Here is a sample embedded lesson from the Knowledge Commons:
On managing complexity
Here is an interesting podcast regarding complexity and effectiveness from the Harvard Business School by Ron Ashkenas.
Ron argues that organizations are creating excessive complexity which, rather than improving the ability to deliver, are actually impeding it. Some managers become complexifiers who genuinely believe that gathering every possible aspect of a problem will help solve it. Unfortunately, they tend to create enormous amounts of machinery to gather that information and often overload the organization. This – often anxiety driven process – can feel productive but somehow problems never seem to get solved. People develop a knack for being very busy and avoiding the ax man. Jack Welch was famous for getting to the heart of a problem. He would ask simple questions like: What do we need to be number 1 or number 2 in this market?
The real question is how much complexity is required to understand the problem and define a solution. Or perhaps better said, what is the MINIMUM amount of information required to frame the problem within a given context. According to the philosopher Thomas Kuhn, for all practical purposes, the world is an infinitely complex system. Any object / event can be described in an endless number of ways: chemically, geometrically, algebraically. Just when you think you are done, you can imagine another dimension: what are the implications from a quantum physics perspective. Of course not all of these representations are likely to be relevant or useful to solve the specific problem. So the trick is to use the simplest model possible that sufficiently represents the problem space – within a given context.
Ultimately, we can never truly FULLY represent objects / events the real world, we can only come to varying approximations of accuracy in describing them. And, it can actually take MORE time to find the right level of complexity to represent the event space based on the context. Understanding the problem and and how rich the answer needs to be – to be sufficient within it’s context – is the key.
So how does this apply to management and governance in the real world. I have worked in organizations that required tremendous amounts of detail to manage an implementation; the more – the better. Ultimately, initiatives and implementations in this world crushed under their own weight. The result usually meant someone would be fired. The next group leading an implementation would add MORE controls to assure success. When they were crushed by the machine someone there would be fired and so on… In one particularly large insurance organization, the interesting thing is that the driver for change was that customers were leaving the company because everything took too long and it was too painful. They would rather pay more for an inferior product than to deal with the bureaucracy.
In the real world, people would not want or need a stop light on every corner; though this would probably reduce accidents overall. However, no traffic controls at all is worse though it might be the most efficient. That efficiency will quickly disappear as increasingly aggressive driving becomes the norm and accidents begin to clog the roads. Unfortunately, in the business world, reaching a balance is tough politically since the driver for change is usually a triggering event – such as a major project failure.
So how does this translate into project management governance? In one organization, we developed and implemented a very detailed SDLC with guidelines for each phase of the project, templates and a central tool for administering the execution of projects. This was a double edged sword. On one hand there were groups that appreciated any kind of guidance and support in developing their mission critical applications and embraced the methodology readily. There were other groups that begrudgingly adopted the methodology but clearly weren’t happy about it. Then there were groups that straight out said – “leave me alone, we haven’t screwed anything up yet so there is no need for your meddling”. Lesson learned, my second attempt at doing this for another major stock exchange provided 5 Gate Checkpoints as part of the full lifecycle. So if you didn’t need to be told how to do things at least there were some basic controls. The key was a layered approach..
On innovation and change management
So here is an interesting video from Simon Sinek on leadership and inspiring others…
http://www.ted.com/talks/lang/eng/simon_sinek_how_great_leaders_inspire_action.html
Paraphrasing Simon’s theme, leaders inspire by convincing others as to why something needs to be done rather than how or what. He divides the world into the following familiar categories:
2.5% – innovators – need to change the world, need to evangelize
13.5% – early adopters, need to be first
34 % – early majority, will not adopt until someone else has adopted first
34 % – late majority, will adopt after the early majority has adopted first
16 % – laggards, will take a LOT of convincing
This is a great model for any kind of Change Management project. At the NYSE I had the pleasure of working for an ex Air Force Colonel who was a strong believer in this process. We would actually categorize change ‘targets’ into the various categories.
I believe that focusing on WHY (and less about WHAT and HOW) is very true for early adopters but not for the other groups necessarily. I think this has profound implication on how you plan a Change Management project. You have to focus on the early adopters initially and engage on the WHY aspect of the change. As you move to the Early Majority group I do think the strategy has to begin to adapt. You have to begin to talk about the WHAT part of the equation. As you engage with the Late Majority you have to transition to the HOW. I have no hard data on this, or even a scientific basis for this opinion.
Why creativity is broken in education
Charles Camarda – NASA Astronaut and Educator (who I consider a good friend) shared the following link with me regarding creativity.
http://www.ted.com/talks/ken_robinson_says_schools_kill_creativity.html
I totally agree with the premise. We are actually driving out the creativity in our children by making them afraid to make a mistake. I have been guilty of this with my own son as we worked together on his math homework assignments. What I try to do now is to help my son become his own coach. The balance I am trying to strive for with him is to help him understand that quality is important but that he needs to be his own best ally and realize that he will make mistakes. The key is not to let those mistakes get to you as they are not ‘failures’ but a natural outcome of being human. They will be there – expect them and build a process for coping with them.
Why we are ruining our kid’s math education
Here is a great lecture from this year’s TED conference…
http://www.ted.com/talks/lang/eng/dan_meyer_math_curriculum_makeover.html
As an undergraduate Electrical Engineering student, I had a prof (who was actually a great guy so I won’t name him) walk into the first day of Differential Equations and before he introduced himself, he turned – coffee and unlit cigarette in one hand – chalk in the other – and proceeded to derive Maxwell’s Equations on every board lining the walls of the room. He got about 1/2 hour in and stopped, walked back to the first board and started erasing it with his sleeve.. Half the class walked out. I had him for Calc 4 the previous semester and knew he tested directly from the text book so I stuck it out and ended up with an A.
I couldn’t derive Maxwell’s Equations now if you pointed a shotgun at me…
The theme of Dan Meyer’s presentation is that we are not teaching our kids how to do ‘patient problem solving’. We are spoon feeding out kids information to plug into formulas. Most of the time – in the real world – we either have too little information or not enough. In both situations you may still need to come to a solution. In the case of not enough data – assuming that you can’t go back and find more – how do you triangulate to an approximate answer. In the case of too much data, does any of the data lead you to conflicting solutions? And as a result what do you keep? What do you throw out?
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