Jeff Bezos on Customer Obsession, Process, and Machine Learning

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I recently posted from a Steve Jobs Interview his views on process versus content. He clearly said that the process is the problem, while content is the key. I feel that such successful people are the ones who should be our role models and not some ‘process expert’ or professor who never had to run a business by himself.

Frederic Filloux in his recent Monday Note post pointed me to Jeff Bezos 2016 shareholder letter. Jeff Bezos, the similarly charismatic CEO of Amazon discussed many of the subjects that the process community are targeting. They won’t like what he has to say.

True Customer Obsession

Jeff Bezos: “There are many advantages to a customer-centric approach, but here’s the big one: customers are always beautifully, wonderfully dissatisfied, even when they report being happy and business is great. Even when they don’t yet know it, customers want something better, and your desire to delight customers will drive you to invent on their behalf. (…)
[Y]ou, the product or service owner, must understand the customer, have a vision, and love the offering. Then, beta testing and research can help you find your blind spots. A remarkable customer experience starts with heart, intuition, curiosity, play, guts, taste. You won’t find any of it in a survey. (…)
Good inventors and designers deeply understand their customer. They spend tremendous energy developing that intuition. They study and understand many anecdotes rather than only the averages you’ll find on surveys. They live with the design.”

Resist Proxies

Jeff Bezos: “As companies get larger and more complex, there’s a tendency to manage to proxies. (…) A common example is process as proxy. Good process serves you so you can serve customers. But if you’re not watchful, the process can become the thing. This can happen very easily in large organisations. The process becomes the proxy for the result you want. You stop looking at outcomes and just make sure you’re doing the process right. Gulp. It’s not that rare to hear a junior leader defend a bad outcome with something like, “Well, we followed the process.” A more experienced leader will use it as an opportunity to investigate and improve the process. The process is not the thing. It’s always worth asking, do we own the process or does the process own us?”

On Machine Learning

Jeff Bezos: “These big trends are not that hard to spot (they get talked and written about a lot), but they can be strangely hard for large organisations to embrace. We’re in the middle of an obvious one right now: machine learning and artificial intelligence.(…)
But much of what we do with machine learning happens beneath the surface. Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more. Though less visible, much of the impact of machine learning will be of this type — quietly but meaningfully improving core operations.”

My Perspective on the above

I have voiced similar opinions for many years and was often ridiculed by process experts for not falling in line. Yes, I am no Jeff Bezos but reasonably successful nevertheless. As I recently emailed to another manager: “Success comes with people, passion and ingenuity.” Clearly Jeff Bezos is making exactly these points in the above.

If you want to be successful you need to put people before numbers, passion before process, and make sure that the ingenuity does not interfere with or replace both as is currently targeted both with process management and machine learning. Both should be augmenting what people do and help them to make faster and better decisions, but never consider to substitute the human aspect of doing business.

Let me also add that Jeff Bezos is right that Machine Learning (ML) is a complex subject when viewed as an add-on to a current software portfolio. That is not the case if it is integrated into the software platform. Papyrus Software started to provide ML functionality in 2009 as part of its platform with the User-Trained Agent (UTA). There is no AI knowledge required and there is no need for experts who will manage the data. The core functionality of the Papyrus UTA is to learn from the users or customers which actions (Best Next Actions) are the right ones for a particular work scenario and data pattern.

While this may seem to ‘experts’ that this is a simplistic approach to AI or ML, it actually is not! It does not matter what complexity you add or pursue with ML functionality, you always try to figure out what to do next from past data. Which means that the UTA identifies what actions people took in the past based on prevailing data patterns. This includes decision-making as a whole, regardless of who at which level in the hierarchy took the decision to perform a particular action. So it is not simplistic, but simply to the point! Past data do not predict the future, but decision-making based on human experience is the best possible input we can get for future decisions.

So we make it easy for large corporations to get into AI without a huge investment into software or skills.

