Research and development and the needed skills requirement

Research and development and the needed skills requirement

Innovation depends on people who are able to generate and apply knowledge and ideas in the workplace. Research is motivated by curiosity or a need to know about how things are, and what people do or can do. In an era of global competitiveness, industrial ‘research and development’ (R&D) holds great promise for improving the organizational economic well-being. The process of industrial R&D, in which scientific principles and properties of the natural world are transformed into commercial products and processes, consumes large quantities of resources (frequently over several years) before economic gains from product sales are realized. The management of R&D and innovation has emerged as a specialized area in the organizations.

An organization needs relevant R&D to remain effective and efficient. It relies on external support to meet its R&D needs. R&D is defined here as activities designed to advance and sustain the capabilities of the organization in pursuit of its mission. The R&D plan of the organization supports strategic planning by identifying and communicating the set of R&D needs which are reliant on external support. It is intended to help stakeholders understand the context for specialized needs and how they relate to the bigger picture of strengthening the effectiveness and improving the efficiency of organization.

A vibrant research ecosystem in the organization aims to provide meaningful thrust for sustainable research and innovation and promote collaboration between government, universities, research institutes and the industry. The organization is required to build a sustainable research ecosystem which leads to consistent quality research outcomes and enhanced productivity.

The key strategic issues for the organization include (i) maintaining the trust and support of stakeholders, (ii) bridging the gap between workload and resources, (iii) remaining effective in a globalized environment, (iv) adapting to information challenges, (v) operating in a changing security context, (vi) anticipating and responding to new demands, (vii) keeping up with technology and innovating, and (viii) sustaining the workforce and institutional knowledge.

Research is planned search or critical investigation aimed at discovery of new knowledge with the hope that such knowledge is going to be useful in developing a new product or service or a new process or technique or in bringing about a significant improvement to an existing product or process. Development is the translation of research findings or other knowledge into a plan or design for a new product or process or for a considerable improvement to an existing product or process whether intended for sale or use. It includes the conceptual formulation, design, and testing of product alternatives, construction of prototypes, and operation of pilot plants.

Research is an intensely personal activity, strongly dependent on the ideas and imagination of individuals or groups of individuals. Researchers feel a fierce personal ownership of their research. It shapes and dictates their career development and their status with their peers. Research is ultimately linked with fundamental beliefs about working freedom and the opportunity to challenge long standing orthodoxies. Moreover, research, by its very nature is unpredictable, moving in unforeseen directions with unexpected consequences. Further, it is this unpredictability which frequently gives rise to some of the most important outcomes and is hence to be applauded, not curbed.

Research, hence, does not lend itself to control and management. Yet, in the present day fast changing competitive world, there are constraints which need the application of some sort of management framework. Funding and quality issues need priorities to be agreed. Adequate resources are needed to be expended in the optimum way and there are legal and ethical controls to be applied. Research can also imply risk. For an organization, risk-taking is an essential part of organizational vitality, but risk is to be understood and managed. Of course, the same issues arise, but with perhaps slightly different emphasis, in relation to the leadership and management of research in the organizations.

Research leaders and managers also have to make decisions with reference to both scientific dynamics and organizational requirements. Hence, research leaders and managers need to have a general view of a subject matter, as well as the ability to co-ordinate inter-disciplinary efforts and to support individuals who are highly interested in the organizational implications of their fields of endeavour. Research leaders and managers also have to make difficult decisions based on judgments of relative merit, likely impact and potential value, normally across a range of research and innovation activities. It is possible to differentiate three levels of a research system namely (i) the policy and regulatory levels of government agencies, (ii) the strategic level of research in the organizations, and (iii) the operational level where research work is done. A fourth level can be added where groups of researchers are self-governing and the group leaders have autonomy over setting research goal and objectives.

A four-domain model of research management is suggested in a study consisting of (i) the knowledge domain, (ii) the organizational domain, (iii) the sector domain, and (iv) the domain of scientific and administrative projects in the organization. Clearly, research leaders and managers need skills which transcend these four domains. Fundamentally, and with these definitions in mind, the development and delivery of effective research outcomes need leadership and management which falls into two categories namely (i) developing individuals to become leaders in research in a discipline area which is broadly defined, and (ii) developing individuals to become leaders of research normally in an organization or group of organizations.

The two categories of development described above need different sets of knowledge, skills, attitudes, and behaviours but these are not mutually exclusive. In addition, there is a clear distinction in practice and in the theory between leadership and management which applies to research and innovation just as much as it does in other fields such as commercial and manufacturing industries. According to Kotter, leadership encompasses activities such as establishing direction, and aligning, motivating, and inspiring people so as to produce change. Management, on the other hand, is concerned with activities such as planning and budgeting, organizing and staffing, controlling and problem solving, all of which serves to establish predictability and order.

R&D comprises creative and systematic work undertaken in order to increase the stock of knowledge and to devise new applications of available knowledge. This includes (i) activities aimed at acquiring new knowledge or understanding without specific immediate commercial applications or uses (basic research), (ii) activities aimed at solving a specific problem or meeting a specific commercial objective (applied research), and (iii) systematic work, drawing on research and practical experience and resulting in additional knowledge, which is directed to producing new products or processes or to improving existing products or processes (development). R&D includes both direct costs such as salaries of researchers as well as administrative and overhead costs clearly associated with the organizational R&D.

