The Oracle APS and Demantra Specialists Copyright © Inspirage LLC, 2009. Private and confidential. All rights reserved Page 1 Strategic inventory levels

The Oracle APS and Demantra SpecialistsThe Oracle APS and Demantra Specialists

Copyright © Inspirage LLC, 2009. Private and confidential. All rights reserved Page 1

Strategic inventory levels to satisfy customer requirements

Northern Cal OAUG Training DayJanuary 21, 2009

Sridhar HoskotePartner, Inspirage LLC


Agenda

• Introduction• Business Challenges• Supply Chain• Need for System Support• IO implementation• Integrating IO with constrained ASCP• Cutover process• Results and Summary• Q&A



Inspirage is recognized as a premier consulting firm specializing in Oracle Advanced Planning and Demantra Applications.

• Founded by former Oracle APS Product Development Senior Managers responsible for design and development of many APS applications

• Strategic partnership with Oracle product development in

– Areas of new product design and development

– Preferred partner for training other System Implementers

• Recognized as subject matter experts within the Oracle APS community

– Numerous highly successful reference clients

– Leadership role in OAUG special interest groups for Advanced Planning and Demantra

– Contribute to knowledge sharing by presenting in forums such as OAUG and Oracle Open World conferences



Inspirage Customers




Inspirage provides the complete expertise of the integrated Oracle forecasting and supply planning solutions

Demand Management, StatsForecast, Multi-tierCollaboration

Workflow, AF/DM, Chaining, MemberManagement Consume

Forecast

Constrained / Optimized Planning

SO History

DM

ASCP

GOP

Schedule,Un-schedule orders

Advanced Planning

ERP

Release orders

Schedule orders

Trading PartnerCollaboration

CP

S&OP Monitor plans to actual, collaborate, and respond

Distribution/ ServiceParts Planning

Collect PlanningData

SNO

StrategicSourcing

Detailed Scheduling

PS

IO

InventoryStrategy


Introduction

• Source Photonics designs and manufactures wide variety of optoelectronic devices

• Broad product line of PON, Telecom, and Datacom transceivers• One of the largest volume suppliers of non-VSCEL based

transceivers in the world~ 4-6M per year of 1310nm and 1550nm transceivers



Oracle footprint

20062006 20072007 Summer 08Summer 08 November 08November 08

Ora

cle

Execu

tion

prod

ucts

Const

rain

ed A

SCP

Inve

ntor

y O

ptim

izat

ion-

Phase

1

Feb 09Feb 09

Inve

ntor

y O

ptim

izat

ion-

Phase

2

Glo

bal O

rder

Prom

isin

g/Pilo

t CP

• Implemented Oracle E business suite in late 2006 and early 2007• Implemented constrained ASCP in 2007• Inventory optimization with demand variability in Summer 08• Integration of IO and ASCP, supplier LT variability in November 09• GOP is slated for early 09



Business Challenges



Business ChallengesCustomers

Request DateRequest Date

Scheduled Ship Date

Scheduled Ship Date

14 wks LT14 wks LT

• How much inventory do you need to satisfy request dates?• Where do you keep those inventories?• How do deal with huge lead time requirements?



Business challenges

• Not able to satisfy requirements by request date with current inventory levels

• Need to determine and add inventory strategically

• Need flexibility in using common materials into large number of finished goods

• Customers do not always provide enough lead times

• Lead times can be up to 14 weeks



Business challenges• Forecast accuracy and demand stability are quite poor

• Supplier delivery performance contributes to uncertainty

• Need to rely upon key trading partners to fulfill demands

• Exploit the natural build lead times to push inventory away from finished goods

• Complex supply chain structure makes it very difficult to plan for inventory levels



Supply Chain



Characteristics of supply Chain

• Generally 5 to 8 levels deeps

• Goes across 3 organizations

• Each end item has anywhere from 100 to 400 components

• Relatively short manufacturing lead times

• Long material procurement lead times

• Extensive commonality of components in each family of end products

• Same common materials can be packaged into a vast number of finished goods



Simplified supply chain BOM



Products fan out



Need for System Support



Several critical complexities to consider

A B

X

C D

E F

D G C HA

I J

YMulti-echelonMulti-

echelon

PoolingPooling

Time varying Inventory

Time varying Inventory

PostponementPostponement



• Consider legitimate drivers for inventory requirements such as Service Levels

• Consider the entire supply chain BOM structure

• Consider uncertainties – namely demand uncertainty and supplier delivery performance

• Consider appropriate lead times at various levels

• Consider dependent demand and propagate need for inventory across the supply chain

Need for programmatic inventory calculation



Modeling



Modeling

Strategic Inventory

Strategic Inventory

Demand Variability

Lead Time Variability

Service Levels

MAPE (Mean Absolute Percent Error) for each product line

MAPE (Mean Absolute Percent Error) for each product line

Primary driver for setting this was based on OTD

Primary driver for setting this was based on OTD

Via simple probability distribution of lateness

Via simple probability distribution of lateness

Supply Chain BOM

Supply Chain BOM using BOM, sourcing, routings

Supply Chain BOM using BOM, sourcing, routings



• Demand Uncertainty

– MAPE calculated by comparing history to actual– Default MAPE where there was no history

– Varied MAPE to calculate reasonable inventory levels

• Supplier Delivery Performance

– Set up dummy supplier

– In IO plan all purchased parts were sourced using above dummy supplier

– Lateness distribution associated with dummy supplier

Modeling



Implementing Inventory

Optimization



• Safety Stock method - MRP planned % vs non MRP planned• Lead times – Processing, pre-processing, post-processing,

intransit • ABC classes - plan selects items based on ABC classes• Alternate BOMs and Substitutes – made a strategic decision to

not consider alternates and substitutes• Forecast error measure MAPE fed at item level• Supplier LT variability

