Paper to be presented at the DRUID 2012
on
June 19 to June 21
at
CBS, Copenhagen, Denmark,
Servitization: The Extent and Motivations for Service Provision amongst
UK Manufacturers
Bruce Tether
Manchester Business School
Institute of Innovation Research
[email protected]
Elif Bascavusoglu-Moreau
University of Cambridge
Centre for Business Research
[email protected]
Abstract
Servitization is the provision of services to clients by manufacturing firms. For over twenty years, servitization has been
advocated is a strategy by which manufacturers in high cost locations can compete against rivals based in low cost
locations, as providing services implies closer customer relations, and moving from a transactional approach based on
making and selling goods, to an more relational approach which may involve providing tailored packages of products
and services, sometimes as integrated solutions. Little is known, however, about the extent to which manufacturers
provide services, their motivations for so doing, or the organizational arrangements associated with providing services.
Drawing on a bespoke survey of 256 manufacturers in the UK, this paper provides evidence where previously there was
little. We reveal that manufacturers typically provide several services, and these are commonly packaged with products.
Where services are charged for, this is mainly on a ?pay-by-use? basis, or under fixed price contracts; performance
based contracts are rare. Most UK manufacturers in our sample are therefore service-enhanced, rather than service
oriented. We also examine firms? motivations for providing services, and the characteristics of firms most likely (and
least likely) to provide services.
Jelcodes:L60,M10
Servitization:
The Extent of and Motivations for Service Provision
amongst UK based Manufacturers
Abstract
Servitization is the provision of services to clients by manufacturing firms. For over twenty
years, servitization has been advocated is a strategy by which manufacturers in high cost
locations can compete against rivals based in low cost locations, as providing services implies
closer customer relations, and moving from a transactional approach based on making and
selling goods, to an more relational approach which may involve providing tailored packages
of products and services, sometimes as integrated solutions. Little is known, however, about
the extent to which manufacturers provide services, their motivations for so doing, or the
organizational arrangements associated with providing services. Drawing on a bespoke
survey of 256 manufacturers in the UK, this paper provides evidence where previously there
was little. We reveal that manufacturers typically provide several services, and these are
commonly packaged with products. Where services are charged for, this is mainly on a ‘payby-use’ basis, or under fixed price contracts; performance based contracts are rare. Most UK
manufacturers in our sample are therefore service-enhanced, rather than service oriented.
We also examine firms’ motivations for providing services, and the characteristics of firms
most likely (and least likely) to provide services.
Key Words: Manufacturing; Service Provision; Income from Services
1
1.
INTRODUCTION
Manufacturing is usually defined as the making of goods, articles or products, especially in factories
and by industrial means or processes. Manufacturing conventionally ‘adds value’ by transforming
raw materials into semi-manufactured and final goods, the utility of which is embodied in the
product; this process of transformation typically involves a series of ‘steps’, with the production of
intermediate goods as components or sub-assemblies, within a value chain. Because final and
intermediate manufactured goods typically embody utility that is retained for some time they can
usually be produced at considerable distance from their place of their final consumption. In this,
archetypal manufacturing differs markedly from archetypal or classic services, which cannot be
stocked, are co-produced by the producer and consumer acting together, and are therefore
provided in close physical proximity to the user.
The declining cost and increased speed of transportation, coupled with political changes and
deregulation, is encouraging the globalization of production, and more particularly the migration of
relatively labour intensive manufacturing from high cost locations, such as the United States and
Western Europe, to low cost production locations, such as China an Eastern Europe. As PWC put it:
“50 years ago ... most products used in Britain were designed and produced here. Now a product
produced entirely in one country is a relative rarity – raw materials typically move across many
countries as they are transformed ... [into] basic components, subassemblies, and finished goods.”
(PWC, 2009, p.9)
These and other forces have seen a relative decline of manufacturing in the UK, as a share of the
economy, and as a share of world production. Yet the UK remains the world’s 6 th largest
manufacturer by value of output, and moreover real manufacturing output has grown in value in
most years since the early 1980s. This implies a substantial growth in productivity - real output per
employee - which increased by almost 50% in the twenty years between 1987 and 2007. This
growth is due to investment in capital equipment, new tools and technologies, some up-skilling and
new working practices such as outsourcing, and innovation (PWC, 2009).
The financial crisis of 2008 and the recession that followed led the UK government recognize the
danger of over-reliance on financial services, and the need to ‘rebalance’ the economy, with a
particular focus on manufacturing. The challenge is considerable. The UK’s balance of trade in
manufactured goods has been consistently negative for the past 25 years, and became larger in the
past decade. Moreover, recessions tend to be particularly harmful to manufacturing, with past
trends showing that manufacturing jobs lost in recessions rarely reappear when growth returns. Yet
the need to rebalance is clear: “if the UK does not find a way to produce more export-competitive
goods ... the pound will eventually weaken to a point where Britons will be forced to import and
consume less.” (PWC, 2009 p.9).
The usual remedies to revive manufacturing include a greater focus on knowledge and high value
added, through increased investments in R&D (which is being encouraged by the provision of R&D
tax credits), training (which is being encouraged by the provision of modern apprenticeships), and
quality. This paper examines another strategy, which is a move towards services, which complement
products and production. It is frequently observed that the distinction between manufacturing and
services is becoming less distinct, or blurred, with more and more companies operating in both
areas, bundling goods and services together in customized packages for clients. The aero-engine
2
manufacturer Rolls Royce is the archetypal example (Johnstone et al., 2009; The Economist, 2009).
Rolls Royce has made a significant and successful transition from being ‘a pure manufacturer’ to
being an integrated solutions provider. It now generates around half of its revenue from services,
and looks to capture value throughout the lifecycle of its products. Another example is Xerox, which
has migrated from being a manufacturer of photocopiers, to becoming a ‘documents company’.
It is thought that many other companies, both large and small, old and new, are or have the
potential to do the same. But we know very little about the extent to which this is occurring. One
reason for this is that official sources are poor at capturing the range of a firm’s activities. Firms are
typically classified by their main line of activity. So Rolls Royce is an aircraft engine manufacturer,
and its engine maintenance activity is therefore unrecognised in most official sources. Some
businesses have been reclassified as their profile of activities has changed. IBM was considered a
manufacturer of computer hardware, but the growth of its software and consultancy business,
coupled with the sale of its personal computer division to Lenovo, means that IBM is now considered
a service company, even though it still manufactures mainframe computers (Gerstner, 2002).
However, some firms are ‘wrongly coded’. Dyson Ltd, for example, is a renowned producer of
domestic appliances (especially vacuum cleaners) and is classified as a manufacturer. However, all
of Dyson’s production is undertaken in Malaysia: R&D, engineering and support activities are
undertaken in the UK. This raises the question as to how to define manufacturing. Some, such as
the Institute for Manufacturing at the University of Cambridge, call for a broad definition which
covers “the various activities that need to be coordinated and performed in order to deliver a
physical product” (IFM, 2006); others would say that classifying Dyson as a manufacturing company
in the UK is misleading.
The aim of this paper is to examine the extent to which manufacturing firms based in the UK are
engaged in the provision of services to their customers, their motivations for so doing, and the
organizational implications of providing services. The paper is structured as follows. Section 2
provides a discussion of servitization as a concept and its theoretical underpinnings. Section 3
outlines the methodology and provides a preliminary analysis. Section 4 provides a detailed analysis
of the survey results. And section 5 provides the conclusions. In another paper we will examine the
performance implications of providing services.
2.
SERVITIZATION: THE CONCEPT, THEORY AND EVIDENCE
All manufacturers need to engage in some services (such as administration) to produce their
products, but these services may be for internal purposes only. Servitization occurs when
manufacturing firms provide services to their clients, as part of their value proposition. It includes,
for example, the installation of products, or their maintenance, on a regular or ‘on demand’ basis.
This trend has been variously described as ‘servitization’ (Vandermerwe and Rada, 1989; Baines et
al., 2009), ‘service infusion’ (Brax, 2005; Eggert, 2011), ‘tertiarization’ (Leo and Phillippe, 2001), and
the provision of ‘product-service systems’ (Mont, 2002; Tukker and Tischner, 2006; Johnestone et
al., 2008) or ‘integrated solutions’ (Davies, 2004; Windahl et al., 2004; Hobday et al., 2005; Davies et
al., 2007). The concept of ‘servitization’ is normally attributed to Vandermerwe and Rada (1988),
who – despite a lack of supporting evidence - proclaimed that: “Servitization is happening in almost
3
all industries on a global scale. Swept up by the forces of deregulation, technology, globalization and
fierce competitive pressure, ... manufacturers are moving more dramatically into services”
(Vandermerwe and Rada, 1988, pp. 315). Quinn et al (1990) also argued that in order to gain
competitive advantage firms should move ‘beyond products’ and embrace ‘service-based strategies’
(c.f., Andersen and Narus, 1995).
