STRATEGIC APPLICATIONS OF TOTAL COST OF OWNERSHIP (TCO)
Several trends have boosted the adoption of a strategic purchasing
focus. These trends include more emphasis on the quality of purchased
materials and services, supply base rationalization, and increased
global competition, to name just a few, all in the light of the growing
recognition of the significance of purchasing expenditures (Ellram and
Siferd 1998). Purchasing decisions quite often affect a large part of a
company's total costs, not only in terms of direct acquisition
costs but also regarding indirect costs in the areas of inventory
management, quality assurance, administration, and payment, among
others. TCO is a tool that can serve to analyze these indirect costs,
and is argued to be one of the important instruments in supporting a
more strategic focus on purchasing and supply management (Van Weele
2005; Wouters, Anderson and Wynstra 2005).
Ellram and Siferd (1998) identify three levels of TCO analysis
supporting cost management: operational, tactical, and strategic. In
practice, TCO is mainly applied at the operational and tactical levels.
Examples of this are TCO models developed for the purpose of managing,
measuring, and improving individual suppliers. TCO can also be used to
think about cost at the strategic level; as such, a TCO model could be
the starting point to redesign and make the supply chain more cost
efficient. However, these latter applications of TCO have received scant
attention in prior research. Most of the extant literature focuses on
the mechanisms of constructing a TCO model.
The current research aims to make a contribution to the literature
not only by showing how a TCO model can be developed but also how such a
model can be used to manage suppliers and improve the supply chain
process--as opposed to merely selecting suppliers on the basis of TCO.
The primary objective of the model developed in the current study is not
to facilitate supplier selection, but to assist the firm in managing the
ongoing performance of their supply base and making volume-allocation
decisions.
To help focus these improvement efforts, key performance indicators
(KPIs) were introduced in the TCO model. This represents a contribution
beyond the current TCO literature, by providing an
"intermediate" level of indicators that makes the relation
between certain process improvements and their impact on TCO much more
transparent. It also serves to delineate the respective impact that the
buying organization and the supplier can have on total cost; the KPIs in
the current model refer solely to supplier performance.
This paper presents the results of a case study on a company
operating in the service industry. The focal company, Carglass, is a
leading vehicle glass repair and replacement expert operating in the
after sales or replacement market. Traditionally, TCO models have been
developed predominantly to serve decision making in manufacturing
companies (e.g., Degraeve and Roodhooft 1999). There is little research
on the applicability of TCO in a service environment (Degraeve, Labro
and Roodhooft (2004) being an exception). In recognition of the
ever-increasing importance of services in today's economy, this
seems counterintuitive and should have spawned additional research
interest in the area of TCO in service companies (Axelsson and Wynstra
2002).
The next section explains the concept of TCO and its applications.
Next, the case study carried out at Carglass is presented. After a short
introduction to Carglass and the glass purchasing decision under study,
the research approach is discussed. The current research approach
adheres to the framework developed by Degraeve and Roodhooft (2001),
which serves as a conceptual umbrella for the paper. The final section
addresses conclusions and implications.
CONCEPT OF TCO
TCO is a purchasing tool and philosophy aimed at understanding the
relevant cost of buying a particular good or service from a supplier
(Ellram and Siferd 1998). The concept takes into account all costs that
the purchase and the subsequent use of components entail in the entire
value chain of the company (Shank and Govindarajan 1992), and thus
expands the notion of purchasing cost by combining the life cycle cost
effects with the acquisition price.
The approach requires the quantification of qualitative factors
into monetary terms, which enables supplier comparison not only on
quantitative factors like price and delivery time but also on elements
that are more difficult to measure, like quality. For example, a company
that wishes to incorporate price and quality into a TCO model may wish
to add to the purchase price the cost of rework on items that are below
quality standards, or a cost supplement based on the actual percentage
of quality defects times the cost for purchasing a replacement item.
This approach incorporates all relevant costs in the model. As a result,
comparisons of suppliers and their respective offerings are made on the
basis of evaluation of all relevant performance characteristics on a
monetary basis.
As a management-accounting-oriented purchasing approach, TCO is
most often used for the supplier selection decision (Degraeve, Labro and
Roodhooft 2000; Degraeve and Roodhooft 2000). However, it could also be
used to evaluate a supplier's performance in an attempt to enhance
the value delivered to the buying organization (Carr and Ittner 1992).
Other uses of the cost method include the assessment of the purchasing
department itself (Degraeve and Roodhooft 1999), and supporting
negotiations with suppliers and volume allocation among suppliers
(Ellram 1993).
