One of the challenges when measuring process productivity is deciding on what measurements and metrics to use. Industrial Engineers take a reductionist approach and try to get as much process detail (metrics) as possible. This is useful, but makes it very complex to determine and measure ongoing improvement. From an IE perspective, all of those metrics can be simplified by converting them into an Engineered Labor Standard (ELS) that then gives you a standard scoring mechanism as a percent of standard to evaluate yourself against. The challenge with this approach is that labor standards change over time as modifications to processes are made so it becomes rather complex to track your ELS over time objectively since the underlying formula for the standard can change as well.
We find a better objective productivity measurement for a process is the cost per unit. Ultimately the goal of continuous improvement is to drop per unit cost and improve quality. As you modify and improve processes unit cost should go down. The underlying labor standard may change and need to be recalibrated so using it as the continuous improvement measurement does not work unless you track all standard modifications and normalize them back to baseline.
Unit cost is also a very useful benchmarking measurement to compare your process cost to other operations. For example, if your e-commerce pick cost is 73 cents per line but the median e-commerce pick cost for similar companies is 45 cents per line, then it is likely there are some process changes you need to do.
For a continuous improvement initiative here is how we recommend it should flow:
- Develop a process map of your entire operation.
- Determine where and what data is available for each process and identify gaps.
- Determine primary costing metric for each process.
- Determine primary productivity metrics for each process.
Unit Cost is your ultimate objective measurement but just analyzing cost will not tell you what you need to do. Unit cost will help you determine that you are inefficient on that process, but you will still need to figure how to improve that process. The labor standard metrics and measurement are, however, extremely useful in evaluating a process and ways to improve it. For example, if you look into your picking cost and picking distribution by customer and product, you may find that your cost is too high and that for high volume products, you have excessive travel. As a process change, you may decide to relocate the 20% of the products that are 80% of the volume shipped more conveniently to reduce travel time. This change will not impact the labor standard since each employee is given a set amount of time per foot traveled, but it should lower your per unit cost.
In order to do this type of analysis you do need a robust analytics system. For the initial analysis you can brute force it with spreadsheets, but ideally you want to have this as an ongoing initiative and daily feedback. Easy Metrics can automate the entire data integration and analytics for you and should be considered as a powerful tool in your continuous improvement efforts.
