However, the most common question before these organizations is how much to spend on process improvements, which process needs to be improved or changed on a priority basis, and other practical considerations that necessitate the prioritization from among the available options.

The cost and effect analysis and careful use of design of experiment (DOE) can help the Six Sigma team make cost-effective decisions.

Cause and Effect Analysis

The cause and effect analysis is a systematic way of generating and sorting out the various problems facing any process of the organization. The problem area is identified and the root causes of the problem are sorted out and addressed. Let’s take, as an example, a service center.

The root causes of the problem facing this process is about the effectiveness of the product.  It may be sorted out using the 3M&P model. The 3 Ms stands for methods, material and machine, and the P stands for People.

Methods are the processes and procedures followed by service agents. These could be the assignment of the workflow of the service requests, the requests being transferred to the person who can handle it correctly the first time, and the escalation of the problem when handed over to a person higher in authority. 

Materials is the work environment and the effective incentive structure that has been provided by the company to the agents for correct resolution. The machines are tools available to agents, such as CRM applications and the problem knowledge base. The people are the agents with the appropriate domain skills, problem solving skills and people skills.

How does the company what needs to be done? This is where DOE comes into the picture - it allows for measuring the relative efficiency of one over the other.

Design of Experiments (DOE)

DOE is a structured methodology to define the relationship between factors affecting the process and the output of that process. The 80/20 rule can be applied in the service center scenario. The quality of service is the dependent variable and the factors identified from the cause and effect analysis would be independent variables.

The experiments in this scenario may include selective training of sub-groups of agents. The company may conduct a comprehensive survey to compare the result of this experimental group with that of the control group. It can then be determined if a new CRM system that is given to this sub group is effective enough and gives good result for the subgroup.

It can also be determined if training will be useful, or if a proposed incentive structure to the sub group would be better option for the entire control group as well. Even trying out a new workflow for escalation process is beneficial in having a better performing process.

Further, Analysis of Variance can be undertaken to relate quality of customer service to the above factors. The key in such an analysis is the collection of databases to identify factors that are relevant to others. Thus, cause and effect analysis and DOE are powerful tools to bring about business process improvements.