Difference between revisions of "ANLY482 AY2017-18T2 Group03 Project Overview"
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1. Create a Operations Dashboard to visualize the following KPIs | 1. Create a Operations Dashboard to visualize the following KPIs | ||
| − | Inbound / Outbound Volume over time chart | + | *Inbound / Outbound Volume over time chart |
| − | The purpose of this chart is to visualize the operations performance at various time slices so as to allow operations to have a clear view of the inventory movement patters for the various SKUs | + | **The purpose of this chart is to visualize the operations performance at various time slices so as to allow operations to have a clear view of the inventory movement patters for the various SKUs |
| − | X-axis: Time unit (day, week, month, quarter, year) | + | **X-axis: Time unit (day, week, month, quarter, year) |
| − | Y-axis: No. of units of product | + | **Y-axis: No. of units of product |
| − | Lines: Each line would symbolize the trend for a different SKU. | + | **Lines: Each line would symbolize the trend for a different SKU. |
| − | Product Ranking Chart | + | |
| − | The purpose of this chart is to find out which are the best-selling items and which are the least popular items. | + | *Product Ranking Chart |
| − | Treemap view of the products filtered by month / year | + | **The purpose of this chart is to find out which are the best-selling items and which are the least popular items. |
| − | Product Seasonality Chart | + | **Treemap view of the products filtered by month / year |
| − | The purpose of this chart is to see the seasonality factors of the different products. | + | |
| − | X-axis: Month of the year | + | *Product Seasonality Chart |
| − | Y-axis: Number of pallets | + | **The purpose of this chart is to see the seasonality factors of the different products. |
| − | + | **X-axis: Month of the year | |
| − | + | **Y-axis: Number of pallets | |
| − | + | ||
| − | + | 2. Conduct Associative Rule learning so as to attempt to see if there are affinities within the products within the warehouse so that inventory can be better organized within the warehouse. | |
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=<div style="border-style: solid; border-width:0; background: #149de7; padding: 7px; font-weight: bold; text-align:left; line-height: wrap_content; text-indent: 20px; font-size:20px; font-family:Trebuchet MS;border-bottom:5px solid white; border-top:5px solid black"><font color= #FFFFFF>Provided Data</font></div>= | =<div style="border-style: solid; border-width:0; background: #149de7; padding: 7px; font-weight: bold; text-align:left; line-height: wrap_content; text-indent: 20px; font-size:20px; font-family:Trebuchet MS;border-bottom:5px solid white; border-top:5px solid black"><font color= #FFFFFF>Provided Data</font></div>= | ||
Revision as of 17:31, 2 February 2018
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Contents
Motivation
The company has stayed ahead of their competition by embracing technology in the early days and now, they are starting to dabble into analytics in order to help make use of the large amount of data that they have generated throughout the course of their business. Currently, these information is being stored in their proprietary Warehouse Management System (WMS) which captures transaction information whenever goods are moving in, out or within the warehouse.
The amount of information being managed by the system is massive and it is very complicated, thus managers have to spend time to use pivot tables in excel to better visualize the information being generated in order to get a better view of how the current operations is being run. This uses up valuable time which could have been used for other more important operational matters.
One important information that is very useful to a warehouse manager is an ABC analysis which is an inventory categorization technique. The purpose of this analysis is to classify the inventory into 3 categories. One possible way of doing categorization is shown below.
- ‘A’ items – 20% of the items accounts for 70% of the annual consumption value of the items.
- ‘B’ items - 30% of the items accounts for 25% of the annual consumption value of the items.
- ‘C’ items - 50% of the items accounts for 5% of the annual consumption value of the items.
Not only that, in order to provide even more better insight for their customers, they would also like to be able to have a better view of the seasonality patterns of the products, as well as an affinity analysis of the products to further improve the way the products can be organized in the warehouse to increase the efficiency of the warehouse operations.
Objective and Goals
The main objectives of the project would be to do the following:
1. Create a Operations Dashboard to visualize the following KPIs
- Inbound / Outbound Volume over time chart
- The purpose of this chart is to visualize the operations performance at various time slices so as to allow operations to have a clear view of the inventory movement patters for the various SKUs
- X-axis: Time unit (day, week, month, quarter, year)
- Y-axis: No. of units of product
- Lines: Each line would symbolize the trend for a different SKU.
- Product Ranking Chart
- The purpose of this chart is to find out which are the best-selling items and which are the least popular items.
- Treemap view of the products filtered by month / year
- Product Seasonality Chart
- The purpose of this chart is to see the seasonality factors of the different products.
- X-axis: Month of the year
- Y-axis: Number of pallets
2. Conduct Associative Rule learning so as to attempt to see if there are affinities within the products within the warehouse so that inventory can be better organized within the warehouse.
