WAC Apollo Hospitals - Jahja

October 6, 2017 | Author: Jahja Aja | Category: Forecasting, Patient, Hospital, Foods, Service Industries
Share Embed Donate


Short Description

WAC Apollo Hospitals - Jahja...

Description

Universitas Pelita Harapan Executive Education Center Jakarta

Case Study on Quantitative Analysis Forecasting Demand For Food At Apollo Hospitals

Submitted by: Jahja EMBA Class Batch 3 February 11, 2015

BACKGROUND Apollo Hospitals is established in 1983 in Chennai. As of 2014, the Apollo Hospitals Group was an integrated healthcare organization with owned and managed hospitals, diagnostic clinics, dispensing pharmacies, and consultancy services. Apollo Hospitals now grow to over 8.300 beds across 51 hospitals. The Apollo Hospitals Bagalore at Bannerghatta Road was a tertiary hospital with 250 bed and have an average of 230 patients treated daily. This hospital has some challenge in their operational process especially in estimation of required quantity for food and beverage items. SITUATIONAL ANALYSIS On daily basis, the F&B Division had been preparing food items that were more than 20 % in excess of the quantity that was estimated based on previous experience. There are 45 plate/servings of rice were left over after dinner service one day; the consumption of rice for dinner that same day was 75 plates/portions. Food was prepared for around 230 in-patients daily for breakfast, lunch and dinner. And they ordered food from the menu given to them every day, for breakfast they were taken the food order the day before and for lunch and dinner were taken in the morning. The F&B Staff also had to account for the F&B requirements of out-patients, caregivers/attendants and visitor of the in-patients and the hospital staff. The final quantity of food was decided and prepared based on the orders from all in-patients and based on the experience of the F&B Staff (especially the Head Chef) to estimate. Normally, 10% excess food was prepared to avoid any shortage. PROBLEM ANALYSIS There is some problem that connected one to another in Apollo Hospital. Apollo Hospital forecasting their demand for food is only based the daily menu data from in-patient and based on experience of the F&B Staff. They don’t have a system that could accurately estimate the required quantity of food and beverages. And because there is no system to estimate so there were F&B wastage and impact to the increment of procurement cost for the raw material. DECISION ANALYSIS To solve the problem for F&B wastage, some area for improvement to be focussed are the way of forecasting the demand for food and estimate the number of food should be served. Historical data for food serving and its correlation with number of in-patient can be used for forecasting the demand of food and minimize the wastage. Some action can be taken to solve this problem are :  To minimize possibility wastage from in-patients, change the process of ordering food from inpatients. Set menu for in-patients should came up from Dietician based on the medical condition and consultation with the Doctor. This request by Dietician should be monitor daily and see the correlation between number of in-patients, type of food and wastage occur so it can be forecast for future.  To minimize possibility wastage from canteen for hospital staff, create food coupon and this coupon shold be given to canteen at the beginnng of shift time so F&B only prepare food based on the coupon received. To forecast the demand at canteen, just analyze how many coupon reimburse per day at several interval time so we can predict how many portion should prepare each day.  To minimize possibility wastage from cafetaria for visitor/attendant/caregiver, the food prepared is a standard menu and divide into food package in various size. It also can reduce the leftover food because people will choose the size of serving based on their capability to eat.  Monitor all this activities as the basic database for forecasting the the demand of food.  Manage the raw material supplies and also serving methods, F&B should decrease excess food from pre-consumption process when the food is prepared. No need to cook extra 10% food and change it into by order.

View more...

Comments

Copyright ©2017 KUPDF Inc.
SUPPORT KUPDF