HRM as a predictor of innovation

HRM as a predictor of innovation

Helen Shipton, Aston Business SchoolMichael A. West and Jeremy Dawson, Aston Business School and Centre for Economic Performance, London School of EconomicsKamal Birdi and Malcolm Patterson, University of SheffieldHuman Resource Management Journal, Vol 16, no 1, 2006, pages 3–27

There is growing evidence available to suggest that HR practice is an important predictor of organisational performance. In this article, we argue that HR practices also have the potential to promote organisational innovation. We describe a longitudinal study of 22 UK manufacturing companies and examine the relationship between such practices and product and technological innovation. Results reveal that training, induction, team working, appraisal and exploratory learning focus are all predictors of innovation. Contingent reward, applied in conjunction with an exploratory learning focus, is positively associated with innovation in technical systems. Furthermore, training, appraisal and induction, combined with exploratory learning focus, explain variation between companies in product and technological innovation above and beyond the main effects observed.Contact: Helen Shipton, Work and Organizational Psychology Group, Aston Business School, Birmingham B4 7ET. Email: [email protected]

With increasing worldwide competition and ever more pressing environmental turbulence, organisations’ ability to innovate is seen more and more as one key factor to ensure their success (Cohen and Levinthal, 1990; Leonard-

Barton, 1995; Brown and Eisenhardt, 1997; McGrath, 2001; Tsai, 2001). The logic is that, through introducing new products and new technology, organisations are able to diversify, adapt and reinvent themselves (Shoonhoven et al., 1990). While researchers have accumulated a lot of knowledge about the relationship between HR activity and organisational performance measured in financial terms (Dyer and Reeves, 1995; Huselid, 1995; Macduffie, 1995; Bae and Lawler, 2000; Hutchinson et al., 2003), our knowledge about the extent to which HRM promotes organisational innovation is still relatively scarce.

Innovation is ‘the intentional introduction and application within an organisation of ideas, processes, products or procedures, new to the unit of adoption, designed to significantly benefit the organisation or wider society’ (West and Farr, 1990). According to Roper and Love (2004), innovation is a continuous, evolutionary process, involving the application and re-application of existing as well as new scientific knowledge. Nonetheless, companies find it difficult to innovate on a sustained basis (Department of Trade and Industry, 2000; Katila and Ahuja, 2002). Some scholars suggest that innovation can be achieved by ensuring that all members of the organisation are both receptive to – and have the necessary skills to support – change (Paton and

HUMAN RESOURCE MANAGEMENT JOURNAL, VOL 16 NO 1, 2006 �

© 2006 The Authors.

Journal compilation © 2006 Blackwell Publishing Ltd., 9600 Garsington Road, Oxford, OX4

2DQ, UK and �50 Main St, Malden, MA, 02148, USA.


4 HUMAN RESOURCE MANAGEMENT JOURNAL, VOL 16 NO 1, 2006


Journal compilation © 2006 Blackwell Publishing Ltd.

McCalman, 2000). The argument is that change and innovation frequently fall outside the remit of technical specialists such as R&D professionals and involve those who have most knowledge of the task and the technology required to ensure its effective completion. Thus employees at all levels of the business play an important role in either putting forward suggestions for improvements themselves or supporting others as they do so. HR practitioners are faced with the challenge of developing and implementing the practices necessary to facilitate this process (Laursen and Foss, 2003). There is a research imperative to identify what specific HR practices, or combination of practices, are associated with relatively high innovation at organisational level.

Research investigating relationships between HRM and the financial aspects of performance provides a useful reference point. Two themes are relevant. The first suggests that specific HR practices promote performance, e.g. human resource planning (Koch and McGrath 1996), profit sharing and results-oriented appraisals (Delery and Doty, 1996), selectivity in staffing, training and incentive compensation (Delaney and Huselid, 1996). The second holds that it is more the combined effect of interrelated practices than any one specific variable (Huselid et al., 1997; Ichniowski et al., 1997; Bae and Lawler, 2000; Guthrie, 2001). While there is as yet no commonly agreed frame of reference about exactly what constitutes an HR ‘system’ (Wood, 1999), many scholars agree that a typical system encompasses training, appraisal/performance management and sophisticated selection and socialisation as well as practices designed to promote participation and involvement, such as team-work and reward (Dyer and Reeves, 1995; Huselid, 1995; Macduffie, 1995; Bae and Lawler, 2000; Hutchinson et al., 2003). The importance of developing a ‘learning’ orientation is also frequently endorsed within the literature (cf. McKenzie and van Winkelen, 2004).

Studies investigating HR/innovation relationships have pursued a similar line. Shipton et al. (2005), in a longitudinal study of 30 manufacturing organisations, showed that a combination of sophisticated HR practices predicted organisational innovation to the extent that they influenced each stage of the organisational learning cycle (defined as the creation, sharing and implementation of knowledge). Laursen and Foss (2003) concluded that organisations should adopt ‘high performance’ HR practices, arguing that practices designed to elicit decentralisation facilitate problem-solving at a local level, thereby enabling organisations to draw upon the latent ‘tacit’ knowledge of those closest to the task in hand. They further suggested that knowledge dissemination is enhanced where organisations implement team-based working and where they are committed to practices such as job rotation and project work.1

Building on this argument, we suggest that innovation is a two-stage process: the first stage involving the generation of a creative idea and the second involving its implementation (West, 2002). The first stage involves ‘exploration’ – employees taking risks, experimenting and being flexible in their quest to discover new and different phenomena of interest – whilst to achieve the second stage employees need to work within an environment where ‘exploitation’ is valued, and where they are encouraged to follow prescribed rules to enhance efficiency (cf. March, 1991).