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Posted in Adaptive Case Management, Artificial Intelligence, BPM, Business Strategy, Executives

Ray Kurzweil: How to Create a Mind

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Ray Kurzweil claims that ‚If understanding language and other phenomena through statistical analysis does not count as intelligence then humans have no intelligence either.’ That is a converse argument that should disqualify Kurzweil from ever being listened to again. While humans do use similar learning methods they are mostly not statistical but humans can learn things in AD HOC through a single event. They can create a new neural connection immediately. It just has to be emotionally strong in the experience and that turns it into immediate and dominant knowledge.

Even if we could reverse engineer all functions of the human brain, we still will not be able to emulate our human experience and its emotional context that is the key to human drives, goal setting and decision making. While many see that as a flawed aspect of human capability, the truth is that because of the uncertainty of knowledge and the inability to exert perfect control in the chaotic real world, human emotional intuition works a lot better than all machine like logic.

A natural language assistant and a self-driving car are no proof whatsoever that human-like machine intelligence is possible. It is not the neocortex that defines our ability for art and emotion but our limbic system, which Kurzweil covers briefly but diminishes it as a historic artefact overpowered by the neocortex. Maybe Kurzweil is really a Vulcan?

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Kurzweil often bases his conclusion on converse arguments as the above. For example ‚Because we can’t easily remember things in reverse order memories must be stored in sequence.‘ That does not allow to conclude that it is stored as a stream of information like in computer memory. If the brain was a computer-like construct then reversing the stored information should be easy. That we can’t is rather proof that the brain is not a computer or has no computer like function. Yes, memories seem to be linked together as a series of contents in sequence, but they are indexed by emotional events. If there is no emotional context we do not remember things or if the information is there we can not recall it out of sequence. It is well known that if the thalamus is impacted we experience memory problems.

Kurzweil makes the same mistake again when he argues further that because the apparent complexity of a Mandelbrot set is driven by a simple formula ‘Z equals Z squared plus C‘ it is possible to utilise a similar – still to be found – formula to reverse engineer a complex human brain. He clearly does not consider the problem of chaotic structures and that any natural environment does not consist of one formula but any number of such Mandelbrot sets that interact in totally unpredictable ways. And even if a brain could be constructed the way he suggests it would still develop into a unique structure and not be in any way human-like.

Starting off with an unproven assumption

Kurzweil starts out with the wrong assumption that the brain stores and processes information. There is no scientific basis for this conclusion. While the function of a neuron and a network of neurons can be simulated by a mathematical algorithm, that does not imply that this enables to simulate the complex multi-dimensional biochemical interaction of body and brain that creates and recalls emotional experiences as it sees necessary to support life. The sequence of memories accessible have no likeliness to the information stored in a computer.

Pattern recognition and pattern abstraction into features, even if purely trained, has in itself nothing to do with intelligence. Yes, we see what we can interpret and we miss what is unknown but cognition even if it is hierarchical in abstraction is not yet intelligence.

We do not constantly predict the future as Kurzweil claims, but as we map current experiences to stored ones in the neocortex we travel the neural pathways to likely patterns. The hierarchy of patterns and perceptions does not exist as statistical analysis but as a one time created link. Only when we need to learn things for the sake of learning we have to repeat it often to create a memory access path through a variety of techniques. We lack the emotional immediate access to that knowledge that is created by experience and by the dopamine induced success moment. Which is why we forget learned knowledge quickly while experience remains.

Kurzweil says that it is beyond the scope of his book to consider neurotransmitters such as dopamine and serotonin which is surprising as they are a key element of a working brain. Kurzweil never mentions any of the research that links the amygdala and the limbic system with human decision making. It has been shown that managers that can decide well and quickly have a very active limbic system when doing so. Kurzweil claims that the neocortex has taken over the functions of love controlled by oxytocin and vasopressin and he could not be more wrong. Our neocortex has no other function that to interpret our feelings and desires and makes sense of them while our emotional system has already made them. We can see in brain scans that we have taken the decisions before we actually become consciously aware of them. It means that we decide never logically but always emotionally. If we try to apply ratio and logic we search for additional potential aspects of loss and rewards and the associated emotions and throw them on our decision scale. We have never disconnected from our deep emotional past as Kurzweil claims. The reason why we humans have sex without wanting children, is not because it has become irrelevant but because it is a successful means to strengthen the pair bond of a relationship.

