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MF
36,6
Economic impact of marketing
alliances on shareholders’ wealth
Foo-Nin Ho and Allan D. Shocker
534
Department of Marketing, College of Business, San Francisco State University,
San Francisco, California, USA, and
Yewmun Yip
Department of Finance, Beacom School of Business,
University of South Dakota, Vermillion, South Dakota, USA
Abstract
Purpose – The purpose of this paper is to examine whether marketing alliances create value for
shareholders, and whether the results are robust across different business cycles.
Design/methodology/approach – Using standard event study methodology, abnormal returns
(AR) were computed for 402 firms which formed marketing alliances in a 12-month period covering
three business time periods, namely bull, bear and post 9/11 periods. ANOVA and regression
analyses were performed on cumulative abnormal returns (CAR).
Findings – Significant and positive AR were found on announcement day for firms forming
marketing alliances. When the sample is segmented by market capitalization, small cap firms were
found to stand to benefit the most, particularly when partnering with a large firm. During the bear
market period, marketing alliances tend to benefit small cap firms and firms with low profitability,
whereas during the bull market period, marketing alliances benefit firms with low asset utilization.
Research limitations/implications – Results are limited by the accuracy of the models used to
measure AR.
Practical implications – The results seem to suggest that smaller partners tend to benefit more
from marketing alliance, and the effect changes with business cycle.
Originality/value – The paper analyses how the benefits of forming a marketing alliance are shared
between partnering firms and how the different phases of business cycle influence the distribution of
benefits.
Keywords Marketing, Strategic alliances, Shareholder value analysis, Business cycles
Paper type Research paper
1. Introduction
By definition, a strategic alliance is a formal cooperative agreement between firms
designed to pursue a set of agreed upon goals so as to achieve competitive advantages
for both partners. Strategic alliances in general involve either collaborative effort (nonequity) or joint venture (equity). In a joint venture alliance, both partners share equity
control in a new organizational entity. In a collaborative alliance, neither partner has
any equity stake since no new entity is created, and the goal is to pool and leverage on
each other’s resources to achieve a common goal. Within non-equity alliances, they can
be further classified by two dimensions (Chan et al., 1997):
(1) horizontal vs non-horizontal; and
(2) technical vs non-technical.
Managerial Finance
Vol. 36 No. 6, 2010
pp. 534-546
# Emerald Group Publishing Limited
0307-4358
DOI 10.1108/03074351011043017
Horizontal alliances involve partners in the same three-digit SIC class while nonhorizontal alliances are between firms from unrelated industries. Technical alliances
involve the transfer or pooling of technological knowledge between the partners (e.g.
licensing agreements, and research and development agreements) while non-technical
alliances involve marketing and distribution agreements. An example of marketing
alliance is the common practice by airlines to engage in marketing alliances to promote
their frequent flyer programs such as the formation of star alliance. In times of tight
budgets, an underinvestment in marketing and brands may have a long-term adverse
impact on the firm. Swaminathan and Moorman (2009) find that by pooling resources
together in a marketing alliance with another firm can increase the value of the
partnering firms, particularly for marketing alliances in high-tech software industry.
Zagnoli (1987) find that non-equity alliances account for over 50 per cent of all
strategic alliances, and other researchers find that non-equity alliances offer more
advantages than equity joint ventures. For example, Jensen and Meckling (1991) argue
that non-equity alliances provide an organizational mechanism that aligns decision
authority with decision knowledge, and that benefits and costs resulting from the
decisions accrue fully to the decision maker, i.e. decisions are delegated to a level closer
to the requisite knowledge. Another advantage is the organizational flexibility of such
alliances where new links can be formed or current links disbanded in response to
market demands. On the other hand, there are costs associated with these ‘‘symbiotic’’
alliances – those that relate to searching out reliable partners, designing contracts and
other bonding mechanisms that discourage opportunism, and monitoring the
behaviour of alliance partners (Chan et al., 1997; Klein et al., 1978). In such situations,
companies have to balance between preserving key proprietary knowledge to maintain
their competitive advantage and insuring that partners will see a need to pool their
resources. This conjecture is supported by the findings of Luo et al. (2007) in that firms
must carefully balance between competition and cooperation when working with their
rivals in a cooperative alliance. Conversely, Harrigan (1984) notes that most strategic
alliances usually involve technology or knowledge that companies know they cannot
protect adequately or control.
Over the years, various scholars have studied strategic alliances. For example,
researchers have looked at the theoretical and conceptual foundations, motives for, and
framework of strategic alliances (Varadarajan and Cunningham, 1995); economic
outcome of strategic alliances (Chan et al., 1997); choice between equity and non-equity
modes of alliance (Pisano, 1989); the management and structuring of alliances (Parkhe,
1993). Marketing scholars have also looked at strategic alliances such as intraorganizational cooperation between marketing and other functional areas or other
business units (Ruekert and Walker, 1987) and inter-organizational relationships
between firms (Adler, 1966; Swaminathan and Moorman, 2009; Luo et al., 2007). Some
researchers have also identified the importance of marketing alliances in the overall
realm of strategic alliances. Varadarajan and Cunningham (1995) view marketing
activities as critical factors in the success of strategic alliances especially in a rapidly
changing business and market environments. Other researchers have also echoed this
sentiment in recognizing the importance of integrating marketing in strategic alliances
(Webster, 1992; Day, 1992).
2. Economic value of strategic marketing alliances
Das et al. (1998) and Chan et al. (1997) have found that while strategic alliances create
value for their shareholders especially when there is sharing of technological knowhow, but that is not necessary true for marketing alliances. For technological alliances
involving firms in the same industry, Chan et al. (1997) report a significant positive
returns, and whereas for marketing alliances, a significant positive return is observed
only when the partners are from unrelated industries. In their study on marketing
alliances by high-tech software firms, Swaminathan and Moorman (2009) also find a
Impact of
marketing
alliances
535
MF
36,6
536
significant positive return for both partnering firms. On the other hand, Das et al. (1998)
do not find a significant return to shareholders for the formation of marketing alliances.
Das et al. (1998) find that although investors view alliances formed by more profitable
firms as detrimental to their value, marketing alliances are viewed as more detrimental
than technological alliances. On the hand, Chan et al. (1997) report that firms entering
into strategic alliances tend to outperform their industry counterparts in the period prior
to the formation of the alliances, and therefore, they argue that the formation of an
alliance is not in response to poor performance. Larger firms, especially in technological
alliances, depend critically on their smaller partners for resources (e.g. technological
know-how). This asymmetric dependence enhances the bargaining power of the smaller
partners. This conjecture is supported by the empirical evidence provided by Das et al.
(1998) in that the market reaction to smaller firms’ alliances is greater than the reaction to
larger firms’ alliances. This effect is more prominent for technological alliances, where
smaller partners earn significantly higher returns than their larger partners. However,
there are no discernible differences in the returns earned by the small and large partners
in marketing alliances. Chan et al. (1997) also report similar findings in that smaller
partners tend to benefit the most from forming a strategic alliance, but their larger
counterparts do not suffer a decline in value.
The existing literature seems to suggest that marketing alliances do not create value
unless it is forged between firms in unrelated industries. Why do we continue to observe
the formation of so many marketing alliances? The apparent incongruity between
marketing practices and existing empirical results lead us to investigate further the issue
of whether marketing alliances create value for shareholders. The seemingly conflicting
results on which types of firms benefited the most from forming a strategic alliance as
reported by Chan et al. (1997) and Das et al. (1998) are perhaps due to using different
sampling periods. Essentially, Das’s 1998 study covers the bear market period (i.e. from
1987 to 1991) while Chan’s 1998 study covers a longer period (i.e. from 1983 to 1992)
which includes both the bear and the bull market. In this study, we hypothesize that the
market reacts differently to the different characteristics of firms forming marketing
alliances during different phases of the business cycle. During a bear market, the market
may view the formation of an alliance by a poor performing firm as a positive move
towards profitability and reward the firm for doing that. On the other hand, during a bull
market, since most firms are profitable, profitability may not play as critical a role in
deciding on the formation of a marketing alliance.
Given the limited empirical studies on marketing alliances and their economic
impact, our research objective is, therefore, to re-examine whether non-equity
marketing alliances create economic value for the shareholders. In this study, we look
at non-equity, non-technical marketing alliances (henceforth referred simply as
marketing alliances) and their economic impact on shareholders’ value. Specifically, the
marketing alliances we examined include cross-licensing, co-branding, co-marketing,
and joint marketing. In addition to investigating the economic value of marketing
alliances, we also examine whether there is a redistribution of wealth between
partners. Third, we also examine the influence of business cycle on the economic value
of marketing alliances. Therefore, our research questions about marketing alliances
and their economic impact are stated as follows:
RQ1.
What is the economic return to shareholders from forming a marketing
alliance?
RQ2.
Who benefits the most from such alliances?
RQ3.
Whether business cycle plays a role in influencing the type of firms entering
into a marketing alliance?
The rest of the paper is organized as follows. Section 3 presents data description and
methodology. Section 4 discusses the empirical results. Finally, section 5 offers our
concluding comments.
3. Research design
3.1 Data collection
An event such as marketing alliance is usually well publicized in the media in the form
of business wires. To obtain a sample of firms announcing strategic marketing
alliances, we conduct a search of the Lexis/Nexis database including all business wires
covering the following time periods:
.
bull market period from 1 November 1999 to 28 February 2000 (also known as
the internet bubble period);
.
bear market period from 1 March 2001 to 10 September 10 2001; and
.
post 11 September from 11 September 2001 to 31 October 2001.
Since marketing alliances are commonly announced in the media, within this 12-month
period, our search resulted in close to 10,000 initial hits, and therefore, provided us with
a large enough sample size for the study.
