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The Impact of Management Development on Organizational Performance: A European Study

Christopher Mabey School of Management and Organisational Psychology Birkbeck College University of London Malet St Bloomsbury London WC1E 7HX +44 (0) 20 7631 6753 [email protected]

Paul N. Gooderham

Department of Strategy and Management Norwegian School of Economics and Business Administration Breiviksvn 5045 Bergen NORWAY +47 55 95 9696 [email protected]

Symposium Paper presented at Fourth Conference on HRD Research and Practice Across Europe 2003

Toulouse 23-24 May

CM/UFHRD/03/05/18 1 ABSTRACT

While the contribution of management development as a key element of a strategic approach to human resource management appears undisputable, there is still little empirical evidence that this leads to superior firm performance. Based on interviews with the HRD manager and a line manager in a sample of 700 organizations in seven European countries, this study examines the impact of management development policies and practices upon company performance. Predetermined factors like the sector, size and host-country of the companies explain a significant amount of variance in performance. However, the degree of variance explained is considerably enhanced when discretionary variables are added. In particular a progressive human resource context and the perceived importance attached to management development by line managers are both significant regressors of benchmarked organizational performance.

CM/UFHRD/03/05/18 2

INTRODUCTION

One of the hallmarks of a strategic approach to human resource management (HRM) is the link between human resource policies and business strategies. In recent years there has been a concerted attempt to demonstrate that investment in HRM policies leads to business benefits. An example in a US context is the work of Pfeffer (1998). Drawing on secondary data, from the global automobile industry and other industries, as well as case study evidence of “best practice”, he has shown that the ways in which organizations manage their people are enduring sources of competitive advantage. This focus upon HRM policies and practices which attract, then foster and develop superior capabilities has been found to, among other things, improve export performance (Gomez-Meija, 1988), increase productivity, lower scrap rates and lower employee staff turnover (Arthur, 1994) and enhance employee satisfaction and financial indicators (Bowen and Lawler, 1995).

A consistently influential feature in such studies, and a central element of the resource-based view of human resources, is the relationship between of management development and organizational performance (Becker and Huselid, 1997). In their proposed research agenda for investigating high performance work systems (HPWS), these authors point out that empirically there is a need to gain a better understanding “of the processes through which HPWS add value” (1997:21, italics in original). This is consonant with the conclusions of Martocchio and Baldwin (1997) who, in their review of the strategic organizational training literature, note that “a most pressing need is to determine the domain of strategic organizational training decisions and the processes that lead to these decisions” (1997: 24). The intention of this article is to explore more fully the potential impact of management training upon organisational performance in Europe; it is hoped that this will make both a theoretical and practical contribution. The field of management training is characterised by broad surveys and in-depth case studies, which have yet to produce coherent theory. While at a practical level, there is broad agreement that inadequate management and leadership continues to be a significant inhibitor of economic competitiveness (DfEE, 1998). The British Government has recognised the need to “generate a much better evidence base on the impact of management and leadership skills and actions on organizational effectiveness” (DfES/DTI, 2002: 13) and has noted that, as yet: “there are no credible measures to prove links between management training and development, good management and leadership and performance.” (CEML, 2001). This sentiment is echoed more generally elsewhere in Europe, where the globalisation of the economy and the emergence of a new knowledge-based economy is seen to be challenging the adaptability of European education and training systems (European Commission, 2000).

MANAGEMENT DEVELOPMENT AS A KEY DIMENSION OF PROGRESSIVE HRM

Despite the amount of corporate resource invested in the training of managers, there are surprisingly few studies designed to assess the financial impact of management training and development policies. In the US, attempts to quantify the outcomes of training appear to be confined to a few leading exemplars like Motorola and Sears (Yeung and Berman, 1997) or small case studies of specific training interventions (Barling, Weber and Kelloway, 1996). In the UK, studies have demonstrated a statistically significant relationship between competence-based HRD systems and both individual and business performance (Winterton and Winterton, 1997), and a saving of £270 million has been attributed to a management development programme at British Telecom (Lee, 19XX). Research seeking to measure broader impacts of management training is more plentiful. For example, a life-long learning programme was found to improve staff perceptions of trust and fairness in a Scottish subsidiary of a US multinational (Martin, Pate and McGoldrick, 1999); in a sample of 500 UK organizations, the sophistication of the infrastructure to develop managers positively correlated with the perceived impact and success of management development (Mabey, 2002); in a survey of 1500 managers, a clearly articulated framework of management development led to improved ratings of leadership and organizational performance (Horne and Jones, 2001); and self-management skills training in a US insurance company was found to significantly improve job performance for salespeople (Frayne and Geringer, 2000).

