ANLY482 AY2017-18T2 Group13 Project Overview
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Underperformance such as delays in order fulfillment can be very costly to a logistics company. Hence, Logistics Company XYZ makes it a point to resolve these issues with utmost importance. In the context of this company, processing and packaging are done according to the order requirements during ground operations of the company in which delays can be a result of worker or non-worker related reasons.
Processes can also be inevitably skilled labor intensive. Due to this nature, a single error in the fulfillment of a job is very costly and critical to the whole ground operation process. The company, hence, has made an extra effort to ensure their employees are well-equipped to manage risks and complete the job in an accurate, timely manner. This is currently done by training of onsite workers - after being identified their roles, they are required to undergo a number of training courses to be certified as competent to their assigned orders.
In this project, we will be exploring the reasons for the delay on work order pertaining to the effectiveness of the ground workforce in the company. The project will be broken down into 2 phases which can be described as the following:
| Phases | Description |
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| Phase 1 | a. Identify core activities in the Singapore activities -
By identifying core activities, we will be able to target key areas that affect performance indicators.
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| Phases 2 | Using the insights and analysis generated from Phase 1, the team will be focusing on the following in Phase 2
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Due to the time and resource constraints of the project, the project scope will be narrowed down to analyze the Singapore office of Logistic company XYZ only. In addition, this project will be focusing on the competency of the workforce concentrated in 2 major business units critical to the company performance.
As mentioned above, order fulfillment is a key milestone in the company's business. However, the company experiences that the orders are sometimes delayed. There are different causes for delay and we divide those into three different categories based on the subject that actually caused delay: Worker, Order, Equipment. By looking at these different areas and analyzing data to gain critical insights, the company would be able to reduce disruptions to its ground operation and therefore to result in a successful fulfillment of the order to the client.
The main business question that this project aims to answer is what are the main causes of delays in order fulfillment due to worker. There are 120 different processes in which a delay could occur in. First, we identify the key processes that are core to the business, and identify the delays occurred in those key processes. The delays can vary with worker or non-worker related factors. In the case where the delays are caused by worker related factors, we analyze the training records of the employees, discover training trends within the company, for example, what training courses the workers lack in fulfilling the order requirement, what courses fail to equip the workers with required skill set, etc.
In this project, we hope to achieve the following objectives:
1. Study business model
2. Review existing models
3. Understand nature of data
4. Clean, explore, process data
5. Make discoveries/insights for Logistics Company XYZ to match employees to orders quickly
6. Propose recommendation to help the Human Resource department streamline employee skill sets that are relevant to the company
7. Create a centralized dashboard to reflect training status and key indexes for human development for optimized decision making within the human resource department
The main analysis is done with employee training data, from which our group discover training trends. This data is obtained from Terex, a software that contains employee training data and is managed by the company's Human Resources department.
The following is a list of data fields obtained from the sponsor company.
Currently, the team will attempt to study the data with the following methods.
| Stage | Description | Status |
|---|---|---|
| Data cleaning | To remove incomplete and invalid records | In Progress |
| Data exploration | To study frequencies, distribution, outliers, general patterns of datasets | In Progress |