Data collection for the study is a multi-stage process. In stage one, we search the
Lexis/Nexis database using the keywords ‘‘strategic alliance’’. In stage two, we narrow
the search by using a combination of four keywords; specifically, co-marketing, cobranding, joint marketing, and marketing alliance as these represent non-equity
marketing alliances. From this search, there are 9,847 hits. Every announcement is then
reviewed to see if it meets the criteria of a marketing alliance, i.e. a non-equity
agreement that is non-technical. We exclude all alliances that involve the transfer or
pooling of technological knowledge. Cases, whereby the announcement has both
technical and non-technical components, are also excluded from the final sample.
The filtering process identifies 311 qualified announcements of marketing alliances
involving 402 firms in which at least one partner’s common stock is publicly traded,
and data on daily stock returns and market capitalization are available. Stock price
data are obtained from Commodity Systems Inc and Exchanges hosted on the Yahoo!
Finance web site and the previous year annual financial data for each firm are obtained
from the COMPUSTAT database. The Security Exchange Commission requires
companies to report their financial statements no later than three months after the
fiscal year ending date. To ensure that the firm’s financial data are available on the
event day, we restrict the fiscal year ending date of the financial statements to be at
least three months before the event date.
For comparisons, firms in the final sample (Table I) are further classified by their
market capitalization, which is defined as the price of a share of common stock
multiplied by the number of shares outstanding. Small cap firms are defined as having
a market value of less than $1 billion; mid cap firms have value of between $1 and $5
billion; and, large cap firms with market value greater than $5 billion.
3.2 Measuring abnormal returns
We use an event-study methodology similar to that described in Brown and Warner
(1985) to measure the stock market’s reaction to the announcements of marketing
Impact of
marketing
alliances
537
Table I.
Descriptive statistics of
firm characteristics
274.26
0.80
0.05
0.76
3.99
0.24
3.50
0.25
2.73
27.18
2.45
144.38
0.89
0.05
0.00
0.00
0.02
0.03
1.03
0.89
5.21
307.54
0.00
1.12
Small cap firms
SD
Min
Mean
1,078.65
0.19
0.00
0.03
0.25
0.02
1.02
0.29
5.77
6.04
0.04
0.67
Mid cap firms
SD
Min
57
934.49 2,789.69 1,104.38
3.48
1.23
0.95
0.21
0.07
0.07
6.12
0.48
0.45
37.33
1.81
1.51
0.96
0.58
0.24
25.99
4.15
6.55
0.33
0.02
0.10
26.37
0.04
0.85
5.63
0.15
0.89
15.27
1.23
1.03
778.58
298.46 1325.08
Max
4,851.00
3.40
0.31
2.54
7.64
0.98
47.09
0.21
1.11
0.25
4.65
6373.00
Max
207
85,672.57
1.57
0.03
0.20
1.94
0.53
3.18
0.08
0.16
0.11
0.89
58.04
Mean
101,367.01
0.86
0.03
0.21
1.44
0.22
2.90
0.10
0.32
0.40
0.63
271.44
5,049.28
0.01
0.00
0.01
0.26
0.08
1.09
0.66
2.70
1.81
0.05
0.95
Large cap firms
SD
Min
Notes: The reported F-statistic is for testing if the means of three independent samples are equal; *p-value < 0.10; **p-value < 0.05
n
138
Market cap
278.66
Beta
1.21
Earnings-price ratio
0.06
Book-to-market
0.59
Current ratio
3.16
Debt ratio
0.39
Equity multiplier
2.69
Return on assets
0.11
Return on equity
0.01
Profit margin
3.73
Asset turnover
1.51
Time interest earned 64.54
Mean
538
Firm characteristics
460,770.51
4.39
0.19
1.59
10.48
0.93
15.12
0.28
1.46
2.71
3.98
3362.09
Max
67.85**
8.35**
24.76**
26.41**
9.56**
18.98**
2.78*
51.11**
0.59
2.55*
6.63**
2.95*
F-stat
MF
36,6
alliances. The day when a press release is issued on the formation of a marketing
alliance is defined as the event day (i.e. t ¼ 0). We then examine the behaviour of stock
returns 60 days before the event day, and 60 days after the event day (i.e. t ¼ 60, þ60).
For each of the 402 previously identified stocks, the daily risk-adjusted returns are
estimated using both the market model and the market-adjusted returns (see, Brown
and Warner, 1985). For market-model risk-adjusted return, the parameters of the single
index market model are estimated over a 200-day period (t ¼ 260, . . ., 61) using the
S&P 500 index as the market index. The parameter estimates are then used to calculate
the abnormal returns (ARt) for the period from 60 days before to 60 days after the
announcement day.
However, the results based on a single-index model can be biased due to model
misspecification, as pointed out by Roll (1977). To avoid specification bias, we also
compute the market-adjusted returns for each of the 402 stocks, and again the S&P 500
index is used as the market index.
The cumulative abnormal return CARj (–m, þn) for event window from Day m to
Day þn is then computed for each stock using the following equation:
CARj ðm; þnÞ ¼
tþn
X
ARj;k
k ¼ tm
4. Empirical results
4.1 Sample characteristics
Table I presents the characteristics of firms in the sample. As shown by their
profitability measures, such as returns on assets and profit margin, small cap firms
have lower profit margin as compared to their larger counterparts. In fact, more than
half of the small cap firms are unprofitable prior to their entering into a marketing
alliance, compared to only 5 per cent for the large cap firms. In addition, the common
stocks of small cap firms are not as highly priced by investors as indicated by their
high earnings-price and book-to-market ratios.
Perhaps, because of their low profitability, these small cap firms are not as highly
leveraged as indicated by their average debt ratio of 39 per cent as compared to 53 per
cent for large cap firms. They also have higher liquidity as measured by a high average
current ratio of 3.16. Surprisingly, the small cap firms are also more efficient in the use
of asset as shown by their higher asset turnover ratio. On the other hand, the lower
earnings-price ratios for the large cap firms may indicate that investors expect these
firms to have a higher potential growth rate. The stock returns of these large
companies are also more risky as shown by their higher betas.
4.2 Stock price response to announcement of marketing alliances
For compatibility reasons, we adopt the same event windows as those used by Das et al.
(1998). Since the results using market-adjusted AR are very similar to those using
market-model-adjusted AR, we report only the market-model-adjusted CAR. Table II
presents the average CAR calculated for various event windows. For all firms in the
entire sample period, our results show that, on average, the market reacts positively to
the announcements of marketing alliances for all event windows. On the event day
(Day 0), firms entering into marketing alliances earn, on average, a significant
abnormal return of 0.66 per cent. When we partition the firms in the sample into three
Impact of
marketing
alliances
539
MF
36,6
540
Table II.
Average cumulative AR
over different event
windows
All firms
Small cap
Mid cap
Large cap
Event window Mean t-statistic Mean t-statistic Mean t-statistic Mean t-statistic F-statistic
Full sample
n
Days 3 to 3
Days 2 to 2
Days 1 to 1
Days 1 to 0
Days 0
Days 0 to 1
Days 1 to 2
Days 1 to 3
Days 2 to 1
Days 3 to 1
Bull market
n
Days 3 to 3
Days 2 to 2
Days 1 to 1
Days 1 to 0
Days 0
Days 0 to 1
Days 1 to 2
Days 1 to 3
Days 2 to 1
Days 3 to 1
Bear market
n
Days 3 to 3
Days 2 to 2
Days 1 to 1
Days 1 to 0
Days 0
Days 0 to 1
Days 1 to 2
Days 1 to 3
Days 2 to 1
Days 3 to 1
Post 9/11
n
Days 3 to 3
Days 2 to 2
Days 1 to 1
Days 1 to 0
Days 0
Days 0 to 1
Days 1 to 2
Days 1 to 3
Days 2 to 1
Days 3 to 1
402
2.52%
2.45%
1.82%
1.35%
0.66%
1.12%
1.90%
2.27%
2.32%
2.04%
3.54**
3.77**
3.45**
2.97**
2.03**
2.76**
3.20**
3.44**
3.86**
3.28**
138
4.17%
4.63%
3.07%
2.74%
1.00%
1.32%
3.70%
4.07%
3.86%
3.06%
142
4.10%
2.99%
2.52%
1.43%
0.89%
1.98%
2.76%
3.64%
2.75%
2.98%
3.22**
2.77**
2.94**
2.18**
1.80*
3.06**
2.90**
3.42**
2.76**
2.62**
45
7.09%
5.17%
4.10%
2.02%
1.79%
3.86%
5.39%
6.53%
3.89%
4.65%
19
2.24** 3.82% 1.37
2.01*
3.56% 1.43
2.01*
2.07% 1.08
1.30
2.19% 1.29
1.42 0.38% 0.29
2.76** 0.50% 0.32
2.35** 2.07% 0.98
2.64** 4.02% 1.56
1.62
3.56% 1.69
1.61
1.87% 0.84
219
1.97%
2.70%
1.78%
1.54%
0.51%
0.75%
1.74%
1.64%
2.67%
2.03%
2.10**
2.96**
2.42**
2.27**
1.11
1.34
2.03**
1.74*
3.23**
2.61**
76
4.72%
6.54%
4.22%
4.39%
1.12%
0.94%
4.36%
4.07%
6.19%
4.62%
1.89*
2.71**
2.28**
2.55**
0.97
0.68
1.94*
1.64
2.88**
2.33**
41
0.15%
0.80%
0.40%
0.08%
0.67%
0.20%
0.25%
0.85%
1.02%
1.20%
0.07
0.49
0.26
0.06
0.60
0.13
0.18
0.51
0.56
0.59
17
7.18%
5.63%
4.79%
2.73%
1.65%
3.70%
4.19%
3.31%
6.36%
7.84%
2.30**
2.85**
2.45**
2.47**
1.30
1.43
2.50**
2.47**
2.61**
2.01**
57
3.10%
3.41%
1.48%
1.22%
0.51%
0.77%
1.85%
2.77%
3.03%
1.81%
32
2.27%
2.88%
0.63%
0.57%
1.38%
1.43%
1.27%
1.52%
2.24%
1.38%
2.40**
3.09**
1.62
1.58
0.93
1.04
1.86*
2.37**
3.12**
1.65
207
1.31%
0.77%
1.08%
0.46%
0.47%
1.09%
0.74%
0.96%
1.12%
1.43%
2.09**
1.33
2.03**
1.07
1.39
2.39**
1.37
1.64
1.94*
2.39**
1.70
3.84**
1.50
2.59*
0.28
0.10
2.56*
2.33*
2.26
0.72
78
2.44%
1.59%
1.72%
0.90%
0.67%
1.49%
1.41%
1.88%
1.90%
2.28%
1.96*
1.41
1.87*
1.32
1.60
1.99**
1.45
1.67*
1.78*
2.06**
1.35
1.13
0.79
0.39
1.03
2.54*
1.83
1.96
0.45
0.51
111
1.50
0.09% 0.14
2.35** 0.11% 0.19
0.57
0.44% 0.73
0.62
0.13% 0.25
2.45** 0.16% 0.39
1.74*
0.41% 0.84
1.04
0.11% 0.17
1.12
0.03% 0.04
2.05** 0.45% 0.75
1.02
0.51% 0.80
6
18
1.94*
5.24% 1.60
3.91%
2.51** 5.76% 2.07*
1.31%
2.70** 4.13% 2.22*
2.24%
1.66
1.62% 1.29
2.23%
1.87* 1.30% 2.54*
3.53%
2.68** 1.21% 0.51
3.54%
2.59** 4.29% 2.43*
1.73%
1.08
5.47% 2.67** 2.78%
2.58** 5.60% 1.94
1.82%
2.62** 3.91% 1.27
3.37%
1.67
0.51
0.81
0.93
1.55
1.28
0.69
1.22
0.62
1.15
2.52*
5.28**
2.96*
4.89**
1.10
0.22
2.58*
1.91
5.15**
2.96*
4.48**
2.22
3.78**
3.08*
3.30**
1.74
2.76*
2.92*
3.74**
4.54**
Notes: The reported t-statistic is for testing if the mean of the sample is zero; the reported
F-statistic is for testing if the means of three independent samples are equal; *p-value < 0.10;
**p-value < 0.05
groups based on their market capitalization, the average AR of firms on the event day
in all three groups were statistically indistinguishable from zero. Except for the event
day and the day after the announcement, small cap firms enjoy significant AR for all
event windows. Over a seven-day period, from Day 3 to Day 3, small cap firms
participating in a marketing alliance, on average, earn an excess return of 4.17 per cent.