The activities typically to be considered within the scope of R&D include (i) laboratory research aimed at discovery of new knowledge, (ii) searching for applications of new research findings or other knowledge, (iii) conceptual formulation and design of possible product or process alternatives, (iv) testing in search for or evaluation of product or process alternatives, (v) modification of the formulation or design of a product or process, (vi) design, construction, and testing of preproduction prototypes and models,  (vii) design of tools, jigs, moulds, and dies involving new technology, (viii) design, construction, and operation of a pilot plant which is not of a scale economically feasible to the entity for commercial production, (ix) engineering activity needed to advance the design of a product to the point which it meets specific functional and economic requirements and is ready for production, and (x) design and development of tools used to facilitate R&D or components of a product or process which are undergoing R&D activities.

The activities typically not to be considered R&D include (i) engineering follow-through in an early phase of commercial production, (ii) quality control during commercial production including routine testing of products, (iii) trouble-shooting in connection with break-downs during commercial production, (iv) routine, ongoing efforts to refine, enrich, or otherwise improve upon the qualities of an existing product, (v) adaptation of an existing capability to a particular requirement or the needs of the customers as part of a continuing commercial activity, (vi) seasonal or other periodic design changes to existing products, (vii) routine design of tools, jigs, moulds, and dies, (viii) activity, including design and construction engineering, related to the construction, relocation, rearrangement, or start-up of facilities or equipment other than (a) pilot plants, (b) facilities or equipment whose sole use is for a particular R&D project, and (ix) legal work in connection with patent applications or litigation, and the sale or licensing of patents.

R&D comprise creative and systematic work undertaken in order to increase the stock of knowledge and to devise new applications of available knowledge. A set of common features identifies R&D activities, even if these are carried out by different performers. R&D activities can be aimed at achieving either specific or general objectives. R&D is always aimed at new findings, based on original concepts (and their interpretation) or hypotheses. It is largely uncertain about its final outcome (or at least about the quantity of time and resources needed to achieve it). It is planned for and budgeted (even when carried out by individuals), and it is aimed at producing results which can be either freely transferred or traded in a market place.

For an activity to be an R&D activity, it is to satisfy five core criteria. The activity is to be (i) novel, (ii) creative, (iii) uncertain, (iv) systematic, and (v) transferable and / or reproducible. All the five criteria are to be met, at least in principle, every time an R&D activity is undertaken whether on a continuous or occasional basis. The term R&D covers three types of activity namely (i) basic research, (ii) applied research, and (iii) experimental development. Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundations of phenomena and observable facts, without any particular application or use in view. Applied research is original investigation undertaken in order to acquire new knowledge. It is, however, directed primarily towards a specific, practical aim or objective. Experimental development is systematic work, drawing on knowledge gained from research and practical experience and producing additional knowledge, which is directed to producing new products or processes or to improving existing products or processes.

Though several skills can be needed for innovation, individuals, organizations and industry can draw on different skill mixes at different times. Some factors likely to influence the needed skill sets are the stage of innovation, the type of innovation, and industry structure. In several organizations, innovation means the introduction of ‘new to the organization’ products and processes rather than radical inventions. Business strategies also drive demand for skills, as they provide a framework for decisions about investment, R&D, and human capital. As a result of these factors, while there are differences in the specific skills needed for innovation, in practice, several skills are relevant across the innovation spectrum. As the demand for knowledge sharing and learning increases, ‘soft’ skills such as communication and team work can gain in importance. However, technical skills remain an essential part of several types of work. Continuing globalization can lead to greater emphasis on adaptability and skills which facilitate collaboration across organizations. The ability to work in multi-disciplinary teams can also rise in importance. The growing interest in the environmental and sustainability issues is another trend which has an impact on the set of skills for innovation and research. Definitions of a ‘green economy’ and ‘green jobs’ are not yet settled, but there can be a need for broader skills in existing jobs as well as some new occupations.

One of the key issues with which the organizational management is to grapple is how to effectively manage people who perform research. Within the corporate structure of several organizations, R&D group occupies a unique position. This group of employees is frequently viewed differently from other employees, since these employees are perceived to be self-stimulating, independent, and capable of giving direction to their own efforts. Different studies have proposed that the organizational management is required to grant researchers the autonomy they need to be creative. Otherwise, researchers experience a clash between their expectations and the opportunities available in the organizational setting. How the management can create a research environment which allows people to build on their strengths and let creativity emerge while at the same time ensure that research is both cost-effective over the long-term and directed towards products and processes which can be introduced into the market place.

However, expertise in research needs more nuanced consideration. The disciplines can be understood as distinct intellectual endeavours within which the researchers share common sets of research questions, methods of inquiry, and intellectual approaches to solving problems. Disciplines manifest their differences from one another through distinctions in the use and value of different forms of evidence (e.g., logical, observational, or experimental) or the privileging of data-driven (inductive) or theory-driven (deductive) modes of reasoning. Hence, each discipline maintains its own ‘epistemic culture’ with its own norms, jargon, theories, and essential skills which can overlap to varying degrees with another. Accordingly, expertise is most precisely characterized within a disciplinary context, and even categories of skills frequently conceptualized across the sciences make reference to the state or standards of the discipline. For example, research skills which are normally measured across disciplines include (i) identifying and framing a meaningful and productive question for investigation based on the existing state of knowledge in the researcher’s discipline, (ii) formulating a testable research hypothesis based on a specific question, (iii) designing a valid experiment or empirical test of the hypothesis, and (iv) interpreting data by relating results to the original hypothesis and drawing appropriate, supportable conclusions. Collectively, these skills result in the construction of disciplinary arguments within a scientific discipline, the mastery of which is considered essential for successful researchers.