In this study, we consider the role that HRM can play in managing these two competing agendas. According to our argument, HR practitioners have two main responsibilities. First, they establish the framework whereby employees are clear

Helen Shipton, Michael A. West, Jeremy Dawson, Kamal Birdi and Malcolm Patterson

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about their tasks and have the basic skills necessary to perform effectively (Boxall, 1996; Purcell, 1999). A number of HR practices are important: appraisal and performance management systems, for example, clarify where responsibilities lie and offer support to individuals as they acquire the skills necessary to work effectively (Armstrong and Baron, 1998; Bach, 2000). Second, HR practitioners instigate the mechanisms necessary to promote an exploratory learning focus (Scarbrough and Swan, 1999). Through project working, job rotation and visits to parties external to the organisation, employees can achieve the attitudinal change required to question and challenge existing ways of operating (Cross et al., 2001). Broadly speaking, the first approach involves developing the knowledge, skills and attitudes required to promote performance, whilst the second represents a concern with exploration, with identifying new and different opportunities for the future. Our argument holds that each set of practices will directly promote organisational innovation, and that the effect will be amplified where mechanisms designed to promote exploratory focus are used in conjunction with those intended to develop knowledge, skills and attitudes.

HR PRACTICES PROMOTING EXPLORATORY LEARNING FOCUS

Exploratory learning involves generating new ideas through actively searching for alternative viewpoints and perspectives (McGrath, 2001; Danneels, 2002). This happens in part as employees engage with parties external to the organisation (Cohen and Levinthal, 1990) and in part as knowledge is exchanged within the organisation (Kim, 1993; Dixon, 1994). Exposure to different experiences and points of view makes individuals more willing to examine their own mental models and to make any necessary adjustments, thereby avoiding the tendency to become locked in to limited perceptual frameworks (Tushman and Anderson, 1986; Henderson, 1991). For example, engagement with customers and suppliers can lead employees to question the perceptual model that they hold and to embrace opportunities for change (Thompke and von Hippel, 2002; McKenzie and van Winkelen, 2004). Similarly, intra-organisational secondments may facilitate the transfer of knowledge internally and enrich individuals’ perceptions of the challenges faced by other organisational members (Amabile et al., 1996; Tsai, 2001; West, 2002).

Promoting ‘on the job’ development may be a more effective strategy for this type of learning than endorsing external training events (Stern and Sommerlad, 1999). Through experiential learning, employees gain knowledge that is relevant for the tasks for which they are responsible. They are also likely to anticipate knowledge transfer issues, so the learning acquired has the potential to be applied. This process is facilitated where organisations have developed systems for managing the transfer of knowledge (Kogut and Zander, 1992; Nonaka, 1995). Such systems formally legitimise the value of learning from others within the organisation and, where operated effectively, encourage disparate groups to share their learning.

Hypothesis 1: HR practices that promote exploratory learning will predict organisational innovation.





HR PRACTICES TO DEVELOP KNOWLEDGE, SKILLS AND ATTITUDES

We argued above that HR practitioners establish the framework required to facilitate the ‘exploitation’ of existing knowledge, i.e. whereby employees have the knowledge, skills and attitudes required to perform effectively. This involves providing guidance and support to employees about what behaviours are valued, recognised and rewarded. Given that a typical HR ‘system’ encompasses training, appraisal/performance management and sophisticated socialisation as well as practices designed to promote participation and involvement, such as team work and reward (Dyer and Reeves, 1995; Huselid, 1995; Macduffie, 1995; Bae and Lawler, 2000; Hutchinson et al., 2003), we focus upon these variables.

Induction

There is some debate surrounding the extent to which induction activities (initiating people into the organisation and providing them with knowledge about goals, processes and norms) promote organisational innovation; Simon (1991), for example, argued that early socialisation inhibits creativity and develops a mindset of compliance that may be detrimental. Such perspectives are in line with the ‘attraction, selection and attrition’ model proposed by Schneider et al. (1995). They suggested that organisations recruit and retain only individuals who exhibit characteristics similar to those already employed, holding that new employees in particular are under pressure to conform rather than to challenge, thereby promoting ‘exploitation’ to the detriment of exploration.

On the other hand, induction enables people to operate effectively in the organisation and to recognise performance gaps. This in turn is likely to enable innovation since people will try to close the gaps between current and desired performance, often innovating in order to achieve this closure (King, 1992). Furthermore, through being aware of performance gaps, individuals may look for opportunities to acquire the skills necessary to contribute to organisational innovation. They may, for example, need to improve their capacity to articulate ideas and to work constructively with others, thereby facilitating knowledge dissemination. An effective induction process should put in place a developmental plan to support the acquisition of such skills (Harrison and Kessels, 2004).

Hypothesis 2: Sophisticated and extensive induction procedures will predict organisational innovation.

Appraisal

We argue that the relationship between appraisal and organisational innovation is likely to be positive, although we are aware of little research that addresses this point. A meta-analysis conducted by Guzzo and Bondy (1983) found that appraisal promotes productivity, quality and cost-saving initiatives. Some studies suggest that feedback given during the appraisal process leads to a recognition of the gaps between performance and targets (Guzzo et al., 1985), thereby motivating employees to work innovatively. Through appraisal, employees gain a clearer view of how their tasks ‘fit’ with the organisational-wide agenda (Bach, 2000). Furthermore, appraisal, conducted


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in a way likely to foster learning and growth, may help employees to acquire the confidence necessary to use opportunities presented for higher-level learning (Gratton, 1997).

Hypothesis 3: Organisations which have in place an appraisal scheme will exhibit relatively high organisational innovation.

Training

Formal, structured training is no longer regarded as a universal panacea, in part because two streams of research – the situated learning school (Brown and Duguid, 1991; Lave and Wenger, 1991) and the ‘experiential’ learning perspective (Kolb, 1984; Mumford, 1997; Stern and Sommerlad, 1999) – have highlighted a number of deficiencies. Training may be implemented by people who do not fully appreciate the challenges faced by individuals as they conduct their day-to-day work (Brown and Duguid, 1991). Furthermore, learning transfer problems are endemic (Bramley, 1996), whilst training designed to achieve specific organisational objectives is unlikely to promote the creativity associated with exploratory learning (Levinthal and March, 1993).