For mid cap and large cap firms, although the results are not as robust, significant
positive AR are also observed for event window Day 3 to Day 3. Furthermore, the
results of ANOVA F-tests show that small cap firms enjoy significantly higher AR for
the windows 2 to 2, 1 to 0, 1 to 2, and 1 to 3.
During both the bull and the bear market periods, the market reacts positively and
significantly to the formation of marketing alliances. In the bull market period, large
cap as well as small cap firms enjoy positive significant AR, whereas mid cap firms
show no significant reaction to the news. However, the AR for large cap firms during
the bear market are statistically not significant. Small cap firms, on a whole, show
positive AR for both the bull and the bear market periods.
In the post 9/11 period, small cap firms experience significant negative AR for most
of the event windows, and on the event day they lost 1.65 per cent of their value. Also,
the market does not show any significant reaction to large cap firms engaging in
marketing alliances. When we examine all the firms in the post 9/11 period together,
the AR for firms engaging in marketing alliances are not statistically significant.
Similar to the findings of Chan et al. (1997) and Swaminathan and Moorman (2009),
our results show that marketing alliances create value for shareholders. The results
hold for both the bear market and the bull market period. Small firms participating in a
marketing alliance benefit the most. However, in the post 9/11 period, small firms suffer
a significant decline in value.
4.3 Cross-sectional regression analyses
In this section, we examine whether firm characteristics such as profit margin, debt
ratio, asset utilization, and firm size can explain some of the market reaction to the
announcements of the marketing alliances. Table III reports the results of two
regression models. To allow for possible leakage of information and similar to the
procedure used by previous researchers (Chen et al., 2002; Huang and Walking, 1987),
we use CAR(–1, 0) as the dependent variable. Our results for the full sample show that
small cap firms enjoy a statistically significant positive abnormal return of 3 per cent.
The coefficient for asset turnover was negative and statistically significant which
shows that firms with lower asset utilization can benefit from increasing their sales
through joint marketing, and as a result, will be able to use their assets more efficiently.
Taken together, the results show that small firms and firms with low asset turnover
tend to benefit more from forming a marketing alliance.
However, when we perform the same analysis on different sub-periods, the dummy
variable for small cap firms is significant only during the bear market period. During
the bull market period, firms with low asset turnover benefit the most from forming a
marketing alliance. The results make sense because firms with low asset utilization
tend to have excess capacity, and through forming a marketing alliance, their assets
can be utilized more efficiently. In addition, profitability is not significant, and this is
consistent with the evidence presented by Chan et al. (1997), that is, firms do not enter
into marketing alliances because of poor profitability. However, the results for the bear
market period show that small cap firms and firms with low profitability can gain from
entering into a marketing alliance, and the results is consistent with those reported by
Impact of
marketing
alliances
541
MF
36,6
Independent
variables
INTERCEPT
DSIZE1
542
DSIZE2
DEBT RATIO
PROFIT
MARGIN
ASSET
TURNOVER
n
Adjusted R2
F-value
p-value
Table III.
Regressions of
announcement-period
AR
All
0.002
(0.184)
0.030
(2.809)**
0.009
(0.674)
0.018
(1.005)
0.000
(0.716)
0.008
Model 1
Bull
Bear
Post 9/11
0.018 0.008
0.084
(0.883) (0.521)
(2.293)**
0.016
0.037
0.033
(1.054)
(2.233)** (1.044)
0.016
0.001
0.032
(0.794)
(0.065)
(0.739)
0.002
0.022
0.150
(0.061)
(0.937) (1.695)*
0.000 0.015
0.030
(1.116) (3.306)** (0.848)
0.010 0.006
0.003
(2.709)** (1.693)* (1.417)
396
142
215
0.019
0.003
0.092
2.530
0.920
5.320
0.029
0.472
0.000
(0.282)
42
0.074
1.620
0.181
All
0.017
(1.664)*
0.006
(0.367)
0.000
(0.440)
0.006
Model 2
Bull
Bear
0.027
(1.511)
0.009
(0.637)
0.004
0.005
(0.133) (0.229)
0.000 0.019
Post 9/11
0.073
(2.003)*
0.139
(0.819)
0.044
(1.005) (4.375)** (0.000)
0.009 0.003
0.004
(2.128)** (1.549) (0.751)
397
147
216
0.004
0.001
0.078
1.560
1.060
6.980
0.198
0.369
0.000
(0.453)
42
0.052
1.710
0.182
Notes: *p-value < 0.10; **p-value < 0.05; the dependent variable is CAR(1, 0), the two-day
announcement-period AR for the firms that announce the formation of a marketing alliance. The
announcement period AR is estimated using the standard market model procedure with
parameters estimated for the period 260 days to 61 days before the announcement. DINTERNET
equals one if the announcing firm engages in an internet marketing alliance, and zero otherwise.
DTIME1 equals one if the announcement date is between 1 November 1999 and 29 February
2000, and zero otherwise. DTIME2 equals one if the announcement date is between 1 March 2001
and 10 September 2001, and zero otherwise. DSIZE1 equals one if the firm’s market capitalization
is less than $1 billion, and zero otherwise. DSIZE2 equals one if the firm’s market capitalization is
greater than $1 billion and less than $5 billion, and zero otherwise. DEBT RATIO is the total
debt divided by total assets. PROFIT MARGIN is net income divided by sales. ASSET
TURNOVER is sales divided by total assets. The numbers in the parentheses are the t-statistics
of the parameter estimates. The number of observations varies across different regression models
due to availability of data
Das et al. (1998) in that profitability is detrimental to the value of firms forming a
marketing alliance. Our results seem to suggest that the different sample periods
covering different business cycle may be able to explain the contradicting results
reported by Chan et al. (1997) and Das et al. (1998).
In the post 9/11 period, the only variable that is statistically negatively significant is
debt ratio. A possible explanation is that after a catastrophic event, firms that can stand
to gain the most from forming a marketing alliance are firms which are not heavily
burdened by debt, and hence, are in a better position to fund such marketing alliance.
4.4 Analysis of wealth effects by relative partner size
Finally, we examine if the gain by small cap firms is due to an expropriation of wealth
from its larger partners, and therefore, we compared the change in wealth of pairs of
partner firms. In our sample, we are able to identify 87 alliances with financial
information on the two partners involved in a marketing alliance. We further subdivide
the sample based on the disparity in the market capitalization of the alliance partners,
and dummy coded the difference in the size. If firms from the same market
capitalization group (e.g. alliance between two small cap firms) entered into a
marketing alliance, the size difference code is equal to 0. The size difference code is
equal to 1 if the alliance is between large cap and mid cap or between small cap and
mid cap firms. If the alliance is between small cap and large cap firms, the size
difference code is equal to 2, which represent partners with the greatest size disparity.
In alliances where the differences in market values of the partners is not substantial,
the paired t-test results reported in Table IV show that on average, the CAR’s for the
alliance partners are not different from each other, and the alliance partners do not
experience a significant change in their stock value. However, if the marketing alliance
is formed between a large cap firm and a small cap firm, our results show that smaller
partners enjoy a significant increase in value while the larger partners experience a
negative but statistically insignificant decline in value. The pair test results show that
smaller partners earn greater returns than their substantially larger partners, and the
results are statistically significant for all event windows.