The actual scope of TCO may differ across firms and products. A
process flow diagram can be drawn up to determine where activities of
suppliers take place and then categorize these activities according to
some relevant, purchasing-related dimensions. Activities related to
purchasing can be divided into pre-transition, transaction, and
post-transaction elements. Alternatively, one can use the division by
Ellram and Siferd (1998), which breaks down the purchasing activities
into six categories: management, quality, price, communications,
service, and delivery.
To develop an understanding of total costs, alternative approaches
can be used. The first method is known as the monetary-based method,
which allocates the costs of purchasing an offering (good or service) to
the different cost components based on true costs. Calculations could be
based on activity-based costing (ABC), which explicitly uses the
activities that drive costs to assign (overhead) costs to items. (1) The
monetary-based method is time-consuming, but also precise and relatively
easy to interpret.
Another approach is the cost-ratio or value-based method (Carr and
Ittner 1992; Ellram 1995). The value-based method combines monetary with
qualitative performance information, which is more difficult to express
in monetary terms. On the basis of non-monetary, historical information,
for instance supplier-rating scores of several suppliers, a total cost
factor is calculated (Wynstra and Hurkens 2005).
As a third method, Degraeve and Roodhooft (2000) propose a
mathematical programming decision model that can be formulated for
supplier selection and order quantity determination. This method is far
more quantitatively sophisticated, but offers insights into both
supplier selection and order quantity determination.
In the current case study, the monetary-based approach is used in
combination with the framework proposed by Degraeve and Roodhooft
(2001). In their framework, Degraeve and Roodhooft combine the steps in
the procurement value chain with three levels at which costs could be
aggregated. During the purchasing process, costs could be incurred
during acquisition, receipt, possession, utilization and elimination.
Purchasing activities are divided into three hierarchical levels:
supplier-level activities, ordering-level activities, and unit-level
activities. These levels are subsequently used to assign costs.
The main reason for opting for a more complicated, monetary-based
method is because of the fact that glass purchases are the single most
important purchase category at Carglass. Given the purchase volume
involved, it makes sense to invest in a detailed, more precise method,
as opposed to a more simple value-based method (Ellram 1995; Wynstra and
Hurkens 2005).
IMPLEMENTATION OF TCO ANALYSIS
Despite its conceptual attractiveness, TCO analysis does not seem
to be applied very widely. A recent study investigated the application
of techniques such as TCO and value analysis in Dutch companies. (2) The
study was aimed specifically at the purchase of MRO items, such as
electro motors for the production process, but also contained questions
on the subject of TCO in general (Wouters, Anderson and Wynstra 2005).
The study revealed that many purchasing managers have little experience
in applying TCO and/or value analysis. Interviews with purchasing
managers at a number of Dutch companies also showed that on the one hand
TCO calculations are seen as a very relevant method for the purchasing
process, but on the other they are used explicitly and elaborately only
in a few cases (Wynstra and Hurkens 2005).
The major barrier to TCO implementation seems to be the lack of
readily available data. The data used in the TCO model need to be
specified at a very detailed level and these data are often very hard to
gather in an organization. Other barriers for implementation are
cultural issues that relate to general resistance to change, issues
related to educating and training people in the firm, including the
purchasing function, to overcome misconceptions about TCO and resource
allocation (Ellram 1994).
These barriers could be overcome by following certain steps in TCO
implementation. Using structural equations modeling to analyze the
results of a survey among 310 purchasing decision makers, Wouters,
Anderson and Wynstra (2005) found evidence that top management and
functional management support are important mechanisms to implement
TCO-based purchasing decision making (as opposed to a primarily
price-oriented decision process).
However, in order to achieve the top management support required
for specifically implementing TCO-based decision tools, the purchasing
function must first show a clear commitment to a more strategic
orientation toward purchasing and supply management. The subsequent
steps to actual TCO implementation include building experience with the
analysis of cost and performance of purchase items in an effort to
improve information quality, gaining some initial successes with using
TCO as a basis for purchasing decisions, and only then implementing some
form of TCO-based performance review and reward system (Wouters,
Anderson and Wynstra 2005).
As will be described in the following section, top and functional
management support for the development and implementation of a TCO
analysis tool is quite strong at Carglass, which definitely enhanced the
implementation process. This support was because of the sense of urgency
caused by an analysis of some current problems in the supply management
process.
