Supply Chain Monitoring Ford Parts Supply

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Supply Chain Monitoring Ford Parts Supply
Logistics Case Study

• Roger Merkle
• Former Manager, North American Inventory Planning
  Department

STANFORD UNIVERSITY
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Ford Parts Supply Logistics (PSL)Business
Overview

• PSL operates a network consisting of
• 198K unique part numbers, over 1M SKUs
  (part/location)
• Wide mix of velocity, size, and value
• Vehicle base - 50 million vehicles on the road,
  35 model years
• Logistics network - 2,000 suppliers and 5,900
  authorized dealerships
• 18 HVCs, 3 HCCs, 1 LV/LC, 1 PRC, and 1 NPD
• Service Parts - US, Canada, Mexico and direct
  global export
• Complex logistics hubs, many containers,
  railcars, suppliers, packagers,
  sources/destinations, and paths
• High degree of magnitude and complexity

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Ford PSL Gearing Up for Change

• Acquired and centralizedrelevant data sources
• New systems for forecasting, inventory planning,
  DRP, electronic supplier communication and
  management
• Implemented SupplierPerformance Monitoring
• Reduced inventory bytwo thirds
• Record customer servicelevels
• Record turn rates

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Ford - Lack of Integrated Data
CUSTOMERFULFILLMENTVoice of the customer High
Service Levels Managed inventories Managed safety
stock Managed Costsexpediting, overtime
CUSTOMERFULFILLMENTVoice of the customer (High
inventories) (High safety stock) (High
Costs)expediting, overtime
DISTRIBUTION (Process-focused) Stable Fixed
Costs Low inventory Stable Part Mix Stable
Schedules Low Transportation Cost
DISTRIBUTION High customerservice Stable Fixed
Costs Low inventory Stable Part Mix Stable
Schedules Low Transportation Cost
PURCHASING Low purchase price (High
Inventory) (Stable schedules) (Long lead times)
PURCHASING Low purchase price Low
Inventory Flexible schedules Short lead times
SUPPLY Reliable Suppliers (High
inventories) (Long lead times) FlexibleTransporta
tion
SUPPLY Reliable Suppliers Low inventories Short
lead times FlexibleTransportation
SELL
Returns
DELIVER
SOURCE
(MAKE)
RETURN
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Fords Business Challenges
Analytical Data updated weekly, at best
High levels of processing time variability
Forecast error over supply chain process High
safety stock levels
Different cultures, processes and practices at
each node
Material expedited by teams of people at
headquarters
Highly Reactive - focus on backorders and blame
assessment
Increasing complex supply chain including
external partners and sources as well as non
traditional channels
Metrics not aligned - Data not common
Little ability to prioritize which actions are
critical to the business requirements
Voluminous reports - both paper and
electronic Labor-intensive to collect
Forecast accuracy and safety stock management
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Fords Requirements

• Culture Change
• Enable lean performance of existing systems
• No disruption to existing operations
• Prediction
• Support intelligent, proactive analysis vs.
  reactive
• Predict impact of current plan within lead time
  for resolution
• Prioritization
• Drive data to lowest actionable level in
  organization
• Identify high-impact opportunities
• Combine forecasted and actual demand levels
• Manage material velocity based upon any desired
  variable of prioritization
• Manage escalation

• Model-based analytics
• Adapt to any supply chain, any level of data
  availability
• Calculate metrics across white spaces where
  data availability is poor
• Combine varying sources of data
• Closed-loop issue management
• Support analysis of current operating business
  systems
• Manage variability in real time w/ feedback to
  analysts / source systems
• Manage approval process for recommended changes
• Comprehensive visibility
• Identify segments and processes with biggest
  problems
• Locate specific material throughout the supply
  chain
• Assess historical performance
• Support segmentation

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Build vs. Buy Decision

• Why not custom?
• Integrated solution (data acquisition, data
  model, analysis, prediction, ad-hoc OLAP
  capability, security, alerting, administration)
• Investment in complex algorithm development
• Speed of implementation (rapid ROI)
• Proven business value
• Teradata Supply Chain Intelligence (SCI) provides
  Standard KPIs, Reports Alerts
• SCI Based on Industry Standards Best Practices
• Technology Benefits
• Scalable database architecture
• Operational use of analytics
• Expandable and configurable data model and
  analytics
• Reduced Support Costs
• Multiple database repository support
• Developed Exception Management System(alerting,
  escalation, message broadcasting)
• Ford purchased Supply Chain Intelligence (SCI)
  from
• Teradata, a division of NCR