Defining skills

In the conventional approach, the general concept of skills refers to productive assets of the workforce which are acquired through learning activities. However, various studies do not concur on a robust and accepted definition and classification of skills beyond this general characterization. An appropriate and robust definition of skill has proven elusive. It seems that skill is a more complex and abstract concept or idea than present approaches have been able to capture. In the now vast literature on the impact of technological change on skills, a number of indirect indicators of skill level and change in skill level have been used. Reflecting the elusive and subjective character of ‘skill’, these indicators are typically not the subject of detailed justification and investigation to determine their validity and reliability. They are normally adopted by the researchers as a pragmatic solution to the problem of defining skill or derived by assumption from the theoretical orientation of the researcher.

The most important indicators used for skill are (i) employment distribution by level of occupation, (ii) employment distribution by educational attainment, (iii) wage differentials by educational attainment or occupation, (iv) measuring change in the job tasks and attributes needed to perform a job, and (v) surveys of managements or employees to determine skill levels needed to perform the jobs. The overall conclusion of the majority of the studies over the last three to four decades, with some important exceptions, is that ‘regardless of the measurement of skills…demand for high-skilled employees has risen since the 1970s. This trend is observed in both in the manufacturing… and in the service sector…as well as in the aggregate economy. The higher the skill level of jobs or occupations, the greater the skill upgrading is likely to be’. In several studies, skills and skill levels are defined as some combination of education, training, and experience.


The conceptual framework for data collection on innovation defines this activity as the implementation of a new or considerably improved product (good or service), or process, a new marketing method, or a new organizational method in business practices, workplace organization or external relations. A product innovation is the introduction of a good or service which is new or considerably improved with respect to its characteristics or intended uses. This includes considerable improvements in technical specifications, components and materials, incorporated software, user friendliness, or other functional characteristics.

Product innovations can utilize new knowledge or technologies, or can be based on new uses or combinations of existing knowledge or technologies. Product and / or service innovation entails activities such as design, R&D, acquisition of patents, technology licenses, trademarks, and tooling-up and industrial engineering.

A process innovation is the implementation of a new or considerably improved production or delivery method. This includes considerable changes in techniques, equipment and / or software. Process innovations can be intended to decrease unit costs of production or delivery, to increase quality, or to produce or deliver new or considerably improved products.

A marketing innovation is the implementation of a new marketing method involving considerable changes in product design or packaging, product placement, product promotion or pricing. Marketing innovations are aimed at better addressing customer needs, opening up new markets, or newly positioning the organizational product on the market, with the objective of increasing the organizational sales.

An organizational innovation is the implementation of a new organizational method in the organizational business practices, workplace organization, or external relations. Organizational innovations can be intended to increase the organizational performance by reducing administrative costs or transaction costs, improving workplace satisfaction (and hence employee productivity), gaining access to non-tradable assets (such as non-codified external knowledge), or reducing costs of supplies.

R&D is a part of innovation activity. The conceptual framework for data collection on R&D defines this activity as creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of person, organization, and industry, and the use of this stock of knowledge to devise new applications. R&D entails three activities namely (i) basic research, (ii) applied research, and (iii) innovation activity and skill.

Basic research – It is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundation of phenomena and observable facts, without any particular application or use in view. The Australian Bureau of Statistics subdivides basic research into ‘pure’ and ‘strategic’ basic research. The former is ‘experimental and theoretical work undertaken primarily to acquire new knowledge without a specific application in view. Pure basic research is carried out without looking for long-term benefits other than the advancement of knowledge’. Strategic basic research’ is directed into specified broad areas in the expectation of useful discoveries. It provides the broad base of knowledge for the solution of recognized practical problems.

Applied research – It is also original investigation undertaken in order to acquire new knowledge. However, it is directed primarily towards a specific practical aim or objective. Experimental development is systematic work, drawing on existing knowledge gained from research and / or practical experience, which is directed to producing new materials, products or devices, to installing new processes, systems and services, or to improving substantially those already produced or installed.

Innovation activity and skills – Official surveys of innovation across several countries reveal large and systematic differences in the propensity of organizations to innovate and the intensity of their innovation activity. However, it is to be acknowledged that there are limitations to the use of these surveys to analyze skills. The principal limitations are that such surveys collect only very aggregate data on skills and there may not be a direct linkage between the type of innovation activity and the level of innovation expenditure undertaken by an industry on the one hand, and the employment of people and skills within the industry on the other hand.  This arises since some innovation activities, such as design or patenting, can be funded by one industry, say manufacturing, but their undertaking can be outsourced to another industry, say ‘business services’, which includes industrial design consultancy and legal organizations. Although these complex input-output relations make it difficult to infer the skills and occupations involved in innovation in a specific industry, the official surveys do provide a clear insight into the breadth of skills needed for innovation at an industry-wide level.

Whilst the benefits for the organizations engaging in innovation have long been recognized, it is also the case that at any point in time, only a minority of the organizations actively pursue technological or non-technological innovations. This is in spite of the broad scope of activities included under the definition of innovation and the generous time period over which such activities can occur. There are also marked differences in innovation intensity across industries. There is a similar large variation in the intensity of R&D expenditures across industries. R&D is an important component of innovation activity. Manufacturing has the highest R&D intensity rating. Other business characteristics also influence the propensity and intensity of innovation.