CM/UFHRD/03/05/18 3 In their review of micro and macro HRM research, Wright and Boswell (2002) note the dearth of research tracking the impact of single HR practices, like management training, when compared to multiple practice research at an organizational level of analysis search. In contrast, impressive relationships between financial performance and bundles of high performance work practices have been well documented (see Becker and Huselid, 1997 for a review). In this paper Becker and Huselid refer to “management development and training activities linked to the needs of the business”, as one of four key HRM systems (1997:2).

However, such research is not without its problems, both conceptual and methodological. In their focus upon strategic HR dimensions, such studies have tended to neglect the mediating influence of such things as the salience of management philosophies (Dyer and Reeves, 1995) or contextual factors like capital intensity (Richard and Johnson, 2001). Typically, the actual measures of high performance work systems adopted by researchers are reasonably objective but uninformative about quality (e.g “What is the number of hours training received by employees in the last year?”, from Huselid, 1995:646), or more indicative of stated policy than actual practice (Wright and Boswell, 2002). Another potential flaw is the reliance upon a single respondent to report measures of HR practice, who at the same time provides measure(s) of organizational performance (Guest, 2001; Wright et al, 2001). Finally, Dyer and Reeves (1995) note that there is little consistency in the measures of human resource activities chosen by authors, thus making it difficult to draw conclusions from this accumulation of studies, about the specific contribution of a given HR policy.

When it comes to advising those responsible for HRD in organizations, perhaps the most problematic aspect of research to date is that it fails to explain the linkages between attempts to improve management capability and organizational performance. We know these linkages to be complex (Truss, 2001) but this should not deter us from at least attempting to determine the key steps in the pathway between management development and organizational performance, in the same way that progress has been made to explain the impact of HRM with reference to employee attitudes and behaviour (Guest et al, 2002).

Common-sense logic tells us that the careful development of managers will have a positive influence upon organizational performance. The strong probability that employee development will be a driver of growth and add value to the organization in various ways, both attitudinal and financial, has been well articulated (eg Mayo, 2000); the creation and sustaining of managerial capability remains a central tenet of the resource based view of the firm (eg Mueller, 1995); and empirical studies have provided a encouraging glimpse of how influential progressive people policies can be on organizations over time (eg Patterson et al, 1997). Yet, for all this, we still are relatively ignorant about the variables which bring about such effects and the extent of such impact.

This study addresses the weaknesses in current research in the following ways. First, in order to understand better its specific as one of four high performance HR systems, we will isolate and track the impact of management training and development, taking care to control for other HR practices as cautioned by Wright and Boswell (2002). Second, it has been pointed out that there is relative ignorance about the gap between the formulation and implementation of HR practices (Wright and Snell, 1998); this study will seek to narrow that gap in relation to management development by identifying the inputs to training systems for managers (the relatively predetermined context within which training occurs), the training processes adopted by organisations to deliver and design management development (which are the result of discretionary choices made by HRM specialists), together with the resulting outputs (the amount and range of training activities) and outcomes (the value and impact ascribed to such activities). Several authors have advocated such a systems approach to management development (Garavan, Costine and Heraty, 1995; Doyle, 1996). Third, in order to get beyond the “strong disconnect between the ‘rhetoric’ of human resource management as expressed by the human resource department, and the ‘reality’ experienced by employees” (Truss, 2001; Legge, 1995) this study will seek views from both HRD and line managers in each sample organization. This also allows the most knowledgeable raters to be used for given HR dimensions, as advocated by Huselid and Becker (2000). Fourth, much of the HRM-performance research has relied on surveys with necessarily truncated questions to describe practices that exist across multiple sites (Wright et al, 2001). Here, given the relatively subtle nature of this enquiry, structured interviews are used to allow more finely graded responses and to ensure opportunities for checking understanding and clarifying answers.

CM/UFHRD/03/05/18 4 Having made the case for the proposed study, we now formulate some specific propositions arising from the literature.

THE LIKELY DETERMINANTS OF PERFORMANCE

Human Resource Management Context

Authors have long emphasised the need to align human resource management priorities to the business priorities and/or structural configuration of the organisation concerned (Fombrun, Tichy and Devanna, 1984; Schuler and Jackson, 1987). There is some empirical support for the value of integrating business objectives and human resource policies, including the training of managers (Becker, Huselid, Pickus and Spratt, 1997; Gratton, Hope-Hailey, Stiles and Truss, 1999) together with some more equivocal results (Raghuram and Arvey, 1994). This notion of matching is not without its difficulties in practice. First, the capability of the HRM department to translate business priorities into appropriate human resource goals has been questioned (Huselid, Jackson and Schuler, 1997). Second, it glosses over the inevitable tension between the need for uniformity of strategically-driven HR policy at an organisational level and the value of discretion when implementing policy at a business division level (Legge, 1995). Third, it underestimates the time taken to design and benefit from human resource initiatives, especially those concerned with the enhancement of management capabilities (Wright and Snell, 1998). Finally, the matching model elevates the value of fit, when competitive advantage may actually derive from the capacity of an organisation to allow for constructive deviance in the way it develops its staff (Mueller, 1996). Despite these mixed results and conceptual difficulties, it would seem reasonable to predict that:

Proposition 1: There will be a positive relationship between organizational performance and the extent to which an organization’s HRM is linked to its business strategy.

