jda 2015 v3
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Transcript of jda 2015 v3
7
TOTAL REVENUE
$ in millions
CUSTOMERS
4000+
Introductions
PROFESSIONALS
4800+
LOCATIONS WORLDWIDE
70+
$382 $401
$594
$691
$1,065
Copyright © 2014 JDA Software Group, Inc. Confidential
CONTINUED INNOVATION AND CUSTOMER FOCUS
Voice of the CUSTOMER
$120+ Million in R&D Spend 400 Patents
Copyright © 2014 JDA Software Group, Inc. Confidential
11
Supply Chain Planning Ecosystem
“Apply the Gartner Supply Chain Maturity Model for Better Supply Planning”, Gartner, April 2014
12
Flexible Business Model
Transportation Management
Warehouse Management
Replenishment & Fulfillment
Price & Promotions Management
Order Promising & IBM Commerce
3rd Party Solutions Host/ERP/Other
JDA Platform
Sales & Operations Planning
Demand Management
Copyright © 2014 JDA Software Group, Inc. Confidential
Real Time Integration
In Memory Processing
Cloud Computing SaaS
JDA
Customer-Centric
Copyright © 2014 JDA Software Group, Inc. Confidential
14
Independent and Misaligned Goals
Retailers and Manufacturers Both Struggle with Problems…Independently
Disconnected Models & Systems Create Uncertainty, Accountability Issues and Unnecessary Costs
Supplier-Centric Planning
Retailer-Centric Planning
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Benefits
Pre-built store level metrics
Algorithms that determine root-cause
Auto-cleansing demand history
Tied to supply chain levers
Opportunity
Benefits
Opportunity
One view of key metrics
Enable joint planning with retailer partners
Drill up/ down
Optimized for scale and performance
Benefits
Prescriptive simulation modeling across 5 categories (Promotions, Inventory, fulfillment, deployment, and network strategy).
View tradeoff decisions across multiple simulations
Benefits
Dashboard monitoring of new product introduction performance by store
Drill up/down hierarchy analysis
Daily visibility of performance vs. target
Collaboration Workbench
Root Cause Analytics Simulation Modeling
New Product Intelligence
JDA Flowcasting
Leverage Cloud Computing
16
Flowcasting and Forecast Accuracy
> “Drake said the solution, now live with a couple of retail customers, has delivered the biggest single improvement in forecast accuracy in the history of Kraft, while noting that in a sense Flowcasting has upended Kraft’s existing thinking about the value of traditional forecasting and accompanying resources”
16
Dan Gilmore, Supply Chain Digest , May 11 , 2012
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In Memory Computing
> What difference would it make if you could get a response to a Master Planning question in a matter of minutes or seconds?
> A response that was - Global - Optimised - Costed - Revenue and Margin Aware - Customer focused
> Utilising In-Memory Computing technology makes that possible.
Copyright © 2014 JDA Software Group, Inc. Confidential
18
Plan Management Planning Control Tower
> Agile Workbench enables fast response to events via guided resolution paths powered by a live in-memory simulation engine
- Respond to disruptive events quickly and
profitably
- Triage and resolve exceptions via pre-packaged resolution levers
- Perform rapid what if simulations to try out various scenarios
- Update the plan of record in incremental fashion
19
The Shift in Production Planning
> Weekly production plan
> Load leveling based on the primary
bottleneck constraints
> Manual plan tuning was expected as part of
the planning process
> Material availability was primarily MRP and
procurement issue
In the past . . . Today . . .
> Increased demand volatility requires daily
production planning
> Floating bottlenecks (due to high demand
mix)
> Production planners don’t have time to
respond to volatility
> Must consider material availability due to
volatile material costs and increased lead
times
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Order Promising Maturity
Maturity
Agili
ty
Level 1
Fixed Lead Times
Level 2
Simple Available-To-
Promise (ATP)
Level 3
Real-Time, Allocated
ATP
Level 4
Real-Time, Allocated
Capable-To-Promise
Level 5
Closed-Loop
Profitable Promising
Lead times are theoretical or averages
based on past performance
Does not adapt to
changing supply and demand
Does not incorporate
supply chain or customer priorities
Simple finished good supply including on-
hand, in-transit, planned and projected
receipts
No reservations for key channels, customers or
tiers
Simple logic to match demand to supply
Differentiated allocation policies for channel and product
segments
Segmentation strategies regularly tuned to business
conditions
Automatic supply-demand balancing
Lights-out promising
with workflows to manage exceptions
Reservations at multiple levels in the
supply chain by channel and product line
On-going proactive
management of response to forecast
Advanced root cause
analysis and exception resolution
Price-point and profit-sensitive reservations
at multiple supply chain levels
Interactive planning adjustments and re-
allocations
Closed-loop feedback on order execution
Tune promising policies
to adapt to changing buying patterns
“Apply the Gartner Supply Chain Maturity Model for Better Supply Planning”, Gartner, April 2014
21
Connecting Planning to Execution
Demand Planning
Supply Chain Strategy
Inventory Optimization
Sales & Operations Planning
Replenishment
Master Planning
Factory Planning, Scheduling
Order Promising
Hours Shifts Days Weeks Months Quarters Years Real-Time
Long-Range Demand Planning
Medium-Range Consensus Demand Plan
Strategic Network Design
Portfolio Segmentation
Tactical Inventory Planning
Strategic Inventory Planning
Executive S&OP Operational S&OP
Distribution Requirements Planning
Deployment Planning
Master Production Planning
Factory Planning & Scheduling
Allocation Planning Order Promising
2. Build to support the plan
1. Plan what you want to sell
3. Promise what you can build
ER
P /
WM
S / T
MS
/ M
ES
4. Deliver on promises
and achieve the plan
23
Take aways
> Some things never change – but some do > Technology is an enabler > Maturity matters – it’s a journey > Innovation
> JDA.com > [email protected] > [email protected]
Copyright © 2014 JDA Software Group, Inc. Confidential