The document discusses optimizing supply chain order processes using customer buying behavior data to enhance order fulfillment and reduce costs. It presents a solution that manages product mix based on popular configurations and improves forecasting to minimize inventory waste. Additionally, it emphasizes the benefits of leveraging analytics for better decision-making and customer experience.

2. Order
ORDERS
Entry
To Supply chain CUSTOMERS
- The orders data contains intelligence
- True “Voice of Customer’
- Based on buying behavior
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3. Higher Demand Response Easy to do Business With
at Lower Cost
- Improve Order Fulfillment - Faster quote-to-order
- Lead time compression - Recommend configuration
- Reduce Inventory - Increase Sales Productivity
- Reduce Obsolescence - Self-serve with best configuration
- Reduce expedite freight recommendation
SKU
Intelligence
Order
ORDERS Entry
CUSTOMERS
To Supply chain
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4. • Challenge
– Manufacturer offers very large number of configuraIons
– High mix volaIlity in demand causes poor mix forecast
– Very high parts inventory cost, High excess and obsolete inventory
– Reduced profits
• Solu,on – Manage product mix based on buying behavior
– Package product based on popular choices
– Offer quick ships with popular bundles  improve lead Ime
– Guide customers to popular choices  higher margins
– Improve forecast to reduce inventory waste  reduce cost
Case study presented with sample data from ACME Computer Corp.
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5. 1st Order Cluster = Percentage of orders with a parIcular choice.
E.g. DVD player. (Also called 1st order take rate)
E.g.
• 88% of the orders have 10/100
Ethernet networking choice
• The average margin on units
with this choice is $112.70
• Av. order to delivery is 3 days
Screen shot from EmcienMix
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6. 2nd Order Cluster = Percentage of orders with 2 choices choice.
E.g. DVD player + Sound card. (Also called 2nd order take rate)
E.g.
• 88% of the order have 10/100 Ethernet networking choice + 1yr warranty
• The average margin on units with this choice is $112.70
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7. Cluster = Highly prevalent combined group of features/ choices
indicaIng customer buying behavior
Screen shot from EmcienMix
E.g. ‐ 66% of the orders have these 12 choices
• Highest popularity of choices
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8. ‐ Recommend
user acIon based
on alerts
‐ User alerts ‐ Tie into business
‐ Push AnalyIcs funcIons
‐ Data model
based on context ‐ (Like RSS feeds)
‐ Creates
Query & Reports intelligence
Business Analytics Proactive Recommendations
Reporting Analytics (Analytics + Business
Applications)
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9. Millions of choice combinations!!!
Is Video card and Model GX most
popular?
Is GXC Networking and Video card
most popular?
Is soipak op sys. And GXC
Networking most popular?
Is 2‐yr warranty and soipak op
sys. most popular?
Online sales, 2‐yr warranty with gaming
machines popular?
2x2.3 CPU with online sales, 2‐yr warranty
with SMB machines popular?
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10. Alerts YOU
on the TOP SELLING Choices
and TRENDS
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11. • Challenges With Old Method
– NO Time For endless querying, No extra staff for endless querying
– Too much human interpretaIon leading to error
• Value of New Method
– Intelligence pushed out to users, Fast and Imely decisions
– Connect to OperaIonal Decision making
– Sustainable value
Gaming machines with 2.3CPU, XC‐video,
Blue tooth and 160GB are selling in NY
Stock 2,000 units in New York Store
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12. Emcien delivers business applications that leverage PUSH Analytics
Forecasting - Improve Asset Utilization
- What are the part kits?
- What is the parts mix for inventory
PUSH
AnalyIcs with SKU
Intelligence Optimize Product Mix
- What SKU’s should we offer?
Alerts you on what - Improve product availability
is selling
Guided Selling/ Spec Builder
- Complete customer choice/spec
- Recommend product at point of sale
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13. • As Easy as 1, 2, 3…
• Please call us for a free trial
– Quickly learn how your customers are buying
– Value
• Improve your product offering
• Improve customer buying experience
• Reduce supply chain cost
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14. www.emcien.com
Sales@emcien.com