By Srinidhi Boray
It is interesting to understand that Six Sigma works on the perfect hind sight and it’s future sight is dependent on the extrapolation of the past statistical information. Meaning it is a derivative of the past. In a way, future is spinning around its past (on its tail) in the Six Sigma realm. What can be inferred from this is that it is useful for applying to those systems that are linearly expanding. When a system is subjected to non-linearity, then Six sigma methodology breaks-down. Methods available within Enterprise Architecture and Six Sigma both have vied for spots within large enterprise as a discipline for gaining significant business process improvements. When businesses are confronted by evolutive transformations, then newer approaches need to be sought. For, basis on which the Six Sigma is founded will be no more relevant. However, if six sigma is combined with EA, then mathematically it turns into integro-differential equation,
Where the EA is about integrating the different parts into a whole
Six Sigma is about dealing with deviations from the qualitative norm, so it is a partial differential equation
Combining both we have integro-differential equation
By Srinidhi Boray
Change affects everybody. And it will happen again and again, when the entropic equilibrium is disturbed. It is a systemic property. It is not driven by a person nor a simple one factor. It is not a property of personality. It is the intrinsic systemic property. Change happens so political reforms happen. It is not the other-way around.
Many factor comes into play for a change to occur. It is very difficult to visualize changes and the transformations. The only thing that can be understood is the process that facilitaes the change not the final form the change will lead into, until it comes to a rest. As John Zachman points, change is a ‘step function’. It is not a liner extrapolation of the past. It is a dynamic evolution of a completely new system, which is very difficult to be envisaged.
From the Theory of Constraints, it is known that the degree of Complexity reduces the degree of Freedom within a certain system boundary. After a certain complexity threshold is reached, the system has to completely metamorphise to overcome the systemic constraint, and to do so, has to evolve into a completely new system. It will not any longer be mere re-form, rather it will be ‘generative’. Certainty can only be held that long. After a certain threshold it will be the fiefdom of the Uncertainty until the next stable state is reached. While discussing harmony, chaos is presumed. The ceaseless juggle between the two is responsible for producing a newer system.