Management Development Practices

It has been consistently theorised that the means by which a firm develops its managers in the long- term and addresses skills gaps in the short term are key determinants of its market performance (Schuler and Jackson, 1987; Butler, Ferris and Napier, 1991). Although the number of empirical studies demonstrating this is small, as noted above, this suggests that the ultimate quality of management training and development can potentially make a material difference to organization’s performance. HRD managers are faced with two important choices here. The first is explicit and concerns the degree to which management training is formalised by the organization through strategic practices. The second is more tacit and concerns the ethos of management development, the thoughtfulness given to the way policies are determined and linked to wider and longer term HR requirements. The propositions expressing these two sets of choices are considered next.

Whether management development policies are formalised and written can be an indication of the strategic importance they have for the organisation (Garavan 1991). This is because such statements suggest a considered and often consultative, rather than an ad hoc approach to the way managers are developed. Although it is generally recognised that such policy documents often represent statements of intent rather than actual practice (Gratton et al, 1999). Appraisal meetings where managers have the opportunity to discuss development needs with their line manager are frequently cited pivotal to effective management development. There is some evidence that using appraisals to identify manager training needs is a growing practice in the UK (Raper et al, 1997) and in Europe more generally (Holden, 1992). This is partly because feedback, when sensitively handled, can be a catalyst to real learning (Alimo-Metcalfe, 1998). It is also associated with effective career planning. In a study of 524 organizations, Baruch and Pieperl (1997) found that active career planning, characterised by performance appraisals, career counselling and succession planning correlated highly with organizations described as having “dynamic, open and pro-active climates”. Another key practice is the effort expended in reviewing management development activities although there is, as yet, little empirical evidence of organisations systematically reviewing the business benefits deriving from management development activities in the UK (DfEE, 1998). Overall, then, the literature suggests that the care given to the diagnosis, design of training and development opportunities and to their subsequent evaluation will be indicative of good practice. From this it might be surmised that:

CM/UFHRD/03/05/18 5 Proposition 2: There will be a positive relationship between organizational performance and the extent to which an organization utilises effective management development practices.

However, practices alone may remain ineffective if not supported attitudinally by the organization. A good indicator of what we might term management development ethos is where responsibility for the training and development of managers lies (or should lie). Here there are two distinct views. There is a strong argument that management development is best managed by the organisation, accompanied by human resource audits, corporately orchestrated action plans and cost-benefit calculations (Ulrich, 1997). This is because those in leadership are seen to be better informed and positioned to advise on the future capabilities necessary to generate rents for the firm (Castanias and Helfat, 1991). A counter argument is that development is most effective when the individual manager takes, or at least shares, responsibility for diagnosing needs and choosing the goals for their own self-development. This view can be sustained from two quite different literatures. The first of these is the learning literature which advocates the value of more tailored, personally meaningful and timely development (Marsick and Watkins, 1997; Raelin, 2000). The second body of literature focuses on internal labour markets and on protean careers and has highlighted the potential for opportunistic individuals to exploit their highly ‘idiosyncratic’ knowledge whilst taking responsibility for their own development (Hall and Moss, 1998). Either way, it appears that taking responsibility for training and development in a proactive rather than an ad hoc manner, and seeking to develop individual potential are both indices of a positive development ethos. To this might be added the use of skills or competency frameworks

There is some empirical evidence that those organisations which give a high priority to training and development, particularly over the longer term, will be those most likely to create a flexible and multi- skilled workforce (Gratton et al, 1999) and perform more successfully in terms of both productivity and profitability (Patterson et al, 1997). And developing managers against a specific set of skills or competencies has also been demonstrated to add value (Winterton and Winterton, 1999). However, the practical difficulties of sustaining a strategic HRD approach should be noted. In only one of Gratton et al’s (1997) eight case organizations was there a sophisticated attempt to link business strategy to human resource strategy (1997:204) and in a study of 22 U.S. ‘leading firms’ Siebert and Hall (1995) found that only two companies, 3M and Motorola, conducted their training of managers in an outwardly focused way and where business priorities were the trigger for development. Notwithstanding this gap between theory and practice, it can be hypothesised that when companies do manage to create a strategic ethos for management development, the performance benefits can be impressive.

