Design for Warranty Cost Reduction
Robert H. Mueller, Ops A La Carte & Marisan Group
Key Words: warranty, warranty cost model, design for warranty, computer, electronics industry
SUMMARY & CONCLUSIONS
This paper develops a process based cost model for
warranty events and applies it to a number of product
instances in the computer and related high tech businesses. It
identifies the principle support ‘meta-processes’ that typically
contributes >70% to the total cost of warranty. From this
model the key warranty cost drivers are identified and the set
of strategies are derived that product development teams can
use to reduce the cost of warranty for products under
development. Proven frameworks for applying the model and
warranty cost reduction strategies during the product
development cycle are presented.
Case study instances are presented that illustrate how
product development teams have applied the model,
strategies and frameworks that reduced the total warranty
costs by 35% are discussed.
1. INTRODUCTION
The total cost of warranty for computer and related hightechnology US based companies is now ~$8B per/year [1].
For many companies, their warranty costs approaches what
they spend on new product development and often matched
their net profit margins; this is particularly true for the
‘commodity’ type businesses such as PCs or personal
printers. Many companies are moving toward an extended
warranty strategy to manage warranty costs. But, this is no
panacea. While extended warranty repairs costs may be
considered an operational expense and not a ‘warranty
expense” from a SEC [10-K] perspective, the effects of
poorer product quality than planned impacts the business’s
bottom line with the same force as warranty costs.
In the past few years the available choices of service
processes used to resolve warranty issues has expanded to
include phone support, Web based and customer self-fix
schemes. This trend has been driven by need to reduce
warranty cost and accelerated by the maturation of the
internet. As both consumer and commercial products
continue to increase the software/firmware to hardware
component mix, these less costly processes need to be
utilized more and more Why? The costs per repair of these
service processes range over 1½ orders of magnitude; from
$30/call for a warrant resolved over the phone to >$700 for
on-site repairs. More importantly, the repair process costs are
the largest contributor to the total cost of warranty; part cost
contribution is typically less than 30% for most products.
Because of the business impact of the cost of warranty,
product development teams are now being challenged to
design products that are both less costly to repair (business
metric: warranty $s) and more reliable (business metric:
annual failure rates, AFR). To more easily meet this
challenge will require warranty costs models that make
explicit not only the impact of AFR on cost, but also the
effect of the process costs associated with the repair of
specific failure modes.
Currently used warranty cost models are dominated by
traditional Failure Modes and Effects Analysis (FMEA), cost
pool based models or models utilizing statistics and
simulation forecasting techniques [6]. FMEAs are heavily
used by the hardware engineering community in the
Aerospace, Military and Auto business segments. Cost pool
based models are most frequently used by the financial and
supply chain communities. FMEA is a proven methodology
for first identifying failure modes or failure mode scenarios
[2,3], then developing strategies to mitigate the risk for each
failure mode during a product’s development cycle instead of
after product launch.
The most popular FMEA
methodologies use the RPN scheme to prioritize the failure
modes, or when cost is used [4], the method is mute on how a
product team calculates cost of repair. Cost pool based
models aggregate warranty costs into large cost pools such as
monthly costs for labor, call centers, material, labor and
inventory/logistics. These cost pool based models [5] are a
natural fit for warranty cost reduction efforts for the supply
chain and procurement areas. Yet, none meets the full needs
for modeling of the development team: the model needs to
have the following characteristics:
• The customer’s problem being resolved is explicit.
• The support processes used to diagnose and resolve the
warranty event are explicit.
• Estimating warranty costs is relatively quick and easy to
do, especially when evaluating design alternatives.
This paper develops a service process based warranty
cost model for warranty events that is grounded in both the
customer’s problem and the support process used to resolve
it. It will identify the primary ‘meta-processes’ used by most
computer and high-tech businesses to service warranty
events. Typical standard costs for each of these will be
discussed. We will demonstrate that these process based cost
models are particularly useful for the computer and other high
technology businesses for both the commercial or consumer
market spaces. They are less useful for the Automotive,
Aerospace or Military business segments because of the
support strategies used in those market spaces.
