5 Empirical Part I: Strategic Groups
5.2 Methodology and Data
5.2.1 Strategic Space and Strategic Variables
gradually expand into attractive adjacent strategic spaces? Therefore this study also tests whether PE firms are traversing the strategic space of the PE sector (see D1).
D1: One or more strategic groups traverse the boundaries of the PE sector D0: All PE firms are within the confines of the PE sector
Provided D0 can be rejected, two interpretations appear to be plausible. Either a strategic group is in the process of traversing the confined strategic space toward another strategic space, and typology, industry definitions, SIC codes, databases and regulation will be adjusted accordingly sometimes in the future. Alternatively, it could also be that a strategic group is shaping the boundaries of the strategic space, i.e. it is either expanding the pre-confined space or it is pioneering a completely new strategic space. The respective hypothesis (see E1) will also be tested.
E1: Traversing strategic groups shape the boundary of the strategic space of PE E0: Traversing strategic groups move on to other strategic spaces
A typical problem of research is that it often does not describe how crucial issues were addressed. It was recommended that underlying methodological decisions should be presented in sufficient detail to allow readers to make informed judgments about findings (Cummings et al. 1995). This is even more vital for studies using strategic grouping approach, given the relevance of researcher judgment (Ketchen et al. 1996). The following section presents the methodology, as well as the underlying data which was investigated during empirical testing.
The subsequent chapter will interpret the results and provide an outlook for future research.
The first step is to choose the strategic space (sector), which in this study is PE. Defining the boundary of a sector is one of the most challenging tasks confronting strategy analyses (Day 1981; Geroski 1998). Practitioners and researchers overly rely on SIC codes, although the whole concept is extremely fuzzy and can be severely misleading (Abell et al. 1979;
Levitt 2008). Besides, businesses pursuing PE activity are classified under a broad range of SIC codes. Therefore a thorough investigation of the confines of PE was carried out (see chapter 2), and a group of the top PE firms by capital supply, based on the 2009 and 2010 annual ranking of Private Equity International, was used as the primary sample.
An initial screening of these firms showed that many PE firms invest across a variety of investment stages, which is in line with the PE definition used in this thesis (see chapter 2.1.3).
In fact, this study is the first to investigate the PE firm on the corporate level. The unit of analysis in this study is the corporate level of the PE firm while in most PE related studies the unit of analysis is the PE fund or portfolio company level. Strategic grouping literature suggests that one should not simply focus on business level characteristics such as product and regional scope or market segment. Corporate parenting can also provide essentials for creating competitive advantage and it would be shortsighted to exclude corporate effects and the role of the HQ unit in the firm (Chandler 1991; Daems et al. 1994). For example, functional strategies such as advertising intensity, reputation development, and sales force characteristics can be critical investments in support of the business strategy.
Choosing the strategic variables along which to group observations is a fundamental step in the application of cluster analysis and perhaps the most important one (Ketchen et al. 1996).
It involves several critical issues and there are three basic approaches (Dutton et al. 1983;
Porac et al. 1990; Thomas et al. 1993): inductive (focuses on exploratory classification of observations), deductive (number and nature of groups in a cluster solution are strongly tied to theory), and cognitive (relies on the perceptions of expert informants such as industry executives, has roots in research on interpretation in organizations, which posits that it is the meaning that top managers attach to phenomena, not ‘objective’ characteristics, which directs subsequent organizational action and performance).
Strategic variables should be chosen in a way that fosters rich descriptions of a sample’s characteristics. Both the inductive and the cognitive approach suit in this context, the latter being preferred because its use of experts enhances the confidence into the relevance of the variables. A small number of strategic dimensions can capture the essence of strategic thrusts, suggesting that it is entirely possible to adopt a pragmatic approach (Meyer et al. 1993;
Ketchen et al. 1996). Following recommendations from methodology experts, this study uses the inductive and cognitive approach in tandem in determining strategic variables.
An initial preparatory cluster analysis pointed to potential strategic groups within the PE sector, helping to identify PE practitioners for in-depth conversations from firms representing each strategic group. All interviews were conducted throughout 2009 and the first half of 2010. They were fully transcribed and reviewed by the conversation participants.34
34 A more detailed overview of the interview process will be presented in chapter 6.
The essence from the in-depth conversations, combined with the essence from an overlaying evolutionist approach, empiricist approach, essentialist approach, and from a thorough synthesis of PE related literature, was triangulated to choose the key strategic variables. Insights from this deep understanding of the sector were also used to weight the strategic variables in order to reflect their relative importance.