Training nonetheless tends to be associated with better organisational performance (Tharenou and Burke, 2002). Training facilitates the development of employees’ capabilities (Lado and Wilson, 1994) and ensures that individuals have the basic skills to perform their roles effectively (Keep, 1999). These attributes are important where there is a focus on fostering innovation, because individuals are unlikely to assess their tasks critically and make constructive proposals for change where they are preoccupied with day-to-day survival at work (Cohen and Levinthal, 1990). Highly planned and organised training is important to promote employee skills, and should be backed up by appropriate investment (Keep, 1999; Ashton and Felstead, 2001).

Hypothesis 4: Extensive training will predict organisational innovation.

Contingent reward

Contingent pay represents that proportion of total remuneration paid where specific performance stipulations have been fulfilled. The term encompasses ‘pay for performance’ schemes at individual and team level, and also organisation-wide schemes, designed to enable the workforce to share in the success of the enterprise. Some scholars argue that ‘pay for performance’ schemes fail to enhance creativity because they undermine intrinsic motivation (Amabile, 1988; Kohn, 1993; Deci et al., 1999). Another related argument suggests that where people feel controlled by another party (i.e. whichever person or group is responsible for determining how dispersed pay is apportioned), they will be relatively less likely to look for new and creative solutions to problems, preferring instead to retain tried and trusted methods of working (Pfeffer, 1998; Thorpe, 2000).

On the other hand, emerging research evidence suggests that it is possible to design reward systems which do not displace attention from the tasks towards the reward (Eisenberger and Cameron, 1996) and that external rewards can encourage both creativity and innovation implementation (Abbey and Dickson, 1983; Eisenberger and Cameron, 1996). In a series of studies, Amabile and colleagues showed that reward perceived as a bonus, a confirmation of one’s competence, or a means of enabling one





to do better and more interesting work in the future can stimulate creativity (Amabile et al., 1996). There is also a body of work examining ‘gainsharing’ as a device for stimulating productivity and innovation that suggests the value of reward for innovation (Cotton, 1996; Heller et al., 1998). Gainsharing is the term used to describe systems used to involve staff in developing new and more effective means of production. Evaluations of ‘gainsharing’ programmes suggest they are effective in increasing innovation, productivity and employee involvement (Cotton, 1996).

Hypothesis 5: Contingent reward will predict organisational innovation.

Team working

Team working will promote organisational performance and innovation to the extent that members are engaged in intrinsically motivating tasks within a supportive organisational context (West et al., 2004). We argue that organisations committed to team working will achieve innovation to a greater extent than those adopting alternative structural arrangements. Teams (operating effectively) present a framework of support for individuals as they deal with the emotionally challenging aspects of change (West et al., 2003). Teams also enable individuals to share the tacit knowledge exhibited by more experienced members (Brown and Duguid, 1991). For example, through working closely with others, uninitiated individuals are encouraged to observe, ask questions, receive feedback and thus achieve optimum performance. Furthermore, teams offer opportunities to draw upon diverse knowledge and skills (de Dreu and de Vries, 1997). Where such diversity can be effectively focused and channelled, there is scope for higher levels of creativity and innovation than would be the case where individuals operate independently (Tjosvold, 1998).

Hypothesis 6: The extent of team working will predict organisational innovation.

A synergistic effect

To reiterate, in our view, there is conceptually a distinction between mechanisms designed to promote exploratory learning and those intended to exploit existing skills. We argue that training, for example, does not necessarily promote the exposure to new and different experiences to which we make reference in our depiction of ‘exploratory learning’. Training interventions, team working and the other HR practices that we consider in this study will impact upon organisational innovation to a greater extent where they are implemented in conjunction with practices designed to promote exploratory learning.

Hypothesis 7: There will be an interaction between HRM practices designed to promote exploratory learning and those intended to develop skills, knowledge and attitudes, such that combinations of these practices will predict innovation above and beyond their direct effects.

METHOD

Sample and data collection

The data were drawn from a data set developed in a larger study of 111 companies conducted between 1992 and 1999 (West et al., 1999). Manufacturing companies in the UK were identified from sector databases. In addition, a number of companies were





identified by local Chambers of Commerce and Trade Associations. This longitudinal study examines market environment, organisational characteristics and managerial practices. Economic performance data were gathered annually (retrospectively to 1990). Senior managers in these companies were interviewed on site. Areas covered in the interview include market environment, organisational structure, competitive strategies, production technology, work design, quality practices, HRM, training and research and development.

Here we report relationships between data gathered in managerial interviews in 22 companies (1996) and data from innovation surveys of the same companies in 1995 and 1997. The 22 companies were selected because data were collected for HR practices as well as innovation. The average number of employees in these companies was 260; the smallest company had 70 and the largest 900 employees. Organisations were drawn from three main industrial groups: electronics and communications, food and drink, and mechanical engineering. These manufacturing sectors were chosen because they contained the largest numbers of UK manufacturing companies and because they employ the largest number of people in manufacturing.

This was a longitudinal study, which involves taking measurements of HR practices, learning mechanisms and innovation at specific points in time. Three time points are involved in this exercise. At Time 1, measurements were taken of innovation and of size and profitability in order to allow us to control for the effect of these variables on the outcome variable (innovation at Time 3). At Time 2, we measured HR practices and learning mechanisms in the ways described below and at Time 3 the final measurement was made of innovation. There was approximately one year between each measurement point. Using a longitudinal design enabled examination of the direction of any relationships between mechanisms designed to promote exploratory learning, people management practices such as appraisal, induction and training, and innovation.

The sampling strategy required that companies were predominantly single site and single product operations with between 70 and 1,000 employees. These criteria were adopted for two important methodological reasons. To characterise managerial practices within companies using single dimensions requires that the companies are relatively homogeneous, so that such aggregation and single dimension categorisation is ecologically sensible. The diversity of product types within organisations must be limited so that technology, work design and production processes are relatively uniform and can also be sensibly described at the firm level.

