Samsung SDS PH And People Plus Staffing Solutions, Inc.: Towards a Key Performance Indicator Model

Abstract

This study analyzes the partnership between Samsung SDS PH and People Plus Staffing Solutions, Inc. and how this affects their employee's deliverables or Key Performance Indicators (KPIs).

Through a descriptive research design, online questionnaires were used as the data collection technique. The questionnaire was based on the need to have a profile of the respondents and their perception of the extent of the KPI attainment versus the KPI planned. The statistical tool used to compute the computational aspects of the statistical analyses was the IBM SPSS Statistics application. Descriptive statistics, frequency statistics, one-sample t-test, Paired t-test, and ANOVA by factors were used to analyze the data

Using One-Sample Statistics, it is then found that all Logistics-oriented strategies set by Samsung SDS PH and People Plus, which are Forecasting, Planning, Product-clustering, and Performance Analysis, are significant and compelling. Through Paired-sample tests, the existing KPIs that enable the logistics-oriented strategies in the different areas of business are evaluated in their efficiencies in terms of On-time Good Receipt, Inventory Consistency, On time Good Issue, On time Delivery, Box Damage Warehouse Percentage, Safety, and Training and are found to be highly efficient.

On-time Good Receipt and Box Damage Warehouse Percentage have adverse effects on forecasting. Thus, immediate corrective action is necessary for this area. The only significant variable to Planning is On Time Good Receipt. The rest of the variables are still needed but do significantly affect planning. On the other hand, all the included variables for clustering of products (On time Good Receipt, Inventory Consistency, On time Good Issue, On time Delivery, Box Damage Warehouse Percentage, Safety, and Training) have no significant effects on the clustering of products when considered singly, that is when they are considered separately. They only become significant when taken as a whole; all these variables must be considered when clustering products. And like in the case of clustering, the included variables are not significant to Performance Analysis when considered singly.

The regression equations show many adverse effects of the logistics-oriented strategies on the KPIs. It is then highly recommended to turn the negatives into positives immediately. There can also be a comparative research study of the same business model (logistics-centered business partnered with 3PL) to gain insights into other logistics strategies and KPIs. Future researchers can also expand the research scope and do a qualitative study on the organizational KPIs which affect Supply Chain KPIs.