Difference between revisions of "ZAN Project Overview"
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[[ZAN_Team|<font face ="Lucida Grande" color="#FFFFFF"><strong>ABOUT US </strong></font>]] | [[ZAN_Team|<font face ="Lucida Grande" color="#FFFFFF"><strong>ABOUT US </strong></font>]] | ||
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| + | <!--Content Start--> | ||
| + | <div align="left"> | ||
| + | <div style="background: #F5FFFA; padding: 12px; font-family: Arimo; font-size: 18px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #2E8B57 solid 32px;"><font color="##4682B4">Project Description</font></div> | ||
| + | <br/> | ||
| + | Hospital X is a pioneer tertiary hospital that provides a comprehensive range of medical and rehabilitative services for children, adolescents, adults and the elderly.This project plans to make use of the dataset provided by our project sponsor to analyse if there is any relationship between the variables and to create a predictive model for likelihood of a patient in defaulting appointments. | ||
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| + | <br/> | ||
| + | |||
| + | <div align="left"> | ||
| + | <div style="background: #F5FFFA; padding: 12px; font-family: Arimo; font-size: 18px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #2E8B57 solid 32px;"><font color="##4682B4">Motivation</font></div> | ||
| + | <br/> | ||
| + | Our project sponsor is a medical professional working for Hospital Y. He specialises in tending to younger patients from the age of 18 years old and below. Patients are usually referred to Hospital X by other medical institutions or they booked an appointment directly. Currently, Hospital X experiences high defaulted or missed appointments rate of about 21% for first visits and 19% for review visits. Defaulted appointments lead to longer appointment lead times, lower operation productivity and overall lower quality of care. Freeing up the time wasted by patients’ no-show would improve utilisation of slots, and even reduce appointment wait time for other patients. By sponsoring this project, our sponsor also hopes to tap into the under-utilised administrative data that is collected by the hospital daily. | ||
| + | <br/> | ||
| + | |||
| + | <div align="left"> | ||
| + | <div style="background: #F5FFFA; padding: 12px; font-family: Arimo; font-size: 18px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #2E8B57 solid 32px;"><font color="##4682B4">Objective & Goals</font></div> | ||
| + | <br/> | ||
| + | The main objective of the project would be to develop the following: | ||
| + | # Creation of an application to sort SKUs by A, B and C categories | ||
| + | #* To provide employees with a high level view of the flow and demand changes for different SKUs. This allows higher level management employees to make important decisions based on it (e.g. eliminate SKUs which are extremely slow moving as they are taking up warehouse space which can be otherwise optimized.) | ||
| + | # Dashboard for quick visualization of inbound and outbound rate for different SKUs | ||
| + | #* Inbound rate: X-axis and y-axis to be date against number of inbound in pieces, carton and pallets per day. | ||
| + | #* Outbound rate: X-axis and y-axis to be date against number of inbound in pieces per day. | ||
| + | #* This reduces both the time and manpower needed for the manual analyzing of data as it provides a general trend and flow of SKUs. For instance, when an employee notices a particular product’s supply running low he will be able to call for a refill immediately. | ||
| + | # Warehouse Utilization Tool | ||
| + | #* To help employees understand fill and flow rate of the warehouse based on historical data. | ||
| + | #* To determine pick rate of warehouse locations and identify most used and least used locations. | ||
| + | <br/> | ||
| + | |||
| + | <div align="left"> | ||
| + | <div style="background: #F5FFFA; padding: 12px; font-family: Arimo; font-size: 18px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #2E8B57 solid 32px;"><font color="##4682B4">Provided Data</font></div> | ||
| + | <br/> | ||
| + | The data will be obtained from the in-house Warehouse Management System (WMS). The company updates the database whenever goods are being received (inbound) and released (outbound). For the purpose of the project’s analysis, the team will be given one year worth of data for each of the companies' SKUs. The size of the data is expected to be approximately 4.2 million rows of data (4 excel sheets) for each company. For each of the companies, there will be 3 sets of data provided, namely: | ||
| + | # Product master sheet | ||
| + | # Product inbound report | ||
| + | # Product outbound report | ||
| + | <br/> | ||
| + | |||
| + | <div align="left"> | ||
| + | <div style="background: #F5FFFA; padding: 12px; font-family: Arimo; font-size: 18px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #2E8B57 solid 32px;"><font color="##4682B4">Methodology</font></div> | ||
| + | <br/> | ||
| + | The data will be obtained from the in-house Warehouse Management System (WMS). The company updates the database whenever goods are being received (inbound) and released (outbound). For the purpose of the project’s analysis, the team will be given one year worth of data for each of the companies' SKUs. The size of the data is expected to be approximately 4.2 million rows of data (4 excel sheets) for each company. For each of the companies, there will be 3 sets of data provided, namely: | ||