Further, there are also marked differences in the composition of innovation activities across industries. Within the category of product and service innovation there are also marked differences in the way industries undertake this innovation. Variation in the methods used by industries to innovate reflect a broad range of factors such as differences in their production technologies, the nature of the product or service they produce, degree of capital intensity and bases of competition. These marked variations in the propensity and intensity of innovation, and in the range of activities undertaken when the organizations do innovate, demonstrate that the demand for skills for innovation is not uniform across the industry and, by implication, that there is enormous variation in the type of skills needed for innovation across industries, organization size and ownership structure.

Radical and incremental innovation and workforce skills – Another perspective on different forms of innovation and their implications for workforce skills is provided by examining the distinction between radical and incremental innovation. Innovation is classified into two broad types of activity, radical and incremental, depending on the processes used and outcome of the activity. Radical innovations give rise to major technological, economic and social change. Examples of radical innovation include the development of printing, railways, electricity, motor vehicles, the transistor, and atomic power.

The principal properties of radical innovations typically include (i) they are subject to great uncertainty, not only in the course of invention, but also in terms of the size of the potential market or even the existence of a market for the new product, service, or process, (ii) they take a long time for the market opportunities to be exploited, largely since the original innovation needs a series of subsequent complementary innovations, frequently taking decades to achieve, (iii) they are ‘disruptive’ and in Schumpeter’s famous description they generate ‘gales of creative destruction’ by making existing products, production systems, and skills technologically redundant, (iv) they affect multiple industries, if not whole economies, and (v) over the course of the last century they are primarily the product of massive government and / or private investment in basic and applied R&D and, consequently, the product of high-level science and engineering skills.

By contrast incremental innovations involve endless minor modifications and improvements in existing products, each of which is of small consequence but which, cumulatively, are of major consequence. Incremental innovations typically include (i) use of existing technologies and standards to effect improvements to existing products and services, (ii) have predictable development costs and market potential, (iii) can be undertaken by a broad range of organizations as it does not necessarily need large investment to develop or implement, (iv) are the principal source of productivity growth in the organizations as new applications are found for existing technologies and as these undergo gradual optimization, and (v) are frequently inspired and developed by direct production employees as users or producers of a good or service or the result of improvements suggested by final consumers of goods and services.

Two leading figures in innovation research Carl Dahlman and Richard Nelson, for example, find that the ‘cumulative productivity impact of small incremental changes which are normally undertaken on the shop floor can be much greater than initial introduction of a major technology’. A key implication of the prominence given to incremental innovation is that it has largely displaced the earlier ‘linear model of innovation’ in which innovation was assumed to proceed from basic scientific research to applied research and then into production and diffusion. Rather, attention has focused much more on the drivers of incremental innovation and the importance of widely distributed skills in the employees to identify and adapt current technologies. On this last point, it is being argued that ‘while not diminishing the importance of breakthrough innovation or of local discovery, the majority of innovation is incremental, involving improvement in products, processes, methods and so on…Hence broadly distributed capabilities are vital and investment in human resources is the essential foundation for innovation.

A key part of the direct production workforce is trade and employee occupations. They play a critical role in incremental innovation given that their training and function in the workforce entails the generation, design, installation, commissioning, adaptation, maintenance, and diffusion of new and existing technologies. Ensuring broadly distributed capabilities across the workforce depends on high rates of participation in quality initial education and training and the efficiency of technology diffusion within the organization. Technology diffusion involves the dissemination of technical information and know-how and the subsequent adoption of new technologies and techniques by users. In several cases, diffused technologies are neither new nor necessarily advanced, although they are frequently new to the user.

Improved technology is diffused in embodied form through enhanced equipment and software or through learning from education, training, and experience. The great bulk of innovation by organizations comprises the application of production processes, products, and services which have already been implemented in other branches of the industry or by competitors. In other words, most innovation comprises the diffusion and adaptation of existing knowledge.

Learning by doing and using are the principal drivers of incremental innovation. In almost all fields of production of goods and services, the repetition of production tasks leads to a gradual improvement in the efficiency of production processes and product / service design and performance. The importance of such ‘learning by doing’ processes has long been recognized, as has the central place of direct production employees in innovation as sources of work-based learning. Such work-based learning is also central to what is known as ‘learning by using’ or, more broadly, user-producer interaction. This form of learning entails the flow of information from the user of products or services to the producer of these products and services.

Users of goods or services provide regular feedback to the producers of the goods and services, communicating suggestions for design and other changes to extend their range of uses, improve their performance or reduce their cost. It has been argued that learning by doing and using, especially amongst direct production employees, is based on the application of ‘practical knowledge’. This is contrasted with ‘theoretical knowledge…which is about pursuit of the truth’ and employs a ‘rule based, instrumental or reductionist logic’. Practical knowledge is application-oriented…unlike scientifically and theoretically generated knowledge which orients itself on criteria such as theoretical relevance and universality. Practical knowledge is generated in application contexts of new technologies and obeys validity criteria such as practicability, functionality, efficiency, and failure-free use of a given technology. These are derived from accumulated experience and well-established and proven and tested routines for solving technical problems.

Learning by doing and using are the result of the accumulation of knowledge generated by experience in the production process or in the use of goods and services. The success of this accumulation depends critically on five factors namely (i) the type of work organization employed in production, especially the capacity of management to motivate production employees to provide feedback, (ii) establishing communication between producers and users, (iii) depends on the willingness of management to act on this information, (iv) the competitive strategy of the producing organization and specifically the extent to which it competes on quality, customization to the customer need, design and achieving cost reductions through innovation and capital investment, and (v) depends on a wide distribution of technical competence within the producing organizational workforce and across the users of its goods and services.

