Question: Data Collection Plan for Late and Missed Deliveries Reduction Project Focusing on On-Time Delivery Percentage and Customer Complaint Rate

We will focus on two key performance indicators (KPIs) from the critical-to-quality (CTQ) tree that are most relevant to the L&M Deliveries Project. The two selected KPIs are:

1. On-Time Delivery Percentage

2. Customer Complaint Rate

These KPIs directly address the core issue of late and missed deliveries, which is the focus of the project. Below is the revised Data Collection Plan:

Data Collection Plan for L&M Deliveries Project

1. On-Time Delivery Percentage

• Performance Measure: Percentage of deliveries that arrive at the customer’s assembly plant by the scheduled delivery time.

• Operational Definition: The percentage is calculated by dividing the number of on-time deliveries by the total number of deliveries made in a given period.

• Data Source and Location: Delivery logs maintained by the Logistics Department and customer feedback reports.

• Sample Size: 200 deliveries (randomly selected from the past 3 months).

• Data Collector: Sarah Lee (Logistics Coordinator) and Michael Brown (Customer Service Representative).

• Data Collection Time/Date: Retrospective data collection for the past 3 months (March 1 – May 31).

• Data Collection Method: Review delivery logs and customer feedback reports for each selected delivery.

• Additional Data to be Collected:

  • Distance to customer location.

  • Traffic conditions during delivery.

  • Type of delivery vehicle used.

  • Customer location (urban, rural, etc.).

2. Customer Complaint Rate

• Performance Measure: Number of customer complaints related to deliveries per 100 deliveries.

• Operational Definition: The rate is calculated by dividing the number of complaints by the total number of deliveries made in a given period, then multiplying by 100.

• Data Source and Location: Customer service logs.

• Sample Size: All deliveries for the past 3 months.

• Data Collector: Michael Brown (Customer Service Representative).

• Data Collection Time/Date: Retrospective data collection for the past 3 months (March 1 – May 31).

• Data Collection Method: Review customer service logs for complaints related to late or missed deliveries.

• Additional Data to be Collected:

  • Weather conditions on the day of delivery.

  • Day of the week (weekday vs. weekend).

  • Number of pallets loaded.

  • Delivery distance.

Rationale for Selecting These Two KPIs:

1. On-Time Delivery Percentage: This KPI directly measures the core issue of late deliveries, which has been identified as a major problem affecting customer satisfaction and increasing costs. It aligns with the project goal of reducing late and missed deliveries.

2. Customer Complaint Rate: This KPI provides insight into customer dissatisfaction, which is a critical outcome of late and missed deliveries. It helps identify patterns or specific issues that may be causing complaints, allowing the team to address root causes.

Alignment with Instructions:

• The revised plan strictly follows the instructions by focusing on two KPIs from the CTQ tree.

• It documents how to measure these KPIs and collect data to understand the behavior of the current process.

• The plan is focused and concise, avoiding the inclusion of irrelevant KPIs.

Completeness:

• All required fields are filled out for each KPI:

  • Performance Measure

  • Operational Definition

  • Data Source and Location

  • Sample Size

  • Data Collector

  • Data Collection Time/Date

  • Data Collection Method

  • Additional Data to be Collected

Quality of Data Collection Plan:

• Operational Definitions: Clear and specific (e.g., On-Time Delivery Percentage is defined as the percentage of deliveries that arrive by the scheduled time).

• Data Sources: Appropriate and reliable (e.g., delivery logs, customer feedback reports, customer service logs).

• Sample Size: Reasonable and justified (e.g., 200 deliveries for On-Time Delivery Percentage, all deliveries for Customer Complaint Rate).

• Data Collection Methods: Appropriate and feasible (e.g., reviewing logs, analyzing customer feedback).

• Additional Data: Relevant and useful for root cause analysis (e.g., weather conditions, traffic conditions, delivery distance).

Relevance to L&M Deliveries Project:

• Both KPIs are highly relevant to the project’s goal of reducing late and missed deliveries.

• The additional data fields (e.g., weather conditions, traffic conditions) will help identify factors contributing to late deliveries and customer complaints.