Earlier efforts in the search of strategic configurations were typically defined across narrow sets of variables, often only one or two. This study incorporates seventeen strategic variables, thirteen endogenous variables and four external variables. The following section presents the sample and sources (see Table 3) and the definition of each variable in more detail (see Table 4).
Strategic Dimension Strategic Dimension Firm dependency
Organizational footprint in US Organizational centralization Institutionalized experience Strategic space proximity Strategic space fuzziness Capital supply
Deal flow Investment size Investment sector focus Investment region focus Investment stage focus Buy to build
Operational efficiency Investment performance Market share
Reputation
Abbreviation Abbreviation FIRMDEP ORGFOOT ORGCENT INSTEXP SSPROX SSFUZZ CAPSUP DLFLOW INVSIZE INVSECTOR INVREGION INVSTAGE BYTOBUILD OPEREFF INVPERF MKTSHARE BRAND
Source Source
Desktop research, Thomson Mergermarket
Mergermarket, Thomson Thomson
Mergermarket, Thomson
Desktop research, Thomson, Mergermarket, Private Equity Intelligence Private Equity International
Mergermarket
Mergermarket, Thomson Thomson
Thomson Thomson Mergermarket
Mergermarket, Thomson, desktop research Private Equity Intelligence
Mergermarket, Thomson Private Equity International Sample
Sample
• Worldwide
• Initial sample: top 130 PE firms by capital supply 2005 – 2010, representing 78% of PE universe
• 37 firms excluded due to incomplete data
• Final sample: top 93 PE firms by capital supply 2005 – 2010, representing 65% of PE universe Strategic Dimension
Strategic Dimension Firm dependency
Organizational footprint in US Organizational centralization Institutionalized experience Strategic space proximity Strategic space fuzziness Capital supply
Deal flow Investment size Investment sector focus Investment region focus Investment stage focus Buy to build
Operational efficiency Investment performance Market share
Reputation
Abbreviation Abbreviation FIRMDEP ORGFOOT ORGCENT INSTEXP SSPROX SSFUZZ CAPSUP DLFLOW INVSIZE INVSECTOR INVREGION INVSTAGE BYTOBUILD OPEREFF INVPERF MKTSHARE BRAND
Source Source
Desktop research, Thomson Mergermarket
Mergermarket, Thomson Thomson
Mergermarket, Thomson
Desktop research, Thomson, Mergermarket, Private Equity Intelligence Private Equity International
Mergermarket
Mergermarket, Thomson Thomson
Thomson Thomson Mergermarket
Mergermarket, Thomson, desktop research Private Equity Intelligence
Mergermarket, Thomson Private Equity International Sample
Sample
• Worldwide
• Initial sample: top 130 PE firms by capital supply 2005 – 2010, representing 78% of PE universe
• 37 firms excluded due to incomplete data
• Final sample: top 93 PE firms by capital supply 2005 – 2010, representing 65% of PE universe
Table 3: Sample and Sources
Whether PE firms are independent or affiliated to e.g. banks, sovereign wealth funds, or pension funds can considerably influence strategic decisions, wealth transfers, and the allocation and repatriation of generated wealth. The variable ‘firm dependency’ (FIRMDEP) measures the share of control rights held by affiliated parties. Given that no database provides this information for all firms in the sample, several sources had to be triangulated and missing data points had to be estimated. The insight generated by the variable ‘organizational footprint in the US’ (ORGFOOT) is two-layered. The US market is the largest and most mature PE market, so ORGFOOT measures both the regional concentration in the US and the footprint in the most mature market. If PE firms undergo a natural evolution path, those with a strong footprint in the US should more likely show signs of more advanced business models. The variable ‘organizational centralization’ (ORGCENT) approximates the centralization degree of each firm. ORGCENT touches on a central theme of expert conversations. Some argued
that centralization is important, assuming that the physical proximity of PE investment professionals would allow for market knowledge and best practices sharing. Others argued that it is difficult to originate transactions from one central office, and that decentralized ‘feet on the ground’ are necessary in order to improve access to more attractive investment opportunities. Measuring full years since firm inception, the variable ‘institutionalized experience’ (INSTEXP) approximates the firm’s experience.