From this model, the key cost drivers will be extracted
from which we will also develop the primary strategies that
product development teams can use to both improve product
reliability and deduce its warranty costs.
Results from case studies will demonstrate how product
development teams have used this model to develop design
alternatives and action plans to reduce warranty costs. While
presenting the case study a few frameworks will be
introduces that the development team used to evaluate what
strategies may be affective for reducing costs of specific
event types and to identify dependencies deeded to realize the
planned cost reductions.
Warranty Cost = nHD1 x (process cost + material cost)
where:
nHD1 = the number of occurrences of the ‘HD1’event type
Now the total warranty cost for all event types can easily
be calculated. Letting N be the total number of warranty
event types for a specific product, the total warranty cost for a
specific time interval is simply given by:
N
Total Cost = ∑ ni × STD Ci
(1)
i =1
1.1 Nomenclature & Notation
AFR = Annualized Failure Rate
ASP = Authorized Service Provider
PCA = Printed Circuit Assembly
TotalCost = the total cost of warranty for the product
N = number of occurrences of an event type for a
specific time interval
ni = number of occurrences for ith warranty event type
STDCi = standard service process cost used to resolve
the ith warranty event type
M = number of warranty event types needed to account
for an acceptable fraction of the total warranty
expense for a specific time interval
Often, dozens or even hundreds of event types may exist
for complex products. Yet, it is seldom necessary to sum
over all event types to get an excellent estimate of a products
warranty costs. Experience has shown that for most products,
only a handful of warranty events dominate the total warranty
cost; the Pareto principle applies.
Hence, it is useful to define M, where M is the number of
warranty event types that account for an acceptable
percentage, say 90%, of a product’s total warranty costs.
Then the cost equation can be re-expresses as:
M
Total Cost = ∑ ni × STD C i +
i =1
N
∑n ×
i = M +1
i
STD
Ci
(2)
2. PROCESS BASED WARRANTY EVENT COST MODEL
At the heart of the cost model is the concept of a
warranty event. To illustrate what a warranty event is let’s
consider this example. A customer is getting a warning
message from the OS that her hard drive is predicted to be
failing in her PC. She calls the call center for support. The
call center agent, after confirming warranty entitlement, talks
the customer through a diagnostic process that confirms a
specific hard drive caused failure type known by the support
team as ‘HD1’. The prescribed resolution is to replace the
hard drive. In this case the customer is directed take the PC
to a local Approved Service Provider for ‘bench repair’
service. Notice that this warranty event has a process to
diagnose the customer problem (the call center working with
customer to diagnose), a specified support process (walk-in
service by a local ASP to repair) and a part being consumed
(hard drive) to resolve the warranty event.
In this model, every warranty event ‘type’ has a unique
linking of a diagnosed problem, a specific support process to
resolve the event and specific material costs(components), if
consumed. The material cost in this case is the cost of the
hard drive itself. All costs such as spare-part inventory
management or inventory logistics are treated as direct,
in-direct or overhead costs to the support process used.
The total warranty cost for all of the hard disk failures of
event type ‘HD1’ can be simply calculated, for a specific time
interval as:
As the second term of (2) becomes much smaller than the
first term, then we can re-write it as:
M
Total Cost ≅ ∑ ni × STD Ci
(3)
i =1
2.1 Empirical Trends
Figure 1 shows a Pareto chart of warranty event types for
a recently modeled commercial computer/printer product.
Each bar represents a specific warranty event type. The YAxis is the total warranty cost for each event type for a oneyear period. The total number of event types having any
activity in this time interval was about 300. 90% of the
product’s warranty costs were accounted for by only a few
event types, in this case M is ~15. Experience has shown that
most products have a similar behavior; almost all products
modeled had less than 20% of the warranty event types
accounting for more than 80% of the costs.
The cost of each warranty event type is further broken
down into the total labor, travel, material, call center and
support overhead costs. The total contribution of material
costs to the total warranty cost is less than 35%. This is also
a typical distribution of total costs.