– Single supplier source for all buy items – Establish ASL relationships– Feed distribution st supplier level

Important set up for IO to run



• Used internal cost roll up instead if actual costs• Set up Weights to increase the rolled up costs• Carrying costs was set to a global value• Set postponement factor to 20• Used profiles to prevent SS calculation on

alternate paths and substitute items

• Used 24 by 7 calendar in all orgs to smooth out safety stock requirements

Other significant set ups



• IO runs with 36 weekly buckets and no period buckets

• Penalty factors chosen to derive stable results• No existing supplies or scheduled receipts

considered• DP scenarios used to feed MAPE numbers

into the plan• Enforce service level plans

Plan options



A

X

LT= 5 daysLT= 5 days


B

Postponed SS is in matched sets

Both A and B will get SS based on max LT which is A

Postponed SS is in matched sets

Both A and B will get SS based on max LT which is A

A

X



B

Postponed SS is based on LT for each component

A and B will get SS based on their LTs

Postponed SS is based on LT for each component

A and B will get SS based on their LTs

Enhanced postponement

NORMAL POSTPONEMENTNORMAL POSTPONEMENT ENHANCED POSTPONEMENTENHANCED POSTPONEMENT

Source Photonics used Enhanced Postponement Source Photonics used Enhanced Postponement Copyright © Inspirage LLC, 2009. Private and confidential. All rights reserved Page 26


• Constrained ASCP plans with decision rules was already in production

• Introduced transient (temporary) safety stock requirements using IO

• Objective was to introduce IO as input without significantly affecting plan quality (lateness, inventory etc.)

• Integrating ASCP and IO was a significant effort– Safety Stocks vary across the horizon and finally disappear

(transient)– No dedicated supplies created to satisfy SS requirements – The actual supplies are pulled forward instead of creating new

supplies. Needed to make room for this effect

ASCP plans with IO as input



• IO calculates propagated Service Levels to derive SS for buy items

• With large number of items at a given level the Service Level tends to go to 99.99% very fast

• Beta factor allowed for tempering the above effect• Source photonics used this factor to fine tune SS

levels for buy items

Propagated service levels



• Plans very intricate and a long supply chain – up to 120 days cumulative lead time.

• Each end item can have to 300 items

• We avoid planning all substitute and alternate paths in IO

• Demand variability modeled via MAPE measure

• Postponement used to push safety stocks through all levels of BOM (max of 8 levels)

• Used ‘enhanced postponement’ logic – lead time specific safety stock for sibling items

• We use supplier lead time variability to model delivery performance

Plan facts



• Enforce Service Level plans

• IO plans approximately 7300 items in 2.5 hours

• Safety Stocks calculated for about 4000 items

• Plan horizon is 36 weeks

• Demand variability specified via MAPE

• Includes both demand and supplier LT variability

• Do not consider scheduled receipts

Plan facts



IO Integration withConstrained ASCP



• Sized the requirements from safety stocks to make it true transient safety stock

• Added additional internal resources to accommodate both regular demands and safety stocks requirements

• Used profiles to minimize shared supplies between regular demands and SS requirements

• Smoothed safety stock requirements such that system had a chance to consume all supplies within plan horizon

Steps taken to make ASCP work



• Lot for Lot• Number of supplies to be scheduled • Number of times to re-schedule shared supplies • Supplies used to satisfy safety stock• Demand and Supply Window widths• Use Optimization Phase dates for pegging• Split planned orders to perform safety stock pegging

Factors considered to fine tune ASCP



Cutover Process



Plans with no postponement,

Demand variability only

Plans with no postponement,


Plans with postponement





Demand and supplier lead time variability



IO plans



• Days of supply needed to hold/support manufacturing activities • Instead of verifying exact SS calculations, concentrated on

factors that could affect SS and sensitivity of SS due to each factor

– Role of lead times in arriving at SS

– Importance of Service Levels in calculating SS

– Important set up issues that could affect SS – ABC classes, SS method, lead times, types of lead times

Explaining output from IO











ASCP plansConstrained ASCP

Plans

Constrained ASCP

Plans

Constrained ASCP

Plans

Constrained ASCP

Plans



• Initially fed SS for only buy items into ASCP

• Provided a gradual ramp up of SS to give a chance for manufacturing and other resources to react

• Made SS requirements transient to avoid pegging to excess– Cut off SS requirements after the longest cumulative Mfg lead

time

– Set SS to zero for a few buckets prior to end of demands

Adoption of IO into ASCP plans



Results & Summary



• The overall safety stock planned is in line with expectations- approximately 6 weeks of inventory in the system

• The inventory value matches with the current levels in plan with no postponement

• Plans with postponement shows improvement up to 20% in inventory value

• Satisfaction of orders by customer request date is expected with a comprehensive execution of IO plans

Results



Summary

• Needed a comprehensive inventory planning system to plan and satisfy requirements by request dates

• Utilized Oracle Inventory Optimization to plan inventory levels

• Used demand and supplier lead time variabilities to influence safety stock requirements

• Significantly improved customer fulfillment and inventory reduction



Question & Answers?

Sridhar Hoskote 510 676 6753

[email protected]


Documents

The Oracle APS and Demantra Specialists Copyright © Inspirage LLC, 2009. Private and confidential. All rights reserved Page 1 Strategic inventory levels