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SERVICE MATTERSS VAT EVERY LEVEL

2007 IEEE International Conference2007 IEEE International Conferenceon Service Operations and Logistics

August 29 2007

Service Supply Chain Customer Value Delivery:Optimization, Performance Incentives & Implementation

Morris A. CohenPanasonic Professor of Manufacturing & Logistics

The Wharton SchoolUniversity of Pennsylvania

&& Founder and Chair, MCA Solutions Inc.

Agenda

1. Strategic Impact of Service Support2. Resource Management in the Service Supply Chain3 I ti C t ti d P f B d3. Incentives, Contracting and Performance Based

Logistics (PBL)4 MCA’s Planning Support System Lessons Learned4. MCA s Planning Support System – Lessons Learned

from Implementation

What is common in these examples?

Company Product Customer

Routers

Semiconductor Equipment

Aircraft Systems

Value generation from the product is key

Product is used to deliver significant value toProduct is used to deliver significant value to customers.

Loss of availability of product is very EXPENSIVEe g cost of line down for Intel > $100 000/houre.g., cost of line down for Intel > $100,000/hour

Customers define value differently in each caseKLA: value = wafer start throughputCisco: value = connectivityBoeing Defense: value = winning the war

Value varies with customer and with timee.g., plane down during a training exercise vs plane down during a war

So, what are the implications -- for product manufacturersSo, what are the implications for product manufacturersdistributors, retailers and service providers?

Implications

Viewing product as a source of value generation rather thanViewing product as a source of value generation, rather than as property to be acquired by customers, presents an incredible competitive opportunity

In fact, product ownership may not even be necessary forIn fact, product ownership may not even be necessary for value generationConvert products to services (“SERVICIZATION”)Deliver product PERFORMANCEp

Sell Solutions (repairs, upgrades, reconditioning, maintenance, technical support, consulting, training) whose demand is driven by product use

Competing by selling products is toughDemand growth is slowCompetition is increasingMargins are lower

Recent Benchmarking Data

S i R 26%Service Revenue 26%Profit from Services 46%Market Share (installed base): 40% / 70% (Services/Partsa et S a e ( sta ed base) 0% / 0% (Se ces/ a tsInventory Turns 6.75*Customer Service (First Time Fill Rate) 82.8%

(2005 Deloitte)(2005 Deloitte)

Questions: Non material cash flows included in turnover?

Inventory depreciation, write-off and costing assumptionsService Metric -- Part Fill rate vs. Up-time of Installed Base

Variation in performance (daily, time average, confidence interval)Segmentation leads to differentiated service and resourceSegmentation leads to differentiated service and resource rationingActual performance vs. promised?

* In a Wharton study of about 10 years ago we observed turnovers of 1.0 - 3.5 for service parts. In a 2007 US defense service study MCA observed a turnover of 0.5

Agenda



from Implementation

How to implement an effective service strategy

1. Select portfolio of products to be supported2. Deliver service products for maximum profit3. Understand and adjust business model4. Design organization & incentives to support

service strategy5. Design service supply chain and optimize

resource management decisions6. Continuous benchmarking and monitoring

Source: Cohen Agrawal and Agrawal ‘Winning in the Aftermarket’Source: Cohen, Agrawal and Agrawal, Winning in the Aftermarket , Harvard Bus Rev, May 2006

Service Supply Network Management Challenges

• Conflicting Objectives: Position resources throughout multi-echelon, multi-indenture network to meet Availability targets, satisfy budget constraints, reduce customer cost of ownership and increase supplier profit

O-Level(Operational)

ownership and increase supplier profit• Dynamic and Uncertain Environment:

Intermittent demand that is difficult to forecast, changing projected weapon system I-Level g g p j p yusage, evolving reliability, engineering changes and product re-design

• Structural Change: Shifting ownership of t d l i ibilit

I Level(Intermediate Repair)

Warehouse Depot

assets and planning responsibilityD-Level(Depot Repair)

Suppliers

Planning Must Incorporate Multiple Hierarchies

• Product

• Major Module (e.g. FRU/LRU)

• Sub-Module (e.g. SRU, SSRU)

• Central Warehouse

• Local Warehouse

• Field Engineer/Repair Loc.