An important consequence of these cost breakdowns is
that, during the design and prototyping phase of product
development, the choice of the components based only on its
impact on manufacturing cost may have very costly
consequences to the product’s overall warranty costs and,
therefore on the business’s overall profitability.
Finally, the fact that the Pareto principle has held true for
all products modeled, this model can be an effective tool in
prioritizing that warranty even types should be prioritized by
what on value to the business as measured by real costs.
Pareto of Warranty Event Costs
labor
Travel
Material
Call
Center
Service
OH
$1,200,000
$1,000,000
The service engineer, after receiving the parts, goes on-site to
perform on-site diagnostics, as necessary, replace failed parts
and finish the repair service process for this repair mode.
Note that the total cost of this overall process includes: call
center costs, part logistics (including all ‘overhead costs’ for
spare part management), labor and travel expenses.
For the computer business and many similar high-tech
industries, the number of frequently used support processes is
very small and are listed in table #1. They range from call
center phone support only to on-site repair. Also listed in the
table for each service process are the nominal costs and their
costs. The costs listed in this table have been derived from a
dozen different products lines in a number of different
companies. Many of the products modeled used different
strategies to deploy their product support including a mix of
in-house and 3rd party partners implementing their call
centers, spare parts management (logistics), on-site service
engineering and bench repair.
Warranty Event Total Costs [$]
$800,000
Process Example – On-site Repair
$600,000
A warranty ‘event’
support process
$400,000
Step 1: Customer makes call, call center
determines entitlement
Start
Step 2: Call center diagnoses problem;
determines on-site repair required and
orders needed replacement parts
Step 3: Service contractor gets parts, travels to
site and replaces parts.
$200,000
Step 4: Defective part is discarded or returned.
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☺
Step 5: Case is closed
Warranty Event
RAMS 2008 ©
Figure 1 – Pareto of Warranty Events
2.2 Warranty Service ‘Meta-Processes’
A key step in building an instance of the cost model is
sorting out how many support processes are used to resolve
warranty events for that product. For efficiency reasons,
most support organizations (or, if support has been
outsourced, their 3rd party agents) have just a handful of
‘meta-processes’ to resolve the vast majority of warranty or
service events. The ‘bench repair’ service process from the
hard drive example was one of these ‘meta-processes’.
Another is the ‘on-site repair’ process often used for higher
end or difficult to move products in the computer, medical
and other related high tech businesses. Let’s look at this
process in more detail (Figure 2).
As with the ‘bench repair’ example, the first steps are
focused on confirming warranty entitlement, problem
identification, diagnostics and determination of what service
process will be used for this event. For this process, the
intervention is an on-site service call performed by an
authorized service engineer. The call center will also initiate
the logistics processes needed to get the parts to the service
engineer identified by the diagnostic process for replacement.
1
Figure 2 – On-site Repair process flow
Note that the process cost range covers almost 2-orders
of magnitude; from as low as $10 for events resolved by
phone support resolved events outsourced to off-shore 3rd
parties to over $1,000 for a multi-visit ‘on-site repairs’ due to
misdiagnosed problems. Web based ‘self-diagnostics and
repair’ processes and on-line ‘chat-room’ support schemes
are not included because of the inherent difficulty of
determining if any specific web site ‘hit’ is a true warranty
event or not.
This large cost difference is one of the economic drivers
pushing the product design teams toward designing for
‘customer self-fix’ or ‘bench repair’ processes for new
products.
Table 1 – Support ‘Meta-processes’ and their typical costs
Service
Process
Phone
Support
On-Site
Service
Customer
self-fix
Bench
Repair
Product
Exchange
Description
A warranty event is
resolved by Call Center
(CC) agent /w no material.
Cost=CC(labor rate*call
length)
A warranty event this is
referred by CC agent to
service engineer for an onsite service call
Cost = CC + labor +
travel +logistics + part
cost
Parts only process where
customer replaces parts.
