, the plastic (meaning freely forming) six layers of neuron networks that is the seat of reasoning and abstract thought, are based on a hierarchy of pattern recognition. Not a new theory at all but pretty well established. It has led to a technique known as “hierarchical Hidden-Markov models,” that has been in used in speech recognition and other areas for over ten years. Very useful, but its limitations are well known. Kurzweil however proposes that his approach will allow human-like intelligence if the processor could provide a 100 trillion operations per second. A human brain is however not just a neocortex! And more processing power is not going to solve that problem.

In machine learning less is always more!

Google isn’t thus betting all its money on Ray Kurzweil but spent recently $400 million to acquire a company called DeepMind that attempts to mimic some properties of the human brain’s short-term memory. It too uses a neural network that identifies patterns as it stores memories and can later retrieve them to recognize texts that are analogies of the ones in memory. Here the less is more approach is used. DeepMind builds on the 1950 experiments of American cognitive psychologist George Miller who concluded that the human working memory stores information in the form of “chunks” and that it could hold approximately seven of them. Each chunk can represent anything from a simple number to an abstract concept pointing to a recognized pattern. In cognitive science, the ability to understand the components of a sentence and store them in working memory is called variable binding. The additional external memory enables the nerual network to store recognized sentences and retrieve them for later expansion. This allows to refer to the content of one sentence as a single term or chunk in another one.

Alex Graves, Greg Wayne, and Ivo Danihelka at London based DeepMind, call their machine a ‘Neural Turing Machine‘ because of the combination of neural networks with an additional short-term memory (as described by Turing).  While this is a great approach it lacks the ability for human interaction and training, which I see as the key aspect for practical use. But variable binding is a key functionality for intelligent reasoning.

Human collaboration and human-computer cooperation

The future is using computing as a tool to improve human capabilities and not to replace them. BPM being thus my pet peeve in large corporations. To illustrate the point I have been making for over a decade, I recommend to watch this interesting TED Talk by Shyam Sankar on human-computer collaboration.

Sankar talks about J.C.R. Licklider’s human-computer symbiosis vision to enable man and machine to cooperate in making decisions without the dependence on predetermined programs. Like me, Licklider proposed that humans would be setting the goals, formulating the hypotheses, determining the criteria, and performing the evaluations, while computers would deal with all operations at scale, such as computation and volume processing. They do not replace human creativity, intuition and decision-making.

So what are the aspects of machine learning that are both available, usable and do not suggest Orwellian scare scenarios? Well, machine learning technology is unfortunately perfectly suited and broadly used for surveillance but lets focus on the positive for the moment. Image and voice recognition and follow-on classification are areas where we have reached the stage of everyday practical use. We have been using image- and text-based document classification in Papyrus for 15 years. Machine learning is used in Papyrus for character recognition, text extraction, document structure, sentiment analysis, and for case context patterns related to user actions – with the so called UTA or User-Trained Agent. Pattern recognition for case management that uses the kind of human-training and cooperation that Sankar suggests has been patented by me in 2007.

What the UTA User-Trained Agent does and my patent describes, is that we do not look for patterns that predict that something will happen again. In human computer collaboration the repeated human reaction to a particular process pattern is interesting and therefore one can make others aware of the likelyhood that such an action is a good one. This ML functions does not just find patterns, it analyses how humans react to patterns. Users can also react to a recommended action by rejecting it. As I do not prescribe the process rigidly but require that goals to be achieved are defined, it is now possible to automatically map a chain of user actions to goal achievement and let a user judge how fast or efficient that process is.

But how practical is such machine learning to simplify process management for the business user. Does it require AI experts or big data scientists and huge machines? Absolutely not, as it too uses the less is more approach. Recognized patterns are automatically compacted into their simplest, smallest form and irrelevant information is truncated. But in 2007 it still used IT data structures and not business terminology. Using an ontology to describe processes in business language enables human-to-human collaboration and run-time process creation, and simplifies human-computer cooperation.

Papyrus thus uses a simplified form of ‘variable binding’ for process descriptions by means of an ontology. Such an ontology definition entry always has a subject, predicate and object just like the DeepMind short term memory. Now, the UTA can identify process patterns using the ontology terms. The first neural-network based User-Trained Agent version in 2007 could not explain why it suggested an action for a process pattern. Using the ontology to identify the pattern similarities in different work processes (really cases) one can tell in business terms why an action is recommended.

