Revolutionizing supply chain management the theory of constraints way: a case study

Abstract

This research describes in detail an application of theory of constraints (TOC) and its resulting benefits on the supply chain performance of India's largest lock manufacturing company over a period of seven years. Using TOC's thinking process, the core constraints that had limited the company's performance in the areas of production, distribution, supply group and projects were identified and eliminated. TOC's unique approach helped the company achieve a significant reduction in its finished goods, raw material and work-in-process inventories at various levels across the supply chain. The stock-outs and excess in the distribution system nearly disappeared. The existing lead times saw a drastic reduction while the availability of items increased to nearly 100% despite significant decrease in inventory levels in the supply chain. The inventory turns of the distributors and retailers more than tripled and their profitability increased significantly. The overall sales of the company grew nearly three times during the six years post TOC implementation. TOC's holistic approach helped the company to double its profits and improve its cash position during the Great Recession.

Keywords:

• TOC
• current reality tree
• replenishment solution
• CCPM

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplemental data

Supplemental data for this article can be accessed here https://doi.org/10.1080/00207543.2018.1523579.

Notes

1 It is explained in Section 6 in detail how Godrej eliminated just these constraints and in the process eliminated most of the UDEs.

2 Large batch sizes was especially a problem with those suppliers who were supplying to multiple companies like Godrej. The lead times of such suppliers could be really large because of huge WIP.

3 In some cases it was not even possible to get materials at short notice or in short quantities as many suppliers have a minimum order size policy.

4 Quite clearly it was an accounting invention where an item produced during the month was recorded as an asset on the company balance sheet. Since the asset was recorded at a value higher than the raw material costs after incorporating the ‘conversion costs’, it was possible to make accounting profits just by producing items and storing them even if there was no immediate demand for such items.

5 Because of the Little's Law.

6 Since the distributors were ordering about one month worth of stock for a given SKU at a time they were able to order only a limited variety of SKUs due to the cash constraint.

7 In most cases the next order was placed only at the start of the next month. Thus the items that ran out of stock in the first week continued to be missing for the rest of month. Moreover, any shortage with distributors invariably resulted in a shortage in the entire region as retailers could not get the desired supply for a long time.

8 The extent of lost sales at GL was directly dependent on the amount of time the fast selling SKUs were out of stock multiplied by the throughput of such SKUs. While it was not easy to measure the extent of lost sales, the company estimated that it could be as high as the current profits or even more. For similar problems involving assessing the impact of lost sales on the system performance the readers may refer to (Goldratt 2008) and (Goldratt, Eshkoli, and Brownleer 2009).

9 A shortage invariably meant a lost-sales for the company as the retailer would push for a competitor's product.

10 Entities numbered (101), (201), (301), (302), (310), (401), (422), (424), (506), (512), (607), (613) in Figures 2–8.

11 GL implemented the simplified version of DBR, also known as S-DBR, in which the market was assumed to be the ultimate constraint (Schragenheim and Dettmer 2000). The plant did not have bottlenecks under S-DBR and operated with a capacity constrained resource (CCR) with protective capacity and planned load (Schragenheim, Dettmer, and Patterson 2009).

12 Two more colours were commonly used: (1) black (B) to represent stock-outs and (2) white (W) to represent buffer exceeding green).

13 The time buffer for each product family was set equal to the half of the present lead time.

14 The number of suppliers covered under the milk-run system had been increasing steadily since 2008 (Figure 13(g)).