Cost = CC + part cost +
logistics
Customer brings the
product to Business/ASP
for repair
Cost = CC + part costs +
logistics + ASP costs
Customer exchanges
defective product for a
‘new’ / Re-furbished one
Cost = CC + cost of
product + logistics
•
Reducing the frequency of the event type by:
o Reduce the component’s AFR
o ‘Design out’ the event type
•
Reducing the process cost contribution by:
o Switch event type to a cheaper support process
(sometimes called changing Support Process Mix)
o Develop better diagnostics tools to:
a) allow support to switch to cheaper support
processes;
b) reduce diagnostic errors of currently used support
processes.
o Improve product serviceability to:
a) support customer self-repair for an event type;
b) reduce total service call length (time to replace
any other service activities required in
repair/calibrate process).
Process Costs
w/o Material Costs
[avg./(min/max)]
$45
($10 - $60)
$600
($300 - $1,200)
$65
($40 - $100)
$125
($70 - $200)
Design Phase– Warranty Cost Reduction Strategies
For each significant event type
M
Wc ≅ Σ ni * ( Costi + Cmaterial)
STD
$ 65
($30 - $100)
Having so few standard meta-processes greatly simplifies
building a product specific cost model since only a very small
number of standard process costs need to be identified and
quantified by the support and accounting community when
building the model. The other independent variables of the
model, event type’s frequency of occurrence and actual
material costs are usually readily available to the product
development team through the support and procurement team
members. Because of its simplicity, the model can readily be
built in off-the-shelf data base and analysis tools such as
Microsoft Access and Excel.
3 COST DRIVERS AND REDUCTION STRATEGIES
By inspection of (3) and from the table of support ‘metaprocesses, two primary warranty cost drivers are apparent
(e.g., performing a variance on it):
•
Number of occurrence for an event type
We will use the Annualized Failure Rate (AFR) of the
component (or sub-system) associated with that specific
event type as its surrogate since we can easily calculate ni
from the AFR and the number of units under warranty.
•
Cost of support process used
These cost drivers directly lead to a number of primary
strategies that development teams can use to impact warranty
costs during product development (depicted in Figure 4).
They are:
Reduce number of occurrences:
Reduce event’s process cost:
•Designing new (cheaper) processes
Design process around new technology.
Design process to meet new market needs
•‘Design out’ the event’s occurrence
Change product ‘features’
Change how product works
Implement ‘feature’ differently
•Switching to a cheaper process
ID features/capabilities needed to support
different process
•Reduce the number of occurrences
Increase HW reliability (reduce AFR)
Improve SW/FW robustness
•Reduce standard process costs by:
Product changes
Process improvements
Outsourcing
Supply Chain re-engineering
RAMS 2008 ©
2
Figure 3 – Warranty Cost Reduction Strategies
4. USING COST MODEL IN PRODUCT DEVELOPMENT
This model has been used to support the development
team’s economic decision-making process for the for various
design alternatives that affect warranty costs in the following
ways:
• To calculate estimates of both the product’s total
warranty costs and costs of specific warranty event types.
• To prioritize the engineering efforts for product
improvements based on warranty costs, not just
manufacturing cost reduction
• To calculate the difference in warranty costs due to
different design alternatives.
• To facilitate the identification of necessary product
features, capabilities and diagnostic tools needed to
realize projected warranty savings of the chosen design
alternative.
• To facilitate the economic trade-offs between
manufacturing costs for specific design alternatives and
the warranty costs (and post warranty period support
costs).
4.2 Evaluating design alternatives
Having the initial model (and its Pareto tables and charts)
the design team started the exploration and evaluation of
specific event types to determine how they were going to
meet their ‘warranty cost budget’. Their Event Pareto was
very similar to Figure 1, where the top 20 event types
accounted for over 90% of their annualized warranty costs.