The interviews

Interviews in the first wave of data collection were carried out with senior managers in each of the organisations. Companies were briefed before the researchers’ visit on what areas the interview schedule covered and were asked to determine which senior managers were best placed to answer questions in each of the interview schedule areas. Interviews were conducted with CEOs (for questions on organisational size and background) and Production Directors and/or HR specialists (for issues surrounding HRM and learning practices). The interviews were used to complete identical questionnaire items at two separate points in time: 1993 and 1995. Interviews always took place on site and in all cases coincided with a tour of the production areas by the researchers. Interviewers were all qualified industrial/organisational psychologists,





who had received a minimum of two weeks’ training in administering the interview schedule. Table 1 summarises the stages involved in the collection of data.

Below we explain how the concepts referred to in the hypotheses were operationalised.

Independent variables

Mechanisms designed to promote exploratory learning Managers were asked to describe the practices employed to promote exploratory learning. A total of eight binary questions elicited this information.

1. Are visits arranged to external suppliers or customers for employees who would not normally have such contact as part of their normal job responsibilities?

2. Are employees working on the shopfloor in one department ever seconded to another department so that they can learn more about the processes and procedures in that area?

3. Are employees working in management in one department ever seconded to another department so that they can learn more about the processes and procedures in that area?

4. Does the company support learning/training that is not work related (e.g. basic skills, hobbies, such as through government-sponsored employee development schemes or employee-led development, or other such employee development skills)?

5. Is training available to management that is work related but not directly necessary for the individual’s current job (e.g. learning about processes that occur in other parts of the factory, courses to increase computer skills)?

Data gathered Purpose Respondent Method of Date data collection

Prior innovation Control variables Technical Postal survey Time 1 – 1993Profitability experts StructuredOrganisational CEOs interviewssize

HR practices: Independent HR Structured Time 2 – 1995training, variables Directors/ interviewsappraisal, Managersinduction, teamworking,contingent rewardand exploratorylearning

Product Dependent Technical Postal survey Time 3 – 1996innovation and variables expertsinnovation intechnical systems

TABLE 1 The stages of data collection





6. Is training available to shopfloor employees that is work related but not directly necessary for the individual’s current job (e.g. learning about processes that occur in other parts of the factory, courses to increase computer skills)?

7. Do you have any procedures for recording solutions to problems or best practice?8. Do you have any mechanisms by which this knowledge (problem solutions or best

practice) is transferred to other areas of the business?

The score for the existence of mechanisms designed to promote exploratory learning was the mean of affirmative answers to these questions across all 22 organisations in the study. This mean was calculated as long as answers to at least six of the eight items were present. Thus scores ranged from 0, where all the responses were ‘no’, to 1, where all the responses were ‘yes’. Internal reliability was satisfactory (Cronbach’s alpha was 0.77).

HR practices designed to exploit existing knowledge Managers were asked about approaches adopted towards induction, training, appraisal, contingent reward and team working. The training variable was developed to reflect the extent to which training was designed to achieve a ‘fit’ between identified needs at organisational and individual level and employee capabilities. Managers were asked whether there was an overall training strategy (giving a yes/no answer). They responded to questions asking them to detail current and recent approaches to training in the organisation (on a five-point scale ranging from 1, ‘very reactive, responding as demands arise’, through to 5, ‘highly planned and organised’). They were asked whether the current annual training budget represented an increase or decrease from the previous year (on a five-point scale, with responses ranging from ‘a big increase’ to ‘a big decrease’). Managers further responded to questions detailing how well the training budget met company training needs (responses were coded on a five-point scale, from ‘wholly inadequate’ to ‘more than enough’). A mean was formulated of these items (Cronbach’s alpha = 0.88) and this was the variable for training used in the study.

The induction scale was similarly intended to explore whether or not organisations were committed to developing employee ‘fit’ with existing goals and values. Managers were asked whether a formal induction programme existed, whether the scheme involved communicating company values to new employees and whether there was any formal means of evaluating whether induction had been carried out as recommended. Responses to these questions were coded on a binary scale. A mean score was formulated to reflect responses to these questions (Cronbach’s alpha = 0.80).

The score for appraisal was derived simply by asking the relevant authority – normally the HR Manager or Director – whether or not a formal appraisal scheme was in existence. Responses to this question were binary. This is a straightforward measure, primarily because we argue that appraisal, on the whole, is concerned more with aligning employee and organisational goals than with exposing employees to new and different perspectives. To consider the relative sophistication of the appraisal process was not a specific purpose of the study.

Contingent reward was measured by asking HR managers at the plants in the study ‘Do you offer any of the following incentive schemes?’ The questionnaire schedule then considers the following financial arrangements: employee share options, profit sharing, group/company bonus schemes, team bonus, individual bonus and merit/





performance related pay. This binary scale was posed for four categories of staff: management, professional, clerical and manual. We developed a scale to apply across all four categories of staff (alpha = 0.72).

We asked production managers about the extent of team working. Respondents were first asked to detail ‘what percentage of management and administrative staff work in teams’ and then ‘what percentage of production staff work in teams’. They were specifically asked to ‘refer only to stable teams’. These items were combined to form one scale with reasonable reliability (Cronbach’s alpha = 0.66).

Dependent variables

Information about product and technological innovation was gathered via a postal questionnaire survey sent to senior managers in each participating organisation. Two surveys – one in 1993 and the other in 1996 – were conducted in addition to the interview surveys detailed above. The questionnaire was labelled as a ‘change’ survey rather than an ‘innovation’ survey as the term ‘innovation’ is likely to introduce social desirability bias. It consisted of open questions and rating scales in relation to new or adapted products and technological innovation (innovations in production technology and production techniques/procedures).

Product innovation This measure represents researchers’ depiction of the extent and quality of product innovation on a 1–7 scale. Respondents gave estimates of the number of entirely new and adapted products developed in the last two years; the percentage of production workers involved in making the new products; current sales turnover accounted for by the new products; and the extent to which the new products were new and different for the organisation concerned.