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SCI Creates Actionable Information

• Process the analytic results into actionable
  information in the format and level appropriate
  for the operation
• Provide analytic results for 4 distinct
  audiences
• Management - personalized for responsibility
• Performance metrics and trends for product,
  processes (including alerts themselves) and lines
  of business.
• Analysts
• Performance metrics identifying exceptions and
  outliers.
• Predictive performance and opportunities based
  upon statistics.
• Specific reports that address points of interest
• Recalls, missing, new product, new processes, new
  facilities etc.
• Operations
• Reactive alerts (standards) events that exceed
  standard
• Proactive alerts (critical) product to be
  re-prioritized to prevent an issue
• Partners
• Late shipment reports, trend analyses

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Solution Example

• Fords Three-Pronged Solution

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SCI Modeling Segmentation

• Supply Chain Modeling
• Utilize daily product position and business
  requirements snapshot
• Re-calculate projected quantities and time via
  models. Projected customer service levels via
  variability analysis
• Comparison to expected aggregated Demand by
  family, SKU, path
• Detailed analysis of segment or aggregate
  performance by time, yield, capacity,
  constraints, .
• Model management at segment levels include
• Segment lead time
• Yield
• Split/merge/path selection
• Long term highly accurate forecasts not required
• Track and tune standards over time

FORD SUPPLY CHAIN EXAMPLE PSL Operation
Demand
SUPPLIERS
CUSTOMERS
REDISTRIB.CENTER(Count 1)
REGIONALDISTRIBUTION(Count 10)
SUPPLIERS(Count 2,000)
PACKAGERS(Count 7)
DEALERS(Count 5,900)
REDISTRIBUTIONCENTER
REGIONALDISTRIBUTION
Segment
INTERVALS
Allocation
Ship to In-Yard
In-Yard toReceipt
Receipt toStock-Keep
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Critical Alerts In Yard
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Critical Alerts In Yard
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Over Standard Alerts
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Inventory Visibility
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SCI From Two To Eight Opportunities To
Avoid Back Orders
Change Ship Date SUPPLIERS Change Ship Date
None PACKAGERS 1. Receive 2.Process
1.Normal/ Critical REDISTRIB.CENTER 1.Receive 2.
Stockkeep 3.Normal/ Critical
None REGIONALDISTRIBUTION 1.Receive 2.Stockkeep
DEALERS
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Standards Management
The actual cycle time for this O/D pair averages
over 6 days, so the assumptions for segment cycle
time are not modeled properly.
Parameter Management scores actual cycle time vs.
the current model parameter to detect segments
with a poor fit.
For the shipments through this segment, the
average cycle time is compared to the standard.
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The current model does take average segment
variability into account. Now actual variability
can be incorporated into the model to drive
accurate safety stock
New model parameter evaluated for fit with actual
shipment transaction cycle times
Drilling into the detailed data for each segment
supports outlier identification and users can
evaluate how well the model fits each segment
within the supply chain.
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Histogram shows the distribution of shipment
cycle times as a percentage of the total shipments
All detailed data supporting the evaluation is
available in the drill.
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Ford Growth in User Base
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Ford ROI

• Benefits
• Reduced Inventories
• Improved Customer Service levels
• Less overtime, expediting, and special handling
• Higher margins
• No new data sources required

• The SCI Solution gives Ford the ability to
  predict and prevent potential back orders - not
  just react
• Powerful Analysis of Every SKU, Every Day on
  hundreds of millions of dollars of inventory
• Daily metrics and historical trending that
  allow reality-based planning to be linked with
  execution management
• All members of the network now perform as a
  synchronized team!

• Results
• 10 One-Time and Recurring Reductions in
  Inventory
• 20 Back Order Reduction
• 25-30 Reduced referrals
• 30 Cycle Time Reduction

Savings in first 6 months alone was five times
the cost of the system.
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Thank You for your Attention
Email ramerkle_at_comcast.net