Data forms a crucial part of any business today. In our article on Clause 9.1.1 - ISO 9001, we discussed how an organization need to establish monitoring and measurement methods which will lead to a lot of data and information gathered and collected within the organization. Clause 9.1.3 - Analysis and Evaluation requires that the organization should analyse and evaluate appropriate data and information arising from monitoring and measurement. These results of the analysis should be used to evaluate:
Methods to analyse data can include statistical techniques.
Why is this important?
Monitoring and measurements established within the organization will generate a lot of data and information. To fully utilize this information, analysis and evaluation of data is required to help the management in decision making. Just gathering and looking at numbers without any analysis and evaluation will just be a futile exercise that will take a lot of effort without any real value derived out of it.
Let’s take an example to understand this better. If you are just tracking the number of returned pieces of your product and not analysing the trends over a period of time, you cannot improve your products or services to your customers. Benchmarking or setting up goals on the achievement of your objectives is a useful method that can be used to identify any red flags beforehand. If your goal (looking at your previous performance) indicates that you do not have more than 2 returns in a month, but suddenly in a month you get 4 return requests, it is an alarm for you to look into the issue and find out the root causes behind it. This will help you in taking timely action before the issue goes out of control and fetch you some bad reputation.
It is, therefore, important that data is analysed, a conclusion drawn out of it, and plans and actions made whenever an unfavourable trend or condition is observed. That is why analysis and evaluation of data is important for any organization. This will help you seize all opportunities of improvement that exist.
Analysis and Evaluation
ISO 9001 requires that an organization collects, analyses and evaluates Quality Management System data. Both analysis, as well as evaluation of data, is important; that means data analysis through statistical techniques, trend analysis, etc. and interpretation of the analysed data so that it can be used in an appropriate manner, for example- for decision making and action planning.
The data may be analysed and evaluated for the below areas:
- Conformity of products and services
Data collected may include defect rates, on-time delivery, number of returns, product or service related complaints, etc. This will help you identify issues in the processes involving the delivery of products /services through the analysis of such data.
- Degree of customer satisfaction
Customer satisfaction data analysis will help you determine key areas where improvement is required. With improvement in processes and addressing all customer concerns, you will be able to enhance customer satisfaction further.
- Performance and effectiveness of the quality management system.
Performance and effectiveness of quality management system may be derived through analysis of data like Cost reduction improvement (including the cost of poor quality), number of internal audit issues, etc. This will give a good indication of the health and effectiveness of the Quality Management System.
- Effective implementation of planning elements
Typically schedule, effort, cost and risks are the elements that may be measured to evaluate the effective implementation of planning. The metrics where you track on-time deliveries, your cost on service against the parameters planned can provide you with a good indication of how planning was effective.
- Effectiveness of actions taken to address risks and opportunities
You can derive how effective was the implementation of mitigation actions planned against the risks by evaluating the reduction in the probability or impact of risks.
- Performance of external providers
ISO 9001 doesn’t just focus on your internal processes but also requires that you evaluate the performance of external providers based on the targets given to them. For example, if you have a vendor who supplies a critical material used in your product, you can set a target for them to provide you with the right and good quality material within a specified time period and then evaluate their performance on basis of targets met or not. This could also be done based on the number of issues found at your end during the inspection when the material is delivered to you.
- Improvements within the quality management system
You can measure these by the number of process improvements suggestions given on the quality management system or on the basis of non-conformities found during internal/ external audits, etc.
Data Analysis and Evaluation Process
Statistical techniques are referenced in the ISO 9001 requirements for data analysis, but these are not mandatory and may not apply in every company’s scenario. Simple trends may be used to monitor progress and identify opportunities for improvement.
Such trends and data should be presented in management review meetings where they should be evaluated further and used for decision making. The exercise becomes meaningful when analysis of data is used as an input to identify opportunities for continual process improvements and corrective actions are taken to address all negative trends.
When developing a process for measurement and metrics collection, analysis and evaluation, it should address the following:
To conclude, ISO 9001 defines a detailed process for monitoring, measurement, data collection, analysis and evaluation. This clause provides you with all the guidance to establish an effective management system whose performance is monitored and measured, analysed and evaluated over a period of time. The objective is to help the organization identify continual improvement opportunities which will further lead to higher customer satisfaction and business growth for your organization.