Despite these calls, servitization received scant attention in the mainstream management and
engineering literatures before the 2000s, but is now seen as a means by which manufacturing firms
in high-cost locations, can differentiate themselves (Tukker and Halen, 2003; Sawhney et al., 2004;
Davies et al., 2007; Baines et al., 2009). By placing a strong emphasis on service, manufacturers, it is
argued, can build stronger relationships with their clients, and so escape commoditisation and
pernicious price based competition. This transition is however considered to be difficult, and may
even risk the survival of the firm (Neely, 2009), for it ultimately involves a switch from ‘making
products’ to ‘providing service’, which requires a shift from a ‘goods dominant logic’ and mindset, to
a ‘service dominant logic’ and mindset, and associated changes in organizational architecture and
the business model (Normann & Ramirez, 1993; Vargo and Lusch, 2004). As Benedettini and
colleagues put it, “Delivering ... value added services means dealing with a new set of challenges for
manufacturing managers” (Benedettini et al., 2010, p. 25). These challenges relates to the so called
‘service paradox’, whereby firms that do engage in the provision of services often perform less well –
at least initially - than otherwise similar firms that do not (Gebauer, et al., 2005; Fang et al., 2008;
Neely, 2009). When fully developed, servitization is thought to be associated with a business model
based on relationships and customer retention, rather than one based transactions, competing on
product characteristics, and the efficiency of production.
An example of how ‘servitization’ can revive a flagging business is the case of the ICI-Nobel
Explosives Company (Schmenner, 2009; Martinez and Turner, 2011). Until the 1990s, this company
had focused on the production of explosives for coal mining, but its fortunes had declined with the
contraction of that market, particularly in the UK. Production shifted to explosives for quarries, but
as the company’s production process had no inherent advantages over that of rivals, and as the
product was viewed as a commodity, price competition was fierce with no brand loyalty. Customers
exploited their advantage: “Quarries could call at just about any time requesting a delivery the next
day and the company was more or less obliged to react or risk losing the business” (Schmenner,
2009, p. 441); being at the beck and call of customers led to further inefficiencies, such as
maintaining an under-utilized fleet of delivery trucks, and to shrinking profits. The only scarce
resource that ICI-Nobel had was deep knowledge of blasting, and a new software program that could
optimise the location of drilled explosive holes and the timing of the blasts. Using these assets, the
company innovated, provided quarries with a complete service, involving planning, drilling holes,
inserting the explosives, and firing the blast. “The quarry did not pay for the explosive anymore.
Rather, it paid for ‘rock on the ground’ that the ICI-Nobel company provided as a service. No longer
did the quarry have to keep blast planners, drillers, and shot firers on the payroll, and no longer did
it have to inventory any explosives or do anything other than dig up the blasted rock and process it
further. ICI-Nobel, for its part, now had a way to extract some loyalty from its customers and build a
barrier to entry versus the competition; the enterprise became very profitable” (Schmenner, 2009,
p. 442).
4
That services form an increasing share of advanced economies is not in doubt. And nor can there be
any doubt that manufacturing and services are closely inter-twined and interdependent. For even if
production is the defining activity of a manufacturing company, achieving a manufactured output
inevitably requires a much broader base of activities, involving R&D, design, marketing, distribution,
service and support” (Schmenner, 2009; Benedettini et al., 2010). This does not mean, however,
that the same company should undertake all of these activities. They may instead be more
efficiently undertaken by different organizations, or by separate business units within the same
organization. Indeed, declining transaction costs has encouraged increasing specialization and a
growth in the outsourcing of activities previously undertaken by manufacturers ‘in-house’ (Langlois,
2003). This is one reason for the growth in services in the economy (Kakaomerlioglu and Carlsson,
1999), and implies the provision of services by specialized service providers is generally superior to
their provision by manufacturers.
However, the relative merits of specialization (focusing as far as possible on manufacturing) or
integration (combining the production of products with the provision of services) varies with
circumstance and technologies, which can change over time (Langlois,, 2003). The question, then is
not, whether ‘after sales’ business opportunities exist, but whether the manufacturer is in a strong
position to capitalize on these. If it is to be successful, servitization ultimately implies finding and
developing complementarities between the production of goods and the provision of services
(Teece, 1986; Milgrom and Roberts, 1990). Without these complmentarities, the manufacturer has
no innate advantages over third party, or independent, service providers. Rolls Royce, for example,
has integrated production and service provision by integrating a whole host of sensors into its
engines, which help Rolls Royce to predict when component are likely to fail, and these components
can be replaced under preventive maintenance prior to failure, and at a time convenient to the
airline customer, rather than upon failure, which will typically occur at an inconvenient time, and in
an inconvenient place (The Economist, 2009). Meanwhile, an apparently similar company,
Bombardier, which in the UK manufactures railway trains, has struggled to grow its service business,
and indeed has seen some refurbishment and maintenance work drain away to specialist companies
such as Transys, Wabtec, Hunslett-Barclay and Railcare.
Ultimately, the interesting question then is when do manufacturers hold an advantage in the
provision of services, or (how) can they attain an advantage, and when do independent businesses
or business units hold the advantage. In other words, when are production and service activities
complementary economic activities best undertaken by the same business? These are complex
issues, which we cannot fully examine here. The aim of this paper is instead to shed light on the
extent to which manufacturers are engaged in the provision of services, their motivations for so
doing, and to explore the organizational implications of this.
3.
METHODOLOGY AND PRELIMINARY ANALYSIS
To examine the extent of service provision amongst UK based manufacturers we conducted a
bespoke survey of firms in the autumn and winter of 2010. The survey was first piloted with six
firms in the late summer of 2010. Imperial College Business School alumni working as directors and
senior managers in UK-based manufacturing firms were contacted, and six agreed to help by
5
commenting on the questions, their phrasing, and the structure of the questionnaire as a whole.
The survey instrument was then amended.
A sample of firms was drawn from FAME, a dataset based on company accounts information
maintained by Bureau van Dijk. Our aim was to include product based manufacturing firms,
especially with an engineering orientation. We selected firms in the following 2 digit SIC(2003) code
industries 25; 28; 29; 30; 31; 32; 33; 34; 35 and 36, which, according to the records in the FAME
database had between 7 and 1,500 employees. We sought to avoid very small firms, due to the
response burden and consideration that the questions were less likely to be appropriate. Because it
is difficult for individual respondents to have an accurate view on the whole of the business we also
excluded very large firms. Large businesses also receive a disproportional number of requests for
information from academic and other surveys, which often leads to lower response rates. This
sample generation process produced a list of 2,515 firms, which was considered sufficient given our
anticipated response rate of 10% and target of 250 responses. We did not set quotas by firm size or
sector of activity.
The names of company directors and senior managers were also drawn from FAME. Where
identified, the name of the Chief Executive Officer (followed by Managing Director) was preferred.
The survey, a 12 page A4 booklet (including covers), was sent by post to these named individuals in
mid-October 2010. A second mailout was undertaken in mid-November 2010. We also provided the
option to complete the survey over the internet. Meanwhile, between October and December 2010
all the companies that had not responded to the survey were contacted by telephone. This revealed
that some were no longer in business (or had moved away from their recorded address), whilst
others were not engaged in manufacturing, contrary to their SIC coding. Some directors and
managers were spoken to directly, and some of these agreed to participate. Those that had agreed
to respond but who had not done so by early December 2010 were sent a third copy of the survey.
We received responses from 267 firms, although 9 of these were not sufficiently complete to be
usable, and were therefore discarded. Two other responses were from firms that were not engaged
in manufacturing, and these were therefore also discarded. The dataset is therefore comprised of
responses from 256 manufacturing firms. Amongst these firms, the item response rates are
generally very good. This sample represents just over 10% of the original target population, or
11.5% if the firms found to have ‘gone away’, out of business, or not to be engaged in manufacturing
are excluded from the sampled population. This response rate is comparable with those achieved by
other, similar surveys, including the survey undertaken in 2010 by the Centre for Business Research
at the University of Cambridge.
Table 1 provides an overview of the sample of responses to the survey. The firms are of various
sizes, fairly evenly divided between four size classes. Just over half are independent firms, with 45%
being subsidiaries of larger company groups. Nearly 80% were established before 1991, with only
5% having been established since 2001. The firms are also active in a variety of industries, with
machinery, electrical and electronics and the miscellaneous ‘other manufacturing’ accounting for
70% of the sample. Table 2 provides further descriptive statistics on the variables we include in the modelling
below. This shows that correlations between variables are generally low, and there are no problems of
multicollinearity, as the highest Variance Inflation Factor (VIF) amongst the variable is 2.63.