I find in the book the repeated and unfounded assumption that the pattern recognition capability of the neocortex is the basis for intelligence. There is no proof of that. The neocortex is purely about automation. It is used to reduce our thinking effort and is not the basis of it. We train the neocortex for example for all motor functions so that we can walk without thinking about which foot to put where. And yes we also train it to recognise higher level abstractions and concepts. But there is no search engine and the neocortex simply filters the abstractions without logical rules.

Are IBM’s Deep Blue and Watson actually AI?

Kurzweil also claims that Deep Blue won against Kasparov because of its stronger pattern recognition ability when in truth it was the programming of Chess grandmaster Joel Benjamin who defined its game strategies. Kurzweil assumes that the patterns stored in the neocortex are similar to the ones used by computers. The neocortex does not store patterns but contains networks which has a few magnitudes more capacity of contextual meaning without being a kind of storage device.

Pattern recognition has nothing to do with understanding while we can have a discussion what that means. I say it is about emotional relevance in a given context. An OCR module can identify a word and verify it against a dictionary. It can recognise multiple words in sequence and analyse it against a semantic rule engine and ensure it is a valid sentence. It can in principle translate that into another language with sufficient accuracy to make it work. All that is not intelligence and this program has no understanding of what it does.  It can not at all identify if the sentence makes any sense. The same is true for the much hyped Watson that won Jeopardy by downloading the Internet and using a huge amount of parallel processors with many different algorithms to quickly find probable answers and select the most likely one. Once again, no intelligence is used in Watson to achieve that. It does not even understand the rules of the game that are programmed into it. It has no desire to win or sees any benefit in winning and feels neither joy nor disappointment either way. it is not intelligent and will not lead to intelligent functionality. I am not saying there won’t be benefits achievable and yes, some may be better than human achievements, but they are still not intelligent.

The possible patterns that the neocortex has linked in its networks are not a prediction of the future as Kurzweil claims, but simply a list of things that happened in the past. The past does not predict the future and chaos causes all tries to perform predictions in the longer future as futile experiments. That includes the idiotic Black-Scholes formula for the future value of an investment. If at all, these are self-fulfilling prophecies like all stock market gambles.

A really strange idea is to return to the long-gone approach of LISP, a language used in early AI systems that produced obviously nothing of the kind. Kurzweil believes that the AI will statistically infer and construct several hundred millions of lines of LISP rules that will represent its knowledge. There is nothing of the kind in the human brain and thus all comparisons end right here.

Consciousness and the Turing Test

But then we come to the all-important question that Kurzweil tries to sweep under the table much like politicians do with unwanted subjects. Turn them into gibberish and cast them aside. He considers that question to be if the artificial intelligence will be self-conscious. He quotes Searle who says that we simply have to create a machine that emulates the brain and then we will also get consciousness. If only we would know how the brain does that. The limbic system, the thalamus and the medulla are key parts of that system but how that actually would interact with a pattern matching engine and a LISP rule set is conceptually fairly far fetched not to say ridiculous. Searle was however the one to state very plausibly that the Turing Test (interviewing an AI to see if it seems human) does not constitute proof of AI.

There is a small part in human and mammal brains called the medulla sitting on top of the spinal cord. If this gets damaged you fall into a coma and thus it has a key function in consciousness. Exactly what we do not know but most likely linking our current bodily experience to our memories. In terms of evolution it is one of the oldest parts of the brain. We had consciousness long before we had a very advanced neocortex. It is rather ignorant to assume that we will automatically get consciousness if we add more processing power to a pattern matching engine.