When marketing alliances are formed between partners with a large disparity in
size, our results are consistent with those reported by Chan et al. (1997) in that smaller
partner firms in a strategic alliance enjoy a statistically significant increase in value
but not at the expense of their larger partners. When marketing alliances are formed
between firms of similar sizes or when the disparity in size is small, marketing
alliances do not create any value for the participating firms.
5. Conclusions and discussion
Our results show that marketing alliances do create value for shareholders. We also
find that small cap firms stand to benefit the most from forming a marketing alliance,
particularly with a large partner. However, when a marketing alliance is formed
between firms of similar sizes, both partners do not gain any wealth from the
marketing alliance. Our findings are in agreement with those reported by Chan et al.
(1997) who also find that small partners in a strategic alliance enjoy a significant
increase in value but not at the expense of their larger partners.
Contradicting empirical evidence are provided by Chan et al. (1997) and Das et al.
(1998) on the effect of prior operating performance of a firm on the value of an alliance.
However, when we re-examined their results by segmenting the sample into bull market
and bear market periods, we are able to reconcile their findings. The sample period of
Das et al. (1998) study covers the period after the 1987 market crash to the end of Gulf
War, which coincides with the bear market. Our results showed that during the bearmarket period, marketing alliances tend to benefit small cap firms and firms with low
profitability; and, this is consistent with Das et al.’s (1998) findings in that marketing
alliances are more detrimental to profitable firms. On the other hand, the sample period
of Chan et al.’s (1997) sample period starts with the Reagan’s years to the end of the Gulf
War, which include both the bull and bear market periods. Our results for the bull market
show that profitability is not significant in explaining the observed AR which is
consistent with Chan et al. (1998) results. In bull market period, our results indicate that
firms with low asset turnover benefit the most from forming a marketing alliance. In the
bull market, firms that are not operating at full capacity are seeking ways to increase its
sales. Investors viewed that forming a marketing alliance is a step in the right direction
for the company, and hence rewarded the companies for taking the step.
The important implications from our findings are that during a recession, it makes
economic sense for small firms with poor financial performance to seek out larger
Impact of
marketing
alliances
543
MF
36,6
544
Table IV.
Analysis of wealth
effects by relative
partner size
Event window
Full sample
n
Days 3 to 3
Days 2 to 2
Days 1 to 1
Days 1 to 0
Days 0
Days 0 to 1
Days 1 to 2
Days 1 to 3
Days 2 to 1
Days 3 to 1
Size difference ¼ 0
n
Days 3 to 3
Days 2 to 2
Days 1 to 1
Days 1 to 0
Days 0
Days 0 to 1
Days 1 to 2
Days 1 to 3
Days 2 to 1
Days 3 to 1
Size difference ¼ 1
n
Days 3 to 3
Days 2 to 2
Days 1 to 1
Days 1 to 0
Days 0
Days 0 to 1
Days 1 to 2
Days 1 to 3
Days 2 to 1
Days 3 to 1
Size difference ¼ 2
n
Days 3 to 3
Days 2 to 2
Days 1 to 1
Days 1 to 0
Days 0
Days 0 to 1
Days 1 to 2
Days 1 to 3
Days 2 to 1
Days 3 to 1
Small partner
Mean
t-statistica
87
3.22%
2.87%
2.81%
2.34%
1.41%
1.89%
2.93%
3.65%
2.76%
2.38%
1.82*
1.97*
1.96*
1.75*
1.47
1.68*
1.96*
1.99**
1.88*
1.62
Large partner
Mean
t-statistica
87
0.35%
0.35%
0.37%
0.57%
0.44%
0.24%
0.21%
0.22%
0.22%
0.50%
0.33
0.41
0.57
0.95
1.15
0.52
0.25
0.22
0.32
0.65
t-statisticb
1.38
1.93*
1.59
1.25
0.97
1.37
1.89*
1.75*
1.57
1.06
43
0.20%
0.76%
0.16%
0.57%
0.42%
0.01%
0.57%
0.06%
0.35%
0.42%
0.10
0.50
0.11
0.45
0.38
0.01
0.34
0.03
0.23
0.23
43
1.13%
0.08%
0.55%
0.92%
0.62%
0.24%
0.27%
0.88%
0.35%
0.79%
0.65
0.06
0.57
1.11
1.03
0.34
0.20
0.52
0.34
0.73
0.55
0.43
0.41
1.04
0.95
0.20
0.42
0.37
0.41
0.56
17
4.40%
3.87%
3.77%
2.61%
1.35%
2.50%
3.09%
4.59%
4.55%
3.58%
1.19
1.05
1.22
1.45
0.82
0.84
0.89
1.11
1.38
1.34
17
2.36%
0.46%
0.91%
1.15%
1.11%
0.87%
0.14%
1.49%
1.51%
1.78%
0.86
0.21
0.50
0.61
1.37
0.93
0.06
0.69
0.81
0.72
0.42
0.77
0.83
0.76
0.13
0.51
0.79
0.69
0.80
0.46
27
7.91%
8.02%
6.95%
6.80%
4.38%
4.53%
8.40%
8.78%
6.57%
6.08%
1.93*
2.56**
2.10**
1.96*
1.93*
1.93*
2.62**
2.08**
1.94*
1.85*
27
2.15%
1.56%
0.26%
0.36%
0.26%
0.16%
1.02%
1.64%
0.79%
0.77%
2.45**
1.41
0.30
0.46
0.44
0.21
0.93
1.45
0.85
0.86
2.32**
2.99**
2.12**
2.01*
1.96*
1.78*
2.96**
2.48**
2.06**
1.84*
Notes: aThe reported t-statistic is for testing if the sample mean is equal to zero; bthe reported
t-statistic is for testing if the paired sample mean is equal to zero; *p-value < 0.10; **p-value < 0.05
firms to form a marketing alliance. This strategy to partner with larger firms allows
smaller firms the access to market and resources that otherwise will be very expensive
to build, and as pointed out by Swaminathan and Moorman (2009) in tough economic
conditions, it makes economic sense for firms to pool resources together to achieve a
set of common goals. Larger firms, on the other hand, can be more selective in their
partnerships. They should try to pick firms that provide some value-added services or
access to certain markets in which they are not currently operating. During an
economic boom, firms with low asset utilization will benefit most from forming a
marketing alliance, especially those that will help expand the marketability and
channel of their products and services. Even though the results do not show a
significant impact of strategic marketing alliances on the value of large firms
compared to smaller firms; however, the value may be seen elsewhere especially when
other studies have found that other forms of strategic alliances do add value in
conjunction with marketing alliances.
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545
MF
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546
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About the authors
Foo-Nin Ho is a Professor of Marketing at San Francisco State University. Ho received his PhD in
Marketing from the University of Mississippi. His research interests include marketing and
consumer ethics, advertising, healthcare marketing, ethnic marketing and consumer decisionmaking. His work has previously appeared in the Journal of the Academy of Marketing Sciences,
Journal of Business Ethics, Marketing Health Service, Journal of Pharmaceutical Marketing and
Management, Journal of Marketing Theory and Practice, Journal of Consumer Marketing, Journal
of Promotion Management, Health Marketing Quarterly, as well as various national proceedings.
Allan D. Shocker is a Visiting Professor of Marketing at San Francisco State University.
Shocker received his PhD from Carnegie Mellon University. His research interests lie in the areas
of customer decision-making, product planning, new product design and development, market
structure analysis, diffusion modelling, and brand equity. His work has appeared in Journal of
Marketing, Journal of Marketing Research, Journal of Consumer Research, Marketing Science,
Management Science, and various other journals.
Yewmun Yip is an Associate Professor of Finance at the University of South Dakota. Yip
received his PhD in Finance from the University of Wisconsin, Milwaukee. His research interests
include market anomalies, Asian financial markets, foreign exchange markets and government
intervention. His work has previously appeared in the International Review of Economics and
Finance, Review of Accounting and Finance, Managerial Finance, Global Business and Economics
Review, and various national and regional proceedings. Yewmun Yip is the corresponding author
and can be contacted at: yyip@usd.edu
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www.emeraldinsight.com/1463-7154.htm
Managing business processes
through outsourcing: a strategic
partnering perspective
K.B.C. Saxena and Sangeeta S. Bharadwaj
Managing
business through
outsourcing
687
Management Development Institute, Gurgaon, India
Abstract
Purpose – The purpose of this paper is to discuss business processes as building-blocks of
organisational capabilities and outsourcing of business processes as a viable management approach to
building strategic organisational capabilities.
Design/methodology/approach – The paper develops a conceptual framework based on “strategic
partnering” to successfully implement “global sourcing” of organisational capabilities and validates
this framework using multiple case studies research.
Findings – The paper identifies business process management, relationship management and the
outsourcing value propositions as the key dimensions for business process outsourcing (BPO) success.
Research limitations/implications – The paper is based on case studies of seven European
clients and ten Indian service providers of BPO services. A larger survey of BPO clients and service
providers may further strengthen the proposed framework and make the findings more conclusive.
Practical implications – The proposed framework helps both the BPO client and the service
provider organisations in understanding the critical role of relationship management in realising the
intended BPO service outcomes. It also helps the BPO clients and the service providers to understand
the risk and business value implications of BPO value proposition.
Originality/value – The paper addresses a dearth of literature on BPO service provision and
establishes the need for dyadic study of BPO services from both the client and the service provider
perspective simultaneously for understanding the dynamics of this emerging service sector.
