دانلود مقاله ISI انگلیسی شماره 341
عنوان فارسی مقاله

یکپارچه سازی کانال های فروش پس از ترکیب و ادغام : رویکرد روش شناختی برای اجتناب از مشکلات شایع

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
341 2007 15 صفحه PDF سفارش دهید محاسبه نشده
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عنوان انگلیسی
Sales channel integration after mergers and acquisitions: A methodological approach for avoiding common pitfalls
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Industrial Marketing Management, Volume 36, Issue 5, July 2007, Pages 589–603

کلمات کلیدی
' سرمایه گذاری مشترک - ترکیب و ادغام - نمایندگان تولید کنندگان - گرایش وابستگی - کانال های فروش - کارت امتیازی متوازن - کارت امتیازی متوازن
پیش نمایش مقاله
پیش نمایش مقاله  یکپارچه سازی کانال های فروش پس از ترکیب و ادغام : رویکرد روش شناختی برای اجتناب از مشکلات شایع

چکیده انگلیسی

This article addresses the integration of sales channels after mergers and acquisitions (M&A) by appraising the strengths, weaknesses, and biases associated with the four most common frameworks for evaluating sales channels (sales management, historical performance, strategic fit, and customer choice) for their appropriateness in a post-M&A context. The authors develop a methodological approach that uses a balanced-scorecard framework to guide managers through the sales channel integration process, and then apply this approach to the merger of two industrial firms' sales organizations across 21 territories. In so doing, they reveal various pitfalls and propose and test some analytical corrections. Longitudinal performance data support comparisons across the different evaluative frameworks; in particular, the sales management and customer choice frameworks provide the most insight into channel partners' post-integration performance. The results support the premise that channel integration can be improved by accounting for factors unique to the M&A context and using an approach that triangulates multiple perspectives.

مقدمه انگلیسی

The strategic role of mergers and acquisitions (M&A) has long been acknowledged (Hennessy, 1978 and Stern, 1967), particularly since M&A activity has exceeded the trillion-dollar annual mark in U.S. industrial markets (Coy, Thornton, Arndt, & Grow, 2005). Because industrial sales channels or intermediaries provide 20–50% of sales revenues for many business-to-business firms (Abele, Caesar, & John, 2003) and the success of M&As depends on successful integration (Capron & Hulland, 1999), many firms face the challenge of optimally integrating their sales channels after a merger or acquisition. Channel integration is especially critical because terminated channel partners have relationships with and detailed information about existing customers and because poor channel decisions result in weak partners and provide competitors a superior channel to market. Furthermore, channel decisions are difficult to reverse, the cost of changing partners is high (e.g., due to lost sales during the transition period and the additional training required for new channel partners), and channel partnerships typically last a long time (Abele et al., 2003 and Weiss and Anderson, 1992). The difficulty of successfully integrating sales organizations after a merger has been well documented in the trade press, which attributes numerous problems and negative results to poor channel selection and integration decisions (e.g., Madell and Piller, 2000 and Sutherland and Turner, 2003). One common pitfall, favoritism or affiliation bias, has been recognized across many aspects of post-M&A integration resulting in poor performance (McBeath & Bacha, 2001). For example, the acquisition of WordPerfect Inc. by Novell resulted in affiliation-related staff clashes that crippled the merger, leading to Novell's decision to sell the newly acquired business (Clark, 1996). However, research literature provides little guidance regarding this important and increasingly prevalent business need to integrate sales organizations (Rangan, Zoltners, & Becker, 1986). Whereas it sheds some light on the best methods for selecting channel partners (Johnston and Cooper, 1981 and Weiss and Anderson, 1992), managing sales channels (Mehta et al., 2000 and Rangan et al., 1992), and handling M&A (Capron and Hulland, 1999 and Mallette et al., 2003), it provides little insight into integrating sales channels after M&A. Moreover, generalizing from these approaches to the M&A context can be troublesome due to its unique characteristics, including (1) separate sales and marketing organizations; (2) organizations that have only a partial knowledge of customers, products, and channels; (3) the tendency of premerger affiliations or bias to overwhelm other decision criteria; and (4) the need for rapid decisions in an often politically charged environment. Overall, the literature provides limited insight into a frequently confronted business decision that has long-term financial ramifications whose many problems and pitfalls the business community already recognizes. Therefore, the research objectives of this study are to develop and test a methodological approach for optimally selecting and integrating sales channels after an M&A while avoiding some common pitfalls. The proposed framework and process take a “balanced-scorecard” approach (Kaplan & Norton, 1996) and integrate four different sales channel evaluative perspectives identified in the literature. The inputs from multiple perspectives (i.e., salesforce, financial performance, business objectives, customers) in a balanced-scorecard framework support a triangulation across different aspects of the sales channels, help promote organizational learning, and may minimize the impact of some problems unique to the M&A context (e.g., Brinberg and Hirschman, 1986 and Chandy, 2003). The process outlined herein also attempts to minimize conflict among participants, which can result in reduced motivation (Covin et al., 1996 and Walsh, 1989) and protracted legal issues (Mohr et al., 1999 and Weiss and Anderson, 1992). We organize this article as follows: First, we review the applicable literature to appraise the appropriateness of existing sales channel evaluative frameworks and identify any problems or pitfalls associated with them in a post-M&A context. Second, we outline our balanced-scorecard channel selection and integration framework and process, including the modifications needed to minimize context-specific biases. Third, we test the framework and process with an analysis of an acquisition in the industrial market and subsequent sales channel integration across 21 territories that used the proposed methodology. The analyses include an evaluation of post-acquisition longitudinal performance across the different evaluative frameworks. Fourth, we present the key findings, managerial implications, limitations, and future research directions.