Consciousness is not just about knowing about oneself. It is easy to have a machine that has the information stored about itself and can report about its status as many machines do that today. So it is not about the performance of that task. A conscious mind is not about performance. It is about experience. It is about applying emotional context to everything. It does not matter how intelligent some machine will be by some scoring system but it will simply lack the human experience particularly in regards to emotions, feelings and bodily existence and it’s desires. These are not drawbacks of being human but it is the essence. That cannot be replaced as Kurzweil suggests with LISP rules declaring some goals. AI will always lack the human experience. Knowing or communicating about sex is a very different thing than actually doing it. The same is true for all human aspects. You can’t describe the feeling of love (what oxytocin and dopamine and endorphines do to the body and mind) to a pattern matching engine with a LISP rule book. Being human has mostly to do with empathy, being able to feel with and for others. Clearly a machine will never do this. It won’t have the emotional basis for human decision making either. Therefore its intelligence will be INHUMANE … and that I am afraid in the true meaning of the word.

Einstein: ‘The true measure of intelligence is not knowledge but imagination.’

Therefore Kurzweil turns in the end of his book to a religious principle. All you have to do is to have faith. If you want to believe its possible we will have AI machines. From my perspective he diminishes the human mind to raise the artificial one and claims that it will be more powerful. I do not think the human mind is mystical or superior in some way but I think it is unfathomable. And the problems we face today are not because our mind is inferior but because we do not consider well enough what it tells us. Flawed logic and pseudo-intellectual contemplation replaces real-world intuition. Computers can already do today so many things a lot faster than a human and while that is good in principle many things are not necessarily to our benefit.

I will still go with Noam Chomsky: ‚Watson is a bigger steamroller. It understands nothing.‘ 

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Posted in Artificial Intelligence, Evolution, Machine Learning

Steve Jobs about Process and Content

I just found ‘The Lost Interview’ with Steve Jobs on Netflix and watched it again. Suddenly he starts to talk about process and content and I am startled because he is using my words. But he is not just talking about document content, but about the business content related to knowhow and creativity. A lot of people think that my opposition to rigid process is silly, but at least I have Steve Jobs on my side.

Steve Jobs: ‘You know what it is? People get confused. Companies get confused. When they start getting bigger they want to replicate their original success. And they start to think that somehow there is some magic in the process of how that success was created. So they start to institutionalise the process across the company. But before very long people get confused and think that the process is the content. And that was ultimately the downfall of IBM. IBM had the best process people in the world but they forgot about the content. And that’s what happened a little bit at Apple too. We had a lot of people who were great at management process and they didn’t have a clue as to the content. And in my career I found that the best people are the ones who understand the content. They are a pain the butt to manage. You put up with it because they are so great in the content. And that’s what makes a great product. It is not process. It is content.’

If you get the chance watch the interview because this was while he was growing NEXT and he predicts the future of computing which he would eventually be doing back at Apple.

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Posted in Adaptive Process, BPM, Content, Process

Artificial Intelligence and BPM

There is no such thing as AI. And in the true human sense there never will be. Skynet will not take over the world. But yes, Skynet will be used by humans to try and take over the world. Not through AI but machine-learning(ML)-monitoring and its kin big-data-mining. Both technologies are perfect for Big Brother. AI is hype, while ML is real but not intelligent in any way.

Most of the people droning on about AI lack the basic understanding what it actually does. And most of the stuff considered AI is not. Not even IBM Watson, which is a glorified full-text search with semantic weighting. The ‘AI-Meeting Coordination Service’ Clara uses a huge man-made library of text analysis to prioritize meetings. Not bad, but not AI. Even the coolest self-driving cars are today dangerous pieces of automated junk. They can’t distinguish between a rabbit and a baby on the road and can’t make a human judgement of such situations. But yes, they might stop earlier than a human at anything uncertain on the road as long as visibility is good enough. That has nothing to do with AI. Superhuman does not mean super-intelligent but just faster at some human like pattern recognition tasks that then execute hard-coded processes. Hey, presto … why not BPM?

As you might know, my stance towards BPM is that it is utterly useless in improving what a business does on a human level. After rigorous testing BPM produces a frozen and dead version of a business knowledge illusion that becomes instant legacy dead weight to the business. It can however automate and dumb down business interactions so they no longer require much intelligence or knowledge and that’s what sells BPM and nothing else. Therefore it is odd to then consider that BPM will be improved by ML, because the ML would primarily be used to replace the hordes of consultants doing the process analysis and optimization. When ML learns from knowledgable staff you can’t replace them and you won’t need outside consultants.

