Is your customer communication solution provider focused on a non-core direction?

After Hewlett-Packard started a massive restructuring in 2012 that has caused job reductions of about 50.000 people until now, it announced in September 2015 another round of layoffs that will cut a further 10% of its workforce of 300.000 until 2018. The company will be split and move 60% of its workforce to low cost locations. That obviously opens the question what will happen with its HP Exstream product. Ever since Exstream was sold to HP, it has been lagging behind the mainstream in Customer Communications Management. HP is a huge business in deep trouble and the tiny Customer Communications segment is unlikely to contribute much to its declining software business. The Exstream product could be discontinued at any time without anyone sneezing at HP over a few upset customers. Exstream and Customer Communications is nowhere near a core element of HP’s business.

HP revenues

It is therefore prudent to consider a move from HP Exstream to ISIS Papyrus and gain the most extensive function set in Customer Communications. ISIS Papyrus had in difference nearly 15% growth in 2015, being the strongest in the last 10 years. On their product website, HP Exstream has apparently no other means left to compete than spreading the false rumor that the ISIS Papyrus Customer Communications functionality is being retired because we withdrew from the Gartner CCM report. Gartner stated in the report that ISIS Papyrus focuses on Adaptive Case Management or ACM. ACM enhances CCM dramatically rather than delivering less functionality. ACM like BPM makes little sense without the ability to consider and execute the natural connection between business content and process goals. CCM makes little sense without the related processes. Analysts think in artificial market segments that they protect vigorously, because if their segment is devoured by another the analyst looses his ‚expertize‘.

At ISIS Papyrus, CCM functionality is used in a 100% of all customer solutions because that is our unique selling point in the artificial ACM market segment. ACM is our unique selling point in the artificial CCM market segment. Only the Gartner Group CCM analysts do not get that. Especially in the area of supporting important and thus extensive document management processes HP Exstream has not added any such features to its portfolio. To actually make state-of-the-art Customer Experience happen, managing just the layout or the textual content of a channel message is nowhere near enough. CX processes supported through ACM make the difference!

It is easy to be happy with a current product if one does not look over the edge of the plate (of the CCM market segment) to what is happening in the industry. Rather than just updating marketing materials and clicking yes in analyst questionnaires, ISIS Papyrus is the only vendor in Customer Communications who actually enables the Customer Experience processes without the need for complex integration.

ISIS Papyrus is the only CCM solution to not only support all digital channels but to actually drive the inbound and outbound processes that make these channels work. There is a direct link between marketing and the actual business transaction that makes money. All other CCM products and especially HP Exstream require extensive integration with CX solutions or BPM to make that possible. There is no common link and management to change the content and its related process in HP Exstream. That is a natural in the ISIS Papyrus Platform. So yes, it is obvious that all Customer Communication Management solutions are not created equal. And yes, now is a good time to consider to drop a product like HP Exstream that has stopped on a busy motorway and is being overrun by everyone.

Customer engagement is NOT a new frontier but has been addressed by ISIS Papyrus years before it crept into the glossies of other CCM vendors. Exstream quotes Gartner Group as saying that “89% of companies plan to compete primarily on the basis of customer experience.” That is utter nonsense because for a 100% of companies customer experience is not a management choice but something that happens regardless of what businesses do. It is the reason we focus on an integrated solution with ACM. Designing a customer experience is utterly useless without the ability to create a seamless goal-driven interaction with the customer using business content on all channels. That becomes really difficult and expensive with a standalone CCM product such as HP Exstream. It is exactly that point that led to a conflict with the Gartner Analysts who consider that capability not-mainstream CCM, proving that ISIS Papyrus is the ONLY VENDOR who currently addresses this integration.

HP Exstream alludes that it can migrate ISIS Papyrus installations. In fact, it has not helped a single business to migrate from ISIS Papyrus and has neither the knowledge nor the product functionality to do so. Other analysts than Gartner have taken the effort to make product comparisons for real and ISIS Papyrus always comes out as a leading and innovative CCM provider with the highest level of process integration. In fact there are businesses that are migrating from HP Exstream to ISIS Papyrus.

As HP states, you should really be worried about the cost of migrating to another CCM solution and you should be seriously concerned that you don’t have the funds or bandwidth for this type of project. HP Exstream is actually proposing to just install HP Exstream as an additional CCM product and create a dramatic fragmentation and systemic breakpoint that stymies progress into a seamless Customer Experience. ISIS Papyrus has in difference always provided substantial functional upgrades for free under the maintenance agreement. There is a continuous stream of innovations as well as customer requests that are being added to the platform and its CCM functionality.

There has not been a single discontinuation of ISIS Papyrus CCM and certainly not after the installation of HP Exstream. Our strong growth comes from the powerful combination of CCM and ACM functionality. We know what our customers need and barebones CCM functionality is a dead-end.

You will get less for your money if you install HP Exstream next to ISIS Papyrus and the additional expenditure in software, consulting and training would be much better spent on actually stepping into the REAL WORLD of Customer Experience and not just following some irrelevant analyst market segments and vendor glossies.

So to add HP Exstream to your portfolio is not a big decision, it is simply the wrong one. The right move is to drop HP Exstream and other outdated CCM solutions and start investing into the future of Customer Experience!

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Posted in Adaptive Case Management, Customer Communications, Customer Relationship Management

Customer Communication versus Adaptive Case Management?

hero-design

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.

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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

Giving up Stability for Agility

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 BPM.com 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.

red-build

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.

Conclusion:

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
Max J. Pucher
© 2007-16
by Max J. Pucher. All rights reserved.
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