Keywords Process management, Outsourcing, Strategic alignment, Partnership
Paper type Research paper
1. Outsourcing of business processes for enhanced competitiveness
For a long time business processes were considered as the means through which
organisations carry out their work, and improving the performance of business
processes would improve the productivity and quality of the organisations, thereby
making them more competitive (Harrington, 1991). However, with the emergence of the
business process reengineering movement, many organisations have successfully been
able to compete on the basis of organisational capabilities, which are largely made
instrumental through the organisation’s business processes (Stalk et al., 1992; Garvin,
1995). According to this view, the building blocks of corporate strategy are not the
products and markets but business processes, and competitive success depends on
transforming an organisation’s core processes into strategic capabilities that
The research reported in this paper is funded by the European Union under EU-India Small
Project Facility (SPF) programme for the project “Business Process Outsourcing (BPO) as
Strategic Partnering: Building Win-Win Relationship between European Customers and Indian
Service Providers” (Contract No. IND SPF/191002/965/95-830).
Business Process Management
Journal
Vol. 15 No. 5, 2009
pp. 687-715
q Emerald Group Publishing Limited
1463-7154
DOI 10.1108/14637150910987919
BPMJ
15,5
688
consistently provide superior value to the customer (Stalk et al., 1992). With this
strategic focus on business processes, outsourcing of business processes is emerging as
a viable approach to acquire strategic capabilities for enhanced competitiveness.
Business process outsourcing (BPO) in simple terms is defined as the movement of
business processes from inside the organisation to external service providers (Click
and Duening, 2005). According to Gartner Group (2004), BPO is the delegation of a
business process to an external service provider who owns, administers and manages
it, according to a defined set of metrics. Specifically, BPO involves contracting with one
or more BPO service providers (vendors) for the provision of execution of business
process operations as per the client organisation’s requirements (Linder, 2004; Kshetri,
2007; Youngdahl et al., 2008).
In the initial stages of BPO, organisations outsourced only their non-core peripheral
processes primarily to reduce their costs and improve their performance. Though this
type of outsourcing delivered benefits to the organisation and impacted directly upon
the bottom line; it did not help them in impacting their competitive position. However,
lately with the emerging strategic focus on the business processes, BPO is extended to
non-core yet mission critical processes such as finance and accounting, human
resources and customer support (Linder, 2004). For instance, British Petroleum’s
outsourcing of finance and accounting to Accenture has helped it to speed up its
post-merger integration of Amoco and Arco (Tan and Sia, 2006). Many organisations
such as United Parcel Service, Solectron and Hewitt Associates have transformed their
core business processes into entirely new industries (Gottfredson et al., 2005). Thus,
BPO is evolving into a strategic process for organising and fine-tuning the value chain.
For many of the forward-thinking organisations – the question is no longer whether to
outsource a “process” (embodiment of an organisational capability) to a service
provider (who is more capable in that process) but rather how to outsource every single
process in the value chain! This would be possible only when for every process to be
outsourced, it is possible to find a “capable” service provider. This newly emerging
philosophy of process outsourcing is being called as “global capability sourcing”
(Gottfredson et al., 2005) or strategic sourcing (Holcomb and Hitt, 2007). Greater focus
on capability sourcing can improve an organisation’s strategic position by reducing
costs, streamlining the organisation and improving quality, and can help them in
exploiting their business processes for strategic advantage. In the global capability
sourcing, the role of service provider is no more limited to the traditional role of an
“agent” who is delegated the responsibility of business process operations for gaining
cost efficiencies. Rather the role changes to a “partnering” role, where the service
provider ensures competency-based service delivery to the client to help them improve
their strategic position (Lacity et al., 2004; Kedia and Lahiri, 2007). This “partnering”
process is also mutual in the sense that the service provider may also plan to succeed in
knowledge-based branding and long-term customer retention (Figure 1).
Furthermore, “global capability sourcing” makes it clear that it is a form of
inter-organisational relationship, in that it involves two separate and distinct
organisations – the BPO client and the BPO service provider – in a contractual
arrangement characterised by a series of interrelated and ongoing exchanges.
Inter-organisational relationships have been studied from several different
perspectives such as organisation theory (Oliver, 1990), marketing (Anderson and
Narus, 1990) and information systems (Henderson, 1990). A common theme in all these
Business process
outsourcing
Client
Service provider
Capability
sourcing
Competency-based
service delivery
Managing
business through
outsourcing
689
Strategic partnering
Improved strategic
positioning
Knowledge-based
branding + long-term
customer retention
perspectives has been that relationships are characterised by a series of ongoing
linkages and transactions that make the relationship participants interdependent, and
thus require coordinated action and cooperation in order to achieve mutual benefits
(Goles and Chin, 2005). We call such a BPO relationship as “win-win relationship” or
partnership (Klepper, 1995; Ploetner and Ehret, 2006), which can be defined as: an
ongoing linkage between a BPO service provider and client arising from a contractual
agreement to provide execution of operations of the specified business process as per
the contract, with the understanding that the benefits attained by each organisation are
at least in part dependent on the other. This partnership is called “strategic
partnership” if the partnering process results into:
[. . .] successful, long-term, strategic relationship (in the sense that it is critical to the
well-being of both the partners because of its high degree of interdependence) and is based on
mutual trust and sustainable competitive advantage for both the partners (Lendrum, 2003).
In spite of the highly promising potential of “strategic partnering” approach to global
capability sourcing, there are very few published case studies of successful BPO
strategic partnering (Lacity et al., 2004; Gottfredson et al., 2005). There is, therefore, an
urgent need to explore in detail the BPO strategic partnering approach and develop a
conceptual framework which may help in mitigating the risks associated with this
approach and encourage more organisations to adopt this approach.
Oddly enough, in spite of the increasing importance of BPO service provider in the
success of BPO initiatives, historically research on BPO has largely focused on the
BPO client side – either on the sourcing decision itself, or on choice of location or
choice of processes to be outsourced, etc. (Aron et al., 2008; Balakrishnan et al., 2008;
Ellram et al., 2008; Graf and Mudambi, 2005; Stratman, 2008; Tan and Sia, 2006;
Youngdahl et al., 2008), but rarely on the BPO service provider, and never on the
dyadic of BPO client and the service provider. This paper describes such a dyadic
study of BPO clients and service providers using multiple case studies, and proposes
Figure 1.
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a conceptual framework for strategic partnering in BPO initiatives. The paper is
organised as follows. Section 2 describes the theoretical background using which a
conceptual framework for strategic partnering can be developed. Section 3 of the paper
develops such a conceptual framework, identifying its various components in different
sub-sections. Section 4 describes a multiple case study based validation of the proposed
framework, which is followed by the conclusion.
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2. Theoretical background
Characterising BPO as a form of inter-organisational relationship, various theories of
inter-organisational relationship can be utilised from organisational economics,
organisational theory and relationship marketing literature. In this section, some of the
major theories – agency theory, transaction cost theory, resource-based theory and
relationship theories are briefly reviewed to understand BPO from an
inter-organisational relationship perspective.
2.1 Agency theory
According to this theory, an agency relationship is present whenever one party (the
principal and the BPO client) depends on another part (the agent and the BPO service
provider). This theory is concerned with resolving two problems that can occur in
agency relationships (Eisenhardt, 1985). The first arises when the goals of the BPO
client and the service provider conflict, and it is difficult or expensive for the client to
verify what the service provider is actually doing. An example could be that the client
organisation wants to reduce the process operating costs but the service provider
wants to maximise its profits. The second is the problem of risk sharing that arises
when the client and the service provider have different risk preferences. This problem
may arise in BPO because of the different attitudes of client and service provider
towards the use of new (improved during transition) process design using new
technologies. The agency theory assumes that goals, self interest and risk preferences
diverge between the BPO client and the service provider (Eisenhardt, 1989a), but it
gives little attention to the cooperative aspects of social life. It is criticised because it
assumes social life is a series of contracts and ignores the existence of social and
authority relationships in economic transactions. However, in BPO most contracts
happen to be somewhat incomplete and social relationships form a major strategy for
mitigating the risks in BPO (Spencer, 2005). Thus, agency theory is not considered a
strong theory for developing a conceptual framework for BPO.
2.2 Transaction cost theory
According to this theory, the properties of a transaction determine what constitutes the
efficient governance structure – market, hierarchy, or alliance (Coase, 1937;
Williamson, 1975, 1979). In selecting a governance mode, organisations attempt to
minimise transaction costs. A market governance mode is preferred when transactions
costs are low and internal governance mode is preferred when transaction costs are
high. This is because in this theory the market is always considered the lowest cost
producer of good or service due to economies of scale and scope. Similarly, the
production cost advantage of the market is overwhelmed by the high transaction costs.
Though this theory provides a sound theoretical basis for understanding market
versus hierarchical governance mechanisms for determining the boundary of the firm,
it is limited because it focuses on single transactions as the unit of analysis (Doz and
Prahalad, 1991). In BPO, the underlying concept is the acquisition of “process
execution” services through continuous interaction between the client and the service
provider to the agreement. However, transaction cost theory at its core views the two
parties as not interacting with each other but directly with the market. Furthermore,
transaction cost theory fails to recognise the role of complex and collaborative
relationships that involve high levels of asset specificity as well as uncertainty and
opportunism, as in BPO. Relational mechanisms such as trust are regarded as
substitute for complex, explicit contracts and hierarchical governance in such
situations (Adler, 2001). For explaining the BPO relationships, we need more than
purely an economic view as we need to understand the ongoing episodes of exchanges
from an individual’s stand point, which is guided by the contract and lapses into
voluntary exchanges (Håkansson, 1982).
2.3 Resource-based theory
Prahalad and Hamel (1990) article has generated substantial interest in the notion of
core competencies and capabilities and has helped popularise a new school of thought
called the resource-based view of the firm. This theory emphasises that resources
internal to the firm are the principal driver of a firm’s profitability and strategic
advantage (Barney, 1991; Wernerfelt, 1984). It rejects traditional economic
assumptions that resources are homogeneous and perfectly mobile. Instead, it
argues that resources are heterogeneously distributed across firms and are imperfectly
transferred between firms (Barney, 1991). Barney (1991) categorised resources into
three groups: physical resources such as plant, equipment, location and assets; human
resources such as management team, knowledge and skills; and organisational
resources such as culture and reputation. Resources enable a firm to conceive of and
implement strategies to improve its efficiency and effectiveness (Daft, 1983).