ML would rather be a full replacement for the shortsighted concept of BPM because it will not require any kind of analysis, or monitoring or improvement as all that can happen through machine learning. But learning how and from whom and with what accuracy? The idea of process mining from unstructured communication has so far not delivered anything realistic.

Companies like Assist.ai and Digital Genius claim to use AI with a human touch to service customers better. It still remains a glorified answering machine. Supposedly some AI can identify that a customer needs support before he knows and offers proactive help. That nonsense will go down as did all the automated help agents on the PC screens. Annoying!!!! Chatbots that are coded to seem human in their responses seem just plain stupid (as they really are) once the conversation moves on.

One of the main issues is that we do not even understand how the brain actually works and all we know is that it is not a computer in any sense. It won’t be emulated by some algorithms even if we should happen to find it. It won’t emulate the biochemistry that makes us human.

Researchers presented recently experimental evidence for a Theory of Connectivity — that all of the brains processes are interconnected — “and that mathematical logic underlies brain computation.” Surely true, but understanding how a neuron works and to emulate that means nothing: neural nets tried that for decades. The research paper describes groups of similar neurons forming a “functional connectivity motifs” (FCM) for possible combination of ideas.

The assumption is that such an algorithm could lead to breakthroughs to have human-like future robot companions. It once again ignores the biochemical aspect that human memory and decision-making is driven by hormones and neuro-transmitters that can’t be emulated in software. It will still lack the human drives and as such compassion and empathy while strangely that is what most people consider to be necessary for ‘better’ decisions.

Just because a machine can recognise a face and maybe its emotional expression does not mean that it can understand and judge what it means. Intelligence does require emotional capability that creates desires and forms compassion and morality. Logic is not reason and it is most certainly not intelligence. Emotional weighting is the basis of decision making in all forms of intelligence we know. It is the key for the complexity of our interaction through language.

A key problem of that human interaction — may it be in written form or speech — is ambiguity. Humans solve it through context which computers find really hard. Modern speech recognition only works so well as it uses a dictionary and grammar library to turn gibberish into probably-aproximately-correct words and sentence structures, similar to what we did 15 years ago for OCR recognition. For a business transaction more is required, as much as I agree that speech is the computer interface of the future. A grammatically correct sentence can still not make any business sense at all and we do not gain great benefits if our inputs are single word answers to questions.

Which is why we at ISISPapyrus focus with ML on defining business ontologies that help to clearly define the terminology of a knowledge domain. It is similar to explaining to a child what a word means. But once user input can match to a domain knowledge model, ambiguity in design and Use Case Interactions is reduced and text or speech becomes well-working input to an application. ML can learn to recognize input correctly in a given context of a capability map and interface the user to the right transactions, guided by user-defined boundary rules and regulative constraints. Like in the human brain a mix of inherited and trained capabilities.

We use ML for automated discovery of Next Best Action recommendations since about 5 years (the patent is a few years older) and found that no one had any interest in using it, mostly for odd reasons. This included general fear of the technology, and aloof rejection of the idea that software could actually do that. Well, it still does in our platform as the famous User-Trained Agent, but those who do BPM do not get it or do not want it. Those who do not like BPM also do not like any ML functionality connected to it.

We do not use ML to emulate human reasoning (which it can’t because it is purely emotional and is why it works so well) but simply observe human actions and interactions in a well-defined environment of our platform. Once the ML software sees repeated patterns of actions and data it will start to recommend these actions, no longer requiring all the BPM mumbo jumbo. But still, there is little interest given the hordes of BPM ‘experts’ who need a job.

But be aware that the best ML pattern matching won’t substitute for emotional interactions between humans and won’t replace human decision making. What ML should be doing is simply augmenting human interaction especially where it cannot be person-to-person. ML can improve human-learning by recommending the best actions of other people.

Humans also do not need more data or more logic rules for better decisions. We need more real empathy and compassion and not just technocrats making policy for political or financial gain. We do have a problem with human decision making today that is not compassionate and when you see how many doctors treat patients, executives treat the workforce or customers and politicians treat their constituency it is clear that the problem is rampant. A shared moral framework is the basis of each society and AI won’t be relevant in that anytime soon.