---- INSERT TABLE 1 ABOUT HERE ---6
---- INSERT TABLE 2 ABOUT HERE ---The questions and responses were all been coded in SPSS. Using logistic regressions, we modelled
the response against the target population. This found that whilst there is some variation in the
pattern of response, with lower response rates for transport equipment firms (SIC 34 and 35), and
for firms based in Northern Ireland, overall there were no statistically significant differences in the
propensity to respond by firm size (as measured by employment), 2 digit industry, or by region. The
model as a whole was not significant. On these criteria at least, the sample is reasonably
representative of the population of firms from which it is drawn. In the analysis that follows we use
the dataset as a simple sample, and no attempt is made to adjust the sample to the population.
The survey asked the firms about their engagement in services. We also examined the extent to
which they were engaged in services using two other approaches. Firstly, using a methodology
similar to Neely (2009), we examined the trade descriptions provided in the FAME dataset for
mentions of services of various types. For example, one company is described as being engaged in:
“The installation, rental and maintenance of electronic security systems and the manufacture and
sale of security products.” This company was coded as being engaged in ‘installation services’,
‘rental services’, ‘maintenance services’ and sales. By contrast, another firm, described as being
engaged in: “The manufacture of a wide range of tooling, incorporating industrial diamond and
other superabrasives”, was coded as not providing any services to customers.
We coded the services described in the trade descriptions of the 256 firms into eight categories:
‘distribution and delivery’ (including logistics), ‘repair and maintenance’, ‘(supply of) spare parts’,
‘leasing’, ‘support’, ‘consulting’, and a miscellaneous category of ‘various other services’. In
addition, we coded whether the firm was described as being engaged in R&D, design and/or
development. Usually it was unclear whether these activities were undertaken solely for internal
purposes, or whether they were made available to clients as services. Similarly, sales and marketing
activities were identified and coded, and presumably these activities were undertaken to promote
and sell the company’s own product, but it is conceivable that they could be applied to products
produced by others, with the surveyed firm acting as an agent or distributor.
---- INSERT FIGURE 1 ABOUT HERE ---Our review of trade descriptions found that with R&D, design and development (RDD) and sales and
marketing (S&M) all included, almost 80% of the firms were identified as being engaged in services
(Figure 1). With RDD and S&M excluded, the proportion of firms identified as engaged in services
fell to just under half, with distribution and delivery being the most widespread, followed by repair
and maintenance services, and installation services. Interestingly the proportion of firms identified
as providing at least one service (excluding RDD and S&M) exceeds the 40% found by Neely et al.’s
(2011) analysis of UK manufacturing firms found on the OSIRIS database.
Secondly, we reviewed the websites of each of the businesses, and found websites for all but two of
the firms. We coded two things. First, whether there was a prominent service or support ‘button’
on the home page, which, if clicked, took the viewer to a page outlining the services or product
support provided by the firm. In the absence of this, we coded whether or not the firm mentioned
providing services, or having a service orientation. No attempt was made to code the particular
services provided.
7
We found that almost half (120: 47%) the firms had the provision of services prominently displayed
on their internet home page (i.e., with a ‘Service’ or ‘Support’ clickable “button”, taking the viewer
to a special section). And almost another third (79: 31%) mentioned services as being part of what
they provide. We found no reference to services on the remaining websites (55: 22% of companies).
This indicates that at least 80% of the firms provide services to customers, considerably more than
was revealed by our (and Neely’s) analysis of trade descriptions. We now turn to the survey results,
the analysis of which constitutes the empirical heart of this paper.
4.
ANALYSIS OF THE SURVEY RESULTS
The Extent of Service Provision
Our survey asked the firms whether or not they provided 15 different services. All but two of the
firms reported providing at least one of these, with the most widespread being delivery services,
whilst the least widespread was product leasing, with or without operatives. Interestingly, our ‘top
five’ services are the same as those identified by Baines et al. (2009), i.e., training, delivery, spare
parts, repair, and customer helpdesks. Like Baines et al, we also find widespread provision of
installation services, but less provision of systems integration, preventive maintenance and
condition monitoring. This may be due to the generally larger size of firms in Baines et al’s sample.
By contrast, we find greater provision of financial services, and more consulting. The survey results
indicate that all of the main services identified in the trade descriptions were much more frequently
provided than is indicated by the trade descriptions. In other words, trade descriptions under record
service provision.
---- INSERT FIGURE 2 HERE ---To analyse which firms provided these services, and which did not, we estimated a series of logistic
regressions. In each model, we included:







[Firm size] the size of the firm, measured by the natural log of its employment.
[Sector] a set of indicator (or ‘dummy’) variables for sector of activity, with ‘other
manufacturing’ acting as the reference sector.
[Ownership] an indicator variable identifying subsidiary firms owned by others (with
independent firms acting as the reference group).
[Age] an indicator variable for relatively young firms established after the year 2000.
[Type of Product] an indicator variables for firms that manufactured stand alone appliances
or equipment, and another for those that manufactured systems, often tailored to particular
customers needs, that combine a large number of components (here, the manufacture of
‘components or parts’ was the reference category).
[Unit Cost of Product] a set of indicator variables relating to the unit cost of the firms main
products. This varied from ‘less than £10 per unit’ (the reference category) through to ‘over
£100,000 per unit’, with four intermediate categories.
[Main Customer Dependency] an indicator variable for firms for which their largest customer
accounted for at least half their total revenues. And a second indicator variable was
8

included for other firms whose five largest customers accounted for half or more of their
income.
[Competition] an indicator variable for firms that claimed to have no more than two
competitors. A second indicator variable for firms with over 10 competitors. Firms with 3 to
10 competitors were the reference group.
We estimated individual regressions for thirteen of the services, with an additional conflated model
for leasing with or without operatives. In four cases – delivery, consulting, managed services, and
leasing - the overall models were not significant, meaning that the variables outlined above failed to
explain any of the variation in whether or not the firms provided these services. Because these
models were insignificant, we do not therefore report their results. Models for ten of the services
were significant, meaning that some of the variation in whether or not firms provide these services
can be attributed to these variables.
---- INSERT TABLE 3 HERE ---The results are reported in Table 3. The figures reported are the exponents of the coefficients,
which means that if there is no significant influence of the characteristics then this number is one, or
not significantly different from one. If firms with this characteristic are more (less) likely to provide
the service in question then the figure will be greater (less) than one. For example, firm size and the
five largest customers accounting for over half of total sales have no significant impact on the
provision of spares parts or consumables (Exp(B) = 0.99 and 1.06 respectively). However, firms
making appliances and systems are roughly three times as likely to provide spare parts or
consumables as firms that only produce components or parts (Exp(B) = 3.31 and 2.83 respectively).
Meanwhile, young firms, and those with fewer than three competitors, are much less likely than
otherwise similar firms to provide spares or consumables (Exp(B) = 0.14 and 0.25 respectively).
Oliva and Kallenberg (2003) distinguish between product and client-process oriented services, and
drawing on this distinction we have grouped the models into those that relate primarily to the
product and its maintenance (spares, repair & maintenance on demand, scheduled maintenance,
condition monitoring and preventive maintenance, and regular product or systems upgrades) and
those that relate to helping the client use the product or system (training, installation, and systems
integration), as well as more general services (help desk and financial services).
These models, which implicitly assume each of these services is provided independently of the
others, show a variety of factors influence the provision of services amongst manufacturing firms.
The nature of the product is often important. Firms that make stand-alone appliances are three
times more likely than those that make components to provide spares or consumables and a
customer helpline, and twice as likely to provide financial services such as insurance and warranties.
Those that manufacturer systems are at least 2.5 times more likely than those that make
components to provide all of these services except a customer helpline and financial services. They
are roughly seven times more likely to provide systems integration services. The sector of
production also matters, with metal product firms being less likely to provide most of these services.
Most probably, this relates to the robust and static nature of most metal products, such that they
require little after-sales servicing. Electrical and electronics firms are three times more likely to
provide systems integration services, and twice as likely to provide regular product or systems
upgrades. Instruments companies are four times more likely to provide regular upgrades. The cost
9
of the product (which probably reflects its complexity), has a strong influence on whether or not the
firms provide almost all of these services, the two exceptions being a customer helpline and financial
services. With all the other services the manufacturers of the most expensive products are several
times more likely to provide the service than manufacturers of the least expensive products. This
stands to reason, as low cost product are typically discarded and replaced when worn out or
damaged, whereas expensive equipment is repaired and maintained. Generally the provision of
services increases incrementally with the cost of the product. This is true of all services except
customer helplines and financial services, and spares and consumables, the provision of which
appears most widespread amongst producers of medium-cost products. This suggests that whilst
the customer or a third party often carry out repairs on mid-cost products, the manufacturer
typically provides repairs and maintenance on the highest cost equipment.