Innovation, product cycles and skills – It has been observed that there is a systematic relation between product and technology cycles and the demand for skills. The use of a new production process or introduction of a new product or service by the organization can result in job tasks becoming less well-defined with attendant uncertainty about effective task performance. Uncertainty regarding operating procedures and expected outcomes needs higher-skilled employees with greater understanding about the production process and capacity to deal with unanticipated results. As the behaviour and properties of products, services, and processes are better understood they become codified in standard operating procedures which can be performed by less skilled employees. There are several examples in industries as diverse as process, computing, and atomic power, where initial production needs highly qualified experts with advanced degrees, but which subsequently uses employees which may need only in-house training. Similarly, for the organizations with products or services which are technologically obsolete or have achieved ‘maturity’ in their market share, there may not be an incentive to devote scarce resources such as higher-level marketing or product development skills, to extend their commercial life.

Benefits of higher skills for innovation – Higher skills for innovation helps in accelerating technical change. There is argued to be a virtuous circle between increased investment in employee education, investment in knowledge creation, such as fundamental research, and an increased rate of implemented technical change. The principal mechanism in this virtuous circle is the unusual properties of knowledge. Firstly, unlike standard economic goods, knowledge, conceived as a factor of production, is not subject to diminishing returns and does not depreciate as each increment in knowledge adds to the total stock of knowledge. Secondly, knowledge is non-rivalrous in that it can be employed by multiple organizations simultaneously without affecting the organizational costs. Another aspect of its non-depreciation and non-rivalry is that having been acquired by an organization, it can continue to be used indefinitely at its marginal cost.

The following arguments are well known and are mentioned in summary form only. Even knowledge, such as outmoded scientific theories which have been ‘falsified’, or failure in the market of a new good or service, act to preclude scientists and entrepreneurs from the pursuit of ‘dead-ends’. Flaherty uses the example of quality systems to describe how knowledge is additive-acquiring knowledge about one aspect of a production system reduces the cost and effort of acquiring additional information about the system. For example, one objective of quality systems is to increase conformity of output with specifications so that ‘as process variability decreases and…knowledge increases, it becomes easier to learn almost anything else about a process…increasing conformance quality increases the effectiveness of efforts to acquire further process knowledge of all sorts…reduced variance increases the power of subsequent hypothesis tests, or reduces the sample size needed to attain a given power effectively falls to zero.

Knowledge is also non-excludable in that there are either no limits imposed by property rights on the use of knowledge or these rights are of finite duration. Further, education, knowledge and skills have the property of a network externality, that is to say, the value in acquiring knowledge by any one user increases at a rate proportional to, or even greater than, the rate of increase in the number of other users. In other words, the productivity of any employee is improved not only by their individual level of skill but also by the average skill level amongst their fellow employees. Also, knowledge is a joint-product of production and hence expanding output also increases the accumulation of knowledge through learning by doing. Knowledge is hence both an input and output of production and innovation.

The different properties of knowledge have been used to argue that the growth of knowledge is subject to increasing returns, that is, ‘knowledge acquired per unit of time is greater if the stock of publicly available knowledge is larger’. In addition, the growth of knowledge raises the productivity of capital investment when it is embodied in more recent vintages of physical capital goods and software. In turn, this is claimed to account for the presence of increasing returns to capital investment at an economy-wide level, as evidenced by the long-run increase in the capital-employee ratio.

These various properties of knowledge have also been used to explain important long-run trends, especially rising workforce educational attainment, rising R&D intensity, and increase in the breadth of technologies subject to R&D by large individual organizations. Firstly, growth in the ‘volume’ of knowledge needs ever higher workforce skills to identify, assess and implement new knowledge. Secondly, the complex input-output relations which typify large organizations need them to keep up to date not only with technological advances in inputs from a multiplicity of supplier organizations, but also to constantly devise new uses and improvements to their own products and services which are also typically used as inputs by a multiplicity of organizations across several industries.

One measure of the above tendency is the growing propensity for large organizations to engage in R&D and patent activity across a range of industrial classifications which is much wider than the industrial classification of the products or service they make. Large organizations and the products they make, depend on several fields of technological competence, the number of which is increasing over time with the widening range of technological opportunities emerging from improvements in computing and other technologies. In order to assimilate this range of emerging technologies, large organizations simultaneously increase their internal competencies, form alliances with external sources, and increase their overall R&D expenditures,

A great deal of knowledge may well be ‘free to use’ but this does not imply that knowledge is a ‘free good’. As has been shown in a study, there are degrees of non-rivalry and non-excludability and frequently considerable private and public investments needed to make knowledge non-rivalrous and non-excludable. The most important example of these private and public investments is education. The study also makes the point that whilst knowledge does not ‘wear out’ or depreciate in a manner analogous to capital equipment there are however considerable costs in its storage. Arrow deals with ‘knowledge’ at a very high level of abstraction, which also hides the fact that much knowledge is ‘sticky’ in that it is not easily transferred. For example, knowledge can be sticky since it is context dependent, say the operation of a unique industrial process or the information can be only tacitly understood.