Business analysts create at design time a business ontology that the non-technical business users will use at run-time to create their processes and content. The technical effort is mostly related to creating interfaces to existing IT systems to read and write business data. At run-time users collaborate in business terminology and as they perform their work they create the process patterns that can be reused. These can both be stored explicitly as templates or the User-Trained Agent will pick up the most common actions performed by users in certain contexts.

Conclusion: We are just at the starting point of using machine learning for process management. IT and business management are mostly not ready for such advanced approaches because they lack the understanding of the underlying technology. We see it as our goal to dramatically reduce the friction, as Sankar calls it, between the human and the machine learning computer. Using these technologies has to become intuitive and natural. The ultimate benefit is an increase in the quality of the workforce and thus in customer service.

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Posted in Machine Learning

The Interdependence of Technology and Culture

Are computers making us smarter or dumbing us down?  However we feel about it, technology will progress and we need to decide for ourselves how we will interact with it. Yet before we can do that, we need to understand how technology is created and how it impacts our lives. We need to understand how human decisions are impacted or what happens when they are replaced by computerized ones. Only then we can make the right choices.

IMG_2598Development of technology depends on uncovering an aspect of nature, from how atoms form molecules, via how bacteria live in symbiosis with the human body, to how humans interact in a social network. It is interesting that technology does not grow and spread equally around the world, but there are hotspots and dead spots. It is both opportunity and culture that shape technological progress.

In The Death and Life of Great American CitiesJane Jacobs argues that the one core aspect of culture that drives progress is diversity of people and ideas. It fosters a creative environment that bubbles with innovation. Let’s not forget that this applies to any social grouping including businesses. The creative work of uncovering technological principles requires an environment of tolerance, prosperity, and opportunities for a diversity of ideas to mix. So quite apparently culture has an influence on technology. Ever since a stone axe has been used to shape the first wooden wheel, new technology is a combination of previous technologies, much like biological organisms are combinations of genes. My most used example is the one of the Apple Appstore ecosystem, setting free the immense creativity pool of its worldwide developer network. It is those applications and content that put Apple in front of Microsoft. Not the Mac or iPhone. As technology progresses, markets of humans using technology increasingly resemble biological ecosystems, with its building blocks being mixed and matched in new and unpredictable ways.

As the number of basic technologies expands the number of permutations and recombinations increases exponentially.  That’s why technological advancement is always accelerating. New technology enables us to uncover even more phenomena and that allows us to build even more technology.

When people say that they are afraid of technology what they are really saying is that they are afraid of people using to technology in the wrong way. As a general guideline we should only do things we fully understand and clearly there is always the military and political aspect to consider. Technology is equally suited for surveillance as it is for control. Too often Technology has been and is being used to kill more people more efficiently. War and peace are both dependent on technology.

And here comes the surprising loopback: Technology more than anything else changes the culture of the social group using it.

Morality and compassion are principle signs of maturity.

So why are people opposed to technology if they apply common sense? A two year old is not afraid of a smartphone, he/she is rather magically drawn towards it and learns within the shortest time how to interact with it. Einstein suggested that common sense is no more than all prejudice collected by the age of 18. Is it just the fear of change or the unknown consequences? I propose that politicians are only too happy to use this fear to enable more government control over technology. Orthodox media just love fear-mongering and especially towards its archenemy, the Internet.

Does that cause us to be prejudiced one way or the other about technology as we mature? Human maturity is mostly about realizing ones own weaknesses and turning them into strengths. Fear protects us but can also stifle. While the ability to forgo immediate pleasures for postponed gains is a sign of maturity there is little benefit by turning such behavior into rigid rules. A lot of it has to do with experience and the related emotional adjustment of ones decisions, also known as the value of failure. If you build airplanes some of them will crash! Using analogies in a future projection will enable a mature person to make large adjustments from small failures. A child that is not overprotected learns through its own experience that the height of a fall is proportional to the pain and that is for most sufficient to not test the limits of that projection. If not it is called natural selection.

Mature people understand intuitively that Collaboration is more productive than antagonistic behavior. Also competitiveness can be a great driver up to a point. So maturity is not just about increasing positive and reducing negative behaviors but about finding a balance while following our drivers. Perseverance, patience, endurance, and tolerance are all going to waste without compassion which is part of the one key human aspect: MORALITY. So what we are really worried about is a lack of morality and compassion that would stop others to use technology against us. But we do not have to just invoke images of Orwell’s 1984 but simply have to look how many businesses are run today and how employees are treated there.