Firms that are highly dependent on a small number of customers, and especially one customer, seem
to be less likely to provide some of these services, including scheduled maintenance services,
training, installation and set-up services, systems integration and a customer helpline. These firms
are however more likely to provide spare parts and consumables. We had not anticipated these
findings, and one possible interpretation of them is that these firms are relatively weak. With the
possible exception of spares, there is no evidence that customers in powerful positions are forcing
manufacturers to provide additional services, which is sometimes suggested (Spring and Araujo,
2009).
Meanwhile, firms with very few competitors are less likely to provide spares or regular product or
systems upgrades, but are more likely to engage in systems integration. Indeed, this may be
endogenous, as engaging in systems integration may limit competition. Firms that face an unusually
high number of competitors are more likely to provide spare parts or consumables, but do not
otherwise differ from those with a normal number of competitors.
Perhaps surprisingly, firm size has very little effect. We had anticipated that larger firms would tend
to provide more services, but firm size is only significant for the provision of regular product or
systems upgrades. It is thought that smaller firms are not disadvantaged in the provision of services
(which are typically difficult to scale up), and our findings support this conclusion.
Firm age and ownership also had very little effect. With respect to ownership, the only significant
difference found was that subsidiary firms are less likely to provide systems integration. Again, this
implies that independent firms are not generally disadvantaged in providing services relative to firms
that are part of larger groups. With regard to age, we found that young firms were much more likely
to be engaged in systems integration, and much less likely to provide spare parts. These findings are
surprising, and may indicate that the young firms in our sample are unusual. Young firms were not
more or less likely to provide any of the other services.
As mentioned earlier, the analysis reported above which is based on a set of individual logistic
regressions implicitly assumes that the provision of each of these services is independent of the
provision of the others. Instead, firms might provide several services which complement one
another. To explore this, we undertook multiple correspondence analysis on the incidence of the
various services. If services are closely related they should appear close together, and the various
‘types’ of services should cluster together (Tether and Tajar, 2008). Whilst this analysis did show
that the services are more or less related to each other, it did not reveal any strong clusters of
10
services by ‘type’, such as the ‘types’ identified by Oliva and Kallenberg (2003). Instead, pursuing the
assumption of independence, we calculated the probability that a firm would provide any number of
these services between 0 and 15, based on the naive assumption that the provision of each is
independent of the other. We then compared this with the observed distribution based on the
count of services provided. This revealed that the ‘expected number’ of services is around seven,
and that many firms provide fewer than this, whilst others provide more than this. We then
classified the firms into three groups: those providing no or fewer than ‘expected’ services (i.e., 0 to
3 services; N. = 47 (18.6%)); those providing more than the ‘expected’ number of services (i.e., 10 to
15; N. = 73 (28.5%)); and those providing around the ‘expected’ number (i.e., 4 to 9; N. = 133
(52.6%)). Later in the paper we examine the factors that distinguish those with no or limited service
provision and those with extensive service provision, from those in the middle.
Income from Services
Next, we examine the extent to which the firms’ reported earning income from services. Overall,
and on average, we find that the firms in our survey reported earning 10% of their total revenues
from services. This is similar to the 12% found by the Engineering Employers Federation (EEF, 2009)
in their 2009 survey. The similarity with the EEF’s result is even more striking given that we have few
transport equipment firms in our sample, whilst the EEF found transport equipment firms tended to
earn the most from services (20%). Meanwhile, the EEF found that on average machinery firms
earned 15% from services – we find 15.7%; and the EEF found metal product firms earned an
average 7% from services; we find 8.1%. We also found that on average rubber and plastic product
manufacturers earned 2.1% of their income from services, whilst electrical and electronics
manufacturers averaged 11.5%, instruments manufacturers 9.5% and other manufacturers 8.6%.
These averages mask considerable variation in earnings from services, however. One third of the
firms in our sample reported earning nothing from services, and half reported earning no more than
5% of their income from services, with a quarter earning over 10%. Only 2.5% reported earning at
least half of their income from services, with one claiming all of its income was due to services. We
checked that this is indeed a manufacturing firm.
To examine this further, and to investigate the factors that distinguish different groups of firms, we
classified the firms into three groups: those that reported earning nothing from services (N. = 80
(33.3%))), those that reported earning 0.1% to 10% of their income from services (N. = 99 (41.2%)),
and those that reported earning more than 10% of their income from services (N. = 61 (25.4).
Before doing this, however, we provide an overview of how the various services were charged for.
As Lay et al. (2010) observe, many services are not explicitly charged for, and are instead ‘packaged’
with products.
Modes of Service Provision
For each of the services asked about in the survey, we also asked how these were provided, where
the options included: ‘provided free or packaged with products’, charged for on a ‘pay-by-use’ basis,
charged for through ‘fixed price contracts’, and charged for by ‘performance based agreements’.
Multiple answers were possible. Figure 3 shows the results of this. This shows that it is
commonplace for many services to be provided for free, without explicit charge, or to be packaged
with products. This resonates with Lay et al.’s (2010) findings; they estimate that amongst European
11
manufacturers ‘indirectly invoiced’ services that are packaged with products are worth at least as
much as directly invoiced services.
---- INSERT FIGURE 3 HERE ---Whilst it is not surprising that most firms that provide customer help-lines or support desks do not
charge for their use, or that delivery and installation are very often included in the price of the
product, it is perhaps more surprising that training is frequently ‘given away’ for free or packaged
with product sales, with the same being true of other services such as systems integration, upgrades,
consultancy, systems integration and condition monitoring. It would appear that many of these
services are not being explicitly charged for, and therefore their true significance is not being
captured by the proportion of income that the firm earn explicitly from services. It is however the
norm to explicitly charge for some services, including leasing, scheduled servicing, for spares and
consumables, and repair and maintenance on demand, amongst others. Interesting here is that for
the majority of these, the dominant charging model is pay-as-you-use, with fixed term contracts
being less widely used, and performance based agreements very rare, being most commonly used
with managed services.
Motivations: Why Do Firms Provide Services?
Another interesting question is why do firms provide services? and the survey asked the
respondents about this. Specifically, we asked “How important are the following reasons for your
provision of product support and services”, with thirteen statements then provided, which the
respondents scored on a 5-point scale between ‘of no importance’ and ‘crucial’ (Figure 4). Six of
these motivations can be considered aggressive or offensive reasons (improving understanding of
users’ needs; helping to differentiate the offer; increasing opportunities for customisation;
increasing opportunities for cross-selling; increases total turnover; increases profitability),1 whilst
five others can be considered defensive (required to comply with regulations; necessary because key
customers require them; increase customer loyalty; helps tie customers in; and increases the
stability of turnover).2 Two environmental or ecological reasons were also included (extends the life
of older products; has environmental or ecological benefits), reflecting the fact that the early
literature on product-service-systems (PSS) had strongly links to ecological motivations (Mont, 2002;
Tukker and Tischner, 2006).
---- INSERT FIGURE 4 HERE ---Interestingly, the defensive motivations tended to be identified as more significant than the
offensive motivations, with the ‘environmental’ motivations less important still. However, further
1
Principal Components Analysis for the ‘Offensive Six’ produces a single component solution, with an Eigenvalue of 3.48,
which accounts for 58% of the variance. Individual item loadings range between 0.73 and 0.80. The Cronbach also for this
set is 0.85.
2
Principal Components Analysis of the ‘Defensive Five’ produces a single component solution, with an Eigenvalue 2.33,
which accounts for 47% of the variation. With the exception of “A” (required to comply with regulations), all component
loadings are between 0.71 and 0.75 (A’s loading is 0.36). The Cronbach alpha for this set is 0.66, which is too low.
Removing “A” increases the Cronbach alpha to 0.73. A single component is again found (Eignevalue = 2.24), accounting for
56% of the variance. Item loadings range from 0.70 to 0.78.
12
analysis showed that firms tended to provide services for a mix of offensive and defensive reasons
(with the correlation between the scores on the two sets of components being 0.8).
Allowed to associate freely, an exploratory Principal Components Analysis of these responses
identified three components with Eigenvalues greater than one. The first of these (Motivation PC1)
relates primarily to the impact of offering services on the business itself, including items such as
increasing turnover, increasing profitability, increasing the stability of income, and providing
opportunities to cross-sell. The second (Motivation PC2) is related to engaging with customers –
increasing customer loyalty, understanding of customers, and increasing the opportunities for
customization and the capacity to differentiate the firms offer. The third component (Motivation
PC3) was weaker, and is related to complying with regulations and ecological benefits.