Adapting to technical change – A related, but somewhat different argument relates higher skills to a faster rate of technical change, in that empirical studies show ‘that more highly-educated individuals tend to adopt innovations earlier and implement and adapt them sooner than less-educated individuals’. This applies both to the consumption of new technologies, for example, in production. More educated and skilled employees are argued to have greater ‘functional flexibility’ in that their greater stock of knowledge increases the rate at which they learn and develop higher order problem solving skills. This greater functional flexibility is also argued to be important for innovation at a macro-economic level, as more educated persons are better able to cope with rapid structural change induced, for example, by innovation. An indicator of this is the strong positive relation between educational attainment and workforce participation and strong negative relation between higher educational attainment and rates of unemployment.

Complementarity of education, training and innovation – It is well established that the propensity of organizations to provide training and the intensity of this training increases markedly the higher the initial educational attainment and prior training of its workforce. , a study of the workforce in the 1990s finds the probability of employees with degrees or higher qualifications receiving organization funded training is close to two-thirds higher than persons whose highest educational attainment is a basic vocational qualification and around 50 % higher than persons with trade qualifications or who had completed high school. The number of hours of training received by managers, professionals, and associate professionals is nearly three times more than persons in clerical occupations and more than five times that of trades people. The study concluded that ‘there are substantial complementarities between education and training’.

This complementarity is attributed to a range of factors which make it more profitable for the organizational managements to invest in training persons with higher initial education, such as the more educated having better learning skills and lower marginal training costs compared to those with less education. Obviously, educational attainment and occupation are also correlated and there are plausible reasons why managerial, professiona, and associate professional occupations receive more workplace training than say, the workforce. For the former group the rate of change in their knowledge base can be rapid and on-going professional development can also be mandatory to maintain membership of professional associations.

Further, there is an association between the propensity of the organizations to innovate and the probability of them providing workplace training. There are two major reasons for this. Firstly, the characteristics which are positively associated with a high propensity to undertake innovation are also associated with a high propensity to provide training by the organization. These characteristics include, for example, large organizational size, public ownership, high capital intensity, etc. Secondly, when an organization introduces a new product, service, production process, or organizational change, new workforce skills are frequently needed.

The complementarity of education, training, and innovation suggests a virtuous circle whereby a workforce with a higher initial level of education stimulates the managements to further develop their productive capacity through training and both of these improve the capacity of the workforce to deal with technical change. Conversely, employees with low educational attainment are much less likely to participate in either management-sponsored training or invest in their own training. A vicious circle is evident whereby low initial educational attainment constrains further acquisition of knowledge and capacity to engage in innovation.

The complementarity of capital investment and skills – The complementarity of human and physical capital can correctly be regarded as a subset of the wider topic of education, training, and innovation. However, its importance warrants separate exposition. The virtuous circle between human and physical capital is evident in the long-run increase in the capital-employee ratio where the quantity of capital per employee has increased alongside an increase in the ‘quantity and quality’ of employees, with the latter measured in terms of rising rates of education. Rising levels of capital per employee and new technologies embodied in capital equipment and software are a critical input into innovation as they permit the introduction of new and improved products, services, and production processes. In turn, the complementarity of higher capital investment per employee and improvements in the quality of employees suggest that more skilled employees are necessary to achieve the productive potential of new capital investment.

Researcher development skill framework

The researcher development skill framework (RDSF) as shown in Fig 1 is made up of five components consisting of a centre and four quadrants, which together cover both the discipline specific and generic skills needed by researchers.

Fig 1 Researcher development skill framework

RDSF centre represents researcher and research. The RDSF places the researchers and their research at the centre. These core skills are unique to the researchers and their research area. In addition to the centre piece, the RDSF has four quadrants. Within each quadrant there are three skills categories which are then broken down into skills areas with examples. To help develop these skills, training, Workshops, and resources are needed. For the researchers and their research, the requirements are (i) subject knowledge (ii) discipline specific skills, and (iii) intellectual ability.

Quadrant 1 represents personal and professional development.  It includes (i) self-management, (ii) career management, and leadership and interpersonal skills. Quadrant 2 represents research management. It includes (i) research planning and income management, (ii) data management, digital literacy, and administration, and (iii) research conduct, integrity and ethics. Quadrant 3 represents communication. It includes (i) academic literacy and writing, (ii) verbal and visual presentation skills, and (iii) publication and dissemination. Quadrant 4 represents engagement and impact. It includes (i) outreach and influence, (ii) knowledge exchange and innovation, and (iii) education.

Personal and professional development – Personal and professional development include (i) self-management, (ii) career management, and leadership and interpersonal skills. The self-management includes (i) well-being, (ii) time management and planning, and (iii) goal setting.

The skills needed for well-being are (i) establishment of work / life balance, (ii) building of resilience, (iii) undertaking the self-care, (iv) building of confidence / self-esteem (e.g., avoiding of impostor syndrome), (v) managing of stress and stressful situations, and (vi) ensuring a healthy workspace (e.g., regular breaks, and ergonomic set up).

The skills needed for time management and planning include (i) management of time, (ii) preparing adequately for the needed tasks, (iii) applying a range of useful planning tools and technologies, (iv) prioritizing key tasks and delegation of tasks as needed, and (v) showing of flexibility in overcoming obstacles.

The skills needed for goal setting include (i) identifying key goals for future and set goals in writing, (ii) undertaking self-reflection and being self-aware, (iii) ensuring goals which are SMART (specific, measurable, attainable, relevant, and time-bound), (iv) considering possible obstacles to the achievement, and (v) involving others in the goal setting process.

