Theory of Constraints (TOC), or Drum-Buffer-Rope as some practitioners know it, was developed by Eli Goldratt in the 1970’s to improve on the shortcomings of Material Requirements Planning (MRP). The objective was to maximize the flow within manufacturing plants while minimizing operational expense and inventory. Essentially, TOC converts the MRP PUSH logic into MRP PULL logic. The application of TOC has had its ups and downs over the years, but a recent and very successful application of the TOC principle can be found in the retail industry.
Theory of Constraints (TOC) applied to Retail
In order to maximize throughput at a production site, the bottleneck operation has to be protected with a defined amount of work, which is equal to the inventory buffer in front of the bottleneck. The composition of this inventory buffer in quantity and time is critical in order to support the continuous supply of work to the bottleneck.
If we think about converting the manufacturing principles into retail principles, the following can be defined:
- throughput is equal to sales in a retail store, which we need to maximise, and
- the inventory buffer is equal to the model or target stock in a retail store, which we need to secure the availability of the inventory to support sales whilst minimizing the inventory held in the store.
Using these definitions will allow us to apply the TOC principles to a retail environment.
Implementation of the TOC Principles in Retail
In order to maximize sales, the inventory in the store has to be carefully managed and fine-tuned. Fine-tuning is a four-step process. Each step has to be applied daily for all item and store combinations across the retail and distribution network.
Step 1: Pareto Analysis
The first step is to categorize items, at a store level, based on their contribution to total sales. Fast movers convert to 80% of total sales, slow movers convert to 20% of sales and non-movers are items that do not sell at all. If a fast mover has an out of stock, the relative negative impact on overall sales is greater than for slow moving and non-moving items.
Step 2: Availability
Once the categorization is established, we apply the TOC principle of minimizing inventory. In a retail environment, we must do 2 things:
- focus our inventory deployment on fast movers
- reduce supply of slow and non-movers
The key to supplying inventory to the store is the availability of an item at store level. The TOC “bottleneck” is to secure the sales throughput of fast moving items, which will maximize sales with a greater impact than slow or non-moving items. Essentially, this converts the practice of PUSHING of inventory into a store to a practice of PULLING inventory to protect the sales of fast moving items. A pre-requisite of this principle is that the initial allocation of inventory to the store is less than 100%.
Step 3: Dynamic Model or Target Stock (TOC Buffer Management)
In any retail environment, changes occur daily. As a consequence, daily recalculations of the item categorization, the availability of stock and the corresponding target levels of stock for all items are required. These will drive the amounts of inventory pulled from the central warehouse to replenish each store. This applies to all items, whether those items are carry overs or limited life items, the main factor is the life cycle and the number of replenishments possible within this life cycle.
Step 4: Under- and Over-Stock across the Store Network
A key feature to maximizing sales is recognizing that there is no ‘one size fits all’ replenishment profile for every store. Based on the consumption patterns of each location, replenishment requirements may differ between stores. However, as a result of the initial allocation, stock required in one location may be held in another. Therefore, re-balancing inventory within the retail network is vital. As store-level target stock levels become visible, relative over- and under-stock situations must be corrected. Repositioning inventory within the store network is essential to maximizing sales.
Implementations have shown that focused attention on matching replenishment with consumption patters can drive availability of fast movers to more than 95%. This has a direct and significant impact on sales. Top line improvements of 20% or more, with equal or lower store inventory levels are not uncommon, resulting in an even greater effect on the store ROI.
The enormous amount of data analysis required to understand the daily consumption pattern for each item and store combination cannot be accomplished without the support of software. The leader in this field is Retailisation. Our solution serves many big brands, mainly in the fashion and sporting goods industries. We offer easy on-boarding via different methods of data exchange with a user-friendly web interface that minimizes the time and effort required to generate real value.