Many would agree that a society has a higher morality if it has more laws and rules to follow. I propose that the opposite is the case. If people would be moral, there is no need for rules and laws. If people know what they are doing there is no need to protect them from their own folly with regulation such as speed limits. And let’s not forget that it is the law that makes the criminal and that the rule makes the transgressor. Many believe that rules and regulations save time and money as they prohibit failures. If that would be true the negative side effect would be a total lack of learning within that organization as there would be no failures and no growth of experience.

Prohibition as the ultimate regulation for both alcohol and drugs led to an empty space in which only criminals – the Mafia then and drug cartels now – define how drugs are being produced and consumed. I have been suggesting to deregulate drugs for two decades and I am no longer alone. The more you regulate, the more you give up control, because the action will take place outside the space you think you are controlling. If you put in place too strict process management then collaboration will bypass it with email and office tools.

In society and in business, rules and the necessary enforcement use up more resources and time than they actually save. An effect called ‘rule beating‘ is well known to system thinkers. Any defined rule will cause people to try and bypass it. The most efficient way to perform any kind of work is if the people involved know what they’re doing and rules are kept to the absolute minimum necessary. ‚Knowing what to do’ is not equal to abstract knowledge that can be encoded in rules. ‘Knowing what to do’ requires a personal experience transposed by ‘pattern-matching’ to the current context.

Giving people freedom is not anarchy! It drives diversity and learning.

While our understanding of human intelligence is limited, recent years have brought the realization that human decision making – the essence of free will – is controlled by our emotional center and is a bio-chemical function and not controlled by rational thinking. That has led some to say that there is no free will in humans. Brain scans show activity for a movement half a second before the human says that he has taken the decision. But how would we really know? Some use that discovery to argue that human decision-making is flawed. Nothing could be more wrong. The human mind has evolved to deal with decision-making under uncertainty. Boolean Logic requires a context of certainty that does not exist in reality.

Free will is also related to the concept of spontaneity, which is to the surprise of many a key concept of physics, especially quantum physics. Just like in quantum physics, spontaneity does not happen into an empty context, but it is that context that enables and is probably connected to the spontaneous action. Is it then still truly spontaneous or free will? A purely philosophical discussion depending on what free will is supposed to mean.

We do know that the human brain has a very plastic biology of layers upon layers. The limbic system is the emotional control mechanism for memory and decision-making and produces emotions such as anger, fear and our core drives. The cortex however stores a virtual representation of the real world as patterns. It uses it to continuously predict the future, based on the past and present. Each pattern recognised can have higher orders of patterns to the depth of 6 layers of the cerebral cortex.

The human brain is thus a bio-chemical pattern-matching device with a huge number of pre-encoded recognition clusters that allow us to sense our surroundings and deduce feelings and recognitions about them. As the world is simply not predictable in the detail and we are unable to know and measure accurately enough, we always decide under uncertainty and therefore an emotionally driven pattern matching concept works the best. Pattern matching is easy to train and easy to cluster into hierarchies. Much better than complex semantic networks that suffer from unresolvable interpretation issues. It is always the interpreter that assigns meaning and not the message creator. One can agree on common ontologies and taxonomies, but it will still be impossible to build logic networks that will be showing or explaining free will decision-making. And that understanding brings us back to maturity and morality! Feeling (through biochemistry) within us the same emotions as others given similar patterns is what allows us to be compassionate and thus moral. Logic can never be moral.

Company culture will change with technology!

One can use technology to do both — empower or restrict. Both will have a strong influence on a business and it will over time change the company culture, for better or for worse. So be careful what you wish for.

It is humans and their free will driven by the emotional context that makes a business moral and mature. A balanced score card or a well-defined process doesn’t. Company culture can’t be described in a few slogans either. There is no way that any kind of business or process maturity can be found in silly and far-fetched templates or boilerplates, models or frameworks, business or otherwise. Why should a business be more mature if it shapes its activity into predefined processes? It may be more compliant if it describes everything in rules but not more moral. Lacking diversity, it will certainly be much less innovative and thus competitive. And yes, one can therefore use the analogy of human maturity to business maturity. Mostly because it is the maturity of humans that make up the business that defines the maturity of the business. Not achieving some abstract level state of perfectly defined process logic. What utter nonsense!

