Six Sigma Key Process Input Variable Overview
Every process has input and output variables. Input variables can be inherent (physical materials needed to complete a process), controlled (the ones we have a degree of control over), or uncontrolled (the ones beyond our control).
Each of these different types of input are considered as Key Process Input Variables (KPIVs). They are central to the Six Sigma methodology of using statistical analysis to enhance and refine production and business processes.
This article will give you an overview of:
- What Six Sigma KPIVs are
- How to identify your business KPIVs
- The role of DMAIC in improving KPIVs
What Are KPIVs?
In Six Sigma training a KPIV refers to a Key Process Input Variable, which are the various factors that can cause an impact during a process journey.
These key inputs can be physical contributions that affect processes, e.g. manufactured products, completing a task, accessing data. Or, they can be notional inputs that directly affect the customer, e.g. durability, spec, features, price.
These inputs can vary in scope and number, but all will impact the variation found in KPOV (Key Performance Output Variables). However, by using Six Sigma processes to analyse, refine and standardise these factors, the input variable (e.g. fabric quality) can be controlled at a constant level and the process should produce consistent output results (e.g. satisfied customers).
How Are KPIVs Identified?
To identify KPIVs, businesses can use Six Sigma methods to map processes and measure their efficacy, which will help identify the variables that are essential control factors in any given process.
Six Sigma encourages structured experiments through the use of statistical modelling and analysis. These help to model process behaviour and understand the cause-and-effect relationships that are present in a system. By identifying potential weak spots or cumbersome inputs, it is possible to amend and streamline them to encourage greater productivity and more profitable outputs.
Processes have to satisfy customer requirements (e.g. price, quality, durability). Therefore, changes to inputs can have a negative impact on customer satisfaction if not fully trialled or modelled beforehand. Six Sigma tools can help improve the results of process improvement as it is specifically designed to minimise flaws, which in this case stands for customer satisfaction.
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KPIVs in the Six Sigma DMAIC Process
The Six Sigma methodology works on a DMAIC (der-may-ick) framework. This methodology comprises of five phases:
- Define the system
- Measure key aspects and collect data
- Analyse the data to verify cause-and-effect relationships
- Improve the process by using design of experiments
- Control the process to ensure that any deviations are corrected before they result in defects
Map your processes and define the problem. Use Six Sigma quality measurement tools to prove that it really is an issue.
How should the process be performing? Identify a baseline productivity figure and then measure to see how the process is performing against your expectations.
Analyse the newly identified inputs and identify the reasons for poor performance.
At this stage, processes can be improved by reducing variation and standardising the inputs. Uniformity breeds productivity and success in Six Sigma philosophy.
When refining KPIVs and improving them, you may need to run several rounds of tests to work out the ideal cost-benefit ratio
Continue to measure the integrity of your KPIVs and establish the process capabilities for them. From here you will need to maintain control of these inputs through the regular use of statistical modelling, which can help ensure productivity rates don’t drop.
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