The next section focuses on developing a TCO model, which enhances
Carglass' capability to better understand the total costs
associated with acquiring their most important purchase item, glass
(i.e., car windows). Traditional TCO studies have been mainly carried
out at manufacturing companies (i.e., Degraeve and Roodhooft 1999). In
contrast, the current study took place at a service company. The model
helps Carglass identify and prioritize certain process improvement
options with suppliers. Moreover, the model provides Carglass with
insights into the consequences of changing the volume allocation among
preferred suppliers. TCO analysis enables the firm to make an explicit
trade-off in determining the allocation percentages.
DEVELOPMENT OF A TCO MODEL AT CARGLASS
Carglass, part of Belron International, is a leading vehicle glass
repair and replacement expert operating in the after-sales market, with
locations in a number of European countries. Carglass' assortment
comprises windscreens (WS), body glass (3) (BG) and rear screens (RS)
for any brand and/or type of car. The windows are mainly passenger car
windows, but also includes some coach and truck windows as part of the
assortment. These windows are purchased from seven suppliers from around
the world, which have earned the distinction of being preferred
suppliers. Two suppliers (later referred to as A and B) make up the
larger part of Carglass' glass purchases.
The suppliers deliver the purchased glass to any Carglass
distribution center in Europe (seven in total). From these points, glass
is delivered to service centers, which service clients with damaged car
windows from points-of-sales located throughout the countries in which
Carglass is represented. An order, which is placed during the day, is
delivered to the service center the next morning. These service centers
carry out the actual replacement activities for a specific client.
Traditionally, Carglass made their purchase decisions based on
purchase price only. However, quality and delivery performance problems
prompted Carglass to initiate supply chain analyses on a regular basis.
These analyses indicated considerable additional costs incurred because
of poor delivery performance, low glass quality, and related issues. For
example, poor delivery performance in some cases resulted in rush
deliveries, thereby incurring additional costs for Carglass. If Carglass
is unable to carry out a rush delivery, the service center will be short
of a screen. As a result, the service center has to buy the screen from
a car dealer, which is more expensive, or else the client cannot be
served.
Carglass discussed the results of these analyses with their board
of directors. As a result, the board directed Purchasing to broaden the
supplier selection process to go beyond price considerations. It was
decided that TCO should be the starting point for this new approach to
purchasing decision making. TCO also became part of a continuous
improvement initiative focused ultimately on reducing the total supply
chain costs.
METHODOLOGY
The aim of the project was to build a spreadsheet-based tool for
calculating the TCO for glass purchases. Carglass distribution (Hasselt
Distribution Center), which supplies service centers in Belgium, the
Netherlands, the north of France, and Nord-Rhein Westfalen, was
identified by Carglass to serve as a test case for the development of
the model. The tool should support purchasing and supply chain process
improvements and annual supplier selections and negotiations. Supplier
selection in this case does not refer to the actual
"recruitment" of a supplier, but to the allocation of the
total purchase spend among the seven existing main suppliers. A
well-performing supplier will thus obtain a larger part of
Carglass' business, up to a certain maximum share.
The initial objective was to implement a TCO management approach
for Carglass' total value chain (from supplier to client). Later in
the research it was decided to limit the study to an analysis of the
stages from supplier to the distribution center (DC). This resulted from
preliminary investigations that indicated that the process from the DC
to the service centers was relatively simple in terms of logistical and
administrative processes, and showed very little variation among the
different suppliers. Furthermore, the majority of the costs associated
with supplier performance will be incurred in the trajectory
supplier-DC. The problems related to supplier performance are solved
mostly in isolation from the service center. While based primarily on
the situation in Belgium, the tool should be generalizable to other DCs.
First, a business process analysis was carried out to identify all
relevant physical and administrative processes associated with
purchasing vehicle glass from suppliers and getting this glass delivered
to the DC. This analysis was performed in close collaboration with a
Carglass business analyst.
A cost driver and rate analysis was subsequently carried out to
determine the relevant cost drivers for allocating costs and their
rates. This was done by studying the actual administrative and physical
handling processes, among others, through interviews with managers and
employees from different departments involved and in situ time studies
of the various activities. For financial and other performance data,
various Carglass systems, databases, and reports were analyzed, such as
the supplier rating and the ERP system. A preliminary model was
developed, which included calculations of TCO values. This model was
presented to and discussed with Carglass on a number of occasions, after
which it was revised. The final model is presented in the current
research.
ANALYSIS
This section presents the results of the process analysis, after
which the relevant cost drivers and the associated rates are determined.
