As usual, here is a retrospective of this year’s activity around BPM. The choice of the themes is mine and the order its presented is random, and do not mean any raking scheme.
Enterprise Architecture: for me it was clear that this was the year where this particular domain expertise got lost. Enterprise architecture suffers from two pains. The first is the concept division between the American School and the European School. The American divide what is business architecture and IT architecture, while the Europeans do not. Envisioning an enterprise system without seeing the whole is an. The second is enterprise architecture relies for a year in static, cumbersome, time-consuming methods to “draw” the architecture and this is not a problem of the framework used. Unfortunately, EA frameworks are not adapting to the needs of the enterprises that need to shift gears quicker. This year I did not have any answers from distinguished enterprise architects how to fix this. Unless there is someone that invents “agile EA”, looks like companies will deal with some outdated skeletons in the enterprise content systems.
Social: One of the hottest themes. But the discussion that is being taken is not the most important. I mean there is lot of hype around building a social practice, use the right tools to collaborate, the bring your own device (actually this is making a huge breach in enterprise architecture) engaging with the customers, etc. But the most important aspects are being forgotten: understand how people are engaged and how it should relate. In other words look to the social dimension of a process. This year, many books about social business were published. I put my hand on two from prominent experts and the ease it took to read the books, seems this area is being treated superficially (probably because is new and there is a need to understand the basics). I measure a domain maturity for the difficulty it is to understand (the more difficult is to jump into the concepts, the more mature it is). Hence, is critical to understand how social patterns look alike (the aesthetics). Does your company have lions or lemurs? Are they working together in a way that is aligned with the knowledge type required to play the process or are you creating variability when you need standardization or vice versa? In other words, how do you put people evolving and gaining new competences to handle the exponential complexity we are facing? How do you put people learning with the others?
It is a commonplace that the world is getting more complex and that organizations are struggling to cope with it with their operations. This is difficult, because complexity is hard to describe. The language of networks patterns can bring visibility how complexity can be handled properly. A good reflexion can be found <here> .
Intelligence. This category includes many scattered sub categories all of them important. They are: big data, mining and prediction.
Before jumping into each knowledge domain, it’s important to make a reflection about why humans are so fascinated with it. We like to predict events but we miserably fail to do it. We like to be sure we do not get wrong in our assumptions. But due changing conditions that we rely to make our wizardry it’s getting more difficult to do it. Sometimes we do not realize that the facts we use to predict changed when the event occurs. That happens because the world is a complex system and there is no linearity in how each variable is related. Thus, we are looking for new predictions models and technology that can help us with one of the major human limitations: being capable to be correct about the future.
Technology can help us, broadly speaking, to make better decisions, but being able to “be sure” is a step that probably is still too far to be a reality. Why? Because intelligent systems do not have the capacity to learn. In a previous experience with IBM’s Watson super computer when asked about what is the capital of North Korea it replied “this country does not have diplomatic relationship with the USA”. The machine was not able to find other way of search and get an answer (actually it did not realize it was wrong). In addition, because machines suffer from what is called cognitive illusion (to understand better the concept read this article how out of context, a system – it can be a human as system we are – makes the wrong decisions).
Talking about predictions, this could take us to a long discussion dedicated only to the subject, nevertheless, strictly speaking within the human dimension, it’s interesting to distinguish two types of person:
• More P or M individual in Gordon Pask’s words;
• More power of Ideas or power of Politics in Rick Brandon’s and Marty Seldman’s words, or;
• More Fox or Hedgehogs in Philip Tetlock’s words.
The former are humans who like to question, evaluate options and engage with others, like to share knowledge and evolve concepts and like to learn with failure.
The last are humans that believe in formal authority, governance, centrality, control, and their ideas cannot be questioned, are somewhat like dogmas.
Foxes, power of Ideas or P Individuals, like o spend time to construct models to understand reality, than unfortunately changes and the models are useless or return wrong answers.
Hedgehogs, politics and M individuals like to blame the errors due to bad luck. This type of human predicts what is called under “smelling felling” approach.
Coping only with this human type variability, should make us wonder why is so difficult to predict.
Talking a about big data, the challenge is real and is here, and without a question is important to get important information about organizations, operations, but 99,99% is noise. In other words, is not relevant. The challenge for big data is to process photos, video, documents where there are data chunks that can be important to understand how good you perform, or to execute sentiment analysis for example.
Scepticism is around process mining. People do not like to believe that it is possible to discover process models and analyse a process from different points of views because they tend to think that there is no data for that. Also, because we know that when exceptions occur, process participants jump off the systems and start collaborating using e-mail. Fortunately, process mining is much more powerful and quick to analyse a process and it has out of the box a huge palette of techniques even in the case where the is no event log.
Self-organization: I will dedicate in the future a post only to this matter, but for know, I sense a shift in the way that companies are embracing change projects. Somehow we were used to implement governance models, to help others to make the change, to design and implement business processes, in other words to sell professional services (from the provider point of view). One of the shifts I talked about at the BPM conference in London this year, the social factor, as I put it: “On the social factor, […] we are facing a displacement of “assembly line” people […] will have to adapt and start pushing their capabilities to new boundaries. This shift has also a profound implication on the type of people companies are sourcing in the labour market. As leading companies expand and operations are outsourced or transferred to low wages economies, the future workers profile will be aimed at highly skilled persons capable of embracing business dynamics”.
People will also question the existing order, like the pianist Glenn Gould, that opposed the way Bach composed. He said that Bach made some errors and some notes should be changed .
The social factor is changing the profile of the people that work at the companies. It’s time to teach these different type of people how to get most of the systems and how to design business processes, because they do not need you anymore, as a provider, as a mentor, as a manager, to do their job, them they will auto organize to deliver it internally. Not only the type of technology will change dramatically and will put people controlling directly process composition, letting IT embedding business logic and system interoperability, as also governance models as we know it, tend to disappear our will be less formal, it will define at maximum the rules of the game people must comply.
Self-organization must not be confused with anarchy, but it will a key human component as finally organizations are seen like organisms, living things that must fight for survival like any other animal. It must adapt or die. Cybernetic management will emerge.
Interested in 2011 list? Click <here>.
 References: Booklet – Bach: The Goldberg Variations.