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Posted in Adaptive Case Management, Artificial Intelligence, BPM, Machine Learning

Customer Communication versus Adaptive Case Management?

I have been quieter on my blog for the last year as I did not see any noteworthy movement in the process and content management arena. But the recent CCM Magic Quadrant Report by Gartner Group needs to be commented in the light of our business and product strategy, that they fail to understand or more accurately chose to ignore. We have generally pretty good relationships with Gartner Group as we go to all their CIO conferences and we met many of our (also CCM) prospects there. I have thus no problem with Gartner but I find their analysts responsible for CCM lacking.

The Magic Quadrant reports by Gartner are not without criticisms and I personally find Gartner’s own claim in court that it is pure analyst opinion very telling. Gartner Group was the target of a federal lawsuit (filed May 29, 2009) from software vendor, ZL Technologies, challenging the “legitimacy” of Gartner’s Magic Quadrant rating system. Gartner filed a motion to dismiss by claiming First Amendment protection since it contends that its MQ reports contain “pure opinion,” which legally means individuals opinions which are not based on fact. 

At ISIS Papyrus Software, 2015 was one of our strongest growth years ever and much of it came from the completeness of our solution in content, process, integration and user front-end. We are both expanding our existing customer base into Adaptive Case Management (ACM) with inbound and outbound content and find new midsize customers who need a fully featured and consolidated solution that also provides Mobile functionality.

This broad offering of our Papyrus Platform is however a substantial problem for analysts because it does not fit the artificial market segments created for their reports. If analysts can’t compare they do not have a job and therefore no business. Thus what can’t be compared must be made comparable. Gartner Group has a substantial conflict of interest because they make more money with the vendors they rate than the business customers they are supposed to advise. We have been a leading vendor in Customer Communications Management (CCM) since WE CREATED the market space by consolidating document mass production, individual correspondence writing and postal and print management. We still are the leading vendor in functional capability and customer satisfaction as the specialist analyst firm Pentadoc recently states.

With the recently published Magic Quadrant for CCM by Gartner Group the following statement appeared in the beginning of their paper: ‘Isis Papyrus no longer meets our inclusion criteria and is transitioning to focus more on case management.‘ They intentionally wanted to make it look as if we no longer provide CCM solutions. We asked them to revise that statement and they declined. To be included in the CCM report you need to have your own software, have more than $10 million in revenue in two major regions, and must provide five customer references. We met those requirements, but the analysts at Gartner Group did however not spend more than ten minutes to look at our solution and showed no interest in the substantial functional enhancements that are our key differentiators. All they wanted was filled out checklists that contained mostly outdated questions mostly in regards to company market position and strategy.

After a few fruitless discussions, WE DECIDED to pull out of the study as it was  misrepresenting our product and our business, both within the CCM domain and especially with the consolidated functionality of our platform that is incredibly valuable to all our CCM customers. Gartner’s rating system is skewed to support large vendors and analyst darlings as it rates a simplistic perspective on CCM through checklists. The company ratings are purely subjective and weighted to enable any chosen outcome.

Gartner gets vendors to fall in line by saying that they ‘can’t opt-out of a marketplace study‘ so we declined to provide references, which in the previous study they had not even spoken too. Thus they state that we do not fulfill the participation criteria and say that we are not active in the CCM marketplace. While they at least mention many other vendors who did not meet the criteria, we were not even included there. To me that behavior is not professional at all, but whimsey, weak and childish. Gartner should really get rid of such analysts as they do hurt their reputation.

So what can you get from the report? Gartner analysts consider CCM a ‘strategy and a market fulfilled by applications that improve the creation, delivery, storage and retrieval of outbound and interactive communications. CCM supports the production of individualized customer messages, marketing collateral, new product introductions and transaction documents. CCM software composes, personalizes, formats and delivers content acquired from various sources into targeted and relevant electronic and physical communications between an enterprise and its customers, prospective customers and business partners. CCM software delivers targeted communications through a wide range of media including mobile, email, SMS, Web pages, social media sites and print.’ Given the way they rate it, one can do much of that with Microsoft Word.