Only the major cost components (i.e., the components that result in
large differences in costs between suppliers) were included. These
drivers could be at the unit level (e.g., material cost per unit), the
order level (e.g., cost of an inspection), or the supplier level (e.g.,
cost of identification and certification of a supplier). This approach
to designing the TCO model closely resembles the method proposed by
Degraeve and Roodhooft (2001). However, their process terminology
(acquisition, reception, etc.) has been translated into the terms used
by Carglass.
Mapping the Relevant Business Processes
Carglass' supply chain performance report was used as a point
of departure for gathering information regarding the glass supply
process and the factors impacting costs. Gaps were filled and
ambiguities were resolved by consulting the strategic sourcing manager,
who was the project leader on behalf of Carglass, and the business
analyst, who was responsible for carrying out the supply chain analyses.
The life cycle of a window was taken as a starting point for
identification of a number of processes, both physical and
administrative. An overview of these processes is given in Figure 1.
[FIGURE 1 OMITTED]
It should be emphasized that physical processes are not the only
relevant aspect for the TCO model. Many physical flows have to be
supported by administrative processes, including supplier monitoring and
administration. Although not all of these activities are shown
explicitly in Figure 1, these processes are also incorporated into the
TCO model, for example, the extra time per window needed for
administering a dealer window. Other supporting processes like acquiring
human resources only have an indirect link with the physical flow of a
window. Therefore, these latter processes are excluded from the TCO
model.
Carglass' main activities comprise ordering and receiving car
windows from preferred suppliers and, after the quality has been
checked, transferring these windows to the service centers. Surplus
windows may either be put on stock in the warehouse or returned to the
supplier. Quality defects are returned to the supplier. If a window
cannot be delivered by preferred suppliers, because of poor delivery or
low-quality performance, Carglass has to buy from dealers (adverse buy).
Buying from dealers can also occur as a result of the introduction of
new windows by a car manufacturer, while the suppliers have no
"copy" of the new window available (dealer buy). (4) The
preferred suppliers will try to develop copies of these new windows as
soon as possible; when they do, a quality confirmation is required
before Carglass orders windows from preferred suppliers. This whole
process is constantly monitored by Carglass.
These activities and their respective cost categories are discussed
in more detail hereafter.
Cost Categories
The life cycle begins with a newly introduced window as part of a
new car brand and/or type. In this case, Carglass' suppliers are
not yet able to manufacture this window. In order to serve clients with
this new car, Carglass has to purchase original windows from a dealer,
which is referred to as "dealer buy."
The next phase is "quality." Newly introduced windows are
"copied" by Carglass' suppliers as soon as possible.
Before a "copied" window is included in Carglass'
assortment, a quality confirmation check is performed to ensure that the
copied window fits the car and that lifecycle quality is according to
standards. In most cases, the supplier performs this confirmation check,
but for one supplier Carglass does its own verification. (5)
When windows have been delivered to the DC, either by the regular
suppliers or by dealers, an inbound "quality check" is carried
out. This is done by means of a random sample check (e.g., check window
no. 1, 7, 9, 13 and 19 from four of the 20 crates received). If a
window, or an entire crate in case of a bad production run, is rejected,
it is returned to the supplier. If windows that are directly needed by
the service center are rejected, Carglass has to obtain these windows
from dealers ("adverse buy").
Windows that have quality defects or that were delivered without
being ordered are returned to the supplier ("supplier
returns"). These windows are collected in separate crates for each
supplier. These crates are returned once a month. One of the suppliers
first sends a representative to approve the return shipment; returns
that are not accepted by this representative cannot be sent back to the
supplier. Furthermore, damaged windows are not always refunded.
If there is a difference between what was ordered and what was
actually delivered, a decision has to be made. When what was ordered
exceeds delivery, Carglass has to perform an adverse buy. This means
that even though the regular suppliers can supply that particular
window, the window still has to be bought from a dealer because of
insufficient delivery.
When the delivery exceeds what was ordered, another decision has to
be made. Carglass can either choose to put the surplus on stock (which
is usually done when it concerns windows that are sold regularly) or to
return the surplus to the supplier with the supplier taking care of the
return transport.
After a window has been accepted, it enters the
"warehousing" stage, which results in "handling,"
"inventory holding," and "storing" costs.
The windows that are accepted are moved into the warehouse in a
"handling" operation. The packages that the supplier uses
impact the amount of handling needed in the warehouse. The costs
associated with this issue are substantial. Indirectly, the amount of
dealer buy increases the warehousing cost, because of the fact that
dealer windows are wrapped separately and thus take more time to unpack
than the crates of the regular suppliers that hold a dozen windows each.