---- INSERT TABLE 4 HERE ----
Organizational Arrangements for Service Provision
We also asked about the organizational arrangements associated with providing services. It is
sometimes argued that the provision of services requires different organizational arrangements
from those required to produce physical products. Oliva and Kallenberg (2003, p. 161), for example,
state: “Transitioning from product manufacturer to service provider constitutes a major managerial
challenge. Services require organizational principles, structures and processes new to the product
manufacturer. Not only are new capabilities, metrics and incentives needed, but also the emphasis
of the business model changes from transaction to relationship based”.
---- INSERT FIGURE 5 HERE ---Figure 5 shows the extent to which the firms agreed or disagreed that they had various
organizational arrangements related to providing services. Most respondents agreed that there was
close communication between their services activities and production, whilst around half: 1. agreed
that they had a dedicated sales force and technicians dedicated to services activities, 2. that their
service personnel were in near continuous communication with customers, and 3. That their service
personnel were trained and empowered to offer services actively to customers. Only a minority of
firms had different incentives and rewards for their service personnel compared with their
production personnel, or had given their services organization its own profit and loss responsibility.
Examined by Principal Components Analysis, these answers load onto a single component with an
Eigenvalue of 4.4. This accounted for 55% of the variance in the data, and item loadings varied from
0.61 to 0.82. The Cronbach’s alpha for the set of eight items was 0.88.
Modelling the Extent of Service Provision
We now model the extent of service provision. As outlined earlier, we classified the firms in our
sample into three groups: those that provide fewer than the ‘expected number’ of services (i.e., 0 to
3); those that provide around the ‘expected number’ (i.e., 4 to 9), and those extensive service
providers that provide more than the ‘expected number’ of services (i.e., 10 to 15). Our aim is to
uncover the factors that distinguish firms that provide few and many services, from those in the
middle that provide a ‘normal’ number of services.
13
We build the models incrementally, starting with the structural characteristics of the firms: i.e., their
sector of activity, size, age and independence. Four sectors are separately identified with dummy
variables, with rubber and plastics manufacturing combined in with ‘other manufacturing’ as the
reference category. Size is measured by the natural log of employment (including working
directors). New firms, established after the year 2000, are also identified with a dummy variable.
And lastly the firms ‘autonomy’ is calculated. This is derived from a survey question (inspired by
Birkinshaw et al., 1998) with four items, each on a five point scale between strongly agree and
disagree, which asked subsidiary firms the extent to which the firms’ management team had full
authority to decide on: 1. Changes to product design and engineering; 2. Outsourcing or subcontracting of production; 3. Switching to a new manufacturing process; and 4. Adding product
support or services to the firm’s portfolio of activities. Principal components analysis found these
items loaded onto a single component, with an Eigenvalue of 2.8 and which accounted for 69% of
the variance in the data. Item loadings ranged from 0.78 to 0.87. The Cronbach’s alpha for the set
of four items was 0.85. We therefore summed these items and rescaled them such that if the
respondent strongly agreed with all four this was coded 1, and if the respondent strongly disagreed
with all this was coded 0. The mean score amongst subsidiaries is 0.87. Because independent firms
are autonomous by definition, these were assigned an autonomy score of 1.
---- INSERT TABLE 5 HERE ---Model 1 with only these structural characteristics found nothing statistically significant that
distinguished firms with no/limited services from those with a ‘normal’ service orientation. Several
factors distinguished firms with an extensive portfolio of services, including being machinery,
instruments or electrical/electronics manufacturers, and having a high level of autonomy. There was
also some indication that young firms are more likely to provide several services (Table 5).
In Model 2 we added in the type of products manufactured – i.e., dummy variables for the
manufacture of appliances and of systems, with the manufacture of components acting as the
reference category. And a set of dummy variables, ranging up to ‘over £100,000’, reflecting
different unit prices for the firm’s main product. This revealed that systems manufacturers were
around half as likely to provide no/few services, whilst firms providing products with mid-range unit
costs (specifically £1,000 to £10,000) were much less likely to provide no/few services. Again, there
was stronger evidence distinguishing firms with extensive service portfolios, with systems
manufacturers and high cost goods manufacturers being much more likely to provide 10 or more
services.
In Model 3 we added in the extent to which the firms dependent on one or a few customers, and the
extent to which they face many or few competitors. With respect to customers, we identified with a
dummy variable those firms which stated that their largest customer accounted for at least half of
their total income (N. = 19), and (excluding these), used a second dummy variable to identify firms
that stated their five largest customers accounted for at least half their total income (N. = 85). We
also used dummy variables to identify those firms that claimed to have no more than two ‘direct
competitors to their core business’ (N. = 24), and those firms that claimed to have more than 10
direct competitors (N. 36). Most firms (N. = 194) claimed to have between 3 and 10 direct
competitors. Our analysis found however that neither customer dependence nor the extent of
competition had any significant impact on the extent of the service offered by the firms.
14
In Model 4a, we added in the principal component scores associated with the motivations for
providing services. Here, Motivation PC1 relates primarily to the impact of offering services on the
business itself, including items such as increasing turnover, profitability, the stability of income, and
providing opportunities to cross-sell; Motivation PC2 relates to engaging with customers – increasing
customer loyalty, understanding of customers, etc.; whilst Motivation PC3 is weaker, but relates to
complying with regulations and ecological benefits. We find that none of these motivations is
associated with having an extensive portfolio of services, but the first two are significantly associated
with offering services: firms which score highly on these components are much less likely to provide
no or few services.
In Model 4b, we substitute the principal components associated with the motivations for providing
services with the principal component associated with organizational arrangements for service
provision. The results show that scoring highly on this Arrangements PC significantly reduces the
probability that the firms will provide no or few services, and significantly enhances the probability
that it will engage in extensive service provision.
Finally, in Model 5, we reintroduce the three dummy variables for the Motivations, whilst retaining
that for the Arrangements. The reintroduction of the Motivations PC dummies removes the
significance on the Arrangements dummy with respect to the provision of no/few services, but
(unsurprisingly) Arrangements remains important for the provision of an extensive set of services.
Motivations are not significant for the provision of an extensive set of services, but Motivation PC2
(enhancing customer engagement) is important for the provision of some service (i.e. it is negatively
related to the provision of no or few services). Meanwhile, we find that customer dependence and
the extent of competition has no significant impact on the extent of service provision, whilst
structural factors (sector, size, age, autonomy) are generally more important for distinguishing
between firms that provide many services (from those that provide around the ‘expected number’)
than for distinguishing between those that provide none or very few (from those that provide
around the ‘expected number’). Autonomy seems to be particularly important for the provision of
an extensive range of services, which is also higher amongst young firms, and those producing
machinery, electrical and electronic products and (more marginally) instruments.
Modelling the Earning of Income from Services
Having undertaken this exercise with respect to the number of services provided, we now repeat it
with respect to the income earned from services, again dividing the sample into three: those that
claim to earn nothing from services, those that claim to earn 0.1% to 10% of their income from
services (the reference category), and those that claimed to earn over 10% of their income from
services. Whilst the number of services provided and the extent of income derived from services
are related, the mapping is not exact. Cross-tabulating these two three way classifications provides
a nine-cell matrix. We find that 125 of the 239 firms for which we have data are located in the topleft to bottom right diagonal (i.e., 52%), meaning that nearly half are off-diagonal, and indeed six are
found in the bottom left and top right cells.
---- INSERT TABLE 6 HERE ---Table 6 provides the results of the modelling. And generally the models are remarkably stable
especially from 2 onwards. Rather than take each in turn, we comment on the overall findings, with
15
a particular emphasis on Model 5, the fully saturated model. We find that with the exception of
being engaged in metal products manufacturing, the structural characteristics of the firm (i.e., their
sector of activity, size, age and autonomy) had no significant influence on whether or not they
earned income from services. Metal products manufacturers are much less likely than otherwise
similar firms to earn any income from services. This is likely due to the highly robust nature of static
metal products, such that once installed they require little ongoing maintenance. Any services (such
as delivery and installation) are therefore likely to be packaged with the product at time of sale.
Similarly, with the exception of being engaged in machinery manufacturing, the structural
characteristics of the firm had no significant influence on whether or not they earned a relatively
high share of their income from services (i.e., over 10%). Machinery manufacturers are much more
likely than otherwise similar firms to earn at least 10% of their income from services. This is likely
due to the dynamic nature of machines and machinery: moving parts wear out, and generally
require maintenance. This provides significant opportunities to earn income, both at the time of sale
(by selling product-service packages) and through servicing the installed base of machines, including
machines originally produced by others.
The type of product being produced, and its unit cost, also had a significant impact, at least in terms
of whether or not the firm earned anything from services (neither or these factors impacted
significantly on whether or not the firm earned more than 10% of its income from services). Firms
producing systems were three times as likely as component manufacturers to earn at least some of
their income from services, whilst the probability of earning income from services also increased
substantially with unit price, peaking with products costing between £1,000 and £10,000. This is
understandable, as low priced products are generally discarded and replaced rather than repaired,
whereas it is sensible to maintain through servicing the value and utility of high priced products.