The career management includes (i) career planning and coordination, (ii) job application skills, and (iii) professional development. Career planning and coordination includes (i) building of networks including referees and mentors, (ii) knowing of promotions indicators, planning, and applying for promotion, (iii) managing of job transitions, (iv) self-assessment of the present skills and career situation, (iv) development of a career strategy and investigating suitable career pathways, and (v) maintaining portfolios as applicable (e.g., teaching or research).

The job application skills include (i) investigating suitable positions and be aware of the present job market, (ii) adapting, designing, and writing the CV (curriculum Vitae) / cover letter / EOI (expression of interest) with the job in mind, (iii) responding to selection criteria using the appropriate format and language, (iv) developing and practicing interview skills, and (v) ensuring a suitable online profile and by using of digital tools.

Professional development skills include (i) identifying professional development opportunities which fill skills gaps identified, (ii) engaging in ongoing professional development in line with career goals, and (iii) maintaining records of career development for employment purposes.

Leadership and interpersonal skills include (i) leadership, (ii) interpersonal skills, and (iii) equity and diversity. Leadership skills include (i) providing vision and strategy, (ii) giving and receiving constructive feedback, (iii) encouraging communication between all members of the team, (iv) motivating and inspiring others, (v) building rapport and strong relationships, and (vi) leading by example.

Interpersonal skills include (i) working well with others, (ii) listening actively and being engaged when interacting with other, (iii) communicating with self-confidence, (iv) communicating clearly, including verbal and non-verbal cues, (v) being reliable, punctual, and delivering what has been promised, and (vi) understanding the importance of empathy and how the behaviour has effects on others.

The skills needed for equity and diversity include (i) accommodating individual differences in learning and communication styles, (ii) knowing how to engage with diverse individuals, (iii) encouraging a culturally inclusive environment, (iv) developing awareness of ‘Aboriginal and Torres Strait Islander content’, and encompassing this in research where possible, and (v) making adjustments as necessary for those with access and inclusion requirements.

Research management – Research management includes (i) research planning and income management, (ii) data management, digital literacy and administration, and (ii) research conduct, integrity and ethics. The skill areas for research planning and income management include (i) research project development, (ii) grant seeking (pre-award), and (iii) grant management (post award).

The skills needed for research project development include (i) identification of funding opportunities, (ii) identification of key support people / mentors to provide expertise / advice, (iii) creation of a research plan including a narrative and case, (iv) development of a budget, (v) finding of research partners, and (vi) understanding types of funding and the funding lifecycle.

The skills needed for grant seeking (pre-award) include (i) preparing sections of a grant proposal, (ii) seeking support from key people / partners, (iii) recognizing common research funding mistakes, problems, and pitfalls, (iv) seeking and responding to the feedback, and (v) applying for funding (e.g., writing and submission of grant applications).

The skills needed for grant management (post-award) include (i) tracking of milestones, (ii) managing of stakeholders / collaborators, (iii) managing of budgets, (iv) managing of grant administration including reporting on progress.

Data management, digital literacy, and administration include (i) digital literacy tools, (ii) research data management, and (iii) administration skills. The skills needed for digital literacy tools include (i) use of reference management software, (ii) use of word processing software, (iii) use of spread-sheet software (e.g., excel, numbers) including basic statistics and pivot tables, (iv) use of quantitative and / or qualitative statistical packages, (v) use of presentation software, (vi) use of teaching technologies and learning management system, and (vii) use of suitable online resources for efficient research.

The skills needed for research data management include, (i) ensuring data is kept securely, and is backed up regularly, (ii) management of data (including collecting and organizing), (iii) maintaining version control and file naming practices, (iv) encouraging practices of good stewardship around data, including open access, (v) managing data IP (information within packet) and ownership in accordance with ethics around data management.

Administrative skills include (i) managing administrative tasks in a timely manner ensuring adequate record keeping, (ii) managing of the calendar / diary, and (ii) managing of the e-mail load.

Research conduct, integrity and ethics includes (i) academic integrity, (ii) research ethics, and (iii) responsible research conduct. The skills needed for academic integrity are (i) to keep informed as to what constitutes good academic practice, (ii) to acknowledge the work of others, (iii) to attribute work correctly including citing all sources used, (iv) completing ongoing research integrity training, and (v) managing resources in a way which minimizes unintentional plagiarism.

The skills needed for research ethics are (i) to stay up to date on current ethics policy, (ii) to obtain the needed ethics clearance for the research, (iii) to assess the ethics of the project through the research and writing phases, (iv) to maintain the needed ethics documentation and reporting, (v) to follow secure practices of data storage, and (vi) to undertake the needed research ethics training.

The skills needed for the responsible research conduct are (i) to follow safe work practices, (ii) to ensure suitable research space induction processes for new colleagues and other employees, and (iii) to be aware of potential risks and hazards and work to avoid them.

Communication – Communication includes (i) academic literacy and writing, (ii) verbal and visual presentation skills, and (iii) publication and dissemination. Academic literacy and writing include (i) written expression, (ii) knowledge of written formats, and (iii) editing and polishing.

The skills needed for written expression are (i) use of the appropriate academic style for the discipline, (ii) to undertake ESL (English as second language) training, (iii) defining of terms as needed, (iv) clarifying of key points, and (v) building of persuasive arguments.