Two people are employed to unpack delivered goods. One of them is
assigned to unpack the supplier windows, and the other to unpack dealer
windows. They both work full time on this job. However, the
dealer-window-unpacker handles some 100,000 windows a year while the
supplier-window-unpacker handles a number close to 1,000,000.
Furthermore, minor variations exist with regard to the number of windows
preferred suppliers pack per crate; the more the windows per crate, the
less the handling time per window.
Regarding the inventory holding costs, forecasts are made for the
coming period based on sales in the service centers. This forecast is
then ordered from suppliers, upon which delivery takes place. Inventory
can therefore exist because of two reasons: (1) there is a difference
between the forecast of sales and what is actually being sold; and (2)
there is a difference between what is ordered from the supplier and what
is actually delivered by that supplier. As the model aims to highlight
extra cost because of supplier behavior, only the second reason was
taken into account as a cause of inventory holding cost.
Once the windows have arrived in the warehouse itself,
"storing" costs are mainly affected by the actual volumes of
windows.
Throughout these processes, suppliers have to be monitored
("supplier monitoring"). Three people are involved in
monitoring and analyzing suppliers' performance and in resolving
any issues that arise.
Finally, the TCO of the different suppliers is affected by their
payment terms ("cash flow").
As the model was to be used for negotiating prices and initiating
improvement actions, it was important for Carglass to be able to monitor
the whole supply process, and not just the problems caused by suppliers.
Therefore, the researchers adopted a process focus instead of a problem
focus. Whereas a problem focus would only take into account costs
because of low performance of the supplier or specific circumstances, a
process focus assists Carglass gain insights into the balance between
regular process costs and costs because of problems (a high supplier
performance could still result in substantive process costs). This
information can then be used in the negotiation process to distinguish
between suppliers clearly. For example, the process focus also includes
the calculation of TCO effects of payment terms. Although current
suppliers have identical terms, Carglass wishes to be able to
investigate the impact that changes in payment terms would have on TCO.
Identifying Relevant KPIs
All cost categories can be related to factors that drive these
costs. For instance, the cost category "dealer buy" is
strongly influenced by the factor time-to-market, as the longer it takes
the supplier to copy a newly introduced window, the more Carglass has to
resort to dealers for these windows. This factor could be regarded as a
KPI, based on which Carglass can monitor ongoing performance, preferably
with the help of their suppliers.
This case study attempted to identify KPIs for all cost-incurring
activities. After initial identification of the costs at the supplier,
order, and unit levels, the supplier-induced costs were separated
explicitly from the other costs. Only supplier-induced costs are taken
into account as these costs are influenced by the actions of the
suppliers. These actions are linked to costs with the KPIs. As a result,
costs are not only measured, but a tool is developed that allows for
actively managing costs and thinking about redesigning the process so
that costs can be eliminated structurally.
Discussions with Carglass employees provided the researchers with
considerable insights into the extent to which Carglass had to buy glass
from car dealers, impacting the glass spend. Mapping the processes
unveiled the extent to which Carglass' forced purchases from car
dealers are directly related to supplier performance in multiple ways.
In the situation where the supplier has not yet copied a newly
introduced window, Carglass has to buy from a car dealer (dealer buy),
which is more expensive. The longer the supplier needs to copy a newly
introduced window, the more the dealer buys for Carglass. Thus, the
supplier's time-to-market is the driving factor (KPI) here.
In the second situation, where the supplier does not deliver on
time or does not deliver what was ordered, Carglass has to buy from a
car dealer (adverse buy), thereby again incurring extra costs. The
larger the difference between what should be delivered and what was
actually delivered, the larger the adverse buy. The driving factor is
delivery performance.
The final situation, where the supplier delivers glass of poor
quality, also results in an adverse buy. The larger the number of
rejects, the larger the adverse buy. The driving factor here is quality
performance.
Therefore, the larger part of the costs is dependent on three
important factors (KPIs): time-to-market, delivery performance, and
quality performance. In addition to this, extra costs are incurred as a
result of the payment terms. A difference in payment terms, for example,
of five days can result in substantial cost savings. This is a fourth
important driving factor.
Finally, some other, somewhat smaller cost categories can be
distinguished. The supplier's delivery performance determines the
cycle stock and the safety stock. More inventory holding costs are
incurred when the stock levels are higher. Interestingly, the costs in
this category are small in comparison with the four categories mentioned
above.