There is no doubt that my core principle of CCM is valid: There is no process (aka customer interaction) without content and content without (being managed by) a process is waste. So to take a view into content creation and not consider how this must be integrated and managed through a process shows either a lack of understanding or other intent. CCM also requires the ability to consider and manage inbound content which ISIS Papyrus was the first to provide in an integrated manner. Already in 2000 a Gartner Group analyst said: ‚ISIS is this strange company who wants to combine scanning and printing and no one knows why.‘

But those Gartner analysts for the CCM market demand that it purely has evolved from the convergence of document printing and output management technologies. It is in fact so much more than a design tool, a composition engine, a workflow/rule engine and multichannel output management. They still discuss our 15 year old background of providing forms design. They claim that our software is ‘old’ because we were the first vendor to combine interactive documents with mass production in the output management channel! New York healthcare provider Wellpoint installed our system for 3000 users in 2002, ran it virtually unchanged for 10 years and then tried to replace it with a ‘more modern solution’ from the Magic Quadrant. They could not even replicate our ten year old software. After they lost two years trying this, we were asked to upgrade the system to our latest software functionality in 2014 and did that in less than three months. The reason is that what Gartner already considers a workflow capability and a (document) rule engine is rather funny. At the same time we designed for them a document component model that reduced the number of templates from 2500 to less than 300. Without the necessary version control and embedded development, test and rollout processes, changes to a document template become a nightmare. Getting an interactive document integrated into an application is at most corporations a large development project. Gartner isn’t interested in all that.

Rather than looking at the capabilities of the products and what benefits they bring to customers, those analysts want to assess everything through questionnaires only. One has to check off a broad list of feature sets, many rather ambiguous and quite irrelevant, missing many core functions we couldn’t sell without for decades. They can’t include those essential CCM features in the lists because we would be the only ones to have them. The rest is a convoluted mess of vendor viability, sales execution, market responsiveness, customer experience, operation assessment, market understanding, marketing, sales and product strategy, not to forget ‘innovation’ and ‘geographic presence.’ But as we had too many unique innovations they were considered not relevant to the CCM market. The weighting is such that the product and service become in the end fairly irrelevant if they rate you low in any of the other areas. With this scheme it is easy to create any rating desired especially if you consider that all ratings are pure opinion!

The simple fact is: The Papyrus Platform is the leading CCM capability in content and process functionality and we are known for our outstanding service quality. If you are interested in CCM then we can show that leading capability in a two week Proof of Concept installation of our platform, which we charge for as professionals and then you REALLY know what such a system can do. You won’t learn that from an analyst ‘Magic Quadrant’ pure analyst opinion.

As it happens, the standalone CCM market is also in saturation. The ‘customer experience’ projects are about content becoming an embedded capability in customer and partner collaboration. So we are not moving away from CCM as Gartner tries to make you believe but we have given it its long-needed home inside customer-focused applications. Yes, we have more new CCM projects with Adaptive Case Management as the driver of content related processes.

Posted in Uncategorized

Back-Office Applications versus Digital Collaboration

You will have noticed by now that I have retracted from the rather useless BPM versus ACM discussion. One reason is that as I predicted many years ago, the approach used in ACM has been assimilated by the big BPM vendors. Not necessarily in true function but for certain in their marketing approach and material. Additionally I find that the people responsible for process management in most businesses are just thinking of processes in terms of controlling work and not in terms of empowering people to achieve process goals, which is a rather short-sighted approach.

As pointed out so many times that I truly feel like a broken record, it is not the predefined process that insures outcome but a well-defined goal that people pursue. I yet have to see goals being implemented in process management that are no more than milestone definitions.

