Inventory Management – Allocation Analytics:
Proof of Concept
Leading National
Retailer
Background and Context
• Problem Statement and Scope
• Proof of Concept Activities
Scope of POC
Like
Product
Demand
Model
Buy & Assortment
Buy
Plannin
g
SellAllocate. Replenish
Lost
Sales
Analysi
s
Store
g...
Impact of Event Sales on In-Season Sales
0
20
40
60
80
100
120
7/2/2005
7/9/2005
7/16/2005
7/23/2005
7/30/2005
8/6/2005
8/...
Current Approach Forecast Sales Patterns – Data Analysis
Price has a significant relationship to,
and inverse effect on sa...
Impact of Price on In-Season Sales
FallWinter
Pants
Price has a significant relationship to, and inverse effect on sales p...
Forecast Results (Forecast Vs Actual)FallWinter
Pants Knit Top
Recommended Allocation Process and Solution Components
Initial Allocation
based on Volume
and Trend
- Allocate sufficient ...
Store Level ForecastsFallWinter
Pants
0
20
40
60
80
100
120
7/1/2006
7/8/2006
7/15/2006
7/22/2006
7/29/2006
8/5/2006
8/12/...
Executive Summary
Business Objective Improve sales and profit through
application of data analysis driven
allocation proce...
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Inventory management – sales forecasting analytics

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No Sales, No Business and No company!! Hence, regardless of an Industry, Inventory Management is important Supply Chain Management. It may be Hospital, Retail Store or what not, all need to sell on pull basis - not push.

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Inventory management – sales forecasting analytics

  1. 1. Inventory Management – Allocation Analytics: Proof of Concept Leading National Retailer
  2. 2. Background and Context • Problem Statement and Scope • Proof of Concept Activities
  3. 3. Scope of POC Like Product Demand Model Buy & Assortment Buy Plannin g SellAllocate. Replenish Lost Sales Analysi s Store groupin g Allocate based on Actual sales Allocate based on event Initial Set & Fixture Analysis Monte Carlo Simulati on The Scope of Proof Of Concept restricted to the allocation, replenishment process and sell only. IN SCOPE
  4. 4. Impact of Event Sales on In-Season Sales 0 20 40 60 80 100 120 7/2/2005 7/9/2005 7/16/2005 7/23/2005 7/30/2005 8/6/2005 8/13/2005 8/20/2005 8/27/2005 9/3/2005 9/10/2005 9/17/2005 9/24/2005 10/1/2005 10/8/2005 10/15/2005 10/22/2005 0 1000 2000 3000 4000 5000 6000 EVT_SELL_PCT TOT_WK_REG_EVT_SELL 0 20 40 60 80 100 120 7/2/2005 7/9/2005 7/16/2005 7/23/2005 7/30/2005 8/6/2005 8/13/2005 8/20/2005 8/27/2005 9/3/2005 9/10/2005 9/17/2005 9/24/2005 10/1/2005 10/8/2005 10/15/2005 10/22/2005 10/29/2005 11/5/2005 11/12/2005 11/19/2005 11/26/2005 12/3/2005 12/10/2005 12/17/2005 12/24/2005 12/31/2005 1/7/2006 1/14/2006 1/21/2006 1/28/2006 0 5000 10000 15000 20000 25000 30000 35000 EVT_SELL_PCT TOT_WK_REG_EVT_SELL FallWinter Pants
  5. 5. Current Approach Forecast Sales Patterns – Data Analysis Price has a significant relationship to, and inverse effect on sales patterns. Event and Price Relationship Because event calendar was not available , event sales were analyzed based on the price data Week into the season is a direct variable in the sale pattern.
  6. 6. Impact of Price on In-Season Sales FallWinter Pants Price has a significant relationship to, and inverse effect on sales patterns.
  7. 7. Forecast Results (Forecast Vs Actual)FallWinter Pants Knit Top
  8. 8. Recommended Allocation Process and Solution Components Initial Allocation based on Volume and Trend - Allocate sufficient qty for the first four weeks -Allocate sufficiently for high velocity low volume stores as well as high velocity high volume stores Buy Plan, Event Marketing Calendar Re-forecast based on actual data and historical trends. - Identify a blend of actual data from the current season and historic data to arrive at a refined volume forecast at store Optimized Initial Allocation - Allocate stock to cover the initial sales curves Inventory Positions Ongoing Allocation Fixture Constraints Fixture Constrain ts Optima l Invento ry cover Solution Component 1 Solution Component 2 Solution Component 3 Allocation Simulation Model Multinomial Logistic Regression Exponential smoothing technique
  9. 9. Store Level ForecastsFallWinter Pants 0 20 40 60 80 100 120 7/1/2006 7/8/2006 7/15/2006 7/22/2006 7/29/2006 8/5/2006 8/12/2006 8/19/2006 8/26/2006 9/2/2006 9/9/2006 9/16/2006 9/23/2006 9/30/2006 10/7/2006 10/14/2006 10/21/2006 cumul_share cumul_pred_share
  10. 10. Executive Summary Business Objective Improve sales and profit through application of data analysis driven allocation process Top Findings in Current State - Lost Sales opportunities - High Initial Allocation - Imbalance in inventory cover across stores - Sub-optimal Response of Allocation systems to in-season sales - Data unavailability and Data Quality for extensive granular analysis Recommendation Short Term: Sales Pattern based allocation Medium Term: Store Clustering & Alternate Size Ratios Long Term: End-to-End Allocation Solution
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