Yes, technology will cause new challenges and further problems. There will be failures. Human creativity will use once again technology to solve those, not a methodology or legislation that restricts and demands safety and conformity. There is no need to fear technology as long as enough humans have the freedom to choose in a democratic environment. Technology that empowers will free the employees minds and unlock creativity and innovation. The same free minds will mostly use their freedom to do the moral thing.

No matter what your opinion is on the subject, the evolution of technology is tightly linked to our own. The use of technology is also tightly linked to the future of your business! Competitive advantage is not achieved through control so get hold of that fear and use technology to empower.

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Posted in Economy, Evolution, Machine Learning

People Management versus Process Management

In recent discussions the proposition was made that my disagreement with BPM came from discussing people management issues in process management. While I totally agree that as an executive my focus is people management I propose that there should not be a process management perspective that does not focus on people. To bring the benefits of process management closer to the people requires today technology — just as with the Social Mobile Cloud — and not methodology. I am not living in a technology dream world, because as an executive I also deal with other executives and high-level management of the largest corporations on a daily basis and I see and hear their management pains.

They all struggle with one thing only and that is getting their leadership to transcend to the lowest management levels. BPM methodology and business architects can never do that but rather are its killer. They freeze management initiative and drive. No one likes BPM and no amount of training and enforcement makes the business do better. It just makes some numbers look better in the short term. Not only I see the dramatic consequences of the politics and the red tape that kills any creativity and innovation. In most businesses it is the least imaginative and least innovative people who propose, demand and in the worst case enforce a BPM approach. Could anyone believe that Blockbuster or Kodak could have been or Blackberry and HP will be saved by bringing in business architects and BPM? That makes me laugh.

Saved by methodology or by the right people?

Microsoft CEO Steve Ballmer had no clue what people want from a Smartphone while Steve Jobs obviously did. Steve Ballmer believed their market analysis, while Steve Jobs said openly that market analysis and focus groups were the killer of creativity. And that applies to all levels of management and all kinds of work. People enjoying working with other people makes a business better. Closest contact with your staff and employees and a good connection with your customers and prospects makes a business better and helps to shape a better business strategy.

I have been told that my BPM criticism is invalid as I am not clear whether I mean methodology, technology, or the practice. Actually, I mean all three together but let me try to ensure that this smoke screen argument doesn’t apply. The need and resulting time and cost for all three as distinct requirements to make the whole approach even usable is a simple proof why BPM is a loosing proposition in the long term. A business thrives by achieving individual customer goals and not by executing rigid processes perfectly regardless of the outcome for the customer. BPM methdology and analysis is FAR, FAR AWAY from people who execute and even further away from the customer. A goal defined there is unbeknownst to the performer and most likely not what this customer currently really needs or wants.

BPM projects are justified by a further focus on using less workers and to replace the ones needed with less skilled ones. This will happen by default because skilled people have no interest to be used as ‘fools with tools.’ Therefore BPM has the unavoidable consequence of lowering the size but also the skill of the workforce in a business. Then you might have a poor process design and no one to see that it is actually so and no one to know how to make it better. The BPM bureaucracy — like all bureaucracies — isn’t close enough to see what goes wrong. They delve into BPM reports that only deal with deviations from the expected and not with customer satisfaction or effectiveness. The ideal process is blind to the unexpected …

There are no perfectly designed processes … Period!

Even worse, much of the logic —  regardless if flows or task conditions — needed for a process cannot be represented in Boolean logic at all. Human decisions are all emotional-experience-driven and not logical. Only reality-removed-intellectuals (imagine Sheldcon Cooper from Big-Bang-Theory) believe we can turn them into logic, but in fact and quite obviously they become inhumane by that very step. Yes, some boundary rules are unfortunately needed for compliance but also there you will find that only a human supervisor can verify that. Therefore there are only processes that have been decided to be sufficient regardless of being wrong or incomplete. For human interaction (aka purposeful collaboration or running a business) there is in fact no ‘fixed predefined realization of logic that provides the outcome if repeated in the same execution context.’ The context is nothing else than the goal to be achieved, meaning a customer outcome or a handover. BPM proponents blindly assume and then propose/claim that what can be done in the closed shop of a factory floor can be transplanted into the chaotic environment of human interaction. Yes, there are processes that need more or less experts, but there is no process that can be done without people who know what they are doing. It needs at least one process owner in the line of business who defines and works toward value goals!