Organisations can obtain above-normal returns if they can use their existing resources
to sustain competitive advantage by exploiting opportunities in the market or
neutralising threats from competitors’ strategic resources. Therefore, organisations
retain strategic resources internally that enable them to sustain competitive advantage
(Mahoney and Pandian, 1992). Strategic resources enable organisations to sustain
competitive advantage, if the resources are valuable, rare, imperfectly imitable and
non-substitutable. Resources might be imperfectly imitable if they involve unique
history, causal ambiguity, or social complexity (Barney, 1991). Similarly, resources are
non-substitutable if another organisation is not able to implement the same strategies
by using alternative resources.
The capabilities sourcing approach and its relationship with BPO have evolved
from the resource-based view of the firm. Organisational capabilities and competencies
are important to the study of BPO, as it proposes the internal competences of the firm
as the potential for competitive advantage. However, Prahalad and Hamel (1990) have
used the concept of capability, competence and core competence as synonymous. Stalk
et al. (1992) attempted to differentiate between core competencies and capabilities, but
they could not provide a meaningful and useful operational definition of these
important concepts. Therefore, for the purpose of this paper, we subscribe to the
definition of Amit and Schoemaker (1993) because it is precise and fits with the
distinction between the concepts of resource, competence and capability. They define
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resources as “stocks of available factors that are owned or controlled by the firm”. In
the context of BPO, the information technology (IT) infrastructure is an important
resource but resources like knowledge and skills residing in the employees are even
more critical.
Central to the Resource Based Theory is the fact that resources, per se, do not create
value (Bowman and Ambrosini, 2000; Porter, 1991); value is created by an
organisation’s ability (or competence) to utilise and mobilise those resources. However,
there are many definitions of competence used by various authors on the subject.
According to Amit and Schoemaker (1993), competence refers to “a firm’s capacity to
deploy resources, usually in combination, using organisational processes, to effect a
desired end” and thus represent “[. . .] a bundle of skills and technologies rather than a
single, discrete skill or technology” (Hamel and Prahalad, 1994). Competence can
therefore be portrayed as the ability to deploy combinations of firm specific resources
to accomplish a given task (McGrath et al., 1995). Finally, organisational capability
refers to the strategic application of competencies, i.e. their use and deployment to
accomplish given organisational goals (McGrath et al., 1995). Within this context,
defining and creating the desired organisational capability would be determined by its
future goals; which in turn establishes the need for improving or developing specific
competencies.
2.4 Relationship theories
These theories propose that inter-organisational relationships are a means of
understanding how firms can gain and sustain competitive advantage. For example,
Dyer and Singh (1998) argue that it is possible for organisations to combine resources
in unique ways across organisational boundaries to obtain an advantage over their
competitors. They define relation rent as:
[. . .] a supernormal profit jointly generated in an exchange relationship that cannot be
generated by either firm in isolation and can only be created through the joint idiosyncratic
contributions of the specific alliance partners.
Relational rents are possible when the alliance partners combine, exchange, or invest in
idiosyncratic assets, knowledge and resources/capabilities. The relational view argues
that the firm can develop valuable resources by carefully managing relationships with
external entities including suppliers, customers, government agencies and universities.
Therefore, a firm can gain and sustain competitive advantage by accessing its key
resources in a way that spans the boundaries of the firm. Competitive advantage can be
embedded in a set of relationships across the boundaries of the firms, rather than
residing inside an individual firm.
Relational theories are important for the study of BPO, as the clients and the service
providers that make relation-specific investments and are able to combine resources in
unique ways to generate relational rents, can gain competitive advantage over the BPO
clients and service providers that are unable to do so.
3. Developing a conceptual model of BPO strategic partnering
Any BPO initiative starts with the BPO client expecting a value delivery in the process
operations (such as cost reduction, process performance improvement, etc.) as
proposed by the service provider as well as the service provider also expecting
a business value addition (such as business growth, longer client retention, etc.)
(Saxena and Bharadwaj, 2007). However, the BPO project may provide the expected
outcome only to the client, or only to the service provider, or to none of the two. In such
a case the BPO project is considered as failed. However, if both the client and the
service provider are able to realise the BPO outcome as expected, the project is
considered successful and may lead to a “strategic partnership” between the client and
the service provider. Our objective here is to develop a conceptual model of the
strategic partnering process. The theoretical foundation for model development is from
the resource-based and the relational views, as described before. Building on the
resource-based view, the model takes into account the competencies required in
the client and the service provider organisations for BPO success. Building on the
relational view, the model takes into account the relationship maturity required
between the client and the service provider for BPO success. Finally, being a dyadic
perspective, the model takes into account the outsourced process characteristics
(Niranjan et al., 2007) and the value propositions from the outsourcing initiative, which
are likely to determine the competency levels and relationship maturity required for
successful BPO outcome.
3.1 Outsourced process characteristics
In order to understand the management implications of the present enhanced BPO
complexity, it is desirable to develop a classification of business processes as viewed
by both the client and the service providers. There have been a number of
classifications of business processes but all of them have been either from the client
perspective or from the service provider perspective. For instance, from the clients
perspective, processes have been classified as traditional, peripheral, critical and
strategic (Jenster et al., 2005); as core, critical but non-core and non-core non-critical
(Dole and Switser, 1998); critical, key and support (Click and Duening, 2005). Similarly,
from the service providers perspective, processes have been classified by NASSCOM,
India as IT-enabled services, BPO; and knowledge process outsourcing (KPO);
functionally classified as finance and accounting, customer interaction services, human
resource management, etc.; industry verticals such as banking financial services and
insurance; legal process outsourcing, engineering process outsourcing, etc. Thus, there
is an acute need for developing a business process classification from an outsourcing
perspective which is easily understood by both the BPO client and the service provider.
An organisation has a number of processes, and theoretically all of them could be
outsourced. However, some of these processes may be more important to the
organisation in the sense that operation failure of such a process may have a higher
business risk. Similarly, some business processes may be easier to understand by the
service provider and therefore easy to migrate to the service provider’s site. We call
these two dimensions of a business process as the criticality and complexity
dimensions (Niranjan et al., 2007). Some authors such as Mani et al. (2006) have
classified processes on its strategic dimension. However, strategic importance of a
business process becomes a somewhat nebulous concept from the service provider’s
perspective, and is not considered a useful basis for a dyadic study of BPO. In this
context, criticality of a process refers to its degree of essentiality without which the
very existence of the client organisation as a functioning business would immediately
cease. Criticality includes the strategic importance of the process as well as its
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importance in the context of all the business processes in general (Pandey and Bansal,
2004). Critical processes are not necessarily a source of competitive advantage (Hinks,
2002), and when outsourced, it is often only to achieve cost savings rather than for
strategic reasons. An example of a critical process from the manufacturing sector,
which is the process of power supply maintenance for the manufacturing plant. Failure
of power supply will cause an immediate, severe and certain damage to the client,
though it may not have any strategic significance. Thus, the measures of the criticality
of a process are the quickness, magnitude and certainty of the adverse impact on the
client’s business when the service provider fails to deliver the process operations.
Complexity of a business process has been excessively studied by researchers in
organisation design/theory (Niranjan et al., 2007). Woodard (1958) defined technical
complexity of a process as the extent to which it can be programmed so that it can
be controlled and made predictable. Perrow (1970) introduced two dimensions of
complexity: task variability, i.e. the number of exceptions encountered; and task
analysability, i.e. the degree to which search activity is needed while performing the
task. Thus, a complex outsourced process is one characterised by low technical
complexity, high task variability and high task analysability. Such tasks depend
primarily on humans and their skills, knowledge and judgment and not on task
automation. Complex processes are frequently, but not necessarily, a source of
competitive advantage, or critical in the sense used above. An example of a complex
process from the manufacturing sector, which is also a source of competitive
advantage, is the process of engine design. A contrasting example of a complex process
is the process of budgeting in an automobile-manufacturing organisation, which is
seldom a source of competitive advantage to the manufacturer. Neither of these two
complex processes is very critical in the sense defined above. Thus, the dimensions of
criticality and complexity of a business process are orthogonal, i.e. an increase along
one dimension is not necessarily associated with an increase in the other dimension.
3.2 Value proposition
Value is a useful basis for determining the importance level of business processes.
A useful approach for understanding value is the “perceived use value” approach,
which defines the value of a product or service as the perceptions that a customer has
of the usefulness of the product or service (McIvor, 2005; Bowman, 1998). According to
Walters and Lancaster (1999), value is determined by the utility combination of
benefits delivered to the customer less the total costs of acquiring the delivered
benefits. For the supplier, value addition will mean that the cost of providing
the customer benefits is less than the price charged, as well as the supplier perceiving
other business value additions such as business growth, improved business
relationships, etc.
A value proposition in the context of a win-win relationship is a statement of how
value is to be delivered to the customer and also how the supplier perceives value
addition for its own business. Internally, it defines the “value drivers” the supplier is
offering to a target customer group along with the activities involved in producing the
value, along with other perceived value addition for supplier’s business, together with
the cost drivers involved in the value-producing activities. Externally, it is the means
by which the organisation positions itself in the minds of its customers. The
contribution of value proposition in promoting a win-win relationship is catalytic if:
.
.
value proposition as understood by the client in terms of proposed value addition
through outsourcing is the same as understood by the service provider in terms
of proposed value delivery; and
the service provider also perceives some value addition to its own business in
some form, such as profits, business growth, brand building, longer customer
retention, etc.
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Table I shows a categorisation of value propositions which we have found common in
BPO sector.
