CAPACITY PLANNING TO INCREASE MECHANIC AVAILABILITY IN AFTER-SALES SERVICE AT PT. ELANG
After-sales service is critical in selling products such as heavy equipment, which require maintenance from mechanics who understand the product. PT. Elang, one of Indonesia's heavy equipment distributors, provides service support after purchase. The company currently struggles to manage the...
Saved in:
Main Author: | |
---|---|
Format: | Theses |
Language: | Indonesia |
Subjects: | |
Online Access: | https://digilib.itb.ac.id/gdl/view/81656 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | After-sales service is critical in selling products such as heavy equipment, which
require maintenance from mechanics who understand the product. PT. Elang, one
of Indonesia's heavy equipment distributors, provides service support after
purchase. The company currently struggles to manage the mechanics for repair
requests from customers. Most of the time, the mechanics are already dispatched
for regular maintenance, so repair requests are challenging to respond quickly to
because of the unpredictable nature of the case. On the other hand, the unit cannot
be used while waiting, hampering the customers’ operation. Complaints and bad
reviews on after-sales service lead to lost customers and significant revenue loss.
This operational issue is related to capacity. Therefore, this study is limited and
focused on capacity planning for mechanics in Indonesia's service support division
of a heavy equipment distributor company.
This study aims to identify the gap between current and ideal capacity, look for the
root causes through the business process review to find where improvement is
needed and propose a suitable capacity planning solution for the company. Both
qualitative and quantitative methods were used in this study. The qualitative method
was through interviews and discussions with the head of service support and the
branch operation head to understand the situation and process. The business process
related to the issue was then analysed with Business Process Modeling and Notation
(BPMN) and the root cause was found with the Current Reality Tree (CRT) method.
The quantitative method was through the sales and capacity data collected from the
company. This data is analysed to determine capacity utilisation. The best
alternative capacity solution was selected using the Analytic Hierarchy Process
(AHP) using XLSTAT and compared to manual Excel calculation. This study
showed that some branches have insufficient capacity to fulfil the after-sales service
demands. Those branches must utilise the capacity beyond what is available,
leading to a negative capacity cushion. The issue happened because of two root
causes: an inadequate number of mechanics and an insufficient integrated system
to support the information flow through related divisions. Three alternative
solutions were proposed based on the root causes. Alternative solutions include
providing service points, outsourcing mechanics, and implementing a cloud ERP
system. The criteria used to evaluate the solutions are cost, effectiveness,
sustainability, ease of implementation, and scalability.
After the AHP calculation and analysis confirmed the result with the head of service
support, it concluded that the solution that could be implemented in the company is
providing service points with the priorities, resulting in 71.03%. The next
alternative is to implement the cloud ERP system, with a result of 15.04% and
outsource mechanics with 13.93%. With this solution, the company considered a
long-term approach with more sustainability and scalability criteria than ease of
implementation. The criteria priorities are cost, effectiveness, sustainability,
scalability, and ease of implementation, with consecutive results of 47.87%, 24.3%,
12.64%, 6.6%, and 8.59%. This study also proposes an implementation plan for
providing service points. This study contributes to solving the problem of mechanic
unavailability and increasing response time in Indonesia's heavy equipment
distributor company. |
---|