Finally, we find that having fewer than three competitors is associated with earning a high share of
income from services. This is perhaps endogenous, but also understandable, as it implies the
provision of more complex, difficult to replicate products, which the manufacturer is in pole position
to then service itself. Less easily explained is why firms that depend heavily on a small number of
customers are around three times less likely to earn no income from services than otherwise similar
firms (whilst this is not true of firms which depend heavily on a single customer).
5.
CONCLUSIONS
Servitization, the provision of services by manufacturing firms to their customers, and a shift from
‘making and selling products’ to providing combinations, or packages, or ‘integrated solutions’, of
products and services, has been advocated for some time as a means by which manufacturers in
high cost locations such as the United States and Western Europe can compete in an era of
globalization and against lower-cost producers in Eastern Europe and East Asia. However,
surprisingly little is known about the extent to which manufacturers in advanced economies such as
the UK provide services, their motivations for so doing, or the organizational implications of
providing services. This paper therefore contributes significant evidence where previously there was
little.
16
Based on a bespoke survey of manufacturing firms, we have found that almost all manufacturers
provide at least some services to their clients. The extent of service provision is also substantially
greater than that revealed by the analysis and coding of trade descriptions (Neely, 2009; Neely et al.,
2011). The most commonly provided service is delivery of products, followed by the provision of
spare parts and consumables, a customer helpline or support desk, and product or systems training.
Interestingly, these same services were also found to be the most widespread in a previous, but
much smaller survey, undertaken by Baines and colleagues (2009).
Although the vast majority of firms provide at least some services to their clients, few earn a large
share of their incomes from the provision of services. We find an overall average share of income
from services of around 10%, which is very close to the 12% found by a survey of manufacturers
undertaken by the Engineering Employers Federation in 2009 (EEF, 2009). Indeed, the similarity in
findings is even more striking when differences in the sample are taken into account. A third of the
firms in our sample indicated they earned nothing from services, whilst only 2.5% earned at least
half their income from services. Given that on average firms provided seven of the fifteen services
our survey asked about, that most claimed to have a clearly defined strategy for services, and that
most also claimed that services are a key part of their value proposition, the discrepancy between
the extent of service provision and the limited amount of income typically earned from services may
seem somewhat paradoxical.
This paradox can be explained, at least in part, by the tendency of firms to package services with
products, such that services are often not explicitly charged for. The income is then attributed to the
product. This appears to be a widespread practice, which is understandable with services such as
delivery and installation, but perhaps less so with training, consulting and other services. This
suggests that services are typically rather more significant to firms than the share of income
attributed to them would imply. And indeed Lay et al (2010) have estimated that manufacturing
firms typically earn at least as much from services that are ‘indirectly invoiced’ (i.e., included in the
product’s price) as they do from directly invoiced services. Were manufacturers do charge for
services, we find this tends to be on a ‘pay-as-you-use’ or fixed contract basis. Very few firms
provide services on the basis of performance-based agreements. This suggests that most of the
firms in our sample are service-enhanced, rather than service-oriented.
In relation to their motivations for providing services, firms tend to cite both defensive and offensive
reasons simultaneously. Defensive reasons include tying customers in, and increasingly the stability
of turnover, whilst offensive reasons include learning about customer needs and increasing turnover
and profitability. Firms also vary substantially in the extent to which they have implemented
organizational arrangements thought favourable to the provision of services, and establishing a
service oriented culture.
We examined the factors that distinguish between firms that provided no or few services, and those
providing many services, both compared with firms providing an average number. Generally
speaking, manufacturers of high value products, of systems, and to a lesser extent of appliances,
were much more likely to provide services than were manufacturers of components. This is
understandable, as cheap goods are normally discarded and replaced, rather than repaired and
maintained, which is the case with expensive, complex equipment. Another factor here is likely to
be the scale of the market. Because there is strong demand for low cost products, the scale of the
17
market will tend to be large, encouraging an increased division of labour, with third party service
providers often in a stronger position to provide services than the original manufacturer.
Manufacturers of machinery were also more likely to provide many services, which is
understandable due to the dynamic nature of machines. Interestingly, the number of competitors
did not generally influence the extent of service provision, and nor did high dependency on one or a
few customers. We did find that firms motivated to learn more about their customers tended to be
more likely to provide at least an average number of services, whilst those that had implemented
service oriented arrangements tended to provide the most extensive range of services.
Finally, we examined the factors which distinguished firms that reported earning nothing from
services, and those that earned a relatively large amount, from those that earned an average
amount. This showed that metal products manufacturers were four times more likely than
otherwise similar firms to earn nothing (explicitly) from services, whereas machinery firms were
about four times more likely to earn at least 10% of their income from services. Firms that had
introduced organizational arrangements for service provision were also significantly more likely to
earn at least 10% of their income from services. Meanwhile, manufacturing systems, and higher unit
priced products, tended to increase the chances that the firm earned income (explicitly) from
services, but did not tend to impact on how much of their income the firm earned from services.
All told, this paper sheds considerable light on the provision of services by manufacturing firms. This
understanding provides a valuable platform upon which to understand strategies and managerial
choices. Too often, in our view, bold or sweeping statements are made, such as this one:
“In today’s business landscape, manufacturers are inventors, innovators, supply-chain
managers and service providers, as well as producers .... Firms in the UK must respond
[to the competitive threat of China, etc.] by constantly adapting their business
models, product offerings, processes and service systems in order to stay competitive
by delivering higher value manufacturing.” (Benedettini et al, 2010, p. 6),
Change comes at a price – it has costs as well as benefits. It makes considerable sense for
manufacturers of expensive systems to have and to develop a services strategy, but the same
strategy would not be sensible for a manufacturer of low cost components, or highly durable metal
products. And manufacturers also need to consider how they charge for services. Charging explicitly
for services is sometimes advocated, as it encourages both the provider and the user to consider the
costs and benefits of the services. But the provision of services can also have spillover benefits. For
example, by engaging in installation and training the manufacturer can gain considerable insight into
how its products are used, which can lead to further product improvements (Orr, 1996). The key
here is to exploit the complementarities that can arise when offering both products and services. In
this context, it may even be sensible to provide services at a loss in order to gain market intelligence.
A full consideration of these matters is beyond the scope of the present paper, as is an analysis of
the performance implications of providing services, which we will address in a companion paper.
18
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21
Figure 1
Services reported in Trade Descriptions
80%
79%
68%
60%
47%
40%
25%
30%
28%
20%
10% 8%
3%
2%
1%
1%
0%
Figure 2
Extent of Service Provision
94%
78%
74% 74%
69%
60% 59%
44% 42%
37% 35%
29%
12% 11%
3%
22
4%
Figure 3
Modes of Service Provision
0%
20%
40%
60%
80%
100%
Customer Helpline
Insurance / Finance
Product / Systems Training
Product Delivery
Product Installation
Consultancy Services
Systems Integration
Managed Services
Product / Systems Upgrades
Condition Monitoring
Leasing with Operatives
Repair on Demand
Spares / Consumables
Scheduled Servicing
Leasing without Operatives
Free or Packaged
Pay-by-Use
Fixed Contract
23
Performance Based
Figure 4
Helps Differentiate Our Offer
Offensive
Aids Understanding Customer Needs
Increases Total Turnover
Increases Firm's Profitability
Increases Opportunities to Cross-Sell
Enables Increased Customisation
Defensive
Key Customers Require Them
Increases Customer Loyalty
Helps Tie Customers In
Improves the Stability of Tunover
Neutral
Required to comply with regulations
Extends Life of Older Products
Has Environmental Benefits
No Importance
Minor Importance
Quite Important
24
Very Important
Crucial
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Motivations for Providing Services
Figure 5
In Close Communications with Production
Have Dedicated Service Salesforce & Technicans
In Close Communications with Customers
Service Personnel offer Services Actively
Service Operations are Distinct & Separate
IT System used to closely Monitor Services
Service Personnel Rewarded Differently
Service Organization has own P&L Responsibility
Strongly Disagree
Disagree
Neither
25
Agree
Strongly Agree
100%
90%
80%
70%
60%
50%
40%
30%
20%
0%
10%
Arrangements for Service Provison
Table 1 – Characteristics of the Sample of Respondents
Industry
Rubber & Plastics
Metal Products
Machinery
Electrical & Electronics
Instruments
Other Manufacturing
6.3%
14.8%
20.3%
18.8%
9.4%
30.5%
Firm Size & Ownership
8 to 49 employees
20.9%
50 to 99 emp’s
31.1%
100 to 199 emp’s
27.6%
200+ emp’s
20.5%
Independent Firms 55.1%
Subsidiary Firms
44.9%
Year Established
Before 1981
1981-1990
1991-2000
2001-2005
2006-2010
59.0%
19.5%
16.4%
3.1%
2.0%
Table 2 – Descriptive Statistics
Var. #
1
2
3
4
5
6
7
8
9
10
11
12
13
13
15
16
17
18
19
20
21
22
23
24
25
Variable
Sector: Rubber/Plastics
Sector: Metal Products
Sector: Machinery
Sector: Electr-ical/onics
Sector: Instruments
Sector: Other Manuf.