As discussed, the packages that the supplier uses also have an
impact on the amount of handling needed in the warehouse. Finally, a
large number of quality defects will result in a higher number of
supplier returns. Whether or not the supplier reimburses these rejects
can contribute to substantial costs as well. In the current situation,
rejects are not reimbursed by any of the suppliers. The representative
sent to Carglass by one of the suppliers to check whether the supplier
should accept the returns or not comes from abroad and visits once every
2 months. The other suppliers ship returns monthly. Handling of supplier
returns obviously involves some labor costs too, but their magnitude is
negligible in comparison with the costs discussed earlier.
For each of the different cost categories identified, Table I lists
the KPIs that impact these costs.
Determining Cost Formulas
Cost calculations were developed for the different cost categories
mentioned earlier. The data needed to perform the calculations were
drawn from Carglass' supplier rating, ERP, and accounting systems.
For some categories, it was harder to gather data than for others, as
data were available at varying levels of detail.
The costs for each cost category were calculated on a separate
sheet, making it easy to link the costs to a specific category. The
suppliers, in one way or another, can influence all cost drivers. These
cost drivers or KPIs enable Carglass to determine in what way and to
which extent a change in supplier performance affects the associated
costs. In Appendix A, one can find the complete specifications of the
cost formulas, including the KPIs.
RESULTS
The following sections present the results of the case study. The
model is presented, after which its use is elaborated.
Final TCO Model
The final model has been developed in a spreadsheet (Microsoft
Excel). The spreadsheet consists of a series of calculations for the
different processes identified as being important. Most of the sheets
are interlinked, providing an easy reference to the underlying
calculations. Figure 2 provides an illustration of how the TCO per
supplier is broken down into individual cost components.
The spreadsheet works based on a central sheet, in which the
general data can be put, as well as on a separate KPI sheet. The KPI
sheet contains factors contributing to high costs, such as
time-to-market, delivery performance, quality performance, and payment
terms. Furthermore, the spreadsheet highlights graphical overviews of
the cost structures per supplier, both in absolute and relative numbers.
Finally, the spreadsheet presents an overview of the relative TCO
performance per cost category/process. The best performing supplier is
set at 1, while the others are valued relative to the best performer.
[FIGURE 2 OMITTED]
Use of the Model
The spreadsheet can be used to compare suppliers on different cost
categories/processes. The information obtained from this comparison can
be used to allocate the glass portfolio to suppliers, including which
car brand/type windows to obtain from which supplier, or to discuss
areas for improvement with suppliers and to negotiate glass prices. The
KPIs provide the opportunity to carry out sensitivity analyses, so that
Carglass can set targets before entering negotiations. The model thus
provides insights into the consequences of changing the volume
allocation among preferred suppliers, which allows Carglass to make an
explicit trade-off in determining the allocation percentages.
Carglass is using the TCO model in different ways. Between August
2003 and March 2004, the responsible purchasing manager had conducted an
extensive internal "roadshow" to demonstrate the model and
create awareness among the different buyers and other functions across
Europe. Based on feedback from various sources, minor modifications have
been made in the grouping of cost categories and the user interface. In
2004, the tool was used to guide and monitor two strategic drivers for
supplier improvement: reduction of time-to-market and the reduction of
stocks. Incidentally, it has already been used in discussions with
individual suppliers to explain volume shifts toward other suppliers,
trigger process improvements and, to a lesser extent, negotiate price
reductions. The data needed to update the TCO model were then integrated
into the monthly supply management reports in order to monitor cost
savings.
CONCLUSIONS AND IMPLICATIONS
The fact that the spreadsheet has already been partially adopted
and developed further proves its added value to Carglass. Even the
gathering of data, which is usually a large barrier to the development
of TCO models, was relatively easily overcome because Carglass assigned
a business analyst to the project. Furthermore, the resistance to change
was low within the organization as Carglass initiated this project to
assist in overcoming some of the challenges associated with short- and
long-term financial consequences of variations in supplier performance.
This paper shows that TCO can be a useful tool to uncover the
obvious as well as the hidden costs of conducting business with
different suppliers. This does not only hold true for use in supplier
selection but also in negotiation rounds. While Carglass does not wish
to choose among its suppliers, it does wish to be able to shift volume
between them when necessary. Admittedly, the calculated rates may not
provide a complete picture of costs; they do offer an estimate of the
relative magnitude of the different cost categories. In the negotiation
rounds, Carglass can now focus on the cost savings that are concealed in
the contractual terms, which affords opportunities for both Carglass and
suppliers to improve their businesses.