Innovation in technical systems This measure represents researchers’ depiction of the extent to which organisations were committed to innovating across the range of technical (as opposed to administrative) aspects of the business. The measure encompassed product innovation as well as innovation in production technology and production processes. Account was taken of responses to questions surrounding the introduction of new machines or systems such as single cycle automatics, CNC and robots. Respondents were also asked about changes in production techniques/procedures, which focused on such changes as the introduction of scheduling and planning systems (e.g. MRP II), just-in-time management or total quality management. Respondents listed the three most significant changes in these categories introduced over the previous two years. They also gave estimates of the magnitude and novelty of the changes for their organisation on a five-point scale, ranging from ‘very small’ (1), to ‘moderate’ (3) and ‘very big’ (5). Further questions asked, for example, ‘what percentage of your production workforce had to be retrained to use this different technology?’ Responses were captured on a seven-point scale.

Researchers rated responses to these questions. They were all at least Masters level organisational psychologists with considerable experience of site visits, and interviews with senior management, in UK manufacturing companies. Each section was given an innovation rating on a seven-point scale from 1, ‘not at all innovative’, to 7, ‘very innovative’. These were based on the types of change introduced, their magnitude and novelty and the impact on the workforce and the manufacturing process. An


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overall innovation rating was given by raters to each company; researchers also gave ratings for innovation in technical systems, as described above.

The innovation questionnaire was piloted in six companies and, following minor changes to terminology, was sent out to the Managing Director and the Head of Production of each of the companies. Multiple copies were sent in order to increase the response rate and for the purpose of checking reliability of responses. Eighty-one out of 111 companies returned completed questionnaires. There were no differences between the respondents and non-respondents in parameters such as size, productivity, profitability and HR practices. Twenty-two of these companies were used as the basis for this study, since these companies also provided data on organisational learning and HR practices. Again, there were no differences between these companies and the wider sample on parameters such as size, productivity, profitability and HR practices.

Reliability and validity of innovation measures To check for differences in innovation ratings by respondents between those companies where the respondent was or was not the Managing Director, analyses of variance were run on all innovation measures, with respondent position as the independent variable, controlling for organisation size. There were no significant differences. Concurrent validity was assessed by correlating innovation ratings with employee ratings of the climate for innovation in their companies. This was based on a climate survey administered in 36 of the original 111 companies in the wider study (see West et al., 1999). The correlation between innovation in products (ratings made by researchers based on managers’ responses to the questionnaire) and employee ratings of the climate for innovation in their organisations was 0.40 (p < 0.01). There was also a strong relationship between employee ratings of climate and managerial reports of changes in production technology (r = 0.45, p < 0.001). Also, ten follow-up site visits and interviews were used to validate information from the postal questionnaires. Over 90 per cent of innovations noted in the postal questionnaires were subsequently observed on site. Concurrent validity is therefore acceptable.

To assess the reliability of the ratings of innovation, 40 questionnaires from the original 111 organisations were rated by three researchers. All questionnaires were assessed initially by rater A. For rater A and rater B, Kendall’s coefficient of concordance was 0.86 (p < 0.001). For raters A and C the coefficient was 0.8 (p < 0.001). Where more than one manager completed questionnaires in firms (in 27 cases), inter-rater agreement was calculated across the questionnaire items. The average reliability was 0.94.

Control variables

Size Organisational size was represented by counting the number of full-time equivalent employees in each organisation. These data were log transformed in all analyses to normalise the distribution.

Profitability Three main sources of information were used to determine company performance: company accounts, management accounts and the Central Statistical Office database. Profitability was measured as profits before tax, deflated by the producer price index of the industry in which the firm belonged and normalised on





firm employment to control for size. For this analysis (though others are also taken) real profits per employee were averaged for the period 1991–3. These formed our control variables for the Time 1 aspect of the study (see Table 1).

Prior innovation The research design allowed us to measure product innovation at Time 1 in the ways described above, and to use this measurement as an additional control variable for the dependent variable (product innovation, or innovation in technical systems, at Time 3).

Analytical strategy

Our approach was to enter the two groups of HR variables – those designed to promote exploratory learning and those designed to exploit existing knowledge – separately into a regression analysis. We then entered both sets of HR variables together to determine which accounted for more of the variation in innovation. For the final step, we calculated the effect of any interaction between the two groups of HR variables on product and technological innovation.

Since the sample size was small, it was desirable to keep the number of variables in the regressions to a minimum. It was found, by preliminary analysis, that size and profitability had no effect on the outcome variables. However, it remained possible that these variables would interact with the other independent variables, so the analyses were run twice: once with organisational size, prior profitability and prior innovation as control variables; and once with prior innovation as the sole control variable.

RESULTS

Means, standard deviations and intercorrelations between the variables are shown in Table 2. It can be seen that there are statistically significant correlations between both innovation variables and five hypothesised predictors (exploratory learning focus, training, appraisal, induction and extent of team working), except for between appraisal and innovation in technical systems where the correlation (r = 0.39) is not significant. There is no significant correlation between contingent reward and either type of innovation.

Table 3 shows the results of regression analyses to test hypotheses 1, 2, 3, 4 and 5 with just one control variable (prior innovation). The results when all three control variables were used were very similar – the increments in R2 due to each variable were similar, and although the adjusted R2 (which adjusts for the number of predictors relative to the sample size) was substantially lower when more control variables were used, the increments for each step were almost identical to those for the unadjusted R2. This is important, as it suggests the results with only one control variable are reliable, which makes regression using a small sample more justifiable. Therefore only these analyses are reported here.

The variable measuring mechanisms designed to promote exploratory learning accounted for 39 per cent (p < 0.01) of the variance in product innovation and 34 per cent (p < 0.01) of the variance in innovation in technical systems. Hypothesis 1, that organisations that develop practices to promote exploratory learning have relatively high levels of product innovation at a later point in time, was supported.





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9 0

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0

.03

0.57

**

0.57

**

0.52

* 0.

61*

0.23

11.

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1.63

1.38

0

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0.2

7 0

.25

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6 0.

40

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0.

03

0.47

* 0.

38

0.29

12.

Ext

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4

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3

5.3%

0

.13

0.1

2 0

.30

0.1

8 0.

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0.48

***

0.27

* 0.

44*

0.20

0.

35*

0.07

a Alt

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h th

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num

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; **

p <

0.01

; ***

p <

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01.