The skills needed for the knowledge of written formats are (i) composing of different text types (e.g., book chapter, conference paper, journal article, etc.), (ii) use of the correct paragraph structure including topic sentences, (iii) providing summaries and analyses of the work of others, and (iv) organizing and managing the literature.

The skills needed for editing and polishing include (i) editing and proof-reading written documents, (ii) maintaining consistency in long documents, and (iii) seeking feed-back on written work and consult with others.

Verbal and visual presentation skills include (i) verbal skills, (ii) visual skills, and (iii) reflection listening and asking questions. Verbal skills include (i) ensuring vocal clarity and clear pronunciation, (ii) composing of speeches and use of story-telling to engage audiences, (iii) speaking persuasively, (iv) pitching ideas, and developing pitches for different audiences, and (v) adapting the message to the audience.

Visual skills include (i) designing of effective slides and visual aids for presentations, (ii) use of suitable images which comply with copyright, and (iii) presentation of information visually in a format which is suitable for the task (e.g., infographic, concept map, Gantt chart, and network diagrams etc.)

Skills needed for the reflection, listening and asking questions are (i) providing constructive comments and feedback, (ii) thinking critically about what is being presented, (iii) formulating thoughtful questions, (iv) listening actively, and (v) engaging with the work of others.

Publication and dissemination include (i) preparing for publication, (ii) compiling and submitting, and (iii) post submission and other publication process skills. Skills needed for preparing for publication are (i) developing a publication plan keeping in mind publishing schedules / time-frames, (ii) selecting suitable destinations for the publications (journal, book, etc.) based on research impact and to avoid predatory publishers, (iii) understanding open access requirements (green, gold, and hybrid), implications, and costs, (iv) identifying the key gaps which the publication is required to meet, and (v) determining the  co-author roles and responsibilities.

The skills needed for compiling and submitting include (i) compiling of the publication in a timely manner, (ii) editing and proof-reading of the submission keeping in mind the instructions to authors, (iii) checking that the references are correct and are suitable for the publisher, and (iv) obtaining needed image permissions and checking that images are in correct electronic format, resolution, etc.

Post-submission and other publication process skills include (i) responding appropriately to feedback within the allocated time-frame, (ii) editing for a journal and conducting peer review, (iii) publicizing new publications, and (iv) sending information of published work to research office / research repository.

Engagement and impact – Engagement and impact include (i) outreach and influence, (ii) knowledge exchange and innovation, and (iii) education. Outreach and influence and Impact include (i) profile building, (ii) media skills, and (iii) wider community engagement skills (public).

The skills needed for the profile building include (i) building of the personal brand and making visible and accessible the self, (ii) evaluating the impact using metrics and alt-metrics, (iii) communicating the ‘so what’ of the research (research value proposition), (iv) establishing and maintaining of the professional profile accounts  (e.g., ResearchGate,, LinkedIn), (v) maintaining a social media presence and know how to optimize it, (vi) writing of impact statements, and (vii) obtaining and maintaining of an ORCID ID and populating it with the publications.

Media skills include (i) contributing to media (e.g., television, radio, print media), (ii) making the message interesting and relatable, (iii) building of the relationships with the media, and (iv) adapting content for the medium.

Wider community engagement skills (public) include (i) engaging of lay audiences, (ii) being involved in public debate, (iii) influencing policy and providing submissions to the authorities and government (e.g., ministry inquiries), (iv) taking research into the community, and (v) contributing to the industry.

Knowledge exchange and innovation include (i) innovating thinking and planning, (ii) opportunity seeking, and (ii) opportunity management. The skills needed for innovating thinking and planning include (i) identification of the commercial value and potential commercial / start up pathways, (ii) identification of key support people / mentors to provide expertise / advice, (iii) understand user engagement strategies and end user needs, (iv) exploring options such as consultancies, internships, sponsored research arrangements, and licensing, (v) identifying potential customers and markets and building relationships, (vi) managing the self’s IP including patents, copyright, trademarks and designs, and (vii) recognizing the commercial, social and environmental impacts of the research.

The skills needed for the opportunity seeking include (i) present commercial pitches, (ii) networking / making professional connections and leveraging them, (iii) negotiating, (iv) building partnerships with industry, (v) carrying out of scope and cost of the potential projects and (vi) soliciting and responding to feedback.

The skills needed for opportunity management include (i) being aware of and managing of the commercial obligations and risk, (ii) managing of stake holders / partners / collaborators, (iii) reporting on progress (meeting requirements), (iv) managing finances and administration, and (v) managing and meeting expectations.

Education include (i) research led teaching, (ii) supervision, and (iii) mentoring. The skills needed for research-led teaching are (i) communicating effectively and present research in an engaging way, including in online environments, (ii) ensuring that research-led teaching and assessment addresses learning outcomes, (iii) designing curriculum keeping in mind the need for active, student centered, problem based, experiential and collaborative learning, (iv) selecting and using appropriate teaching and learning technologies for research-led teaching, (v) giving comprehensive, structured, and actionable feedback which promotes learning, and evaluating teaching practice and employing reflective practice.

The skills needed for supervision include (i) setting expectations around the supervisory relationship, (ii) engaging in ongoing training and professional development around supervision, (iii) providing constructive and timely feedback, and (iv) monitoring student progress and wellbeing.

The skills needed for mentoring include (i) sharing of knowledge and skills, (ii) building a rapport, (iii) asking suitable questions and providing sound advice, (iv) encouraging mentees to pursue opportunities and to take strategic risks, and (v) managing and meeting of expectations.

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