Their strategy to meet their goal of a 30% reduction in
Projecting Warranty Savings
Planned engineering actions:
Event1: reduce AFR by 50% and reduce time of repair by 50% (labor cost)
Event6: re-design for self-fix by qualified customer IT resources
Pare to o f Wa rra nty Event Cos ts
Travel
Material
Pareto of Wa rranty Event Cos ts
Call
Center
Service
OH
labor
$500,000
$450,000
$450,000
$400,000
$400,000
$350,000
$350,000
Warran ty Event Total Costs [$]
Warranty Event Total Costs [$]
labor
$500,000
$300,000
$250,000
$200,000
Material
Call
Center
Service
OH
$250,000
$200,000
$150,000
$100,000
$100,000
$50,000
Travel
$300,000
$150,000
$50,000
$-
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$ent
[Note: This team did not use the FMEA methodology for
product design risk assessment. But, the information from a
FMEA would very nicely feed into this cost model. Also, for
‘green field’ products, the initial FMEA’s failure mode
scenarios could also very easily be used to seed the cost
model. Each failure mode would be paired with its
appropriate support process and a relative frequency of
occurrence for the failure could be estimated.]
The teams used a combination of graphics and tables to
specify and document what the reduction in warranty costs
would be for the chosen set of action plans and design
alternatives. Calculating and visualizing the effects of design
alternatives, in both frequency and dollars, is a relatively
straightforward task in the Excel based model. For example,
Figure 4 depicts the effects alternatives for two specific event
types. The first labeled Event1 shows the effect of two
changes to the product: reduce AFR of a PCA board by 50%
and reduce the total time necessary to complete the on-site
repair by 50%. The second event labeled Event2 show the
effects of a single change: redesign the product so that
‘qualified’ customer resources can replace the failed
component. This example graphically depicts the equality of
AFR reductions and support process choice as first order
drivers of warranty costs.
ent
Since the new product would have very similar
architecture and function to existing products they choose to
build a cost model for a similar product currently in
production for which they had easy access to product support
information. The first step was to identify the main support
processes used by support for the current product. They used
all the processes in Table 1 except for the ‘bench repair’ and
‘product exchange’ processes.
From accounting, they
obtained the current standard process costs. With the
standard process costs known, building the initial warranty
event cost model was reasonably straightforward. Together
with the support team they tabulated the frequency of
occurrences for the top 50 warranty event types. Combining
each event type’s associated material costs, process costs and
its frequency, they then constructed (using Microsoft Excel
spreadsheets) the cost model and its corresponding Pareto
charts. Finally, they added a number of new event types for
the new features and functionality planned for the new
product using similar event types from the current product as
a ‘guide’ to estimate both support process costs and
frequency of occurrence for them.
4.2 Projecting warranty cost saving
Ev
4.1 Building cost model and Pareto chart.
warranty costs was to develop, design and implement design
alternatives for each event type on the Pareto that, when
evaluated by the model, predicted a total warranty cost of
less than 3.9% of projected product revenue. The framework
in Figure 2 was developed to facilitate these discussions. It
illustrates the different design options or ‘handles’ that can be
turned to reduce warranty costs. Since many of the design
alternatives involved either improving the efficiency of the
on-site service process or designing the product for customer
self-repair, significant involvement by the support and
technical marketing groups in the early design phase was
critical.
Ev
How teams have used the model during the product
development phase to support the decision making process
when choosing between features, functionality and design
alternatives can best be exemplified by waking through a case
study. Also two frameworks used to develop and choose
design alternatives will also be introduced.
In this case study, the development team was starting
another design cycle for a ‘follow-on’ high volume,
moderately priced ($5,000 – $7,000 depending on options)
product. They had easy access to most support information.
The current product’s annualized cost of warranty was ~5.6
% of total revenue; a competitive position when compared to
their competition, but not a competitive advantage.
Strategically, management had set a goal of reducing
warranty costs by 30% for all products under development to
avoid engineering expense reductions in the future.
Warranty Event
Warranty Event
current
planned
RAMS 2008 ©
14
Figure 4 – Projecting warranty savings
4.4 Identifying Dependencies
The team then developed the next level of design details
that would be needed to realize the warranty savings.
