Week 12 - Redesign Principles and Tactics (2)

Source / Reference:
1)"Model-based Rapid Redesign Using Decomposition Patterns" by Chen, Li ; Macwan, Ashish ; Li, Simon
J. Mech. Des.  -- March 2007 --  Volume 129,  Issue 3, 283
http://scitation.aip.org.ezproxy.lb.polyu.edu.hk/getabs/servlet/GetabsServlet?prog=normal&id=JMDEDB000129000003000283000001&idtype=cvips&gifs=yes




Subject:
Other model of process redesign: Model-based Rapid Redesign


Motivation:

We have been taught about the Five Phases BPR Methodologies and in the phase three - process redesign, there are many redesign principles and tactics, such as Streamline, Lose Wait, Orchestrate, Mass-customize, Synchronize, Digitize and Propagate, etc. These redesign tactics and principles mainly depend on human involvement. Is there any other ways to help redesigning process in a systematic approach which can be done by system? I have found an article that may explore the possibility of process redesign that can be assisted by some mathematical approaches. The article is “Model-based Rapid Redesign Using Decomposition Patterns”, although the title seems like talking about redesign, it is not fully related to redesign a process. However, the idea and methodology discussed may be useful for redesign a business process.


Introduction to Model-based Rapid Redesign Using Decomposition Patterns
The article presents a pattern-based decomposition methodology for rapid redesign to support design customization in agile manufacturing of evolutionary products. The methodology has three functional phases. The first phase, called design dependency analysis, systematizes and reorganizes the intrinsic coupling structure of a given existing design model that is represented using the design dependency matrix. The second phase, called redesign partitioning analysis, generates alternative redesign pattern solutions to form a solution selection space through a three-stage procedure. The third phase, called pattern selection analysis, finds an optimal redesign pattern solution that entails the least potential redesign effort. Each pattern solution identifies and delimits the portions of the design model that need to be recomputed, thus expediting the redesign solution process. In such a way, one can treat the re-computation of the entire model, which is a conventional and computation-expensive solution approach, only as the last resort to solve the redesign problem given.


1st phase: design dependency analysis
A general redesign problem is formulated as a constraint-based computational model that is composed of parameters and constraint functions. The parameters describe the physical constituents and/or behavioral properties of concern for a design. And the constraint functions define the design correlations and mappings between the parameters. In this context, the design dependency matrix (DDM), a mathematical incidence matrix, can be used to capture and convey the dependency information inherent in the design model. The DDM-assisted decomposition can be applied as an effective means for simplifying the design problems that are intractable in size and complexity.


2nd phase: redesign partitioning analysis
The goal of partitioning is to convert a diagonal matrix into possible pattern solutions, or rather, to identify which redesign decomposition patterns from the library and their redesign pattern solutions correspond to the diagonal matrix. Upon the concept of the partition point, the redesign partitioning analysis is developed to address the placement of partition points in order to generate all the applicable redesign pattern solutions from a diagonal matrix.


3rd phase: pattern selection analysis
To provide a means to evaluate alternative pattern solutions to find the optimal one, two matrix pattern metrics are derived to quantify the redesign effort entailed by any given redesign pattern solution: intensity and interdependency. The intensity metric is used to estimate the scale of redesign potentially involved in improving the deficient performance levels. Also, the interdependency metric is used to estimate the redesign propagation potentially induced due to coupling.

Conclusion
This model uses mathematical methodology to analysis the dependency among process and decomposes the process. Through this analysis, the partitioned process can be analyzed and redesigned to obtain the optimal process pattern.
We can apply this model in redesigning a business process. First we have to define the dependency of activities with a business process. Then we can build a design dependency matrix and follow the three phase methodology above. Finally, we can get the best possible redesigned process. However, the mentioned methodology has a greater improvement on complex process. If the process is rather simple, the model may not be very useful for redesigning since the dependency and sequence are non-changeable. 
If we can apply this model agilely with the redesign principles and tactics, a better process can then be redesigned.