ANLY482 AY2016-17 T2 Group21 : Finals
| Exploratory | Mid-Term | Finals |
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Survival Analysis
Due to the censored demand identified during our exploratory analysis, using survival analysis provides a way for us to handle such hidden values. Survival analysis will be performed using the JMP built-in survival functions. We will be using two features:
1. Basic survival function
- Applies Kaplan-Meier estimator to account for censored values
2. (Cox) proportional hazards fit
- Fits a linear model between predictors (explanatory variables) and the hazard function.
- Parameters estimates show how predictors affect the hazard function.
Product Stock-Out Time
To account for non-stockout products, we perform our survival analysis of product stock-out-time with the following definition:
- Subject: A product identified by name and size
- Time to event: Time in days for a product to stockout
- Censor: 0 if product stockout, 1 otherwise
Figure 8 Here
The above analysis shows a more accurate median time of stockout of 18 days, which is longer than our sponsor’s target of achieving a stockout period of 7 days. From the survival plot, we can also see that 68% of all products still remains on the shelf after 7 days after launch. It is, therefore, useful to understand which products groups have a longer stockout periods. We further add groupings by category to our analysis.
Inventory Performance Grid
A goal of our project is to make it accessible for our sponsor to utilize SA in their decision making process. To achieve this, a clear data representation is needed to help our sponsor understand their product demand. Our group came up with a visual decision tool called the Inventory Perofrmance Grid which relies on both Sell-Through Rate and Average Rate of Sales on a product to produce actionable insights for our sponsor.
We created an example based on 4 different products which we sold in a 2-days, 7-days, and 30-days time window.
With the above metrics for each products, we can now visualise each product’s inventory performance on an inventory performance grid.
The figures above depicts an inventory performance grid of the products A, B, C, and D in a 2-day, 7-days, and 30-days time window respectively. Sell-through rate and average rate of sales combine to produce an inventory performance grid that helps us understand different aspects of merchandising. Sell-through rate depicts stock sufficiency while the average rate of sales is a measure of the popularity of the product. With that, each product can be classified into different quadrants, with each quadrant representing different business meaning.
