![Advisera Mark Hammar](https://advisera.com/wp-content/uploads/blog_authors/markhammar.jpg)
April 22, 2014
As I mentioned in my article on Monitoring and Measurement: The basis for evidence-based decisions, if your company is to try to make good evidence-based decisions to improve its effectiveness and efficiency, the evidence needs to be accurate and adequate to assess whatever process or product is being reviewed. In addition to this need for adequate and accurate data, there is a need to analyze this data in a way that is meaningful and useful for the people in your organization who use them for making the decisions. Deciding what data to analyze further is as important as deciding what data to collect in the first place.
Along with the two main areas of ISO 9001 on monitoring and measurement, there is a separate section that talks about analyzing appropriate data, which demonstrates the effectiveness and suitability of the quality management system. This is required to find where continual improvement can be applied to make the QMS more effective; and, of course, the data is generated by the applied QMS monitoring and measurement and any other sources. In particular, there are four areas highlighted as being important for the analysis of data:
Customer Satisfaction: This is one of the most critical areas for a company to be successful, yet it can be one of the hardest to monitor. Customer satisfaction is not just how much you feel that you have met the product or service requirements, but more about how the customer perceives that you have met the requirements. Some examples of things to monitor would be customer returns, comments by customers in personal interactions or online discussion groups, or feedback on why a customer did not accept a sales proposal. Monitoring how well your customers feel you are doing can be critical for the survival of your company.
Characteristics and trends, including opportunities for preventive action: The use of trends to promote the prevention of problems before they can occur is a crucial step forward for a reactive company to become proactive. Improvements are made when a company can move from fighting fires to preventing problems from occurring. For instance, when reviewing incidences of operator error, you could find that an increasing trend might indicate a change in training needs, or a change in the work environment, which could be corrected before worsening and causing shipment of defective product or services. As the saying goes, an ounce of prevention is worth a pound of cure; this is even more true when discussing a customer’s perception of how well your company meets their needs.
Suppliers: In most cases, a company will depend heavily on the performance of their suppliers to ensure that they themselves can perform for their customers. As a case in point, working with suppliers to improve delivery times by reducing complexity of the product requirements might be one way to improve the overall delivery time to customers. Continually improving how well your suppliers work for you can greatly improve how well you can perform for your customers. This is often ignored, to the peril of the company trying to improve the satisfaction of its customers.
When reviewing the data from monitoring and measurement, it is important to discern what data shows that a process is functioning well, and what data should be investigated further to determine if improvements can be made. Taking data that has been collected from well-thought-out monitoring and measurement and applying good decisions on which data to analyze further can lead to better improvement activities. This can happen best if you reduce the amount of time spent analyzing data for processes that are already satisfactory, and focus the effort of data analysis on those processes which show promise for improvement. A focus on improvement in the right places can improve not only how customers perceive the company, but also the financial bottom line by eliminating the wastes of poorly performing processes.
Click here to see a free sample of Matrix of Key Performance Indicators.