Can you develop early warning supply chain metrics to measure performance?
Recently, there was some unfortunate news about two Navy ships involved in two separate incidents. On June 17th, 2017, USS Fitzgerald collided with a container ship named MV ACX Crystal, off the coast of Japan. Then, on 21 August 2017, USS John S. McCain was involved in a collision with the Liberia-flagged Alnic MC off the coast of Singapore and Malaysia, east of the Strait of Malacca. Both incidents were very unfortunate and caused a loss of lives and damaged the ships.
A few weeks later, I saw a news report that suggested that the subsequent inquiries into the incidents revealed that the training records on these ships were not up to par. In fact, many of the training certifications had expired. I wonder if further studies will establish lack of training as the cause of the accidents. In this case, falling behind in training certifications could serve as an early warning for increased risk of future accidents.
In recent webinars and presentations, I have been talking about Early Warning Systems within the context of supply chains. The news story above made me think of several examples where a supply chain would use similar concepts to develop early warning metrics.
The idea behind developing such supply metrics is simple.
Look hard at your supply chain and identify early warnings that you can measure, report on, and fix before bad things happen.[Read More: 5 Things to Know About Setting Up a Better Supply Chain Performance Measurement System]
Examples of How to Identify Early Warning Supply Chain Metrics
Quality Issues: If your concern is that too much sub-quality product will lead to your customer taking their business elsewhere, then here is a way to think about an early warning:
- Do you do routine quality checks (you had better if the concern above is valid)
- Historically, what is the percent of products that fail the test?
- Do you see a sharp increase or even a slow trend in the percent fail?
In other words, metrics used to measure supply chain performance that captures the percent fails in the QA process could be the early warning that foretells a customer leaving because of quality issues. As soon as this metric begins to go in the wrong direction, corrective measures can be started. This can be way before any bad consequence shows up; hence it is an Early warning.
Too much demand: Suppose you are a business driven by trends and every once, in a while, you observe that the demand shows very sharp uptrend blips. On close analysis, this seems to be caused by activity in social media, specifically, when a famous person makes a very positive tweet about your product, leading to a barrage of re-tweets thereby generating demand among their followers.
In such a case, the early warning would be to monitor the tweet volume and see if it shows a sudden increase. This could be evaluated for a positive (or negative) sentiment which can then be used as an early warning for an increase (or decrease) in demand.
Gap to Budget: Management teams never like it when the business is unable to deliver what was promised to the wall street or published as an internal budget. However, this is identified as part of a dashboard when it is already too late. It turns out that one can develop an early warning for this. And if such an early warning exists, then creative sales departments can take steps to fill up the pipeline to get the business back up to the levels that were promised earlier. An Early warning around this can be done in two ways:
- For month to month, one can look at the open order data and compare it to historical ratios till that point in time. Too high or too low would initiate an action.
- For yearly or quarterly data, one would compare Year to Date or Quarter to Date data to historical data points. Again, gaps would initiate actions.
Developing an array of early warnings for consequences worthy of avoiding allows a business to use them as levers and to control the outcome to some degree. The business value of this can be tremendous, leading to personal gains as well. All Supply chain planners would benefit from developing an array of early warning supply chain metrics relevant to their business.