Specifically, for each warranty even type targeted for
significant reduction they identified the features, functions,
capabilities or support diagnostics tools needed to realize the
goal of the design change. Figure 5 shows an example of
another framework used to evaluate the different design
proposals.
Because many of the changes required
considerable changes to both the product design and in how
the product would be supported once released (including the
diagnostic tools that would be needed by the support team to
correctly diagnose event types that would use a customer
self-repair process) this was a cross-functional team including
R/D, manufacturing, marketing and support resources. Also
note that the table’s ‘Importance’ column included customer
satisfaction considerations to help balance the need to reduce
warranty costs and customer satisfaction (company brand).
In fact marketing frequently calibrated customer satisfaction
with both how well specific support processes such as phone
support worked and customer satisfaction with the support
processes that were used (customer self-repair vs. benchrepair by an ASP).
Dependency Planning
BIOGRAPHY
Warranty events naturally fits to how product teams
make decisions throughout the product life cycle.
Warranty
Event
Importance*
Planned Actions
Required
features, functions,
capabilities, or
diagnostic tools to
realize savings
Projected
Warranty
Costs
[$]
Projected
Warranty
Savings
[$]
1.
Design for
improved
serviceability
[1½ hr. total]
Reduce AFR by
50%
1.
Cabinet
re-design
ID component
with ½ of current
AFR
$150K/yr.
$298K/yr
Design for self-fix
by customer IT
staff
1.
Cabinet
re-design
Write/deploy
diagnostic tools
$158K/yr.
$167/yr
…
…
[1to10]
Event 1
8
2.
Event6
7
1.
…
…
…
2. J. Bai and H. Pham, Warranty Cost Models of Renewable
Risk-Free Policy for Multi-Component Systems.
European Journal of the Operational Research, vol. 146,
2004
3. S. Kmenta and K. Ishii, Scenario-Based MFEA: A Life
Cycle Cost Perspective.
2000 ASME Design
Engineering Technical Conference
4. R. Latino and K. Latino, Root Cause Analysis–Improving
Performance For Bottom Line Results, CRC Press, 1999
5. D. Kuettner, Data-Driven Warranty Management,
Warranty Chain Management Conference, 2005
6. Kleyner, Sandborn, Boyle, Minimization of Life Cycle
Costs Through Optimization of the Validation Program –
A Test Sample Size and Warranty Cost Approach, RAMS
2004
2.
2.
…
e-mail: bobm@opsalacarte.com or
robert_mueller@marisan.com
Note: Importance ranking includes both customer satisfaction and branding considerations
RAMS 2008 ©
15
Figure 5 – Dependency Planning
After appropriate validation that the designs were viable,
the goals, new features and functionality (including
diagnostic tools development) where then incorporated into
the overall Project, Reliability and Test Plans. Appropriate
metrics and other criteria were added to the exit criteria of
their development life cycle.
4.5 Case Study Results
The warranty costs for the product used in this case study
were carefully tracked through the first 18 months after
market introduction. The results were:
• Actual total warranty costs were 5% less than their
targets.
• Relative cost contribution by warranty event type of the
new product’s event types mostly tracked what the model
predicted.
• Customers were very satisfied with the customer selfrepair process: good diagnostics (diagnosed problem
correctly) and faster time to repair with less hassle.
REFERENCES
1. E. Arnum, Warranty Week. May, 2007,
www.warrantyweek.com
Robert H Mueller, M.S., CQE
Ops A La Carte & The Marisan Group
1030 Oakland Ave
Menlo Park, CA 94025 USA
Robert Mueller has 35 years of experience in product
development and management of software intensive products
for the computer, analytical and medical industries at
Hewlett-Packard and Agilent Companies. Robert Mueller
received his B.S. and M.S. degrees in Physics from Northern
Illinois University before joining Hewlett-Packard Co. He is
currently a senior consultant with both Marisan Group and
Ops A La Carte focused on R/D product strategy
development, agile development methodologies, Warranty
and SW Reliability engineering. He is a Certified Quality
Engineer.