Proposition 3: There will be a positive relationship between organizational performance and the degree to which an organization creates a positive ethos toward management development

The Perceived Importance of Management Development When reporting on the activities and impact of management training, previous studies have almost exclusively relied on the views of HRD managers and/or the senior team. While this may be appropriate to gain an accurate picture of HRM context, management development policies and process factors so far discussed, when it comes to experience of management development, we would argue that line managers are the key informants (Huselid and Becker, 2000). Given the often cited gap between espoused and actual practice of HRM generally (Truss, 2001, Mabey et al, 1997; Legge, 1995) and management development in particular (Clarke, 1999; Mole, 1996), this perspective is a vital way of testing reality at a grass-roots level.

Proposition 4: There will be a positive relationship between organizational performance and the degree to which managers positively evaluate their experience of training and development

The Amount and Diversity of Management Development Any assessment of management development needs to, in some way, measure the extent of training and development activity undertaken. A convenient and conventional way of assessing management development activity is to measure the annual number of training days (Huselid, 1995; Koch and

CM/UFHRD/03/05/18 6 McGrath, 1996; Patterson et al, 1997). There are problems with this. As Becker and Huselid (1997) admit “an index measure simply indicates that ‘more is better’, and an evaluation of this assumption awaits further study” (1997:6). Number of training days is an imprecise and possibly misleading measure if used alone. It is important to know something about the methods and quality of development undertaken (Mansfield and Poole, 1992). Some research suggests that managers learn more from their day-to-day work, from colleagues, from observing other managers and from other life experiences than they do from management training programmes (Davies and Easterby-Smith, 1984; Kotter, 1995; Dawes et al, 1996). For example, McCall et al., (1988) suggest that socialisation to an organisational culture is best learned on the job, and this may also go for many of the less task-specific skills. In order to quantify the overall contribution of management development, measures are required which separately illustrate the type and diversity of management training as well as volume.

Proposition 5: There will be a positive relationship between organizational performance and the amount of management development undertaken

Proposition 6: There will be a positive relationship between organizational performance and the diversity of management development practices.

METHOD

The results reported in this study were generated from 1400 telephone interviews conducted with the HRD manager and a line manager in 700 domestically-owned organizations. This represents the first phase of a larger project researching management training and development systems in Europe, funded by the European Commission. Participating countries were selected to represent the five typologies of management training and development previously discovered to operate in Europe (Bournois et al, 1994). In addition to Germany (group1), Denmark and France (group 2), Spain (group 3), United Kingdom (group 4) and Norway (group 5), Romania was chosen as an example of an emerging European economy, typical of a country seeking future membership of the European Community.

The sample

A stratified sampling frame was agreed by all the partners which provided a reasonable representation of organizations by size, sector and annual turnover, within an overall design constraint of 100 firms per country. Using local databases, contact was made by the research team with the HRD manager or equivalent, targeting only host country owned companies and omitting public/not for profit organizations in each respective country. Each HRD manager was asked to identify some managers in their organization who might be willing to participate in the study. Those that were unable or unwilling to do so were dropped from the sample. This procedure was followed until each country reached its quota, yielding matched pair data for a total of 100 organizations. Of the 896 contacted, 701 agreed to participate, representing a response rate of 75%. The distribution across the total sample was as follows: manufacturing 34.3%, transport and distribution 21.3% and the services sector (including financial, and insurance companies as well as legal, business and management consultancy firms) 44.3%. All countries broadly mirrored this breakdown, with the exception of Germany where services was over represented at the expense of transport and distribution.

Given the focus of the study, which was structured management development activities (formal or informal) initiated by the employer, it made sense to only include companies with 20 staff or more. The eventual sample achieved our goal of being evenly spread across four size categories: 20-99 employees (25%); 100-249 (23.6%); 250-499 (22%); 500 or more (28.3%). As might be anticipated smaller firms were over-represented in Spain and Romania, and a relative scarcity of firms with 250-499 staff in the latter also. In contrast, organizations employing more than 5000 staff were over-represented in the highly industrialized German sample and to a less extent in Norway. A final characteristic of the sample was size, as measured by annual financial turnover. Structuring the overall sample according to the 25th, 50th and 75th percentiles resulted in a distribution of approximately 21% of organizations falling within each of the following four turnover bands: up to £5.7 m; between £5.7m and £20.7m; between £20.7m and £93.3m; and over £93.3m. Here, the country distribution was far more uneven. As

CM/UFHRD/03/05/18 7 might be anticipated, 81% of German companies registered turnover as more than £20.7m, compared to 49% in UK, 41% in France, 24% in Spain and none in Romania. In fact two thirds of Romanian firms had a financial turnover of less than £5.7m.