Product

• Piece Part

Geographic

• Customer

Optimize SERVICE PERFORMANCESERVICE PERFORMANCE

SPO

SERVICE PERFORMANCESERVICE PERFORMANCE

With Minimum Asset Investment & Operating Costs

While respecting BudgetPlanningHorizon

• Budget Planning

Customer

• Supplier Lead Time

While respecting Budget Constraints

Budget Planning

• Long Term Forecast

• Inventory Positioning

• Event/Order Management

• Repair, Replenish, Ship Lead Times

• Next Day Customer Response

• “x-hour’ Critical Response

“The “Long Tail” of Parts Demand (Semiconductor Equipment)

900

1000

90 0%

100.0%The forecasting methods found in traditional planning systems are inappropriate for most service parts

700

800

900

70.0%

80.0%

90.0%

500

600

bers

w/ D

eman

d

50.0%

60.0%

Part

s w

/ Dem

and

~ 80% of parts with demand have average

monthly demand of <=2

300

400

Part

Num

b

30.0%

40.0%

% o

f Tot

al P

~70% of parts with demand have average

monthly demand of <=1

0

100

200

1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 96

0.0%

10.0%

20.0%

1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 >9

12 Month Unit Demand

PT5

PT5 Changed animationPhilippe Thys, 2005-9-28

The New E-Supply Chain for Retail Products

As inventory holding and distribution costs 0, 1) it is optimal to stock infinite variety1) it is optimal to stock infinite variety2) demand for outliers is revealed

e.g. records, music, books

(48% of Amazon’s revenue is from tail)

Service Parts are Different

Sh t t hi h f i t tiShortage costs are high for service parts response time must be lowHolding costs are high due to modularity & complexityg g y p yReliability is high and demand is erratic and difficult to forecast

1) stock a subset of parts at forward locations2) stock backup inventory at central locations2) restrict investment to meet budget constraint2) restrict investment to meet budget constraint3) select / position resources to maximize product uptime

Risk Based Planning Hierachy

TACTICAL• Redeploy Existing Inventory• Allocate Scarce Resources• New Buy & Repair Orders• Piece Part Replenishment

STRATEGIC• Network Design• Budgeting• Set Readiness Targets • Position inventory

EVENT• Global search and sourcing of

resources• Automated detection,

diagnosis, repair.• Service Support, PBL Contracts • Rationing, prioritization

X

5T 4T 3T 2T Time

X

Multi-Period PlanningBudget ConstraintsBudget ConstraintsReadiness Targets

Respect Business Rules and PBL Contracts

Service Support as a Real Option

St t i S iSB d t

Pre-EventDecisions

Post-EventDecisions

StrategicDeploymentOf Assets

Inventory investmentTechnical staffRepair capacity

ServiceDemand

FulfillmentDemand Transfer,

Fulfill Delay, Substitution,Rationing

Incentives

ServiceAsset

Re-DeploymentInventory investment

Technical staffRepair capacity

BudgetPlanning

Product designPricing

Outsourcing

Customer

Pre-emptiveRepair,Replace

Provider

CustomerConsequencesProduct restore time

Opportunity costs

p

Service EventsProduct Failures,

Maintenance EventsUpgrades

ConsequencesProvider costs

& revenue

EnvironmentalEventsInstalled base changesNPI/EOLRegulatory changesStructural opportunitiesSupply Chain

Performance Assessment

Supply ChainEventsMaterial MovementsSupplier CommitmentsCustomer Requirements

CustomerCustomerValueValue

ProviderProviderProfitProfit

Expected vs Risk Value of Availability

P{Avail > α} > x

Meanα

Examplesp- peacetime vs. war time surge - new customers and contracts- new product launch - response to competitor push

Agenda



from Implementation

A Transition Towards PBL in the US Military

Commercial antecedents to PBL over the last 20 years:

GE Rolls Royce jet engines- GE, Rolls Royce jet engines- Honeywell, Rockwell Collins avionics- Lucas Aerospace landing gear- Garrett auxiliary power units.

“Th f PBL i b i f t t th i di id l“The essence of PBL is buying performance outcomes, not the individual parts and repair actions … Instead of buying set levels of spares, repairs, tools, and data, the new focus is on buying a predetermined level of availability to meet the [buyer’s] objectives.”