Conceptualized by recognized strategic grouping studies (Daems et al. 1994), the variable
‘strategic space proximity’ (SSPROX) measures the proximity of a PE firm toward the pre-confined strategic space. In this study SSPROX measures the share of assets under management in traditional PE of total assets under management. Although SSPROX indicates the share of traditional PE activity, it does not provide any information about the fuzziness of the remainder. Therefore, the variable ‘strategic space fuzziness’ (SSFUZZ) was also introduced, ranking the order of the cluster to which the firm belongs. Another preparatory cluster analysis was carried out specifically to identify groups of firms within the PE sector, showing different degrees of strategic fuzziness. The alternative would be to measure the degrees of related and unrelated diversification. However, this would have not been practicable given the disadvantages laid out above. SSFUZZ follows a more objective approach by investigating the specific business composition of each firm.
Strategic Dimension Definition
Firm dependency (control rights held by 3rd party strategic owners) / (total control rights) Organizational footprint in US sqrt (number of offices in US)
Organizational centralization ln ((assets under managem ent) / (number of offices)) Institutionalized experience full years since firm inception
Strategic space proximity (assets under m anagement in PE) / (assets under management) Strategic space fuzziness rank order of segm ent cluster to which the firm belongs
Capital supply neg sqrt (1 / ((capital raised over last 5 yrs) / (capital raised by all firms over last 5 years)))
Deal flow sqrt ((number of relationships to 3rd parties) / (average number of relationships to 3rd parties of all firms)) Investment size sqrt ((average PE deal size) / (average PE deal size of all firms))
Investment sector focus sqrt ((investment value of top two sectors) / (total investment value)) Investment region focus (investment value of top two regions) / (total investment value) Investment stage focus (investment value of top two stages) / (total investment value)
Buy to build (average investment holding period) / (average investment holding period of all firms) External Variables Definition
Operational efficiency ln ((assets under managem ent in PE) / (investment professionals in PE)) Investment performance sumproduct (net IRR; value of PE fund) / (sum of values of all PE funds of firm) Market share sqrt ((assets under management in PE) / (assets under management of all PE firm s)) Reputation neg ((capital supply rank 2010) - (average capital supply rank 2010 of PE firms in sample)) Combined external variables CEV
Table 4: Definition and Normalization of Strategic Variables
Some experts argued that the ‘supply of capital’ (CAPSUP) is one of the most important, perhaps the most important, strategic dimensions for the PE firm. CAPSUP reflects this relevance. ‘Deal flow’ (DLFLOW) is the other variable which weighs as much as CAPSUP. It is difficult to measure deal flow, notably the quality of deal flow. Ideally the researcher would need to see what the investment committee sees. It was recommended that the centrality in networks is an acceptable indicator for deal flow. Therefore DLFLOW is measured by the
number of firm relationships to third parties over the average number of relationship to third parties.
The following five variables are commonly viewed as the most important strategic dimensions with respect to investment decisions of PE firms. First, the variable ‘investment size’ (INVSIZE) measures the average deal size of firm deals compared to the average deal size of all firms in the strategic space. The variable ‘investment sector focus’ (INVSECTOR) measures the concentration of firm investments in the firm’s top two sectors. The variable
‘investment region focus’ (INVREGION) measures the concentration of firm investments in the firm’s top two regions. The variable ‘investment stage focus’ (INVSTAGE) measures the concentration of firm investments in the firm’s top two investment stages. Finally, the variable ‘buy to build’ (BYTOBILD) compares the average investment holding period of the firm to the average investment holding period of all firms in the sample.
To test for statistical validity of the results, four external variables were used. First, the variable ‘operational efficiency’ (OPEREFF) measures the firm economics by measuring the ratio of assets under management in PE over number of investment professionals in PE.
Second, the variable ‘investment performance’ (INVPERF) measures the weighted net IRR of firm PE funds. 1994 was defined as ‘vintage’ threshold and 60% was defined as ‘payout ratio to investors’ threshold. Third, the variable ‘market share’ (MKTSHARE) measures the share of firm assets under management in PE of assets under management in PE of all PE firms.
Fourth, the variable ‘reputation’ (BRAND) approximates the reputation of the firm by measuring the development of capital supply rank as an indicator. The fifth external variable CEV is synthetic and comprises the four other external variables, OPEREFF, INVPERF, MKTSHARE, and BRAND, being weighted 30%, 30%, 20%, and 20%, respectively.