In the earlier post I had introduced the next challenges that an organization would face. The challenges were
In this post I will discuss the first challenge.
Organizations constantly strive to grow. They grow sometimes at the cost of profitability, sometimes at the cost of bad service and sometimes using amazing interpretations of the law of the land. But, grow they do.
Growth is not easy. It requires a lot of patience and perseverance. Perseverance is something many organizations possess in abundance. They are quite dogged when it comes to growth, but patience is something that is very thin to sometimes non-existent. Large organizations want it fast. They have the money and they often believe, often erroneously, that throwing technology, people and money at a problem will yield magical results.
The current backdrop of both economic environment and technological advances makes available an opportunity that organizations are finding it hard to ignore even in a small measure. Online capabilities are providing visions of rapid success. Online capabilities break geographical barriers. They also break the difficult and often painful face to face meetings.
Online-ness brings many benefits but is also brings about chaos. It is able to do so because of what Jamshid refers to in his book – Systems Thinking – as ‘Multi-mindedness’. He talks about a progression of a mechanistic system to a uni-minded animal to multi-minded socio-cultural organizations. An organization he says has purpose as opposed to an animal seeking a goal. The difference being here that a purpose of an organization ultimately is to serve many goals as wished by the many minds in the organization.
Ergo – chaos results. But how do complex systems lead to chaos? When the number of agents in a multi-minded system increases and the ability to influence fellow agents’ increases beyond a point of the ability to understand and predict the resultant behavior of the overall system reduces. Jurgen Apello in his book Management 3.0 depicts this in a simple diagram.
A stock market with so many players and a large amount of cause and effect linkages is chaotic according to him as the degree of predictability and degree of understandability is low. On the other hand it is easy to understand ones underpants and your watch given some time. A city, team dynamics in a small team is complex.
Large organizations deal with large number of agents in their business. For example take a large hotel chain with over 200 properties across the globe. The sheer number of suppliers they manage across would be staggering, managing local customs and customers, catering to the local geographical needs and be seen as a global brand is the challenge.
An airline for example would have the rug pulled underneath it when the ATC goes on strike. The level of control on the ATC is near zero as far as the airline is concerned. The situation is chaotic. Imagine – not only is the local airports affected but the event avalanche spreads across the neigbhourhood and soon become unmanageable
The important issue here is to know to what degree organizations would spend their time understanding their system and what level of predictability would they want from systems that would help them predict.
One of the key characteristics of a chaotic system is that small changes in the input lead to extraordinary changes in the output. Hence when the horizon of prediction is not large, it would be possible to predict only the next few steps. Climate is one example of chaotic system. Weather prediction is usually done for the next two or three days or perhaps a week with decreasing level of confidence as the time increases.
It is there important for organization to iterate in small steps and look one step ahead and use that predictive output to gain competitive advantage in the business. It is important here to understand the in chaotic system the maximum degree of confidence is obtained during predicting the next few steps. It is important therefore to have a strong feedback system and continuously predict the next few steps. Software system used in such activity need to be calibrated often and the efficacy usually deteriorates rapidly with time. This is not unlike the story of Sisyphus and his labour. We will never know whether Sisyphus succeeded – but if he had had, then it would have been using small steps!
Roger Sessions in his book – Simple Architecture for Complex Enterprises – states “In analyzing complexity, fast iteration almost always produces better results than in-depth analysis”. He referred to this as Boyd’s Law of iterations. We see now it is generally accepted that requirements are always fuzzy, ever-changing. It is as I had once mentioned gathering requirements is like picking tea leaves. The adoption of the iterative sprint method of development being popular is no surprise then.
With such changes in the environment status quo is a meaningless term. While organization can do well enough, if they carry on doing whatever they do, there is a time when it just does not work. It is a time to park your horses, take them to a drink and wait patiently. It is time to change and change very dramatically.
This is what I refer to as the Phoenix strategy.
Organization should seek to kill themselves. They must postulate theories of becoming redundant. I had a discussion with an automobile tyre manufacturer and I had asked him how his company is planning to retire. Fortunately it will be a while before Michelin’s Tweel is in the mainstream.
The Phoenix strategy requires the organization needs to die – rise from the ashes – and die again. This is best expressed as a graph.
The organization carries on.
- When the time is right – it seeks to kill itself.
- This implies it has to seek a new avatar.
- Create one avatar if necessary.
- Don the new avatar.
- And carry on in the next phase.
- ‘Carry on’ itself is series of iterations of understanding and predicting, acting on the next step.
The next two challenges would detail in the challenge of Connectedness and Cascading Customers.