Defense Acquisition Guidebook Section 5.3q

“”DoD 5000.1, the Defense Acquisition System, requires program managers to develop and implement PBL strategies that optimize total system availability while minimizing cost … The preferred PBL contracting approach is the use of long-term contracts with incentivescontracting approach is the use of long-term contracts with incentives tied to performance.”

The Undersecretary of Defense, August 16, 2004

F-35 Joint Strike Fighter (JSF) project

Incentive problem in a typical PBL supply chain

Customer (DoD)CONTRACT

Prime

CONTRACT

CONTRACTSSupplier 1 Supplier 2 Supplier 3 Supplier 4 Supplier 5

Avionic system Engine

Landing gearMechanicalWeapons

Elements of Incentive Contracting

Decentralized decision making:Suppliers invest into spare parts inventories, repair pp p p , p

capacities, product reliability and optimize their supply chains to maximize their profits.The Prime wishes to induce desired actions from suppliersThe Prime wishes to induce desired actions from suppliers

using contracts and wishes to achieve certain product availability for the Customer.

Outcome with respect to both total supply chain costOutcome with respect to both total supply chain cost and up-time performance is uncertain:

Suppliers may act opportunistically and get away with little effort.

Contracting parties are averse to risk.

Incentive Contracting in Defense Procurement: Fixed Price vs. Cost Plus vs. PBL contracts

Fixed Price Contract Cost Plus Contract Performance Contract

Maximum risk on suppliers.

Reduced risk for suppliers.

Maximum risk on suppliers.

Greatest incentives to

d

Least incentives to

d

Moderate incentives to

dreduce costs.

No

reduce costs.

No

reduce costs.

HighNo performance incentives.

No performance incentives.

High performance incentives.

Insight #1: The optimal contract with suppliers

Fixed Payment Cost Sharing+ PBL+

To allocate To share To ensureTo allocate profits

To share risks

To ensure performance

Source: Kim, S.H., M. Cohen and S. Netessine. 2007. Performance Contracting in After-Sales Service Supply Chains. Forthcoming in Management Science. Available from http://www.netessine.com.

Insight #2: Contract terms should evolve over time

Small performance incentive

Large performance incentive

P d tLimited cost sharing (Fixed Price)

Extensive cost Product

Product maturity

sharing (Cost Plus)

Uncertainty in support cost Volume of use

deployment

PBL

TimelineCost-plus contracts

Fixed-price contracts

Insight #3: Does PBL induce reliability improvement?

Availability target

Inventory (S)Cost of ownership

High

LowOptimal reliability-inventory combinationunder old (material) contract

Optimal reliability-inventory combination

Optimal reliability-inventory combinationunder performance contractwith customer ownership

SMaterial

Optimal reliability-inventory combinationwhen supply chain is integrated

SIntegrated

= Optimal reliability-inventorycombination under performance contract with supplier ownership

SPBL

RMinimumReliability (R)

RIntegrated

SIntegrated

RPBL

RMaterial

Supply chain performs best under PBL with supplier asset ownership

= RMaterial

Anecdotal Evidence of PBL Success: Material Availability & Response Time

F-14 LANTIRN

Navy Program Pre-PBL Post-PBL73% 90% Material

F-14 LANTIRN

H 60 A i i

F/A-1862% 85%

Availability increased an

average of 30%-H-60 Avionics

F/A-18 Stores

71% 85%

98%65%

g %40% through

PBLF/A 18 Stores Mgmt System (SMS)

Tires 70% 85%

98%65%Aircraft and

Equipment Logistics Response Times

APU

AEGIS65% 95%

65% 90%Response Times

(LRTs) decreased an

f 70% 80%65% 95% average of 70%-80% through PBL

Wharton Empirical Study: Drivers of PBL Contract Success

PBL Structure•Contract terms (length, incentive)•Ownership/control structure•Output targets•Program scope

Managerial Decisions•Stocking level at each base/depot•Repair capacity/capability•Supply chain structure designS ifi ti f t t l t

Performance Outcomes•Availability•Cost of Ownership•Reliability•Specification of contractual terms

•Product re-design

•Reliability•Response time

Exogenous Factors•Product complexity•Part reliability•Product costProduct cost•Demand profile

Agenda



from Implementation

MCA’s Positioning in Service Decision Support

SIO

How long did it t k f

Strategy TacticsMulti-Period/What-IfNetwork Optimization

How will t

take for customer’s

mission critical product to be

t d t

How much to invest in

i

How to utilize current resource

deployment to id

PBL

customer asset

management and support

i

restored to effective use?

