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A large food company asked us the question, “How much finished inventory should we be holding?” Our answer surprised them: “NONE”
The answer was the result of a detailed analysis of a year’s worth of data. The main findings were:
- On 95% of the days that products came off the end of the packing lines, there were open sales orders, greater than the day’s production.
- The average customer order is placed 9 days ahead of the requested delivery date, very few require immediate delivery.
- Most deliveries are made early.
- Demand within each month, and throughout the year, is quite even.
The evidence shows that they are a make to order, NOT a make to inventory company, as they thought they were. Their mind set looked like this:
They held the classic view that making a sale depends on having the inventory available. Whereas the reality is that most of the inventory in the warehouse is not available for sale, it is product on it’s way to a customer, with the exception of a small volume of less popular products. So, “how much inventory should we have?” is the same as “how long does it take you to make a dispatch?”. It is their customers who are the “stockists”, not them.
What reinforced the mindset are the organizational responsibilities. Production is responsible for putting products in the warehouse, and the outbound logistics team is responsible for dispatch.
They should be thinking like an airline, selling seats.
They are not selling inventory, they are selling future production. The timing of deliveries, rather than inventory, is the buffer between production and sales. So, a planning system, to support the revised mindset should have the following features:
- Driven from the orderbook
- Based on finite scheduling
- Delivery promises based on available capacity
- 95% of production pre-assigned to a customer order.
- Line change-overs timed to optimize due date performance.
- DDMRP principles used for small volume products.
The data analysis was done using our Fast Excel Development Template and was completed within one week. A year’s worth of data was extracted from their ERP system and included 3 million inventory movement records. This allowed us to derive the inventory of each item in each location on each day, as well as insights into the patterns of sales order intake, production and sales. The analysis has given them new insights into their business and sparked a significant change in their mindset.