Title

LRBT supply chain optimization

Degree

Master of Business Administration

Faculty / School

Faculty of Business Administration (FBA)

Project Type

MBA Research Project

Abstract / Summary

LRBT is a non-profit organization providing free eye care to the poor. They have two tertiary hospitals, 17 secondary and 56 primary centers all across Pakistan. The objective of this project was to understand and examine the existing supply chain system of LRBT, identify gaps and improvement areas. The scope of this project is limited to Korangi (Tertiary) Hospital and North Karachi (Secondary) Hospital. To make the LRBT supply chain system more efficient the focus of the project was on four main areas which are forecasting, inventory, procurement process and pharmacy management. The tools used for initial analysis include ABC Analyses which ranked the products based on quantity, value and numbers of transaction. Another tool which was used called Pareto Analysis which categories the medicines on the bases of value which revealed that out of 533 items there were only 53 items that made 80% of the total value. Out of these 53 items 20 items contribute to 50% of the value and for that reason the focus of the report is on top of the line items. The forecasting at LRBT is done with the help of a self-devised formula which assumes a lot of subjectivity in future prediction therefore, different mathematical forecasting model has been considered. Three years of transactional data has been collected from the year 2015 to 2017, the data was limited to Korangi (tertiary) Hospital and North Karachi (Secondary) Hospital only. Before applying any model normality distribution check was conducted on all the top products discovered by Pareto Analysis. Next a suitable forecasting model was selected for LRBT which could treat the seasonal data with trend. For this purpose different qualitative and quantitative forecasting models were studied and tested and finally with that regard exponential smoothing with trend and seasonality is proposed. It is also called winter's model and it can be tweaked with respect to different products having various trend and seasonal cycles. LRBT's approach towards inventory management is fairly simple and before ordering an item it subtracts 'stock in hand' and the 'pending orders' to get the 'quantity to be ordered, LRBT tries to maintain safety stocks of 2 to 2.5 months at every location. A fixed time period model has been suggested which incorporates safety stocks based on desired service level and the variability in demand. A complete analysis of procurement to pay (P2P) cycle of LRBT was conducted and a deep understanding is developed. Upon studying the whole P2P Cycle it was observed that it takes 10 days for PR to convert into PO. Some suggestions are given in report that will reduce this time by 20% approximately. LRBT is doing a good job and it can get even better if some performance metrics are introduced, therefore some Key Performance Indicators (KPls) are suggested which will enable to track performance at glance and will make the progress more measurable.

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