The interview schedule was based on that used in prior UK studies (Thomson et al, 1997; Mabey et al 2000). However every effort was made by the research team to ensure dynamic equivalence of all terms, definitions and meanings in each of the seven country contexts. To this end each country interview schedule was back translated. The interviews which were arranged in advance, were conducted by telephone and in some cases face to face, and lasted between 20-30 minutes for HRD managers and a little less for line managers. Questions were asked about industrial and management structure, the organization’s HRM strategy and management development policy, its preferred methods and practices for management and career development and mechanisms for evaluation. Line managers were interviewed about their first-hand experience of training and development, their views on the policies and practices adopted by their employer together with an overall assessment of the effectiveness of the training provided for managers.

The independent variables The following measures were used as independent variables. Apart from organization size and the amount of management training, variables were created by factor analysis (see Table1).

Insert Table 1 about here

Human Resource Context refers to the degree to which a strategic stance is taken by those responsible for HR in the firm. This is based on two measures: one ‘upstream’, asking respondents whether HR plays an active role in formulating business strategy and the other ‘downstream’, namely asking about the extent to which HRM is linked to business strategy (alpha = 0.79). Collectively these measures were predicted to have a direct influence upon organization performance, as well as providing the overall context within which management training and development policies are forged.

The two constructs relating to the development processes adopted by an organisation are intended to reflect the choices made concerning the way it typically diagnoses, designs and delivers management training. One concerns Management Development Practices: having an established management development policy, conducting appraisals at which development needs are discussed, the use of career planning and fast-track programmes and the systematic evaluation of management training (alpha =0.66). The other is more attitudinal and is referred to as Management Development Ethos: it comprises the extent to which the organization takes responsibility for management training and development, the degree to which managers are developed against a specific set of skills/competencies, and a concern with the long-term development of managers and an emphasis on developing potential (alpha =0.68).

It was felt that line managers were best placed to report on the outputs of management development policies and practice in their organization. Amount records the average number of days per year spent by managers on training. Diversity reflects the range of different methods typically utilised to develop managers, either internally and externally (alpha = 0.56). Perceived Importance is a multi-faceted measure, tapping the degree to which line managers believe the management development is credible and influential; the priority given to MD, the perceived link between MD and business priorities, whether it is linked to skills/competencies, the extent to which MD achieves its objectives and its overall impact on the organization (alpha = 0.85).

Dependent Variable

The dependent variable is organizational performance. In order to derive a quantifiable measure of benchmarked performance for each participating organisation, the seven-item index developed by Delaney and Huselid (1996) for their study of HRM practices was utilised. The authors maintain that “measures of perceived organizational performance to correlate positively…with objective measures of firm performance” (1996:954). Three items make reference to the quality of products/services and

CM/UFHRD/03/05/18 8 customer relations, two refer to the ability to recruit and retain staff, and two refer to the quality of relationships between staff (alpha = 0.80). In all cases respondents are asked to rate their organization’s performance over the past three years compared to competitors in their sector. The use of a self-report measure of performance is justified on a number of grounds. First these items were felt to represent a rounded and robust index of the kind of performance criteria likely to be influenced by investment in management development. Second, as pointed out by Machin and Stewart (1996), more objective measures of performance, such as those created by accountants for annual reports, are often socially constructed and therefore distorted. Third, it could be argued that it is the perceived view of corporate performance rather than more objective, quantified measures, that actually influences the way managers act and the way decisions are made (Guest, 2001; Mayo, 2000). Finally, in line with recommendations to avoid measurement error, the organizational performance index was derived from the average of two raters per organization, the HRD Manager and a line manager (Wright et al, 2001).

Control Variables

While this paper views management development as an important determinant of organizational performance, a range of non-discretionary factors should also be taken into consideration and controlled for. Of these we regard the impact of country, sector, size and firm growth as being of particular significance. Country as a factor embraces those aspects of a firm’s national setting that may enhance organizational performance. As such it will include state intervention in the form of, for example, direct and indirect subsidies, the general economic climate as well as the quality of the national infrastructure including communications, the banking system, clusters of high-performing firms and the education system. The variable was created as a categorical regressor represented by dummies for Denmark, France, Germany, Norway and Romania with the UK as the reference category. The Sector of a firm can also influence organizational performance. Manufacturing industry has contracted within most European countries not least because of global competition, while service industries have enjoyed strong growth. Here, sector is a categorical regressor represented by two design variables in the regression analysis, with manufacturing and transport with services left out as the reference category. Size is generally viewed as a function of long-term historical performance with firms growing in size as they accumulate those resources that confer competitive advantage and superior organizational performance. Here it is operationalised as the number of employees employed with scores converted to a standardised five format. Finally, it is conceivable that a current strong organizational performance might be due to high financial Growth; this may be sustained over several years or of a relatively temporary nature deriving, for example, from first-mover advantage. Here this variable is operationalised as the degree of recent change in financial turnover and number of managers experienced over the past three years together with expected change in these measures over the next three years (alpha = .54).