This categorisation of value proposition has implicit in it an increasing level of
realisation difficulty from transactional to strategic levels. That is to say, transactional
level of value proposition is relatively easy to deliver by a service provider compared to
strategic level of value proposition, which may be very difficult (if not impossible) to
deliver! Often the failure in reaching a win-win relationship could be because of
the failure in aligning the value propositions as understood by the client and the
service provider. Therefore, an important requirement of a win-win relationship is
the congruence in understanding the value proposition by both the client and the service
provider.
Another implication of value proposition categorisation is its perceived
attractiveness in the context of a particular candidate process for outsourcing. For a
non-critical non-core process, a transactional value proposition may be adequate and a
transformational or a strategic value proposition may not be feasible because of high
resource requirements and more intense change management requirements. However,
for a core as well as critical business process, a transactional value proposition may not
be very attractive, and any thing less than a transformational or a strategic value
proposition may not be even worth considering for outsourcing.
3.3 Management competencies
Shi (2007) states that a BPO service provider’s competence in managing business
process, BPO project and technology bears direct impact on the success or failure of a
BPO project. Thus, management competencies form another important variable which
determines the success or failure of the BPO project (or the BPO outcome).
Consequently, even though the BPO service providers still focus on the level of their
products (service), the BPO clients are getting more interested in service providers’
competencies, such as the “availability” of the service provider, the efficient delivery of
Client’s value proposition and service provider’s
value delivery
Transactional. Cost and process throughput
Transformational. New business competencies
through process transformation
Strategic. Opportunity for business
transformation through strategic alliance
Service provider’s value addition
Business growth. Opportunity to increase sales;
opportunity to get outsourcing of other processes
Longer customer retention. Opportunities for
longer term customer tie in; new business
opportunities
New value adding services. Creating new services
from newly developed core competencies; very
long-term relationship with clients
Table I.
Categorisation of BPO
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the service provider’s solution and the service provider’s expertise in the client’s own
business (Golfetto and Gibbert, 2006; Möller, 2006). This market-based competences
view requires the service provider to develop a clear understanding of its own
competencies, not so much in “internal terms”, but in terms of client benefits (Golfetto,
2003). In a BPO initiative two competencies are a must in both the client and the service
provider – process management competency, and outsourcing management
competency. These competencies are described below.
3.3.1 Business process management competencies. Business process management
(BPM) competencies are at the heart of the BPO service provision, though it is also of
major concern for the client organisation. For the client organisation, BPM
competencies in their increasing order of criticality are:
.
Process knowledge. It is a well-known fact that when a process is in operation
internally for a long time and is not being formally managed, the very knowledge
about how the process actually operates is scanty and distributed across the
entire set of process operators (Bitici and Muir, 1997; Harmon, 2003). Obviously
such an unmanaged process if outsourced, is unlikely to deliver any of the
benefits of outsourcing let alone building a win-win relationship. Therefore,
when a process is considered as candidate for outsourcing, the first thing which
needs to be acquired by the client is the knowledge about the process in
insourced form.
.
Process measurement and monitoring. It is also well-known that in an
unmanaged or informally managed process environment, even if process
knowledge is available, performance measurement (such as process cost, process
cycle time, etc.) is also either missing or informal (Valiris and Glykas, 2004).
This means that either the performance data are not collected, or if collected,
process performance indicators are not calculated, or even if they are calculated,
they are not monitored to see if the performance is at an acceptable level. Thus,
the next critical requirement for process outsourcing is that the client must have
a process performance measurement system in place so that it could ensure that
the process performance standards defined in the service level agreements
(SLAs) indeed provide performance benefits of an acceptable degree to the client
organisation.
.
Process performance exploitation. The last and most critical competency for the
client is the capability to exploit a process operating at the desired level of
performance to deliver the business benefits it was intended to give (Malone et al.,
2003). If that does not happen, it is very unlikely that the client will get the
intended business benefits when the process is outsourced and operating at a
much higher performance level (Power et al., 2006).
In short, the candidate process must be formally managed to yield its intended business
impacts, before it is outsourced for providing enhanced business benefits. Next, for the
service provider, the process management competencies play even more critical role as
they form the very basis of service provision. According to our research, the following
BPM competencies are considered most critical for the service provider:
(1) Process transition. Process transition or migration refers to moving the
insourced version of the candidate process from the client site to the service
provider site in an (improved) mutually agreed upon outsourced form, and to
demonstrate it to perform at the agreed upon performance level. This seemingly
simple process migration is in fact very complicated, and even some of the very
experienced service providers often seem to make mistakes in it, at least
initially. Its complexity comes out of the following implicit activities, which are
also very error-prone:
.
acquiring the process knowledge, if the candidate process is unmanaged at
the client organisation;
.
improving the candidate process so as to bring its performance at the agreed
upon level; and
.
to implement this improved version of the process at the service provider’s
site in an error-proof manner so that it can pass the demonstration test.
(2) Process performance management. This competence refers to the capability of
improving the operations of the outsourced process to the agreed upon level or
even better. The performance measures which need to be managed fall in three
categories:
.
process cost performance, which is required to ensure that process operation
cost leaves the expected level of profitability for the service provider;
.
process output performance, which is often specified in the form of key
performance indicators (KPIs) in the SLAs of the contract; and
.
process outcome performance, which refers to the effectiveness of the
process in meeting the intangible business impacts, which were intended
through the outsourcing of the process.
3.3.2 Outsourcing management competencies. Many executives and managers believe
BPO to be a technical innovation best left to the technology administrators. This belief
results from the IT origins of BPO, when the outsourcing adopters used outsourcing
for software development or to staff help-desks and call centres. BPO has evolved far
from IT-specific roots and now encompasses nearly every business process. Though
the implementation of a BPO initiative will always involve a technology component,
but for that matter so does implementation of an accounting system at a super market
chain. That is to say, nearly every modern business innovation comprises both a
technical and a social component, involving human interfacing with technical systems.
Likewise, BPO is also a socio-technical business innovation that provides a rich new
source of competitive advantage. That is, BPO requires skilful management of both
people and technology (Click and Duening, 2005), and therefore management of BPO
requires a diverse set of skills in order to be successful.
For the client organisation, outsourcing management competencies identified in our
research are:
.
Vendor due diligence, which refers to assessment of service provider in terms of
their capability in the process domain, past experience, successful track record,
etc. The success of strategic partnering depends on the fact that the service
provider has the capability and the history of delivering the proposed value
additions in the outsourced process; and any mistakes in service provider
selection could be very expensive for the client organisation.
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.
.
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.
.
Outsourcing management structure, which refers to the existence of a formal
structure to manage outsourcing.
Contract facilitation and monitoring, which is required in case of multiple service
providers for coordination and synchronisation of various services, resolving
conflicts between various users and service providers in a collaborated manner,
and managing both excessive user demands and cost overruns by service
providers.
Performance monitoring and control, which refers to monitoring and controlling
performance of every individual process outsourced.
Vendor development, which is required when the client organisation is looking
beyond existing contractual arrangements to explore the long-term potential for
service providers to create win-win relationships.
For the service provider, the outsourcing management competencies required are:
.
process due diligence, which refers to assessment of the candidate process by the
service provider from the perspective of inhouse capability to deliver the services
demanded as well as its profitability;
.
contract negotiation and monitoring; and
.
performance monitoring and control, which is the same as in the case of client
organisations.
3.4 Relationship management
BPO client and service provider relationship becomes a critical factor for BPO success
when the process to be outsourced is both complex and critical, and it is not possible to
envisage all possible scenarios in the service contract (Webb and Laborde, 2005; Shi,
2007; Niranjan et al., 2007). Relationship management thus becomes important in
outsourcing when it is no longer an incremental activity, and presents challenges to
both the BPO client and the service provider. Unlike the traditional buyer-supplier
relationship, the BPO relationship must be meticulously planned and managed from
the beginning of the project with a strategic intent. Very often BPO agreements focus
on the contractual structure used to formalise the BPO relationship. However, as BPO
becomes a strategic way of capability sourcing and spans across regional borders, the
contractual structure may not sufficiently align incentives across the firms nor
effectively coordinate their activities. BPO relationship management involves four
fundamental characteristics:
(1) Depth of relationship. The closer the outsourced process impacts upon client’s
business success, the greater the strategic importance of the business process
being outsourced, and therefore, the higher is the client’s risk in outsourcing.
Hence, the more strategic the outsourced process for the client, the greater the
depth required in the BPO relationship. Based on this criticality, the depth of
BPO relationship can be categorised as follows:
.
arm’s length relationship, which is largely driven by the outsourcing cost
and the SLAs in the contract;
.
cooperative, which necessarily involves intense dialogue between the client
and the service provider; and
extension of client’s organisation, where the client service provider
relationship has a high level of dependency and commitments from each
other.
(2) Scope of the relationship. This is defined by the number of service providers
working with the BPO client in the outsourcing of different business processes.
Multiple service providers give more and diversified opportunities for
knowledge sharing between the client and the service providers.
(3) Choice of assets to use. BPO requires handing over the control and maintenance
of the outsourced process. Therefore, it raises the issue of whose assets
(especially people, physical infrastructure and technological assets) to be used
by the service provider.
(4) Choice of business culture to adopt. This issue becomes important when the
process is outsourced offshore, and therefore, the business culture in the two
countries, such as business regulatory environment and business practices may
be different.
.
Relationships have a number of perceptive and measurable outcomes that indicate the
relative success to both the clients and the service providers. It will, therefore, be
helpful to develop a BPO relationship maturity model which can be used to describe an
evolutionary improvement path that guides an organisation in terms of how to manage
its maturity growth from the initial level to the highest maturity level (Harmon, 2003;
Gottschalk and Solli-Saether, 2006). The maturity model adopted in this research
identifies the following four maturity levels of BPO relationships:
(1) supplier relationship;
(2) extended supplier relationship;
(3) partner relationship; and
(4) strategic partner relationship (Lendrum, 2003).