A modern business is therefore one where all people are involved in producing value for the customer. As the target customer is an individual and only in a statistical illusion belongs to a certain demographic, quality is achieved by individual, non-automated service. That is the most effective and at the same time the most efficient. Centralized, fully automated service centers do not have a focus on the customer. They focus on reducing cost through standardization and automation. Rather than claiming that the service center frees up staff to focus on customers (which is hardly ever true) get rid of the internal-non-customer processes that you need the service center for. Spend the money saved to hire staff for actual customer service.

From the perspectives of customer experience, people management and workforce psychology the process environment must be so flexible and easy-to-use that people are willingly letting go of email and MS-Office. Why are these tools so much liked? Because they are independent of IT and ‘experts’ telling employees what to do. They are also the only means to complete the lacking processes. What ever you do in process management it will only succeed if you get business-user-driven adoption! Productivity and customer satisfaction is not about turning people into BPM-controlled robots, but people actually enjoying what they do. The more detail you force on them the more resentment you will get.

BPM architects can’t imagine that the people actually doing the job know what they are doing. But actually they don’t know the job required. I have not yet met an architect who knows how to run a business or how to manage people. And they shouldn’t bother. Architects — both Business and IT — just have to create an IT framework and environment that empowers the business and does not enforce process illusions. Architects can maybe design stuff, but the reality is that human interaction defies any architectural effort. One simply can’t design a process that involves individually acting agents, aka as humans. One can design a great product if it focuses on how people will use it. If all you focus on is making it cheap, your business will be the next Nokia and not the next Apple!

I am certain that a BPM center of excellence and its consequence of process-optimized service centers can be likened to a centrally controlled, pseudo-communist bureaucracy that will never improve the long-term prospects of any business in the reality of a dynamic, if not chaotic economy.

Welcome to the Real World – Outside the Matrix (ah, BPM)!

In the real world — meaning outside the BPM-illusion — there is only work to fulfill goals. There is no process or case and there is no distinction between them. The distinction is an artificial one created by a BPM perspective. That the other work can or ought to be managed through a more flexible case management environment only came up in recent years. I therefore propose that the BPM process control illusion ought to be thrown out because of its obvious drawbacks for a business, mostly in respect to people management. Processes are not a business asset. People are. The work these people do has to target goals and those deliver handovers and finally outcomes. BPM ought to simply define that and make it accessible in real-time, but instead needs a lot of bureaucracy by experts to achieve that. What I propose with ACM is too a form of BPM, but it departs from the the currently separated methodology, technology and practice because it consolidates them for business people.

ACM is different from BPM in that the performers always have freedom — unless it is explicitly reduced in some areas — to target a well-defined, visible goal. As they perform their work, their knowledge is captured within the case and can later be used to improve it. BPM is the opposite: workers are guided and controlled and in a few situations they can do a few ad-hoc things. In most situations however, the undefined detail is executed outside the BPM environment and lost. The whole point of ACM is to not even try to automate what can’t be automated but to provide the best possible support for the performer and create transparency and learning where non exists today.

Adaptive Case Management in my definition can perform everything current BPM TECHNOLOGY can, plus the indisputable need for business content. It provides a simple METHODOLOGY to define value streams as goal trees and guides otherwise undirected execution with constraints for compliance. All work can be described by business users and saved as more or less structured templates. In this manner it brings the power of a process management PRACTICE directly to the line-of-business. It provides top-down transparency for guidance and bottom-up transparency for execution without the limitations and drawbacks of the current state-of-the-art in BPM.

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Posted in Adaptive Case Management, BPM, Business Architecture, Business Strategy, People Management

BPM plus CM is not Adaptive Case Management

My previous blog post caused once again quite some stir with various BPM proponents who feel deeply insulted that I do not accept their expertize in optimizing businesses. I am simply not into superstition. I am ok with Astrology though.

But as it happens there is a lot less uproar than there used to be. One of the reasons is — as I predicted five years ago — that the BPM community has assimilated the ACM vocabulary and now claims that one can do Case Management (CM) — adaptive and mostly not — applications with their BPM suites. Even analysts run ACM studies based on that premise. A BPM suite can mimic case-like functionality by renaming some parts accordingly. While some work performed in a case can be sub-processes or ad-hoc tasks thats where the similarities end. For me an ACM environment has to support explicit goal-orientation and validation linked to embedded data and content. ACM embeds the ability to design flow-diagram processes too. Most of all, ACM is a solution that supports a modern business and people management paradigm and is not stuck in 1910 and Taylorism.