| + | # Product master sheet | ||
| + | # Product inbound report | ||
| + | # Product outbound report | ||
| + | <br/> | ||
| + | |||
| + | <div align="left"> | ||
| + | <div style="background: #F5FFFA; padding: 12px; font-family: Arimo; font-size: 18px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #2E8B57 solid 32px;"><font color="##4682B4">Project Scope</font></div> | ||
| + | <br/> | ||
| + | The data will be obtained from the in-house Warehouse Management System (WMS). The company updates the database whenever goods are being received (inbound) and released (outbound). For the purpose of the project’s analysis, the team will be given one year worth of data for each of the companies' SKUs. The size of the data is expected to be approximately 4.2 million rows of data (4 excel sheets) for each company. For each of the companies, there will be 3 sets of data provided, namely: | ||
| + | # Product master sheet | ||
| + | # Product inbound report | ||
| + | # Product outbound report | ||
| + | <br/> | ||
| + | |||
| + | <!--Content End--> | ||
Revision as of 10:27, 31 December 2016
Hospital X is a pioneer tertiary hospital that provides a comprehensive range of medical and rehabilitative services for children, adolescents, adults and the elderly.This project plans to make use of the dataset provided by our project sponsor to analyse if there is any relationship between the variables and to create a predictive model for likelihood of a patient in defaulting appointments.
Our project sponsor is a medical professional working for Hospital Y. He specialises in tending to younger patients from the age of 18 years old and below. Patients are usually referred to Hospital X by other medical institutions or they booked an appointment directly. Currently, Hospital X experiences high defaulted or missed appointments rate of about 21% for first visits and 19% for review visits. Defaulted appointments lead to longer appointment lead times, lower operation productivity and overall lower quality of care. Freeing up the time wasted by patients’ no-show would improve utilisation of slots, and even reduce appointment wait time for other patients. By sponsoring this project, our sponsor also hopes to tap into the under-utilised administrative data that is collected by the hospital daily.
The main objective of the project would be to develop the following:
- Creation of an application to sort SKUs by A, B and C categories
- To provide employees with a high level view of the flow and demand changes for different SKUs. This allows higher level management employees to make important decisions based on it (e.g. eliminate SKUs which are extremely slow moving as they are taking up warehouse space which can be otherwise optimized.)
- Dashboard for quick visualization of inbound and outbound rate for different SKUs
- Inbound rate: X-axis and y-axis to be date against number of inbound in pieces, carton and pallets per day.
- Outbound rate: X-axis and y-axis to be date against number of inbound in pieces per day.
- This reduces both the time and manpower needed for the manual analyzing of data as it provides a general trend and flow of SKUs. For instance, when an employee notices a particular product’s supply running low he will be able to call for a refill immediately.
- Warehouse Utilization Tool
- To help employees understand fill and flow rate of the warehouse based on historical data.
- To determine pick rate of warehouse locations and identify most used and least used locations.
The data will be obtained from the in-house Warehouse Management System (WMS). The company updates the database whenever goods are being received (inbound) and released (outbound). For the purpose of the project’s analysis, the team will be given one year worth of data for each of the companies' SKUs. The size of the data is expected to be approximately 4.2 million rows of data (4 excel sheets) for each company. For each of the companies, there will be 3 sets of data provided, namely:
- Product master sheet
- Product inbound report
- Product outbound report
The data will be obtained from the in-house Warehouse Management System (WMS). The company updates the database whenever goods are being received (inbound) and released (outbound). For the purpose of the project’s analysis, the team will be given one year worth of data for each of the companies' SKUs. The size of the data is expected to be approximately 4.2 million rows of data (4 excel sheets) for each company. For each of the companies, there will be 3 sets of data provided, namely:
- Product master sheet
- Product inbound report
- Product outbound report
The data will be obtained from the in-house Warehouse Management System (WMS). The company updates the database whenever goods are being received (inbound) and released (outbound). For the purpose of the project’s analysis, the team will be given one year worth of data for each of the companies' SKUs. The size of the data is expected to be approximately 4.2 million rows of data (4 excel sheets) for each company. For each of the companies, there will be 3 sets of data provided, namely:
- Product master sheet
- Product inbound report
- Product outbound report