Size (Ln Employment)
Established after 2000
Ownership (Subsidiary)
Autonomy Score
Manuf. Appliances
Manuf. Systems
Unit Cost: £10 to £100
Unit Cost: £100 to £1k
Unit Cost: £1k to £10k
Unit Cost: £10k - £100k
Unit Cost: Over £100k
Top Cust. 50%+ of sales
5 Top Custs 50%+ sales
< 3 Competitors
> 10 Competitors
Motivation PC1
Motivation PC2
Motivation PC3
Arrangements PC
Mean
S.D.
Min
0.06
0.15
0.20
0.19
0.09
0.30
4.55
0.05
0.45
0.92
0.68
0.52
0.13
0.25
0.15
0.18
0.11
0.07
0.33
0.09
0.14
0.00
0.00
0.00
0.00
0.24
0.36
0.40
0.39
0.29
0.46
0.95
0.22
0.50
0.16
0.47
0.50
0.33
0.44
0.36
0.39
0.31
0.26
0.47
0.29
0.35
0.96
0.96
0.96
0.96
0.00
0.00
0.00
0.00
0.00
0.00
2.08
0.00
0.00
0.13
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
-3.55
-2.72
-2.32
-2.20
Max.
1.00
1.00
1.00
1.00
1.00
1.00
8.52
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
2.39
2.45
2.98
2.08
Abs Max
Correl.*
0.17
0.28
0.33
0.32
0.21
0.33
0.21
0.21
0.15
0.16
0.15
0.23
0.26
0.28
0.25
0.28
0.24
0.20
0.20
0.13
0.13
0.44$
0.18
0.23
0.44$
VIF
1.32
1.35
1.75
1.58
1.36
Ref.
1.16
1.19
1.69
1.67
1.36
1.31
1.93
2.52
2.17
2.63
2.37
1.36
1.29
1.15
1.17
1.56
1.23
1.19
1.89
* Absolute value of the largest correlation between this and any other variable
Note, Ownership and Autonomy Score are correlated at 0.57, but do never appear in the same models.
$
Motivation PC1 and Arrangements PC are correlated at 0.44. Their next highest correlations are 0.16 and 0.25 respectively
26
Table 3: Modelling Specific Service Provision – Binary Logisitic Regressions
Spares &
Consumables
Size
Rubber & Plastics (d)
Metal Products (d)
Machinery (d)
Electrical & Electronics (d)
Instruments (d)
Ownership (d)
Young Firm (d)
Firm makes Appliances (d)
Firm makes Systems (d)
Unit Cost £10-100 (d)
Unit Cost £100- £1,000 (d)
Unit Cost £1,000-£10,000 (d)
Unit Cost £10,000-£100,000 (d)
Unit Cost >£100,000 (d)
Top Customer = 50%+ of Sales (d)
Top 5 Customers = 50%+ Sales (d)
<3 Competitors (d)
>10 Competitors (d)
Constant
Model Chi-square
-2 Log Likelihood
2
Nagelkerke R
Exp(B)
0.99
0.54
1.62
3.19
1.20
6.26
1.51
0.14**
3.31***
2.83**
3.49**
5.04***
28.86***
20.45***
12.55**
9.85*
1.06
0.25**
3.56*
0.14
91.8***
169.1
0.474
Training
Size
Rubber & Plastics (d)
Metal Products (d)
Machinery (d)
Electrical & Electronics (d)
Instruments (d)
Ownership (d)
Young Firm (d)
Firm makes Appliances (d)
Firm makes Systems (d)
Unit Cost £10-100 (d)
Unit Cost £100- £1,000 (d)
Unit Cost £1,000-£10,000 (d)
Unit Cost £10,000-£100,000 (d)
Unit Cost >£100,000 (d)
Top Customer = 50%+ of Sales (d)
Top 5 Customers = 50%+ Sales (d)
<3 Competitors (d)
>10 Competitors (d)
Constant
Model Chi-square
-2 Log Likelihood
2
Nagelkerke R
Exp(B)
1.25
0.36
0.33**
0.65
1.09
5.70
1.69
1.21
1.50
2.54**
1.44
1.81
2.38
4.26**
17.31**
0.20**
0.78
0.57
0.59
0.36
57.8***
231.4
0.301
Repair on
Demand
Exp(B)
1.30
0.45
0.38*
0.54
0.90
3.07
0.91
0.58
1.71
2.40**
3.42**
7.66***
21.19***
28.04***
90.11***
0.78
0.86
1.03
2.16
0.06
91.8***
217.7
0.432
Scheduled
Maintenance
Exp(B)
0.94
0.27
0.41*
1.28
0.76
2.34
0.74
1.39
1.64
2.57***
1.61
1.68
5.43**
12.96***
16.72***
0.27*
0.50*
0.99
1.29
0.19
99.1***
243.8
0.439
Condition
Monitoring
Exp(B)
1.06
0.65
0.31**
1.18
1.08
2.20
0.71
1.61
1.37
2.56***
1.76
2.12
5.13**
11.09***
24.67***
0.86
0.88
0.71
1.45
0.06
84.4***
246.6
0.390
Regular
Upgrades
Exp(B)
1.47**
n.a.
0.21**
1.38
2.18*
4.51**
0.80
2.40
0.86
3.36***
1.69
1.27
1.64
3.44*
6.10**
2.40
1.11
0.25**
1.12
0.02
87.4***
237.8
0.405
Installation
& Set-up
Exp(B)
1.36
0.59
0.58
1.30
0.64
0.75
0.92
1.53
1.79*
3.31***
2.51
2.10
7.28***
10.58***
25.20***
0.27*
0.92
0.88
1.21
0.05
86.2***
249.5
0.394
Systems
Integration
Exp(B)
1.17
n.a.
0.32*
1.19
3.16**
2.01
0.52*
19.04***
0.53
6.73***
1.04
1.49
1.14
4.15*
10.16***
0.20**
1.85
2.83*
0.75
0.04
105.1***
197.6
0.488
Customer
Helpline
Exp(B)
0.87
0.40
0.50
0.97
0.91
2.44
1.00
0.79
2.93***
1.00
1.75
2.86*
0.88
1.89
1.31
0.20**
0.55*
1.50
1.60
2.81
43.3***
243.2
0.233
Financial
Services
Exp(B)
1.29
0.35
0.41*
1.15
0.60
1.48
0.83
1.14
2.18**
1.66
0.91
1.68
2.23
2.67*
2.24
1.06
1.06
1.32
1.19
0.16
40.0***
297.0
0.200
All models have 249 to 251 observations. *** Significant at 1%; ** Significant at 5%; * Significant at 10%
27
Table 4: Principal Components Analysis of the Motivations for Providing Services
Components (63% of variance)
Providing Support/Services ...