In difference, the focus of case management is to provide containers of information for particular coordination requirements. As work progresses certain information content is gathered and can be used to make decisions. But case management systems require substantial coding to provide guidance to the user. Some types of case work such as investigative cases do not have any pre-configurable progression but they still would have clearly defined goals.

I do not want to get into a technical hair-splitting of differences but stay at the larger issues of running a business. Adding case management to BPM does not improve what BPM does for a business as it continues to ignore essential people management aspects. It is not making the creation and innovation of work any easier. Businesses solely thrive on continuous innovation and not through performing old approaches faster and cheaper. Faster and cheaper means less people and less knowledge and thus a reduction of the ability to change work in accordance with changes in the market. Even while you exploit process knowledge you need to be able to explore the new. And that is not achieved by CM functionality that exists somewhere outside a currently rigid process.

Is continuous innovation through failure really necessary?

Rather than scientific studies on workplace psychology and expert papers I have used the example of the Apple Appstore social network in the past. It is a verifiable proof of the success-through-failure approach. It provides an ecosystem of autonomous innovators who thrive through the power of evolution. The best apps will succeed, while many won’t. Steve Jobs himself failed multiple times until he succeeded. But when Apple was run by bean counters it went from an innovator to the verge of bankruptcy within a few years.

Quite obviously, innovation is not just inventing new successful products, but much rather a focus on customer value. Innovation must happen continuously on all levels, in the small and in the large, while not all innovation efforts will succeed. Soichiro Honda said: “Success represents the ONE percent of your work that results from the 99 percent that is called failure.” Tom Watson Jr. put it differently: “If you want to succeed faster, double your failure rate.” As an executive and manager you have to allow and moreover promote the opportunity to fail, which is diametrically opposed to perfect business processes as demanded by BPM or SixSigma. James March linked already in 1991 company politics and decision theory to knowledge exploration and exploitation. You most certainly won’t get your BPM bureaucracy to change from the idea of ‘the one perfect process’ to supporting innovation through failure just because you added CM functionality to BPM. I say that your only chance is to get rid of the BPM-optimization mindset in your business.

Knowing what does not work is often more important than what works. Often the difference between success and failure is minute. But nobody likes to share his failures, right? ACM enables large organizations to fail and innovate faster by ensuring that gained knowledge becomes transparent and reusable without needing a bureaucracy. It can even happen anonymously. An employee producing a failure is possibly doing your business a larger service than the one who did it right.

How to deal with complexity and the speed of change?

BPM, Six Sigma or Lean will not support, promote or provide true knowledge-from-failure innovation. Perfect and cheap processes designed by an outside consultant are stale and dead. Standardized processes in code-freeze kill the germs of infectious innovation! Giving the process owner authority to pursue assigned goals any way he wants as long as he achieves outcomes, operational targets and handovers is Appstore-like social empowerment needed for success. Autonomy is further a key element in employee (and thus customer) satisfation. Allow for a variety of processes and tasks to fail or succeed until the best ones sustain. For effectiveness you need to allow processes to be improved by the people who perform them. That is additionally the most natural and efficient approach to optimization. Governance should at most define the high-level business entities and ontology to reduce ambiguity but not nail down low-level processes.

Outside manufacturing, we deal today with a business complexity and higher speed of change, which makes it near impossible to ensure a business delivers customer value through rigid work instructions. However, knowledge workers — or small teams with an embedded process owner — listen to customers, translate goals into needed activities, and then execute based on their intuition, skill and experience. In the larger focus of customer experience they improve outcomes without flow-diagrams, Boolean if/then/else logic or Big-Data statistical predictions.

Yes, many people in large organizations don’t care today about outcomes because they are jaded by bureaucracy. But that is not their fault and the worst reaction is to kill the business dynamics even further in a spiral to mediocrity or worse bankruptcy. The ability to ADAPT (change future process execution through learning by doing) is very different to Ad-Hoc or Dynamic processes. Therefore adding CM to a BPM platform is simply a smoke screen and a ruse.

ACM is about empowering people to deliver autonomously value to customers while making effectiveness and efficiency transparent to management.

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Posted in Adaptive Case Management, BPM
Max J. Pucher
© 2007-19

by Max J. Pucher. All rights reserved.

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