TAB

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2 M

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, sta

ndar

d de

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ions

and

cor

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Training explained 40 per cent (p < 0.01) of the variance in product innovation, and 51 per cent (p < 0.001) of the variance in innovation in technical systems. Induction accounted for 16 per cent (p < 0.05) of the variance in product innovation, and 31 per cent (p < 0.01) of the variance in innovation in technical systems. These analyses provide support for Hypothesis 2.

The regression analyses further reveal that appraisal explains 35 per cent (p < 0.05) of the variance in product innovation and 20 per cent (p < 0.05) of the variance in innovation in technical systems, thus supporting Hypothesis 3. Extent of team working explains 48 per cent (p < 0.05) of the variance in product innovation and 32 per cent (p < 0.01) of the variance in innovation in technical systems, providing support for Hypothesis 5.

In order to analyse whether there was an interaction effect between the sets of HR practices – those intended to promote exploratory learning and those designed to exploit existing knowledge – they were entered jointly in the regression analysis, together with their multiplicative interaction term. The results are presented in Table 4.

There were statistically significant interaction effects between exploratory learning focus and appraisal when predicting product innovation but not innovation in technical systems, and between exploratory learning and both training and induction when predicting innovation in technical systems only. Furthermore, the interaction between contingent pay and exploratory learning explains 45 per cent of the variance for innovation in technical systems. These results provide partial support for Hypothesis 7, which proposed that there would be an interaction effect between exploratory learning and mechanisms designed to promote existing knowledge (training, induction and appraisal) and innovation. The interaction effects between exploratory learning and appraisal, and between exploratory learning and training, are shown graphically in Figures 1 and 2. The results for induction are depicted in Figure 3.

Dependent variable Innovation – products Innovation – technical systems

b R2 Adjusted R2 b R2 Adjusted R2

Prior innovation 0.44* 0.19 0.15 0.31 0.10 0.05 (control)1. Exploratory learning 0.52** 0.44 0.39 0.58** 0.40 0.342. Training 0.53** 0.45 0.40 0.69*** 0.56 0.513. Appraisal 0.47* 0.41 0.35 0.43* 0.28 0.204. Induction 0.46* 0.35 0.28 0.56** 0.41 0.355. Contingent pay 0.19 0.29 0.21 0.11 0.11 0.056. Extent of team 0.34* 0.37 0.33 0.50** 0.32 0.27 working

Note: Independent variables (except for controls) were entered in separate regression analyses.* p < 0.05; ** p < 0.01; *** p < 0.001.

TABLE 3 Results of regression analyses showing effects of exploratory learning, training, appraisal, induction, contingent pay and team working on innovation





Dependent variable Innovation – products Innovation – technical systems

b R2 Adjusted R2 b R2 Adjusted R2

Prior innovation 0.44* 0.19 0.15 0.31 0.10 0.051. Exploratory learning 0.52** 0.44 0.39 0.58** 0.40 0.34 Appraisal 0.38* 0.58 0.51 0.32 0.50 0.42 Interaction 0.50** 0.69 0.69 0.28 0.56 0.462. Exploratory learning 0.52** 0.44 0.39 0.58** 0.40 0.34 Training 0.35 0.52 0.44 0.54** 0.59 0.53 Interaction 0.32 0.60 0.51 0.38* 0.70 0.633. Exploratory learning 0.52** 0.44 0.39 0.58** 0.40 0.34 Induction 0.25 0.48 0.39 0.37 0.50 0.42 Interaction 0.36 0.57 0.47 0.40* 0.61 0.524. Exploratory learning 0.54* 0.43 0.36 0.60** 0.37 0.29 Contingent reward 0.30 0.55 0.46 -0.01 0.38 0.25 Interaction 0.19 0.58 0.46 0.50* 0.57 0.455. Exploratory learning 0.53* 0.52 0.40 0.57** 0.41 0.27 Extent of team working 0.38 0.61 0.48 0.33 0.48 0.32 Interaction 0.27 0.66 0.52 0.34 0.57 0.39

* p < 0.05; ** p < 0.01; *** p < 0.001.

TABLE 4 Results of regression analyses showing moderating effects of HR variables on the exploratory learning–innovation relationship

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Low Exploratory learning High Exploratory learning

Exploratory learning

Inno

vati

on in

Pro

duct

s

No formal appraisalFormal appraisal

FIGURE 1 Appraisal, exploratory learning and innovation in products

Figure 1 shows that, when there is a high exploratory learning focus, there is a much stronger relationship between the presence of a formal appraisal system and product innovation than when exploratory learning is low. This supports the

(Note: Low exploratory learning is one standard deviation below the mean value; high exploratory learning is one standard deviation above the mean value.)





1

1. 5

2

2. 5

3

3. 5

4

4. 5

5



Inn

ovat

ion

in T

ech

nic

al S

yste

ms

Low Training

High Training

FIGURE 2 Training, exploratory learning and innovation in technical systems


interpretation that a combination of exploratory learning and skill development may be a potent cocktail for encouraging innovation.

Figure 2 shows that, when there is high exploratory learning in organisations, there is a much stronger relationship between the sophistication and extensiveness of training in organisations than when exploratory learning is low. This supports again the interpretation that a combination of exploratory learning and skill development may be potent in encouraging innovation. Whilst this was not the subject of a formal hypothesis, it is apparent upon scrutiny of the results that high exploratory learning in combination with weak approaches to training seems a worse combination (in terms of innovation in technical systems) than low exploratory learning and weak approaches to training.

Figure 3 shows that, when there is a high exploratory learning focus, there is a much stronger relationship between the sophistication and extensiveness of induction practices and product innovation than when exploratory learning is low. Moreover, high exploratory learning with poor induction is associated with lower levels of product innovation than when there are few mechanisms designed to promote exploratory learning and induction is poor. Again, this is a counter-intuitive finding which was not the subject of a formal hypothesis.

Finally, there is a significant interaction effect for innovation in technical systems when we combine scores for contingent reward with HR practices promoting an exploratory learning focus. The interaction variable accounts for 45 per cent of the variance for this type of innovation (p < 0.05). This significant relationship was not





observed for product innovation. Thus we present some, but not complete, support for this aspect of our final hypothesis.

