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Efforts and Effects in Transforming the Enterprise

According to Wikipedia, the Pareto principle states that “for many events, roughly 80% of the effects come from 20% of the causes”. Economist Vilfredo Pareto developed the principle by observing that 20% of peapods in his garden contained 80% of peas. 

This term has found its way in boardrooms in a bid to find a formula to be efficient in a never ending turblent sea of change that faces the enterprise. Referring to Pareto’s observation in his garden, for 20% of peapods to contain 80% of peas also implies that 80% of the rest of the peapods only contained 20% of peas. In other words looking at the effort versus effects we would say the 20% peapods producing 80% peas were very efficient while the 80% peapods producing 20% peas were very inefficient.
But indulging further on this, the assumption is that 80% of the peas produced by 20% of peapods were all good peas. This may not be the case. It is also true to say that not all the 20% peas produced by 80% peapods were bad. In other words, less effort that produces large effects doesnt mean these effects are necessarily good effects. They are likely to be a combination of good and bad effects. On the other hand, more effort producing little effects doesnt mean that these effects are bad all effects.  
Supposing the 20% peapods that produced 80% peas had 90% of bad peas and 10% of good peas. Further on, supposing the 80% peapods that produced  20% peas, had 90% of good peas and 10% of pad peas. In this scenario, which set of peapods was more effective and efficient in producing good effects? On effectiveness, 90% good effects (of 20% total effects) came from 80% effort. On efficiency, 10% good effects (of 80% total effects) came from 20% effort. Both of these cases, point to an immature process of transformation. While less effort is used to produce more, the good effects are too few to justify efficiency. On the other hand, while more good effects are produced, there is too much effort expended.
These scenarios characterize many an enterprise. We may call the set of 20% peapods “agile” and the set of 80% peapods “waterfall”. Note that these two terms are used for illustration purposes and not necessarly to compare the agile and waterfall methodologies, although there are certain subtle resemblances. Going back to the argument, while “agile” in this case used less time and effort to create tremendous effects, little of that effect was actually absorbed rightly by the enterprise. On the other hand, while the slower and more rigid “waterfall” took too long to deliver little effects, almost all of these effects were abosborbed rightly, little as they may be.
In this case, does it mean “waterfall” was better than “agile”? This quesiton cannot be answered at face value (some enterprises often fall for this trap). It would require a deeper understanding of the context that led to choice of either of these methods based on the information available and how they were adopted as suitable to produce the desired effects.    
According to POET(TM) to adopt any framework, “the framework should define different levels of maturity recognising that there is no right or wrong way of doing something but rather there is a continuum of maturity and that anyone utilising a framework is the best person to judge what level of maturity is appropriate for them.” This definition must not only be for purposes of assessment but also to determine how and why to move from that level of maturity. So if say, the “agile” framework was assessed on WHAT, HOW, WITH WHAT, BY WHO and scored well on WHAT, HOW and WITH WHAT but scored poorly on BY WHO, chances are the good effects will be significantly diminished. On the other hand if “waterfall” framework was assessed and scored well on WHAT, WITH WHAT and BY WHO but scored poorly on HOW, chances are the required effort will be significant.
Albert Einstein is quoted to have said, “we cannot solve our problems with the same level of thinking we used when we created them”. The context of choice of approaches transformation cannot be bound by the context in which problems exist. There must be new information which exposes possibilities of maturity of how an enterprise “does” transformation in order to increase the chances of 20% peapods producing 80% good peas while decreasing the chances of having to use 80% peapods to produce 20% good peas. Transforming transformation increases the chances of achieving 80-20 principle in a pragmatic way.
About the Author
Peter Muya, is an award enterprise transformation practitioner, possessing 15 years experience conducting mid and large-scale transformation projects in the telecommunications, financial services and public sector industries. He is the co-founder and a managing partner of PTI Consulting, a pan-African consulting practice providing ICT related business advisory services


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