Supplier relationship is largely characterised by the service provider having a
cost-plus strategy and mentality, delivering services on thin margins with little or
nothing differentiating them in a positive way from their competitors. The extended
supplier relationship, the level (2) of BPO maturity, is characterised by delivery
services in full, on-time and to the specifications. It involves meeting and servicing
process outsourcing requirements via cost reduction and value adding initiatives
such as service enhancements, maximising responsiveness, etc. Partner relationship
is characterised by high client’s reliance on the quality, consistency, reliability and
dependability of external skills and services to ensure that client meets their own
business requirements. Lastly, strategic partner relationship, which is the highest
level of relationship maturity, is characterised by all the “win-win” partnering
relationship as well as shared visions, strategies and a wealth information sharing
among the client and the service provider.
4. Validation of the BPO strategic partnering model through case studies
Case study research is particularly well suited to new research areas or research areas
for which existing theory seems inadequate (Eisenhardt, 1989b). It is also a method of
choice when the phenomenon under study is not readily distinguishable from its
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context, and when a how or why question is being asked about a phenomenon over
which the researcher has no control. Since, BPO is a new research area where existing
theories may not be adequate, case study is used in this research. The research
questions on which the case study research is focused, are:
RQ1. Whether “strategic partnering” leads to BPO success?
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RQ2. If yes, what are the factors which lead to successful “strategic partnering”?
4.1 Selection of case studies
Selection of cases is an important aspect of building theory from case studies (Eisenhardt,
1989b), as an appropriate selection of case studies controls extraneous variation and
helps define the limits for generalising the research findings. However, since the purpose
of these case studies was to validate a theory (conceptual model) of BPO, the choice of
cases was based on theoretical sampling rather than statistical sampling (i.e. cases are
chosen for theoretical rather than statistical reasons) (Glaser and Strauss, 1967). The goal
of theoretical sampling is to choose cases such as extreme situations and polar types in
which the process of interest is “transparently observable” (Pettigrew, 1988). As this
research is about the win-win relationship among European BPO clients and Indian
service providers, case studies were selected using the following criteria:
.
BPO clients. Dutch or British organisations that have outsourced at least one
business process to an Indian service provider or have a BPO captive centre in India.
.
BPO service providers. BPO service providers who have major operations in
India and have at least one Dutch or British organisation as their client.
A total of seven client and ten service provider organisations were studies. The list is
given in Table II.
The selection was made on the basis of sub-classification within both the client and
the service provider categories, as explained below. The sub-classification was based
on organisational attributes of interest, such as size, process management style, BPO or
KPO, etc. These sub-classifications are described below:
(1) Sub-categories of BPO clients:
.
small versus large organisations, in order to see if organisation size makes
any difference in strategic partnering;
Table II.
BPO client and service
provider organisations
BPO client organisations
BPO service provider organisations
Cendant Corporation/eBookers, UK
InDraft Solutions, UK
Thames Waters, UK
Elsevier Publishers, The Netherlands
NedTech, The Netherlands
Barclays Bank, UK
ABN-AMRO Bank, The Netherlands
Technovate eSolutions, Delhi
COMAT, Bangalore and The Netherlands
Xansa, NOIDA
Thomson Digital, NOIDA
CADSE, Bangalore
Tata Consultancy Services, The Netherlands
Logica CMG, Bangalore, UK and The Netherlands
Exëvo, Delhi
Ram Tech, Delhi
ZenSaar, Bangalore
outsourcing for processes versus process portfolio management, in order to
see the difference in outsourcing management approaches and their impact
on strategic partnering; and
.
BPO versus KPO, in order to see how knowledge intensity in a process
impacts strategic partnering.
(2) Sub-categories of BPO service providers:
.
captive centres versus third-party service providers, in order to see if the
governance structure plays a role in strategic partnering;
.
BPO and IT outsourcing versus pure BPO, in order to see how outsourcing
service provision of both IT and business processes impacts strategic
partnering; and
.
service providers of BPO versus KPO, in order to see how knowledge
intensity in a process impacts strategic partnering.
.
4.2 Development of case study protocol
The general way to achieve reliability in case study research is to conduct the research
so that another researcher could repeat the procedures and arrive at the same
conclusions. One prerequisite for allowing other researchers to repeat an earlier case
study is the need to document the procedures followed in the earlier case. Yin (2003)
proposes to create a case study protocol to increase reliability. A case study protocol is
a document which contains an overview of the project (objectives, issues and topics
being investigated), field procedures, interview guides and/or survey questions
(instrument) as well as a guide for case study report (Paré, 2004). Consequently,
separate protocols were made one for the client organisations and the other for the
service provider organisations, which were based on the conceptual model of BPO
strategic partnering given above.
Unfortunately, operationalising the protocol, especially the interview instrument,
posed many problems. First was the confidentiality issue. The service providers
showed their inability to provide details related to clients identification as well as to
provide financial figures related to business performance (except for those who were
listed on the stock exchange and their financial information was publicly available).
The second major problem was the number of people who could be interviewed, and
the details they provided in response to our questions. Some organisations (both clients
and service providers) allowed us to visit multiple offices and interviewing two to three
persons of senior management cadre, whereas many others gave access to only one
person and whatever details that person could provide in response to the interview
questions, was the only information available for research. As for secondary
information available from business magazines and web sites, it varied from one
organisation to others. Generally, not much information was available from secondary
sources for the small organisations (whether clients or service providers), and whatever
information was available, it was generally financial or marketing-oriented in nature,
and therefore not of much use to the context of our study.
In view of this limitation, there emerged an acute need for revising the protocols.
Since, the main thrust of this research is on “win-win relationship” or strategic
partnering, it was decided to retain the dyadic nature (both clients and service
providers together) of the case study research and limiting its scope on the basis of
Managing
business through
outsourcing
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available common information (which could be obtained through the interviews) for all
the client and service provider organisations. These revised protocols are given in the
Appendix.
4.3 Analysis of case studies
Since, a detailed analysis of all the cases cannot be included here, only an indicative
analysis of the case studies is given below.
4.3.1 BPO client organisations. Reasons for outsourcing. Most client organisations
had outsourced more than one processes except NedTech who had outsourced only one
process, which is “product design”. In fact, many clients such as Cendant
Corporation/eBookers, Barclays Bank, Elsevier, etc. were of the view that they could
outsource any of their processes if they could find a competent service provider.
In terms of types of the processes outsourced, most outsourced processes were of
“support” or non-critical type, but some client organisations such as Cendant
Corporation/eBookers, Thames Waters, Elsevier and Barclays Bank have also
outsourced processes which fall in the “non-core but critical” category. There was one
client organisation – NedTech, who had outsourced the product design process, which
for them was a “core as-well-as critical” process.
As for reason for outsourcing, it was cost reduction for all the processes, but for
non-core but critical processes, it was also process performance improvement in
addition to the cost reduction. However, in case of NedTech who had outsourced a core
as-well-as critical process (product design), their expectation was that they would
be able to enhance their business through outsourcing as NedTech is a medium-size
company and they themselves were not able to do all the product design work which
they could have got from their customer (which was a major aeroplane manufacturer in
Europe).
The outsourcing process is generally taken through a service provider due diligence
process. Many client organisations who have outsourced a larger number of their
business processes, had a separate organisational function for managing the BPO
function. For instance, in Cendant Corporation, it was the operations department; in
ABN-AMRO, it was the strategic sourcing department, and so on.
BPO outcome. All the client organisations were able to realise the intended benefits
of BPO. Many clients who had outsourced a large number of processes, had access to
many service providers. These organisations followed a “process portfolio” approach
and were continuously monitoring the performance of all their processes. Whenever
they found that a particular service provider is not able to provide the desired level of
process performance, they decided to bring the process back in-house or to outsource it
to some other vendor working with them.
BPM competency. Whereas all the clients stated that they use a structured due
diligence process for evaluation and selection of service providers, most of them were
either not able to provide the details of the process or refused to reveal the details
saying the process is internal and confidential. However, the client organisations who
had outsourced a large number of processes and followed a process portfolio approach
for managing the outsourced approach, had a specific department or group of people
for the process management function. For example, Cedant Corporation allocated this
job to their global operations department; ABN-AMRO had a separate strategic
sourcing department and a vendor selection group for process outsourcing and
management; Barclays Bank also had their global operations department looking after
it, and so did Elsevier Publishers.
Outsourcing management competency. The contracts with the service providers
were negotiated through the legal or contracts department, but the monitoring of the
contract was done by the department/person responsible for monitoring the
outsourcing process.
As for the expectations of additional service provision, the clients who outsourced
only one or two processes and/or worked with only one service provider had this
expectation. Examples of such clients were InDraft Solutions and Thames Waters.
Relationship management. As the scope and nature of BPO has expanded from its
focus on cost and process efficiency to encompass BPO as a means of improving the
client organisation’s overall business performance and furthering its strategic goals,
there has been a growing realisation that the relationship between the client and the
service provider organisation plays a critical role in the success or failure of the BPO
arrangement (Quinn, 1999; Kern, 1997). Thus, relationship management is a very
critical success as well as failure factor for win-win relationship.
Relationship has a formal dimension, which is contractual in nature. In other words,
what type of governance structure is there between the client and the service provider
organisation? However, it has been seen that proper contractual or governance
structure is only a necessary condition but not a sufficient one for win-win relationship.
There is also an informal dimension of BPO relationship which is characterised by a
series of ongoing linkages and transactions that make the client and the service
provider organisations interdependent, and thus require coordinated action and
cooperation in order to achieve mutual benefits (Goles and Chin, 2005).
Consequently, relationship management in the client cases was evaluated by:
.
how the relationship with the service provider was monitored;
.
what type of governance structure was in place with the service provider; and
.
what type of processes, if any, were in place for relationship management/
knowledge sharing.
The monitoring of relationship was mostly informal and subjectively judged by the
person in charge of process management and outsourcing. Generally, the quality of
relationship was judged by...
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