Table 5 summarises the main results of the study.

DISCUSSION

Scholars have for many years been preoccupied with identifying what HR practices are associated with various dimensions of organisational performance. Empirical studies suggest that not only are specific HR practices associated with effectiveness (Delaney and Huselid, 1996; Delery and Doty, 1996; Koch and McGrath, 1996), but that HR ‘systems’ encompassing a combination of practices may have a stronger effect than any one variable (Huselid et al., 1997; Ichniowski et al., 1997; Bae and Lawler, 2000). Few studies have explored the relationship between HRM and organisational innovation (see Shipton et al., 2005), although this theme represents an important perspective to take into account where organisations are seeking to respond proactively to the challenges presented by the external environment (Shoonhoven et al., 1990).

Results from this study suggest that two groups of HR mechanisms are likely to enhance innovation in work organisations. Those designed to promote exploratory learning and those intended to exploit existing knowledge (training, induction, appraisal, contingent pay and team working) are related significantly to innovation in products and technical systems. Contingent reward has no direct effect upon either type of innovation, but a significant effect becomes apparent when we enter this variable into a regression together with exploratory learning. Similarly, training, induction and appraisal, combined with exploratory learning, have a more powerful effect upon the dependent variables in combination than where they are applied

1

1. 5

2

2. 5

3

3. 5

4

4. 5

5



Inn

ovat

ion

in T

ech

nic

al S

yste

ms

Low Induction

High Induction

FIGURE 3 Induction, exploratory learning and innovation in technical systems






separately. This applies for appraisal combined with exploratory learning where we focus upon product innovation. The effect is apparent for innovation in technical systems where training is combined with exploratory learning, and for induction combined with exploratory learning. Furthermore, our measure of contingent reward – whilst not significant when entered separately for either type of innovation – was significantly and positively related to innovation in technical systems when combined with our measure of exploratory learning. There was no significant interaction effect, however, between the extent of team working and exploratory learning for either type of innovation considered in the study.

Why does the combined effect of exploratory learning, together with the other HR variables considered in the study, not apply to both types of innovation? We suggested earlier that change and innovation frequently fall outside the remit of technical specialists and involve those who have most knowledge of the tasks and technology required for their successful completion. There is thus an imperative to take steps to ensure that all members of the organisation have the necessary skills and motivation to support change (Paton and McCalman, 2000). Our results suggest that employees may exert a stronger influence upon innovation in technical systems than upon product innovation. This may be because shopfloor workers have a deeper knowledge of the work systems and the technology that they use than about potential new

Hypothesis Supported1. HRM practices that promote Yes – for product innovation and exploratory learning will predict innovation in technical systems organisational innovation

2. Sophisticated and extensive induction Yes – for product innovation and procedures will predict organisational innovation in technical systems innovation

3. Organisations which have in place an Yes – for product innovation and appraisal scheme will exhibit relatively innovation in technical systems high organisational innovation

4. Extensive training will predict Yes – for product innovation and organisational innovation innovation in technical systems

5. Contingent reward will predict No – no significant results for either organisational innovation type of innovation

6. Extent of team working will predict Yes – for product innovation and organisational innovation innovation in technical systems

7. There will be an interaction between Supported in part. Where our HRM practices designed to promote measures of induction, training, exploratory learning and those intended appraisal and contingent reward were to exploit existing knowledge, such that combined with ‘exploratory learning’, combinations of these practices will the interaction variable was significant. predict innovation above and beyond the There was no significant interaction for direct effects of these practices team working/exploratory learning and either type of innovation

TABLE 5 Summary of results





products. Thus, the interaction effects that we observe in this study apply by and large to this form of innovation. In other words, both induction and training focus on the process of doing the job and the means of achieving organisational objectives rather than on product innovation specifically. Contingent reward similarly tends to promote focus upon goals perceived to be readily achievable (such as innovating within a domain with which employees are familiar).

Appraisal, on the other hand, combined with exploratory learning, appears to impact significantly upon product innovation. Given that many manufacturing organisations are likely to invest responsibility for product innovation in R&D departments or specialist functions, this represents an important new perspective to take into account. Perhaps, as literature suggests, appraisal exerts a more powerful influence upon employees’ motives, learning orientation and understanding of organisational goals than many other HR variables (Murphy and Cleveland, 1996; Bach, 2000). This deeper understanding, combined with a willingness to consider the new and different alternatives gained through exploratory learning, may lead employees to make constructive suggestions for new products, either independently or in combination with specialist functions.

There has been much debate about the role of contingent reward in promoting performance (Eisenberger and Cameron, 1996; Deci et al., 1999). In line with research suggesting that where people feel controlled by another party they will be unlikely to look for new and creative solutions to problems (Pfeffer, 1998; Thorpe, 2000), we found no direct relationship between contingent reward and either type of innovation considered in this study. Implementing contingent pay in conjunction with practices designed to promote exploratory learning appears to be a constructive strategy for promoting innovation (in technical systems), however. This finding is depicted in Figure 4. With low exploratory learning there is a negative relationship between contingent pay and innovation, but with high exploratory learning the relationship is positive. We would suggest that, through applying these mechanisms in combination, individuals acquire a breadth of knowledge and are simultaneously encouraged to look for opportunities for applying the knowledge that they have gained. Through emphasising exploratory learning, organisations may overcome the limitations associated with pay for performance schemes that closely prescribe behaviour.

To promote exploratory learning via secondments, visits to customers and suppliers, through training beyond job requirements, and knowledge management practices (such as recording best practice solutions to problems) is a pervasive strategy for encouraging innovation, and Table 3 reveals that doing so impacts positively upon both types of innovation. Thus, on balance, organisations engaging in exploratory learning through adopting the combination of experiential and knowledge management practices detailed above are more likely to be innovative than those which exhibit no such commitment. This is, in part, because people generally learn better through the work process itself than through engaging in classroom-based activity (Stern and Sommerlad, 1999) and in part because individuals are more inclined to think creatively where they are exposed to new and different experiences. They may, for example, make connections between divergent stimuli, and envisage possibilities that may not have occurred to them otherwise (McGrath, 2001; Tsai, 2001). Conceptualising innovation as a two-stage process (West, 2002), we argue that exploratory learning promotes creativity to a greater extent than innovation implementation.