Examples of these are shifting quality confirmation activities to
the supplier and investigating the option of committing adverse buys
with non-preferred suppliers instead of dealers. Additionally, Carglass
can now more thoroughly realize the enormous impact that differences in
payment terms have on TCO. This particular finding has specific and
immediate usefulness in negotiating. Occasionally, a supplier has lower
costs of capital than the customer and thus may be more interested in
extending payment terms rather than giving price reductions. In general,
one could argue that using TCO analyses in supplier negotiation
increases the number of variables on which to negotiate, thereby
increasing the possibilities of a "win-win" solution.
This paper has also demonstrated that in the case of a
monetary-based TCO model, it is crucial to develop an accurate, precise,
and complete representation of the physical and administrative processes
in the pre-transaction, transaction, and post-transaction phases of the
purchasing process. Even though the processes at Carglass are relatively
straightforward and lack complex production processes, this process
analysis is quite time consuming.
The identification of KPIs and explicit connection of these
indicators to the different categories of costs is a relatively novel
feature of this type of analysis. The indicators as such were not new to
Carglass, which makes it easier for purchasing decision makers to adopt
and embrace the TCO analysis model. At the same time, linking the
indicators to cost calculations and demonstrating the actual financial
effects of certain performance variations on different indicators serve
to make the tradeoffs between improving on one indicator versus the
other more transparent.
Furthermore, it has been a conscious decision to develop KPIs that
can be explicitly linked to the supplier's performance. Improving
the performance of the total supply chain requires improvements in the
performance of all the parties involved, including Carglass.
Carglass' objectives have been translated into KPIs, and
subsequently these KPIs are the starting point for developing KPIs for
the supplier by investigating how the supplier can contribute to total
performance improvement.
Obviously, there are opportunities for model enhancement and
refinement. An important limitation of this study lies in the level of
aggregation. Even though Carglass' management system contains
detailed information on item level, the time span of this project was
too short to develop the model at this level of detail. The model
therefore only provides calculations of the total costs incurred per
supplier, for the different items combined (front, side and rear
windows).
In addition, not all costs associated with the supply of windows
are incorporated into the model, as discussed earlier. Admittedly, doing
this would result in a more accurate model. However, the initial
experiences demonstrate that in its current form the tool creates
sufficient understanding of the factors impacting the TCO of car
windows, thereby providing Carglass with actionable information with
which to manage their suppliers and to improve their overall purchasing
and supply management processes.
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APPENDIX A: COST FORMULAS
* Dealer buy
** TTM factor = {Time-to-market} x {Number of windows} x {Share of
purchase spend}.
** Dealer buy because of new window = {Annual purchase volume
dealer} x {Percentage dealer buy because of new window}.
** Dealer spend supplier = {TTM factor}/{[SIGMA](TTM factor)} x
{Dealer buy because of new window} x {Purchase price
preferred/non-preferred/dealer - Purchase price preferred supplier}. (6)
* Quality confirmation
** Labor cost of quality confirmation = {Number of people assigned
to quality confirmation} x {Labor cost} x {Percentage of labor spent on
quality confirmation}.
** Quality confirmation cost per supplier = {Number of checks
necessary to accept a new window} (7) x {Labor cost of quality
confirmation}.
* Quality check
** Labor cost of sample check = {Annual purchase volume} x {Sample
percentage inbound quality check} x {Average time spent on checking one
window} x {Labor cost per hour}.
* Supplier returns
** Value of returns = ({Number of returns} x {Weighted average
preferred price}).
** Part of returns inventory = {Value of returns}/{[SIGMA](Value of
returns)}.
** Warehouse cost returns per supplier = {Part of returns
inventory} x {Warehouse cost}.
** Opportunity cost of supplier windows = {Value of the returns} x
(1 - {Refund rate}).
** Labor cost of returns = {Number of people assigned to quality
supplier returns} x ({Annual labor cost}/{Annual working time}) x
{Average time spent on returning one window} x {Number of windows
returned}. (8)
* Adverse buy
** Number of WS/BG/RS not delivered = {1 - Supplier performance
WS/BG/RS} x {Annual purchase volume WS/BG/RS}.
** Adverse buy because of non-delivery = {Number of windows
WS/BG/RS not delivered} x {Percentage bought from
preferred/non-preferred/dealer} x {Purchase price
preferred/non-preferred/dealer - Purchase price preferred supplier}.
** Number of WS/BG/RS of low quality = {Number broken/scratch
A/inclusions A (WS/BG/RS)}/{Number of windows checked} x {Total annual
purchase volume}.
