A socks manufacturing company in India turned to TQM to improve its supply chain. In Part One, the case study elminates a significant cost for the company – delivery delays. Part Two of the case study looks at the broadening of the application of process improvement beyond deliveries.

A fledgling socks manufacturing company in India was working to supply export markets in Europe and U.S. The company was receiving a lot of customer complaints, however, due to delivery problems. The company decided to use total quality management (TQM) and just-in-time (JIT) manufacturing principles to help resolve delivery delays. Their story will be told in two parts:

  1. How TQM helped resolve customer complaints
  2. How the company was bitten by the “quality bug” and used TQM to increase operational efficiencies beyond their delivery issues
The complete case study is available for purchase on the iSixSigma Marketplace.

The Project Begins

A two-day program introduced company management (including the general manger of sales and the heads of operations, manufacturing, planning and IT) to the basic principles of TQM – customer delight, JIT, total quality control and total employee involvement.

Through brainstorming and prioritizing exercises, the management team determined that the critical-to-quality attribute for its customers was on-time delivery. However, the company was struggling to meet delivery schedules.

A cross-functional group was formed to resolve this problem. The group scheduled fortnightly meetings to ensure that a plan was created and followed.

The company’s improvement story follows the seven steps of TQM:

  1. Define the problem
  2. Analyze why (find the root causes)
  3. Brainstorm countermeasures
  4. Test ideas
  5. Implement in regular production, modify ideas
  6. Standardize results
  7. Prepare quality improvement story

Step 1: Define the Problem

When asked to identify problems associated with the delays, member of the improvement team said they ran the gamut from lost orders to additional costs (from shipping delayed orders by faster and more expensive means). These conversations revealed that there were no agreed-upon metrics or ways to determine what constituted a delay and how to quantify those delays.

The team agreed that to monitor improvement in the process they would measure the additional costs incurred due to the delays. If those costs went down, it would indicate that delays in deliveries had been reduced. An initial analysis of data revealed this cost to be 3 percent of sales. The group agreed to try to reduce it by 50 percent – to 1.5 percent of sales.

Step 2: Analyse Why (Find the Root Causes)

Brainstorming for possible causes of delivery delays produced the list shown in Table 1.

Table 1: Possible Causes for Delivery Delays
Possible Causes Category of Cause
Lack of professionalism General
Improper information flow System
Contingencies not built in Planning
Improper goal setting Planning
Time wasted in paperwork System
Manpower requirement incorrect Planning
Preventive maintenance irregular Planning
Data formats not usable by all System
Documentation system not followed System
Orders beyond plant capacity Planning
Raw material ordering unsystematic Planning
Individual responsibilities unclear General

Categorizing the possible causes revealed that most of the causes resulted from an inadequate planning system. The next step was to examine the planning system used in the supply chain and determine its relationship to delivery delays.

Members of the improvement team role-played a typical sales scenario to further reveal the root causes of the delivery delays. Below are listed the members’ actual roles and the roles they played for the exercise:

Table 2: Team Member Roles
Actual Position in Company Role for Exercise
General manager of sales Production manager (1)
Production manager General manager of sales (2)
Planning manager Planning manager (3)

In the role-play scenario, the general manager of sales (2) calls from a customer meeting in Europe and requests an order of 50,000 socks for a customer. “Delivery is required in 45 days. Can we commit? I need to go back with a yes or no in 15 minutes.”

The production manager (1) and planning manager (3) huddle together and consider the question. Is there enough material? Are the machines available? Do we have manpower and uncommitted capacity? The discussion between the two is not simple – no clear planning template exists upon which to base an answer. Fifteen minutes later the managers continue to argue, but need to answer the sales general manager. They respond, “Take the order, we will manage!”

Essentially the production and planning managers advised accepting an order without having any idea if they could full the customer’s delivery requirement. This role-play exercise highlighted the dysfunction of the planning process.

Step 3: Generate Countermeasure Ideas

The nuts and bolts of an effective planning system for the socks manufacturing company are:


  • Manufacturing capacity
  • Capacity availability when required to meet delivery (when making commitment to supply)
  • Resources needed to meet commitment – materials, manpower and machines

Selling: To capacity

Operations: On-time delivery

At one of their fortnightly meetings, the improvement team planned the next month’s operations – systematically. A planning system evolved from this two-day meeting as described below:

1. Manufacturing capacity. This topic was hotly debated, as sock designs, length of run, manpower availability, new design development and more all affected that measurement. Opinions differed even so far as the machine speeds that needed to be considered. After a lengthy discussion a consensus was reached for calculating capacity for the mix and type of socks usually processed.

2. Capacity availability. Before an order could be booked, the company had to be able to verify capacity. As demonstrated in the role-play exercise, such answers often required protracted debates with no clear metrics to use to make appropriate decisions. The team developed a machine-load planning template that maps the machines and their capacities net of changeovers, maintenance allowances and efficiencies, and would be used to track the daily utilization of the machines.

3. Deliveries required. A continuing challenge was that the scheduled orders were not known among critical personnel, even for the current month, let alone planned in detail. To address this, the machine-load planning template would also be used to document orders and indicate which machine is booked for what dates. It will be updated daily with new orders and the previous day’s deliveries.

Sales team members were asked to document orders in three categories:

  1. Confirmed orders with firm delivery dates
  2. Orders being negotiated with likely delivery dates
  3. Possible orders in the future

It was agreed that the last two categories were not commitments, but would be built into the planning template to aid in delivery scheduling and material planning. As orders moved from possible to confirmed, the required capacity would be blocked on the planning sheet and teams would be ready to take action.

The sales team was asked to update the order book on a dynamic basis – or once a week if no new orders were booked.

When asked to commit to a new order by a specific date, the team could easily map production for the new order based on the existing bookings. They could now commit to new orders with confidence when delivery was feasible. If the required schedule was not feasible they could offer alternative dates or suggest breaking an order into parts in order to meet a customer’s needs.

4. Capacity planning. In conjunction with the order book updating, capacity planning would also be updated dynamically (again, no less than one time per week).

Commitments for deliveries would be made by booking available capacity when a new order was confirmed by filling up machine capacity beyond already committed dates. Significant delays in production for whatever reasons would need future capacities to be remapped to the new situation. Thus, a dynamic planning system evolved.

5. Management coordination. To keep on track with the new system, the improvement team scheduled a recurring monthly meeting to plan for the next four to six weeks of production and deliveries.

Step 4: Test the Ideas

This system was introduced and reviewed fortnightly in the TQM team meetings.

Step 5: Check the Results

The change between the no-system process and system process is shown in Figure 1. The more months the dynamic planning system was in process the more significant the cost savings to the company.

Delivery Delay Costs Per Month
Delivery Delay Costs Per Month
The complete case study is available for purchase on the iSixSigma Marketplace.

After only five months of the countermeasures being implemented, the costs due to delays were eliminated.

Step 6: Standardize Results

Months 11 to 13, the months following the initial drop to zero delay costs, repeated that success. The system was institutionalized, and further automated by integrating with the company’s internal computer system.

Step 7: Prepare Quality Improvement Story

The successful elimination of delivery costs was present to the company’s senior management. This project was such a success that management wanted to address other waste within its factory. Part Two of this article will look at how this sock manufacturing company moved to implement continuous improvement across the business as a whole.

Part Two of this article will focus on the expansion of the application of TQM to other parts of the company.

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