Definition of Consequential Metrics:
« Back to Glossary IndexPrimary metrics act as reference points in the life cycle of a Six Sigma project. Some widely known primary metrics would be customer service, product quality, and on-time delivery. There are also secondary metrics that can help to determine if a project is improving and goals are being met. These are known alternatively as consequential metrics.
Overview: What are consequential metrics?
These are the metrics that can be used to spot and measure potentially negative side effects resulting from process improvement efforts. While performance or quality may have increased due to process improvement, consequential or secondary metric tracking helps determine if other problems have been created. Some examples of these kinds of metrics would be Defects per Unit (DPU), Defects per Opportunity (DPO), Rolled Throughput Yield (RTY), Parts per Million (PPM), Defects per Million Opportunities (DPMO).
3 benefits of consequential metrics
These metrics offer a great number of benefits in order to help ensure the success of a project:
1. Protection measure
These types of metrics ensure a project goal is not reached due to the sacrifice of anything else integral to successful processes.
2. A comprehensive view
Consequential or secondary metrics help to provide a much fuller view of operations.
3. Minimizing mistakes
Consequential or secondary metrics are vital for catching output failures and variations that are impossible to determine from looking at the primary metric alone.
Why are consequential metrics important to understand?
You cannot go into a project solely focused on the primary metric. Understanding the consequential or secondary metrics are important for the following reasons:
1. Separates useful from non-useful information
Understanding these types of metrics can help separate useful information from the clutter and allow you to make better decisions.
2. Allocation of resources
Having a good understanding of these types of metrics can help make sure that resources are managed and allocated better in pursuit of the primary metric.
3. The right direction
The use of these types of metrics can help your team be sure that a project is moving in the right direction, so having a robust understanding of these types of metrics can make or break a project.
An industry example of consequential metrics
A sales team has a lot of outstanding invoices that are well past a comfortable due date. They need to collect on a large percentage of these invoices in order to stay in the black. The team identifies collecting on these invoices as their primary metric. Some of these clients have been doing business with the sales team for decades, and it can be an uncomfortable effort to enforce collection. It is proposed that discounts could be offered to these long-term clients, provided that the discounts do not put the organization into the red. In this situation, not losing the business of the long-term clients as well as not offering discount levels that become damaging to the organization could be seen as metrics that are consequential.
3 best practices when thinking about consequential metrics
Here are some practices to think about to help make the right decisions in your use of these types of metrics:
1. The number of these metrics to use
Using just one consequential metric is common, but having 3 or 4 that are complimentary to the primary metric is best.
2. They are not spin-off benefits
Some projects see these kinds of metrics as spin-off benefits from reaching the primary goal. This is not how these kinds of metrics should be used.
3. These metrics are always present in a project
These types of metrics are always present. The only time to ignore them is when the primary metric is absolutely critical, as in the medical field where a situation can be life and death.
Frequently Asked Questions (FAQ) about consequential metrics
1. How to identify consequential or secondary metrics?
Often, these types of metrics will be rather intuitive to identify. If you are well aware of the process, brainstorming is a good way to determine these types of metrics in relation to the primary metric.
2. How many metrics can I use?
There is really no limit to the number of metrics that you can use, but it is best to keep things fairly simple. Keeping it to 3 or 4 of these types of metrics is recommended for most projects. Some projects, of course, are simply too complex for this to be the case. In complex projects, it really just comes down to identifying as many metrics as are present that could negatively impact the primary metric and limiting impact as much as possible.
3. How many primary metrics should there be?
Ideally, for any DMAIC project, there should be only one primary metric.
Keeping tabs on these types of metrics is just smart
All projects should have a clear goal in mind. However, it is important that you are not creating more problems for yourself on the way to achieving that goal. Knowing the potential results from operational processes on the way toward reaching a project target is just smart business.
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