From my recent conversations with companies one topic is becoming increasingly prevalent — stock loss. This problem impacts the business operations of a range of industries and company types. From the automotive industry with both OEMs and Tier 1 suppliers, through to packaging companies supplying the CPG industry.
Stock loss isn’t selective on item size either. It can include boxes containing smaller parts, and massive reels of paper weighing many tonnes.
The Causes of Stock Loss
Sources of stock loss can include:
- Incorrect part movement
- Scrap with parts being dropped and damaged
- Shipping inaccuracy from warehouses and suppliers
- Manual mistakes in the processes
- Supplier performance
- Inaccurate forecasting
Split shipments can also cause issues. Even if the supplier has delivered all the parts, this may not get reconciled.
How Stock Loss Impacts an Enterprise
Stock loss can have dire consequences on a company’s manufacturing output and business performance. Potential issues include delayed production runs. If the necessary parts / raw materials are not in the right place to complete the planned production schedule, delays are inevitable.
One clear knock on impact of this is to customer services and adherence to SLAs. This is especially important if there are penalty clauses in your contracts.
Then there is the procurement of replacement materials / inventory. Depending on the circumstances, this may require expedited freight — with the associated premium costs.
All of this increases the cost of goods sold and affects operating margin. These are serious consequences, especially as many of the companies I meet acknowledge that some of this is avoidable.
Stock Loss and Process Monitoring
Accidents happen, and things do get dropped and damaged. But what about the avoidable examples such as inaccurate purchasing, poor shipping procedures and supplier underperformance? These are issues that companies can, and should address.
Many avoidable examples are process related. When a company designed its business processes it was assumed that they would be followed. This design would have allowed for the potential of a few, rare, exceptions.
But is that still the case today? As time goes by, more variations stealthily creep in, unnoticed. This doesn’t happen overnight, a few more here, a few more there.
One company I met with estimated that from their point of ordering to the point of goods arriving, and being in the right place at the right time, their ideal designed process was adhered to 80% of the time, with around five variations. However, using Process Intelligence, a data driven approach, proved that there were over 140 different process variations. What’s more, only just over 50% took the “happy path” through the system.
As a result of stock loss, staff are chasing things instead of making things.
This is an inefficient use of time and resources. Furthermore, it could result in unfulfilled production orders and less than satisfactory customer experience.
The Benefits of Process Intelligence
Process Intelligence allows you to clearly see how your processes are really working every day — not how you assume they work. Process variants, anomalies and bottlenecks of all kinds can occur. This is because processes are dynamic.
A clear picture of how your processes are working in real time also allows you to uncover opportunities for process improvement.
The potential savings and benefits through understanding this and making the necessary changes are significant. But this is not a one-and-done task. You need to continually monitor your processes.
Process mining is the first step into understanding the causes of stock loss. Once you are aware of the root causes, you can treat these — not the symptoms. Stock loss is a symptom of suboptimal processes. The root causes could lie in inaccurate forecasting, supplier underperformance, customs hold ups and other global logistics issues to name a few.
If you think you could reduce stock loss (or find other areas to increase value in your supply chains) through a data driven process mining approach, or if your processes are running well, and you want to validate, please contact QAD or connect with me on LinkedIn.