There is much discussion in the literature highlighting the importance of achieving a balance: engaging in exploratory learning whilst simultaneously supporting individuals as they exploit the knowledge that they have acquired in this way (Levinthal and March, 1993; Benner and Tushman, 2003). We argue that the HR practices considered in this study (training, appraisal, induction and contingent reward) are designed to promote learning towards the ‘exploitation’ end of the exploration/exploitation continuum. Research suggests that these variables tend as a general rule to promote the achievement of specific organisational objectives, thereby promoting compliance rather than creativity (Brown and Duguid, 1991; Simon, 1991; Murphy and Cleveland, 1996; Deci et al., 1999). This may explain why appraisal, induction, training and contingent reward account for more of the variance for innovation in technical systems where they are applied in conjunction with measures designed to promote exploratory learning.

The interaction variable for team working/exploratory learning accounts for 8 per cent of the variance for innovation in technical systems and 4 per cent of the variance for product innovation (see Table 4). These results are not statistically significant, although team working entered separately is significantly associated with both types of innovation, accounting for 27 per cent and 33 per cent of the variance respectively (see Table 3). Many scholars endorse the importance of team working as a mechanism for achieving innovation (cf. West et al., 2004). And indeed teams (where they operate effectively) present an environment whereby individuals are enabled to deal with the emotional and cognitive challenges associated with change and innovation. One would therefore expect to find a positive relationship between the interaction variable capturing team work and exploratory learning. That no such results are apparent may be a factor of the limited number of organisations to which we have access in this study. Our tentative results here deserve further research scrutiny.

1

1.5

2

2.5

3

3.5

4

4.5

5

Low Contingent Pay High Contingent Pay

Low Exploratory learning

High Exploratory learning

Inn

ovat

ion

in T

ech

nic

al S

yste

ms

FIGURE 4 Contingent pay, exploratory learning and innovation in technical systems






Intriguingly, results suggest that high exploratory learning in combination with weak approaches to training is a worse combination (in terms of innovation in technical systems) than low exploratory learning and weak approaches to training. This is also the case for induction. In other words, high exploratory learning combined with weak approaches to induction results in lower levels of innovation than may be the case where exploratory learning is low and induction is not given a high profile. What theory could explain these findings? We speculate that a failure to train employees may lead to difficulty in perceiving how the different experiences and perspectives acquired through exploratory learning may be applied in order to achieve organisational goals. Our results suggest that where this balance is inadequately managed – or where people have opportunities to learn from new and different experiences but are not clear about the purpose of doing so – organisations are unlikely to achieve high levels of innovation on a sustained basis. With regard to induction, it is possible that individuals who encounter a complex environment (with high levels of exploratory learning) but have no clear idea of how to use knowledge acquired in this way will find it difficult to apply any knowledge acquired to good effect. Furthermore, employees who encounter a complex environment with many opportunities for skill development may be overwhelmed if the socialisation process is not systematically handled, partly through the use of good induction procedures (Harrison and Kessels, 2004).

This study presents a number of practical implications. If, as we suggest, organisations are more likely to survive and prosper where they promote innovation and engage in sustained efforts over time to introduce and apply new ideas, it is necessary to consider how best to draw upon the skills and knowledge of the whole workforce. People management practices have an important role to play in fostering organisational innovation because they signal to employees that innovative activity will be recognised and rewarded (Laursen and Foss, 2003). Managers should therefore consider how to prevent individuals becoming locked into limited perceptual frameworks and should endeavour to develop mechanisms designed to promote new and different thinking. At the same time, organisations should implement mechanisms designed to develop existing knowledge, skills and attitudes. Induction, training, appraisal and contingent reward, designed and implemented effectively, help to ensure that employees are clear about their tasks and have the basic skills necessary to perform effectively. Furthermore, teams have an important and perhaps not fully acknowledged role in enabling organisations to appropriate the knowledge of employees at all levels of the hierarchy.

One major limitation of this study is the very small sample size – only 22 organisations were included in the analysis. Despite the more limited statistical power that this obviously entails, large and significant results were still found. In fact, many of the relationships found were significant with p < 0.01. To ensure these results were not due to shrinkage (artificial inflation of effect sizes due to a small cases-to-variables ratio), we also inspected the adjusted R2, which takes these factors into account. Increments in the adjusted R2 were similar to those in the actual R2; thus we are convinced that the effects are not just a result of having relatively few organisations. For future research, it would be useful to assess the extent to which our results hold given a larger sample size. Furthermore, researchers could develop a stronger measure of exploratory learning, taking account not just of whether organisations encourage





individuals to visit suppliers and customers, but of the number of times over a specified period that such visits occur. One could also consider the role of appraisal, training, induction and contingent reward, by assessing the extent to which such practices promote innovation implementation as opposed to idea generation.

The research design has a number of strengths. We control for prior innovation, thereby strengthening our case for suggesting that the HR variables measured promote the innovation outcomes reported. By controlling for the effect of size and profitability we can exclude alternative interpretations, e.g. that organisations performing well had the resources to innovate and to develop effective HR systems. We draw upon distinct and separate data sources in our analysis of dependent and independent variables.

Finally, this is, to our knowledge, the first study to directly consider the relationship between HRM and organisational innovation, controlling for prior innovation. This study thus presents a potential new avenue for research. We believe that HR practices – effectively designed and synchronised – enhance learning and empower people at all levels to instigate change and innovation. People are central to innovation performance, and the findings of this study suggest that relatively high levels of innovation can be achieved where people are empowered to make changes at local levels through effective HR practice.

Note

1. Knowledge – its creation, dissemination and implementation – represents ‘justified true belief’ combined with ‘a capacity to act’ (McKenzie and van Winkelen, 2004).

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HRM as a predictor of innovation

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