RESULTS

Table 2 is a correlation matrix that features all the study variables. It shows that HR Context, MD Ethos, Perceived Importance and Amount are all strongly positively correlated with organizational performance. Despite being weaker both MD Practices and Diversity are also positively correlated with organizational performance at a statistically significant level. Insert Table 2 here

Table 3 contains a two-step multivariate regression analysis. Step one is exclusively concerned with the results of regressing organizational performance on our four control variables. When interpreting the country-coefficients it is important to remember that the UK is the reference category. In fact, the regression constant may be interpreted as the predicted value on organizational performance for UK firms when the remaining regressors are set to zero. The coefficients for Germany and Romania are

CM/UFHRD/03/05/18 9 close to zero and are not statistically significant. This means that German and Romanian firms resemble UK firms with respect to organizational performance controlling for sector, firm size and turnover. The coefficient for France is negative and statistically significant. This indicates that French firms have a weaker organizational performance than United Kingdom firms. Finally, we can observe that the opposite is the case for Danish, Norwegian and Spanish firms.

Insert Table 3 here

We note that sector indicates a very small inter-sector effect for manufacturing in relation to organizational performance when measured against transport, but a significantly negative effect for service firms. The effect of firm size is statistically significant but negative implying that the smaller the firm, the better its organizational performance. This is the opposite of what we had expected. Finally, turnover has a strong positive effect on organizational performance.

The R-square statistic measuring the effect of the four control variables on the variance in organizational performance is .106. When we add the discretionary variables, this increases to .230 underscoring the importance of these factors. In particular the second step of our regression analysis confirms the importance of HR Context, Perceived Importance, Diversity and, to a lesser extent, MD Ethos. These findings are largely consistent with the findings of the correlation matrix. However, unlike the correlation matrix, the regression analysis indicates that Amount does not have a significant impact on organizational performance.

DISCUSSION

First and foremost our findings indicate the importance of nearly all of the keys elements associated with management development for organizational performance. Amount of management is the only element that fails to influence it. That management development has this clearly tangible impact when we take into account the effects of seven national settings, sector, firm size and turnover underlines not only the robustness of our finding, but also its broad applicability. Given the spread of national settings it is reasonable to suppose that investing in management development represents good practice for European firms in general. Given that we have included Romania this finding would appear to hold good for east European firms as well as west European firms.

Although the issue of size only figures as a control variable in our analysis we find its negative effect on organizational performance noteworthy. In essence smaller firms have a superior organizational performance. Although, further research is clearly required, we may nevertheless surmise that large firms should examine ways in which they might create stand-alone operations that duplicate the features of small firms.

CONCLUSION

Studies tracking the performance impact of high performance HRM practices invariably include management training as key element, but this does not allow us to assess the specific contribution of management training and development practices. Of the few that have taken the training of managers as their exclusive focus, none have identified the particular aspects of policy or practice, diagnosis or design, content or process, which prove to be influential. Without such explanation those responsible for management development in organizations remain uninformed about the effects of policy and implementation decisions they can and should be making when developing their management capability. A second problem when reporting on the activities and impact of HRM and HRD is that previous studies have tended to rely on the views of HRD managers and/or the senior team. While these respondents have a privileged perspective, it is also likely that, as custodians of management development, their views will be biased. This study seeks to overcome these weaknesses by testing propositions which incorporate all those elements derived from the literature as most likely to influence the way in which management training is delivered and evaluated. And, in order to secure the grass- roots reality of management development, the views of HRD managers are complemented with the views of line managers within the same organizations. Results demonstrate that human resource and

CM/UFHRD/03/05/18 10 management development variables have a significant impact on performance which is a benchmarked measure taking into account the quality of products and services, the ability to attract and retain key staff and the quality of relationships within the firm. Indeed these factors explain a good deal more variance in performance than the size, sector and country in which the firm is located. The fact that it is the discretionary variables which make the difference, as against those over which they have no control, should come as some encouragement to HRD managers seeking to justify investment in strategically oriented and thoughtfully implemented management training and development activities.

References To be completed

CEML (2001) Managers and Leaders: Raising Our Game, Report of the Council for Excellence in Management and Leadership, London

DiMaggio, P and Powell, W (1983) The iron cage revisited: institutional isomorphism and collective rationality in organizational fields, American Sociological Review, 48, 147-60

European Commission (2000) The Quality of Vocational Training: Proposal for Action, Directorate- General for Education and Training, Brussels

CM/UFHRD/03/05/18 11 Table 1: Study Variables (with Cronbach  Values)

Variable Items n  Control variables Size No of employees 698 n/a

Growth Recent change in turnover 699 0.54 Future change in turnover Recent change in number of managers Future change in number of managers Independent Variables HR Context Active role of HR 700 0.79 HR link to business strategy

MD Ethos Responsibility by organisation 698 0.68 Link to competencies Long term focus Aim to develop potential