نتیجه گیری انگلیسی

The overall difference in scores between the two reps exceeded the decision threshold in 62% of the territories (standard deviation 1.11–.25), which made the rep choice clear in those cases. In another 19% of the territories, a combination of the overall score, similar results in three of the four framework recommendations, and the sensitivity analysis supported a single rep firm. Thus, in only 19%, or four territories, were the results too close or ambiguous to indicate a single best rep firm. For each of these territories, after sensitivity analyses were performed across and within frameworks and a lengthy discussion had occurred, a vote by the integration team generated the final decision. The final split between the two suppliers' rep firms was relatively similar; 55% of the reps chosen were previous channel members for the acquiring firm, and 45% were previously affiliated with the firm that was acquired (the one external rep firm also was chosen). As we predicted, affiliation bias was a key pitfall in the sales management framework without the recommended empirical corrections. The paired mean differences for raw or uncorrected employee ratings were significant (p < .05) for all evaluative dimensions, as we summarize in Table 3. The average mean difference across all the dimensions was 0.433 (p < .01), and because these are standardized scores, this result can be interpreted at 0.433 standard deviations. Thus, on average, employees rated sales channels with which they were previously affiliated 0.433 standard deviations higher than they did sales channels from the other supplier. In the uncorrected scores, Supplier A's employees chose their “own” channel partner 90% of the time, and Supplier B's employees chose theirs 81% of the time. These empirical results are consistent with comments from the sales managers and channel members, who described their experience during past consolidations as “politically rather than performance driven” and noted that “the acquiring sales organization typically shows favoritism towards existing channel structure based on past relationships.The least amount of affiliation bias is observed for product synergies (0.215, p < .05) and organization structure, facilities, and systems (0.367, p < .01); the largest bias occurred for sales and marketing capabilities (0.672, p < .01). These results are intuitive, in that synergies and organizational factors can be more objectively evaluated, which reduces opportunities for bias, whereas sales and marketing capabilities are more subjective and prone to bias. The same analysis after correcting for affiliation bias shows a different result. The mean differences for previous affiliations are not significant for four of the evaluative dimensions (cf. sales coverage, mean difference of − .130, p < .05) or the average of the evaluative dimensions. With these corrected scores, Supplier A's employees chose their “own” channel partner 48% of the time, and Supplier B's employees do so 57% of the time. Again in line with our predictions, upward versus downward selling bias appears to be another potential pitfall managers should avoid when integrating sales channels. The correlation analysis (Table 4) of the overall scores (corrected and standardized) between the sales management and customer choice frameworks was significant (r = .268, p < .05), which implies that sales managers' and customers' perspectives are only moderately related. The sales channel partner recommendations by the sales management framework disagreed with the customer choice framework in 38% of the territories. These findings again reinforce comments made by sales channel personnel during qualitative interviews. For example, even when there was a competitive process among the channel members, the reps perceived that the winner was typically whoever “put on the best show,” with little regard for “true sales capabilities.” Apparently, the sales channels' effort to sell upward to sales managers during territory visits or meetings sometimes masks their lack of sales effectiveness focused downward toward customers.In Table 4, we summarize the correlation analyses among the final scores from the four evaluative frameworks, the balanced framework, and sales growth in the sales channel one year after the integration. Of the four frameworks, only sales management and customer choice are significantly and positively related (.268, p < .05), which suggests that each framework