** Adverse buy because of low quality = {Number of windows of low
quality} x {Percentage bought from preferred/non-preferred/dealer} x
{Purchase price preferred/non-preferred/dealer - Purchase price
preferred supplier}.
* Warehousing
* Handling
** Total number of crates = {Total annual purchase volume}/{Average
number of windows per crate}.
** Total number of dealer packages = ({Number of WS not delivered}
x {Percentage bought again from dealer} + {Number of BG not delivered} x
{Percentage bought again from dealer} + {Number of RS not delivered} x
{Percentage bought again from dealer} + {Number of windows of low
quality} x {Percentage bought again from dealer})/{Average number of
windows per dealer package}.
** Total number of hours spent on crates/dealer packages = {Total
number of crates/dealer packages} x {Time spent on crate/dealer
packages}.
** Labor cost of supplier windows/dealer windows = {Total number of
hours spent on crates/dealer packages} x {Annual labor cost}/{Annual
working time}.
* Inventory holding
** Cycle stock = {Purchase volume} x {Average ordering interval}.
** Total annual inventory cost = {Cycle stock} x {Value per stock
keeping unit} x {Interest rate}.
** Safety stock = {k} x {sd demand during leadtime}, where sd
demand during leadtime = [square root of ((average leadtime)[.sup.2] x
[[sigma].sub.demand.sup.2] + (average demand)[.sup.2] x
[[sigma].sub.leadtime.sup.2])]
* Storing
** Warehouse cost per supplier = {Cycle stock}/{Maximum capacity of
the warehouse} x {Warehouse cost}.
* Supplier monitoring
** Total labor cost of supplier monitoring = {Number of people
assigned to supplier monitoring} x {Labor cost} x {Percentage of labour
spent on supplier monitoring}.
** Labor cost supplier monitoring per supplier = {Percentage of
total supplier monitoring} (9) x {Total labor cost of supplier
monitoring}.
* Cashflow
** Interest cost = {Interest rate} x {Total annual purchase value}
x (30 - {Payment term}).
AUTHORS
Krisje Hurkens is a consultant at Significant B.V., a company
providing consultancy services on procurement and support services, The
Netherlands.
Wendy van der Valk is a Ph.D. candidate in purchasing and supply
management at the Erasmus Research Institute of Management, RSM Erasmus
University, in Rotterdam, The Netherlands.
Finn Wynstra is the NEVI professor of purchasing and supply
management at the Erasmus Research Institute of Management, RSM Erasmus
University in Rotterdam, The Netherlands.
The authors would like to thank Ms. Kristel Hoegaerts, Business
Analyst, and Mr. Raf Verheyden, Strategic Sourcing Manager Carglass
Europe from Belron International, for their assistance and sponsorship
of this project.
(1) A company does not necessarily need to have an ABC system in
place before a TCO model can be implemented, although it may ease the
data-gathering process.
(2) Value analysis is a concept that is often used for products
that are in the engineering phase. Especially regarding the maintenance
and service costs, TCO and value analysis are aimed at the same aspects.
(3) Body glass windows are located on the sides of a car.
(4) Dealer buy and adverse buy thus refer to the same processes,
but differ with regard to their causes. Dealer buy occurs because the
preferred suppliers have not yet produced the new window (the buy is
inevitable), whereas an adverse buy is caused by low performance (the
buy is undesirable).
(5) Carglass does not rely on the quality system of the supplier
because this system does not conform to European standards.
(6) The preferred supplier price is the expected price, as the
supplier does not yet deliver the window.
(7) The time spent by Carglass on quality confirmation activities
is a function of the number of times Carglass needs to perform the
quality confirmation. The supplier can bring down the costs associated
with quality confirmation by delivering high-quality copied windows
("first time right").
(8) The number of windows returned is a function of the quality and
the delivery performance.
(9) The time spent on monitoring individual suppliers is a function
of the delivery and the quality performance. It is difficult to develop
a formula that approaches this function; however, Carglass can base the
calculations on estimations of time spent (percent) on an individual
supplier based on Carglass' historical experience and future
expectations.
Table I COST CATEGORIES AND KEY PERFORMANCE INDICATORS
Cost Categories Key Performance Indicators
Dealer buy Average time-to-market
Quality confirmation Number of checks necessary to approve new window
Quality check Quality performance
Supplier returns Quality performance
Delivery performance
Refund rate
Adverse buy Delivery performance
Quality performance
Warehousing
Handling Average # of windows/crate
Inventory holding Average leadtime
Standard deviation lead time
Storing Purchase volume
Supplier monitoring Time spent on monitoring
Cash flow Payment terms