MD Practices Managers’ careers planned 700 0.66 Use of fast track Policy statement developed Development needs discussed Review of MD activity

Importance Reflects business strategy 701 0.85 Link to competencies High Priority Meeting objectives Positive impact

Diversity Number of external delivery techniques 701 0.56 Number of internal delivery techniques

Amount Number of days 673 n/a

Dependent Variable Organization Performance reported by HRD managers 698 0.88 Performance Performance reported by Line Managers

Italics indicate that responses are taken from Line Manager interviews

CM/UFHRD/03/05/18 12 Table 3 Multiple Regression

Model Summary

Change Statistics Adjusted Std. Error of R Square Model R R Square R Square the Estimate Change F Change df1 df2 Sig. F Change 1 .326a .106 .092 .4422 .106 7.665 10 646 .000 2 .478b .228 .209 .4128 .122 16.873 6 640 .000 a. Predictors: (Constant), FGRO, DSDIS, DNO, ZCD2, DDK, DSP, DRO, DSMAN, DFR, DGE b. Predictors: (Constant), FGRO, DSDIS, DNO, ZCD2, DDK,Coefficients DSP, DRO,a DSMAN, DFR, DGE, FDIV, FPRA, FHRI, FIMP, ZCM8, FETH Standardi zed Unstandardized Coefficien Coefficients ts Correlations Model B Std. Error Beta t Sig. Zero-order Partial Part 1 (Constant) 3.852 .071 54.173 .000 DDK .134 .065 .102 2.065 .039 .090 .081 .077 DFR -.223 .064 -.171 -3.470 .001 -.239 -.135 -.129 DGE 7.884E-02 .067 .060 1.184 .237 .012 .047 .044 DNO .139 .065 .106 2.148 .032 .082 .084 .080 DRO 5.688E-02 .068 .041 .833 .405 .046 .033 .031 DSP .127 .064 .096 1.975 .049 .071 .077 .073 DSMAN 1.438E-02 .040 .015 .357 .721 .014 .014 .013 DSDIS -.101 .047 -.088 -2.144 .032 -.115 -.084 -.080 ZCD2 -4.64E-02 .018 -.102 -2.613 .009 -.101 -.102 -.097 FGRO 6.262E-02 .018 .134 3.480 .001 .128 .136 .129 2 (Constant) 3.992 .083 48.292 .000 DDK .149 .062 .113 2.391 .017 .090 .094 .083 DFR -.167 .061 -.128 -2.728 .007 -.239 -.107 -.095 DGE 3.799E-02 .063 .029 .605 .545 .012 .024 .021 DNO 5.638E-02 .063 .043 .892 .373 .082 .035 .031 DRO -.153 .070 -.109 -2.174 .030 .046 -.086 -.075 DSP 9.072E-02 .062 .069 1.464 .144 .071 .058 .051 DSMAN 3.241E-02 .038 .033 .856 .392 .014 .034 .030 DSDIS -9.76E-02 .044 -.086 -2.212 .027 -.115 -.087 -.077 ZCD2 -7.67E-02 .018 -.168 -4.296 .000 -.101 -.167 -.149 FGRO 4.212E-02 .017 .090 2.479 .013 .128 .098 .086 FHRI 4.707E-02 .020 .101 2.308 .021 .247 .091 .080 FETH 4.436E-02 .024 .095 1.846 .065 .236 .073 .064 FPRA 5.927E-03 .021 .013 .286 .775 .082 .011 .010 FIMP .129 .020 .280 6.481 .000 .329 .248 .225 FDIV 3.258E-02 .018 .070 1.787 .074 .099 .070 .062 ZCM8 -6.99E-03 .017 -.018 -.414 .679 .127 -.016 -.014 a. Dependent Variable: AVD22M14