At our ISIS Papyrus Open House we had great discussions at the management circle on this subject. It became quite clear that large organizations are simply not capable in their current structure and culture to take a different view of processes. Unless the large consulting companies will start to recommend to them to do this differently they will continue to work the outdated way. Unfortunately both the consulting companies and the BPM vendors would have to speak up against their own business to make that happen. So it won’t. It therefore also makes not much sense to try and sell such an approach to large businesses. I have to admit that despite my opposing stance to the purely sales-driven concept, what can be sold are pre-packaged applications that some call ‚Smart Process Apps’ as they bypass some of the immense effort imposed by a BPM bureaucracy. But those apps are back-office focused and lack the crucial ability for goal-driven, digital collaboration with customers and partners. These apps represent additional silos and typically struggle with the dynamics of integrating with content and communications abilities as that would break their rigid processes.

The 'Digital' Collaboration Contract

The ‘Digital’ Collaboration Contract

In the meantime outside the business and IT illusions of the large enterprises the world has changed and continues to change. The change imposed by those forces won’t be subtle nor elegant as promised by the consulting firms. It will be brutal and disruptive as the businesses that can’t adjust will disappear one way or the other. While the principles of Uber or Airbnb in a much broader range of new markets can’t be generalized they show that the infrastructure for a different kind of business-to-employee-to-customer relationship does already exist. It is utterly unused by the large corporations who fail to see the writing on the wall.

Karl Marx had proposed that the world would be divided into people who owned the means of production – the idle rich shareholders – and people who worked for them. Those large businesses still operate that way. Following the Industrial Revolution, having a good job meant it was unionized and secure, with company benefits, such as health-care insurance, vacations and retirement pensions. Both governments and unions are still doing their part to reduce the agility of businesses with labour laws that are supposed to protect employees from being laid off. In effect, those laws are stopping companies from hiring more people. Automation and outsourcing are the consequences with the disappearance of job security.

Ronald Coase, the British economist and 1991 Nobel Prize recipient in economics published in 1937 ‘The Nature of the Firm.‘ He proposed that a firm should be able to find the cheapest, most productive goods and services by contracting them out in an efficient, open marketplace. The realities of employment complexities however caused the creation of ever larger companies that were supposed to dominate and control their market space at all costs. All that growth generally leads to organizations becoming bureaucratic, with a focus on planning, efficiency and costs, destroying the ability to quickly embrace new ideas and technologies when market conditions change.

Advances in information and communication technologies are having a huge impact but not the one we would initially expect. Economies of scale and network effects are leading to organizational consolidation and a winner-take-all world where still only the largest survive. Fragmentation and consolidation will co-exist with each other to a greater or lesser extent across different companies and ecosystems. Apple has found the ideal combination of continuous customer-focused creativity and its amazing ability to manage a huge world-wide supply chain.

How is that possible? It won’t happen by hiring a consulting firm or implementing BPM. Just as language shapes our brain’s ability to think, the use of information technology shapes our behavior as customers and the ability of businesses as suppliers. The most valuable and fastest growing companies are those that use technology to satisfy their customers needs in new and visionary ways. It used to be heresy and unimaginable to IT architects that customers would be allowed to directly access a banking system. Today it is the gold standard by which a bank’s customer service is judged.

It is further no longer possible to ignore that the four layers of customer interaction, business interaction and content, compliance and policy rules, and data transactions have to converge. Back-Office Applications will continue to enforce a customer disconnect. Mobile and browser front-ends must connect to a homogeneous digital collaboration infrastructure that does not restrict but empowers company staff to service in a flexible but still compliant manner.

But clearly it will not be open and unmanaged interaction like on Facebook. Those interactions will have to be private and secure and driven through the goal definitions of a customer service contract. It is the applications that enable this kind of digital collaboration with customers that will make or break a business these days regardless of its size. Digital Collaboration provides the only true real-time ability of a business to interact with its customers and not an illusionary real-time view of old Big-Data analytics and predictions. What nonsense!

It is the executive who decides how technology will reshape the way a business works and he needs to fulfill his vision in a much shorter time than typical software development projects, regardless if in-house or outsourced can deliver.

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Posted in Adaptive Case Management, Customer Relationship Management

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
Max J. Pucher

Max J. Pucher - Chief Architect ISIS Papyrus Software

© 2007-17
by Max J. Pucher. All rights reserved.
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