... Is required to comply with UK and/or EU regulations (Defensive)
1
-0.10
2
0.19
3
0.83
... Is necessary because key customers require them (Defensive)
0.10
0.67
0.16
... Increases customer loyalty (Defensive)
0.11
0.83
0.10
... Helps to improve our understanding of customer needs (Offensive)
0.34
0.74
0.18
... Helps to differentiate our offer from those of our competitors (Offensive)
0.36
0.69
0.01
... Enables us to increase the customisation of our products (Offensive)
0.47
0.49
0.17
... Increases opportunities to offer other products and product-service
combinations (e.g., as solutions) to our customers (Offensive)
0.67
0.27
0.08
... Helps to tie-in our customers, creating barriers to competitors (Defensive)
0.63
0.55
-0.11
... Enables us to increase our total turnover (Offensive)
0.86
0.26
0.05
... Enables us to increases the stability of our income year on year (Defensive)
0.82
0.16
0.22
... Helps to extend the life of our older products (Other motivation)
0.52
-0.07
0.50
... Enables us to increase our profitability (Offensive)
0.72
0.29
0.10
... Has environmental or ecological benefits (Other Motivation)
0.32
0.17
0.59
# of firms = 234. Rotated Component Matrix: Comp. 1 = 28.1% of variance; Comp. 2 = 23.3%; Comp 3 = 11.3%
Cronbach’s α for items 7,8,9,10 & 12 = 0.90; for items 2,3,4, & 5 = 0.80; for items 1 & 13 = 0.449
28
Table 5: Modelling the Extent of Service Provision
Model 1
Exp(B)
Model 2
Exp(B)
Model 3
Exp(B)
Model 4a
Exp(B)
Model 4b
Exp(B)
Model 5
Exp(B)
No and Limited Service Provision (i.e., Firm provides 0 to 3 services, compared with 4 to 9 services)
Sector: Metal Products
Sector: Machinery
Sector: Electr-ical/onics
Sector: Instruments
Size (Ln Employment)
Established after 2000
Autonomy Score
Manuf. Appliances
Manuf. Systems
Unit Cost: £10 to £100
Unit Cost: £100 to £1k
Unit Cost: £1k to £10k
Unit Cost: £10k - £100k
Unit Cost: Over £100k
Top Cust. 50%+ of sales
5 Top Custs 50%+ sales
< 3 Competitors
> 10 Competitors
Motivation PC1
Motivation PC2
Motivation PC3
Arrangements PC
1.32
0.70
0.74
12%
0.19
0.99
1.00
0.76
18%
18%
2.01
1.25
1.08
0.28
0.93
1.61
1.59
16%
0.57
0.48*
1.46
0.53
0.19**
11%
0.24
0.35
2.05
1.35
1.12
0.27
0.92
1.84
1.65
16%
0.57
0.49*
1.60
0.54
0.20**
11%
0.24
0.35
0.89
1.25
1.48
1.06
1.97
1.95
0.82
0.31
0.87
10%
5.44
1.85
0.43*
0.57
1.55
15%
0.45
0.15**
0.18*
0.29
0.53
1.35
1.38
0.94
0.61**
0.48***
16%
0.72
1.78
17%
2.55
1.15
0.24
0.97
1.88
1.96
0.63
12%
0.51
1.91
0.53
0.18**
0.17*
0.32
0.73
1.14
1.39
0.89
0.50***
2.00
19%
2.53
0.83
0.29
0.90
15%
4.52
1.76
0.48*
0.57
1.69
18%
0.48
0.15**
0.15*
0.26
0.57
1.25
1.33
0.89
18%
0.70
0.52***
0.75
0.75
Extensive Service Provision (i.e., Firm provides 10 to 15 services, compared with 4 to 9 services)
Sector: Metal Products
Sector: Machinery
Sector: Electr-ical/onics
Sector: Instruments
Size (Ln Employment)
Established after 2000
Autonomy Score
Manuf. Appliances
Manuf. Systems
Unit Cost: £10 to £100
Unit Cost: £100 to £1k
Unit Cost: £1k to £10k
Unit Cost: £10k - £100k
Unit Cost: Over £100k
Top Cust. 50%+ of sales
5 Top Custs 50%+ sales
< 3 Competitors
> 10 Competitors
Motivation PC1
Motivation PC2
Motivation PC3
Arrangements PC
Residual -2 LL
2
Model χ
2
McFadden Pseudo R
1.26
4.70***
2.39**
2.92**
1.11
13%
2.79
6.78*
445.3
31.7
0.06
0.78
2.35*
1.75
1.91
1.20
2.45
13%
7.05
1.45
3.35***
3.75
3.85
3.20
16.83**
22.04***
387
117.65
0.23
0.75
2.51*
18%
2.00
1.92
1.19
12%
3.13
17%
6.03
1.35
3.62***
4.39
19%
4.23
3.89
20.18***
28.16***
0.50
1.27
1.47
18%
2.07
384.4
121.7
0.24
0.68
2.49*
14%
2.17
2.07
1.11
15%
3.02
11%
8.63
1.55
3.59***
4.25
4.21
3.75
20.65***
27.95***
0.51
1.18
1.34
18%
2.09
1.22
1.15
16%
1.30
359.2
146.9
0.29
1.41
3.50**
3.23**
11%
3.19
0.80
3.90*
18.46**
1.59
4.59***
3.71
3.27
2.86
15.96**
10.62*
0.72
1.66
1.50
14%
2.49
4.00***
344
162
0.32
1.43
3.42**
3.09*
10%
3.30
0.79
3.79*
15.60*
1.62
4.36***
3.79
3.66
3.08
18.22**
11.82*
0.69
1.61
1.28
14%
2.47
0.93
1.06
1.16
4.13***
331.7
174.4
0.35
All models have 251 observations. *** Significant at 1%; ** Significant at 5%; * Significant at 10%
29
Table 6: Modelling Income from Services
Model 1
Model 2
Model 3
Model 4a
Model 4b
Model 5
Exp(B)
Exp(B)
Exp(B)
Exp(B)
Exp(B)
Exp(B)
No Income from Services (i.e., No income from services, compared with services = 1 – 10% of turnover)
17%
19%
Sector: Rubber/Plastics
3.26*
2.92
3.36
2.77
3.20
2.91
19%
Sector: Metal Products
1.89
3.74**
4.49**
4.26**
4.20**
4.05**
15%
19%
Sector: Machinery
0.32**
0.46
0.37
0.40
0.52
0.52
17%
Sector: Electr-ical/onics
0.52
0.83
0.77
0.67
0.81
0.74
Sector: Instruments
0.49
0.95
0.82
0.78
0.85
0.83
Size (Ln Employment)
1.16
1.00
0.99
0.98
1.04
1.00
19%
Established after 2000
0.37
0.64
0.47
0.64
0.50
0.60
Autonomy Score
0.12**
0.28
0.29
0.36
0.29
0.32
Manuf. Appliances
0.79
0.83
0.78
0.84
0.83
Manuf. Systems
0.31***
0.28***
0.29***
0.29***
0.29***
15%
Unit Cost: £10 to £100
0.38
0.21**
0.18**
0.24*
0.20**
Unit Cost: £100 to £1k
0.19***
0.14***
0.12***
0.15***
0.12***
Unit Cost: £1k to £10k
0.02***
0.01***
0.01***
0.01***
0.01***
Unit Cost: £10k - £100k
0.15**
0.11***
0.10***
0.11***
0.10***
Unit Cost: Over £100k
0.09**
0.07**
0.06***
0.09**
0.07**
Top Cust. 50%+ of sales
2.01
1.59
1.82
1.61
5 Top Custs 50%+ sales
0.33**
0.32**
0.32**
0.31**
< 3 Competitors
0.80
0.82
0.75
0.79
> 10 Competitors
0.80
0.70
0.77
0.69
Motivation PC1
0.80
0.88
Motivation PC2
0.83
0.87
20%
Motivation PC3
1.24
1.31
Arrangements PC
0.75
0.77
High Income Share from Services (i.e., > 10% of Turnover, compared with 1 – 10% of Turnover)
Sector: Rubber/Plastics
0.74
0.72
0.68
0.59
0.80
0.66
Sector: Metal Products
1.33
1.12
1.24
1.27
2.10
1.95
Sector: Machinery
3.48***
2.81**
3.01**
3.43**
3.65**
3.99**
Sector: Electr-ical/onics
1.52
1.50
1.47
1.78
1.97
2.10
Sector: Instruments
1.61
1.31
1.26
1.33
1.64
1.63
19%
Size (Ln Employment)
1.41*
1.40*
1.40*
1.29
1.07
1.04
15%
15%
Established after 2000
0.15*
0.14*
0.14*
0.13*
0.20
0.19
Autonomy Score
0.49
0.45
0.49
0.61
0.97
0.98
Manuf. Appliances
1.14
1.15
1.40
1.29
1.43
20%
Manuf. Systems
1.67
1.67
1.54
1.74
1.69
Unit Cost: £10 to £100
0.73
0.59
0.65
0.58
0.60
Unit Cost: £100 to £1k
0.54
0.48
0.48
0.36
0.35
Unit Cost: £1k to £10k
0.76
0.71
0.68
0.56
0.54
Unit Cost: £10k - £100k
1.04
0.92
0.91
0.62
0.64
Unit Cost: Over £100k
1.49
1.36
1.15
0.59
0.54
Top Cust. 50%+ of sales
1.45
1.81
1.91
2.09
5 Top Custs 50%+ sales
0.87
0.85
1.04
1.00
11%
< 3 Competitors
2.08
2.68
2.91*
3.43*
> 10 Competitors
1.21
1.40
1.35
1.44
14%
Motivation PC1
1.72**
1.41
Motivation PC2
1.02
0.95
Motivation PC3
1.18
1.06
Arrangements PC
2.71***
2.52***
Residual -2 LL
436.2
392.5
382.9
370.2
360.7
355.1
2
Model χ
51.1
119.9
130.9
143.6
153.1
158.7
2
McFadden Pseudo R
0.1
0.233
0.255
0.28
0.298
0.309
All models have 238 observations. *** Significant at 1%; ** Significant at 5%; * Significant at 10%
30