In the preceding article we discussed the theory of how may a manufacturer cope with unpredictable market demands, through assessing market needs – and achieve cost savings. Today, we'll discuss this matter in practice in this Case Study, based on a project conducted by Tefen
Written by Ilya Makovoz, Consultant
Background and Challenges
Our client knew that they were keeping too much inventory. Their inventory policy was archaic, 4-6 weeks of inventory based on an inaccurate and constantly changing forecast that they couldn’t predict.
To put numbers to it, their forecast accuracy was lower than 60%, their SLA hovering around 65% (their goal being 80%), and their forecast in-season was growing year-on-year while their production capacity stayed almost the same.
The results were burgeoning holding costs with a falling service level.
Tefen approached the problem using aspects of Theory of Constraints (ToC), pioneered by Mickey Granott, and traditional statistical approaches.
The first step of this process was to assess the current state and historical trends. This included actions such as:
a. Current production capacity per line per Stock Keeping Unit (SKU)
b. Average sales per SKU per month
c. Standard deviation of sales per SKU per month on a day-to-day basis
d. Historical accuracy of forecast by SKU
e. Overall accuracy of forecast by production line
f. QC lead times per SKU
g. SLA lead times by SKU (average)
h. Production planning lead time
i. Other production constraints (intermediates, etc.)
j. Desired service level
The second step was to develop a model based on the inventory data collected throughout the year. Tefen’s approach used historical sales and standard deviation while incorporating client service level goals to set a safety stock level for each SKU.
The use of historical sales was important since it decreased the reliance on forecasts that are unpredictable and tethered stock levels to actual sales. This safety stock was then set monthly for each SKU using the most updated information.
The third step was to determine high season policy. Tefen’s approach was to minimize the risk of stocking the wrong SKU for the high season.
Using historical accuracy, Tefen could create a strict policy for which SKUs should be considered the most reliable. Using forecasted demand and the overall accuracy of the forecast, Tefen allocated the necessary capacity to produce MTO for each SKU.
When the sum of these allocations was greater than the capacity, these volumes were produced in months with excess capacity (with the most accurate forecasts being prioritized).
By prioritizing the production of excess volumes to the most predictable SKUs we the company maximized the likelihood of selling off our their inventory without losing sales.
The result of the project was the creation of an inventory policy that was leaner and more responsive to unpredictable market demands than ever before.
The average inventory level suggested was 30% lower (on average) than previous years, but with volumes properly distributed across stocks, allowing for improved service for buyers.
This resulted in a working capital reduction, maintenance of service level and conservation of the company’s dominant market position.
Monopoly Building, Operational Excellence, Change Management & Supply Chain Expert