Wh t i th

service resources?

Wh t

provide maximum value?

How to manage i iti tservices

increase sales and profit?

What is the up-time of customer

equipment?

Where to position those

resources?

priorities to match supply with demand?

Sh t t R l Ti

Deploy/PositionResourcesService Strategy Event Management

Re-Deploy &Balance Resources

Long term Short term Real-Time

gy gExecution

MCA’s Complete Solution For Managing The Service Supply Chain Supports This Framework

Composit Business ImpactSignificant reduction in service inventory and supply chain costs with higher service levelsNetwork design and planning capabilities

Network Optimizati

on

Composite

Forecasting

Inventory Optimizati

on

Tactical Optimizati

onCommon Data Model and Scenario Manager

Flexible “What-if” Environment for service business designAbility to simulate a wide range of business scenariosCommon data model across solution modulesFlexible data interfaces and integration paths

g p g paligned with your business requirementsAbility to define and deliver to differentiated service levels Improved planner productivity

Flexible data interfaces and integration paths

Google Maps interface for network modeling/optimizationAdvanced set covering and assignment functionalityJoint inventory/transportation cost optimization

Bottoms-up forecasting designed for a service environmentUtilizes historical demand, installed base, and causal factorsAdvanced best-fit capability for seasonality and trends

y/ p p

B

A

Complex Multi-Echelon/Multi-Indenture ModelingFill-Rate and Availability Based OptimizationBudget and Service Level Constraints

B

C

D

Optimized Replenishment PlanningAutomatic Supply Chain Exceptions (Alert Engine)Asset Rebalancing to Minimize Execution Gap

Real World Challenges for PBL/SCM

PBL contract negotiations require integrated decision support systems

Identification and analysis of performanceIdentification and analysis of performance metricsDetermination of risk allocation across suppliersCombining contract terms to balance risk acrossCombining contract terms to balance risk across service life cycle

PBL contract management requires optimal resource planning and intelligent execution control systemscontrol systems

Resource deployment within budget constraintsCoordination of supplier asset controlTight integration between planning and execution systems

Closing the Gap on PBL Impact

Customer’s Cost of OwnershipSupplier’s Profitability ppp y

AfterMCA

Prior toMCA After

MCAPrior toMCA

PBL Profit Objectives PBL Profit ActualsPBL Cost of Ownership ObjectivesPBL Cost of Ownership Actuals

ConclusionsDelivery of services to enable value creation through product use is a source of revenue growth profit margin customer satisfaction and competitive advantagegrowth, profit margin, customer satisfaction and competitive advantageEffective delivery of such services requires optimized management of service supply chain resourcesCurrent service support management systems often lack the ability to account for incentive effects created by the PBL contractsincentive effects created by the PBL contracts.Our economic models indicate that:

The optimal contract will have a mixture of PBL, cost-sharing and fixed payment terms.O er time the contract ill e ol e from more cost sharing to more performanceOver time, the contract will evolve from more cost-sharing to more performance-based.PBL contract stimulates reliability improvement but works best when supplier owns assets.

There is a lack of empirical evidence on what makes PBL contracts successfulThere is a lack of empirical evidence on what makes PBL contracts successful, companies generally do not keep adequate data.There is an urgent need to apply decision support systems to help with negotiating and executing PBL contracts.Implementation of effective service decision support systems is based on theImplementation of effective service decision support systems is based on the appropriate mix of incentives, optimization models & algorithms, and software systemsSources:M. A. Cohen, N. Agrawal and V. Agrawal, “Winning in the Aftermarket”, Harvard Business Review, May 2006.M. A. Cohen, N. Agrawal and V. Agrawal, “Achieving Breakthrough Service Delivery Through Dynamic Asset , g g , g g y g y

Deployment Strategies”, Interfaces, Volume 36, No. 3, May-June 2006.Kim, S.H., M. Cohen and S. Netessine. 2007. “Performance Contracting in After-Sales Service Supply Chains”.

Forthcoming in Management Science. Kim, S.H., M. Cohen and S. Netessine. 2007, “Reliability or Inventory? Contracting Strategies for After-Sales

Product Support”.

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