may tap into different factors and provide divergent recommendations and/or that the presence of noise in the frameworks may generate unreliable recommendations. In only 37% of the territories (ignoring that which evaluated an external rep firm) do three or more of the frameworks agree. Specifically, historical performance correlated negatively with the three other evaluative frameworks, though only its correlation with the strategic fit framework was significant (− .278, p < .05). In total, these findings suggest that the historical performance criteria and/or timeframe selected may be suspect and reduce the level of confidence managers should place in the historical framework for this sample. More insight can be gained by investigating which framework best predicted future sales growth. Postintegration sales growth was significantly correlated with both the sales management (.369, p < .05) and customer choice (.384, p < .05) frameworks, and historical performance and sales growth correlated negatively (− .278), which, though not significant, is consistent with the negative correlation of historical performance with the other three frameworks. The balanced framework's correlation with sales growth falls in the middle of the range (.211) of the four frameworks, as we would expect because it represents a weighted average of its four constituent frameworks. These findings reinforce the need to not focus solely on the overall score but rather use balanced-scorecard information in a holistic fashion. The integration team believed that, for the products offered by the merged company, both technical and purchasing customer groups had control over decisions that might influence future performance. However, for commodity products, buyers were expected to be the primary decision makers, whereas for new, technically complex, or more proprietary products, engineers would be more critical. Therefore, on the basis of the existing sales breakdown and the organization's future strategic direction, the team weighted purchasing and technical selling effectiveness equally in the customer choice framework. The correlational analysis suggests that the technical group was more informative; channel partners' sales effectiveness for engineers was significantly correlated with sales growth (.434, p < .05) and greater than the correlation with channel partners' sales effectiveness for buyers (.140, ns). Post hoc discussions with sales managers suggested that the timeframes for which the historical performance data were calculated included an industry-wide decline for some of the channel's products and markets, whereas sales growth was calculated during a period of rapid recovery, which may have made the historical performance results spurious. A sensitivity analysis demonstrates that the results changed dramatically according to the timeframe and performance metric selected, in support of the conclusion that, for this sample, historical performance data should be weighted lightly if used at all. When the weighting for historical performance was set to 0, the overall balanced score is significantly related to sales growth (.530, p < .01) and accurately predicts 90% of the channel members ultimately selected. Thus, once the spurious historical performance data were removed, the balanced framework appeared to provide the best indicator of future rep performance. The selection process was completed in less than three months and initiated positive feedback from both sales managers and rep firm owners. The clearly defined and objective basis for the decision process generated appreciative comments from channel members, including “the fairest firing I have ever gone through” and “I wish more suppliers would use more than just the sales managers' opinion in making a decision.” No legal issues developed from terminated channel members, including partners with more than 20 years of history with the supplier. Regional managers also reported that the process helped them learn about one another's businesses: “We not only selected the best rep firm but we also really learned a lot about their [the other supplier's] business” and “I didn't feel as if they [acquiring company] were always going to pick just their own reps.” Finally, senior managers reported that the level of conflict generated from the selection process was low, which enabled the new sales and marketing group to start forming as a team.

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