In this case study, a team wants to be sure their customer-focused business is satisfying its clients. Part 1 focuses on reducing the wait times associated with transferring cargo and documents. Part 2 looks at making more improvements using just-in-time (JIT) principles.
A 15-year-old shipping company with a network of offices throughout India considered being “value-driven, customer-focused” a key driver of its business. Its senior management decided to implement total quality management (TQM) to provide a competitive edge to the company’s customer service; a pilot program was implemented to demonstrate the effectiveness of TQM in a shipping environment. Depending upon that pilot’s success, leadership would decide whether to adopt TQM as a way of life within the company.
A two-day quality awareness program was conducted with management to introduce them to TQM with an overview of why and how it works, and how it can open minds to the exploration of change. The group then brainstormed problems, prioritized the most pressing and selected a theme for the TQM pilot – dramatic improvement in customer service and delivery. Within that focus two projects were selected:
- Delivery of information
- Delivery of cargo/documents (e.g., bills of lading)
A team was selected to work on both projects; this case study pertains to the second project – delivery of cargo/documents. Since the company serviced several shipping companies, its largest customer was selected as the project’s subject.
The project began using TQM’s seven steps of problem solving:
- Define the problem
- Research the causes
- Generate countermeasure ideas
- Test and modify the ideas
- Implement ideas
- Standardize procedures
- Compile quality improvement story
Step 1: Define the Problem
In TQM, the problem equals the desired state minus the current state. The project goal was defined as seeking a “dramatic improvement in delivery of cargo/documents.” The company delivers three items to its customers:
- Documents
- Empty containers
- Cargo
These were prioritized using a weighted average table; documents were revealed to be the priority item in deliveries. At first glance, this seemed odd. Upon reflection, however, it was logical since the company was a shipping agent – not a shipping line. It had little control over processes after the container was loaded on the ship. Up to that point, the timely issue of documents, in particular the bill of lading (B/L), was of vital concern of customers.
To measure the current state, a format for data collection was developed and data was collected. If a particular voyage’s sail date was “s” then the metric selected was the percentage of B/Ls released relative to the date of sailing. The initial data collection results are shown in Table 1 below.
| Table 1: Time of Delivery of Bills of Lading Relative to Sail Date (s) | |||
| B/Ls | s % | s+1 % | s+2 % |
| 119 | 18 | 29 | 45 |
Eighteen percent of documents were released by the day of sailing and 45 percent were released by two days after date of sailing. The desire was to release 90 percent of the B/Ls by s+2 days.
The improvement was carried out in two stages. A description of stage 1 activities follows; stage 2 is featured in Part 2.
Step 2: Research the Causes
When it comes to reducing process lead times, waiting time generally constitutes more than 50 percent of the lead time. To determine if this was the case here, a list of activities required to issue a B/L was prepared, identifying the doer and the receiver (Table 2).
| Table 2 Activities in B/L Delivery | ||
| Activity | From | By |
| Booking slip received | Customer | Department 1 |
| Order issued | Department 1 | Customer |
| Empty container pick-up report | Department 2 | Department 1 |
| Container in yard report | Department 2 | Departments 1 and 3 |
| Shipping bill | Department 4 | |
| Container load plan | Operations | Department 3 |
| Shipping instructions | Customer | Department 1 |
| B/L draft version 1 | Department 3 | Customer |
| First print (FP) of B/L | Department 3 | Customer |
| Confirmed FP from Customer | Customer | Department 3 |
| Print confirmed B/L | Department 3 | Department 3 |
| B/L released | Department 3 | Customer |
The next step was to identify the stages where an activity waits for another activity’s completion.
Steps 3 and 4: Generate Countermeasure Ideas/Test and Modify the Ideas
The team decided to try the countermeasure of minimizing waiting by organizing a “green-channel” run in which the whole team would process one sample ship’s B/L without any avoidable waiting. A B/L tracker was designed to log the days when each step in the process was completed. The tracker shows the cumulative number of containers for which the activity is completed corresponding to the date and activity. The results of the first voyage processed with the tracker are shown in Table 3.
| Table 3: Cumulative Containers/Ship Sailing B/L Progress Tracker | |||||||||||||
| Date | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | |
| Activity | Event | ||||||||||||
| Booking slip received | 1 | 14 | 37 | 51 | 77 | 104 | 104 | 104 | 104 | 104 | 104 | 104 | 104 |
| Delivery order issued | 2 | 14 | 37 | 51 | 77 | 104 | 104 | 104 | 104 | 104 | 104 | 104 | 104 |
| Daily pick-up report for empty container issued | 3 | 4 | 21 | 39 | 62 | 84 | 92 | 98 | 98 | 98 | 98 | 98 | 98 |
| Container-in-yard report received | 4 | 0 | 0 | 0 | 17 | 31 | 49 | 61 | 64 | 65 | 65 | 65 | 65 |
| Shipping bill received | 5 | 0 | 0 | 0 | 0 | 0 | 3 | 5 | 32 | 35 | 60 | 60 | 60 |
| Container load plan received | 6 | 0 | 0 | 0 | 0 | 0 | 3 | 5 | 32 | 35 | 60 | 60 | 60 |
| B/L draft version 1 generated | 7 | 0 | 0 | 0 | 2 | 11 | 16 | 16 | 21 | 47 | 56 | 56 | 56 |
| B/L draft version 1 received from customer | 8 | 0 | 0 | 0 | 0 | 3 | 10 | 10 | 19 | 32 | 54 | 56 | 56 |
| FP received from customer | 9 | 0 | 0 | 0 | 0 | 0 | 1 | 2 | 7 | 13 | 35 | 54 | 56 |
| Confirmed FP received from customer | 10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 9 | 23 | 51 | 54 |
| Updated B/L final document for printing | 11 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 21 | 49 | 52 |
| Number of B/Ls released | 12 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 8 | 11 | 49 |
The observed vessel had 104 containers and sailed on September 23rd. The cumulative number of B/Ls released were as follows:
Up to sailing date s = 11 (11 percent)
Up to s+1 = 21 (21 percent)
Up to s+2 = 49 (47 percent)
The remaining 55 B/Ls were released up to s+10 (i.e., 10 days after sailing).
By making work flow as quickly as possible and minimizing the waiting time before each stage for each container the delivery of B/Ls would be expedited. The team was trained to “keep their in-trays clean” – to keep work-in-process wait time to a minimum.
Step 5: Implement the Ideas
It was time to check the results of this work. A dramatic improvement was achieved as shown in Table 4.
| Table 4: Percentage of Bills of Lading Released Relative to Sail Date | ||||
| s | s+1 | s+2 | s+3 | |
| Pre-project | 11 | 21 | 47 | NA |
| Voyage 1 | 11 | 81 | 84 | 93 |
| Voyage 2 | 33 | 60 | 100 | NA |
The percentage of B/Ls released increased by day s+2 from 47 percent to 84 percent and then 100 percent in the first two voyages respectively.
Part 2 of this case study looks at making more improvements using just-in-time (JIT) principles.