CM/UFHRD/03/05/18 13 Table 2 Correlation Matrix of study variables

Correlationsa

DDK DFR DGE DNO DRO DSP DSMAN DSDIS ZCD2 FGRO FHRI FETH FPRA FIMP FDIV ZCM8 AVD22M14 DDK Pearson Correlation 1.000 -.173 -.170 -.171 -.156 -.170 -.105 .042 -.059 .066 -.034 -.007 -.103 -.111 -.183 -.134 .090 Sig. (2-tailed) . .000 .000 .000 .000 .000 .007 .280 .134 .089 .386 .868 .008 .004 .000 .001 .020 DFR Pearson Correlation -.173 1.000 -.172 -.173 -.158 -.172 -.002 .101 -.037 .050 -.291 -.196 .048 -.174 .113 -.098 -.239 Sig. (2-tailed) .000 . .000 .000 .000 .000 .952 .010 .345 .205 .000 .000 .217 .000 .004 .012 .000 DGE Pearson Correlation -.170 -.172 1.000 -.170 -.155 -.169 .016 -.168 .256 -.060 -.010 .021 .057 .045 .022 -.025 .012 Sig. (2-tailed) .000 .000 . .000 .000 .000 .682 .000 .000 .126 .793 .589 .147 .251 .568 .519 .752 DNO Pearson Correlation -.171 -.173 -.170 1.000 -.156 -.170 -.069 -.032 .018 -.021 .094 .171 .045 .053 -.057 -.208 .082 Sig. (2-tailed) .000 .000 .000 . .000 .000 .077 .413 .652 .592 .016 .000 .254 .177 .144 .000 .035 DRO Pearson Correlation -.156 -.158 -.155 -.156 1.000 -.155 .050 -.046 -.072 .172 .279 .281 .089 .340 -.056 .344 .046 Sig. (2-tailed) .000 .000 .000 .000 . .000 .198 .234 .064 .000 .000 .000 .023 .000 .155 .000 .238 DSP Pearson Correlation -.170 -.172 -.169 -.170 -.155 1.000 .043 .045 -.093 -.069 .063 -.149 -.162 -.036 .150 .182 .071 Sig. (2-tailed) .000 .000 .000 .000 .000 . .266 .253 .017 .077 .108 .000 .000 .362 .000 .000 .069 DSMAN Pearson Correlation -.105 -.002 .016 -.069 .050 .043 1.000 -.368 .100 -.093 -.050 -.041 -.026 .013 -.036 .030 .014 Sig. (2-tailed) .007 .952 .682 .077 .198 .266 . .000 .010 .018 .201 .293 .499 .737 .358 .447 .718 DSDIS Pearson Correlation .042 .101 -.168 -.032 -.046 .045 -.368 1.000 -.001 .017 -.021 .001 -.011 -.051 .030 -.051 -.115 Sig. (2-tailed) .280 .010 .000 .413 .234 .253 .000 . .975 .672 .599 .972 .771 .195 .436 .196 .003 ZCD2 Pearson Correlation -.059 -.037 .256 .018 -.072 -.093 .100 -.001 1.000 -.044 .010 .192 .331 .096 .151 .017 -.101 Sig. (2-tailed) .134 .345 .000 .652 .064 .017 .010 .975 . .264 .789 .000 .000 .013 .000 .654 .010 FGRO Pearson Correlation .066 .050 -.060 -.021 .172 -.069 -.093 .017 -.044 1.000 .094 .151 .083 .119 .060 .108 .128 Sig. (2-tailed) .089 .205 .126 .592 .000 .077 .018 .672 .264 . .016 .000 .034 .002 .126 .006 .001 FHRI Pearson Correlation -.034 -.291 -.010 .094 .279 .063 -.050 -.021 .010 .094 1.000 .548 .253 .262 .038 .176 .247 Sig. (2-tailed) .386 .000 .793 .016 .000 .108 .201 .599 .789 .016 . .000 .000 .000 .326 .000 .000 FETH Pearson Correlation -.007 -.196 .021 .171 .281 -.149 -.041 .001 .192 .151 .548 1.000 .529 .386 .034 .154 .236 Sig. (2-tailed) .868 .000 .589 .000 .000 .000 .293 .972 .000 .000 .000 . .000 .000 .379 .000 .000 FPRA Pearson Correlation -.103 .048 .057 .045 .089 -.162 -.026 -.011 .331 .083 .253 .529 1.000 .244 .143 .069 .082 Sig. (2-tailed) .008 .217 .147 .254 .023 .000 .499 .771 .000 .034 .000 .000 . .000 .000 .075 .035 FIMP Pearson Correlation -.111 -.174 .045 .053 .340 -.036 .013 -.051 .096 .119 .262 .386 .244 1.000 .247 .419 .329 Sig. (2-tailed) .004 .000 .251 .177 .000 .362 .737 .195 .013 .002 .000 .000 .000 . .000 .000 .000 FDIV Pearson Correlation -.183 .113 .022 -.057 -.056 .150 -.036 .030 .151 .060 .038 .034 .143 .247 1.000 .280 .099 Sig. (2-tailed) .000 .004 .568 .144 .155 .000 .358 .436 .000 .126 .326 .379 .000 .000 . .000 .011 ZCM8 Pearson Correlation -.134 -.098 -.025 -.208 .344 .182 .030 -.051 .017 .108 .176 .154 .069 .419 .280 1.000 .127 Sig. (2-tailed) .001 .012 .519 .000 .000 .000 .447 .196 .654 .006 .000 .000 .075 .000 .000 . .001 AVD22M14 Pearson Correlation .090 -.239 .012 .082 .046 .071 .014 -.115 -.101 .128 .247 .236 .082 .329 .099 .127 1.000 Sig. (2-tailed) .020 .000 .752 .035 .238 .069 .718 .003 .010 .001 .000 .000 .035 .000 .011 .001 . a. Listwise N=657

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