5.2.1.1. The social innovation process

Social innovation arises first of all from an unmet social need. The first step is therefore to transform a collective need into a social need, i.e. to make it a cause that goes beyond the strict collective of the individuals concerned. Thus, the struggles against unemployment, poverty, poor housing and global warming are now considered to concern all societies (see Box 5.3).

The second step is to propose a solution to meet this need. This solution generally combines a technical dimension with a social or societal dimension (see Table 5.3).

This table gives several examples (not exhaustive of course) of a combination between a technical dimension (here: a platform, an object, know-how) and a social dimension (here: sustainable consumption, recycling, charity, volunteering). Thus, Internet platforms can be used to promote sustainable consumption through the sale and purchase of secondhand clothing, as well as through charity, with the resale of tickets with donations to charitable associations, or through voluntary work, with the establishment of links between volunteers and associations. As for technical objects or tools, the table mentions “Fairphones”, smartphones designed with separately renewable parts, which increase the lifetime of the device (see Box 5.4), or sophisticated recycling trash cans, as well as isothermal shelters for the homeless, designed to conserve heat and therefore provide (certainly temporary) shelter solutions in the event of extreme cold. Finally, the last column is devoted to know-how in the repair and refurbishment of objects, which is part of both sustainable consumption and recycling objectives. These skills can also be a means of integration for unemployed people.

Finally, social innovation aims to address an unmet social need by combining a social dimension of changing practices with a technical dimension (e.g. digital platform, specialized know-how). It can be described as responsible insofar as it seeks to meet major societal challenges and aims at a form of ethics.

5.2.1.2. The actors of social or responsible innovation

Another characteristic of social or responsible innovation is that it involves many actors, sometimes not used to cooperating together: companies, government actors, research institutions, non-market organizations (Klein, Laville and Moulaert, 2014). Thus, the social innovation ecosystem can be divided into several categories of actors: designers, funders, supporters and users.

The designers of social innovations can have different statuses: associations, NGOs, companies, start-ups, individuals or groups of individuals, etc. Some innovations can be directly associated with the names of individuals, such as École 42 founded by Xavier Niel in France (see Box 5.5), while the affiliation of other initiatives is much more difficult to establish, as in the case of free software and code (see Box 5.6).

Financers of social innovations can take many different forms:

• – solidarity-based finance (investment funds specializing in the social and solidarity economy, for example);
• – corporate foundations;
• – crowdfunding platforms;
• – public funders (States, local authorities, public institutions, etc.);
• – classic banks.

These different actors are not mutually exclusive, as the same social innovation project can benefit from several funding sources.

Actors who support social innovations can contribute in different ways. Thus, some actors aim to provide information and guidance to project leaders, while others aim to provide development and management assistance (incubators, professional networks, etc.).

Finally, the users of social innovations are also extremely diverse (individuals, associations, etc.).

Among these different actors, the role of States is both highlighted and questioned in the literature on social innovation (Laville, 2014). Indeed, by aiming to meet a social or collective need, social or responsible innovations sometimes take over from public authorities in certain fields traditionally covered by them (e.g. the fight against poverty, the fight against illiteracy).

However, they do not necessarily reflect a disengagement of the State, which can support the shareholders of social innovations through financing or aid policies. Moreover, ensuring the conditions for the emergence of social innovations in sovereign domains could be an important quality of a truly democratic state (Laville, 2014).

5.2.1.3. Responsible technological innovation, a response to the criticisms and threats associated with technological change?

Finally, social innovations seem to respond to the main threats identified in the first section, while at the same time allowing the main opportunities to be seized. In particular, they make it possible to meet certain societal challenges (recalled, for example, in Chapter 2) and seek to respect a form of ethics. In the field of technological change, we take this into account by calling them responsible technological innovations (see Table 5.4).

Thus, responsible technological innovation is applied to several areas that respond to many of these criticisms, in particular: the integration of unemployed people, which is to be compared with the risk of automation and job destruction, and sustainable development, to be compared with ecological risk. Moreover, responsible technological innovation aims to meet a social need and, in this respect, it responds to the risk of a technicist ideology disconnected from reality and the risk of war and violence. Thus, some innovations seek to reduce crime or the effects of war on individuals. Secondly, social or responsible innovation arises when a social or collective need is not covered by dominant institutions and therefore often benefits dominated populations, which explains its links with the social and solidarity economy (Laville, 2014). In this way, it partly responds to the risk of discrimination related to technological change. Finally, one of its characteristics is to put the human being at the center and to promote the social and human dimension over the purely technical dimension, which responds to the risk of prescriptive technology and the alienation of the human being through technology. Many responsible technological innovations also meet the objective of empowering individuals, which contradicts the image of an alienating and prescriptive technology. Fighting the digital divide is another area in which responsible technological innovations are multiplying, such as Simplon.co, a start-up that targets the most vulnerable populations.

5.2.2.1. Organizations as places of production for responsible technological innovations

Many responsible innovations are the result of organized collectives of individuals: companies, associations, cooperatives, unions, NGOs, etc. The social and solidarity economy sector thus includes many of these organizations (see Box 5.7).

The links between responsible innovation and the social and solidarity economy are particularly strong. Thus, the voluntary sector has historically been a laboratory for responsible innovation, particularly in the technological field, since associations have had to find solutions to social needs not covered by public authorities or companies (in the fields of housing, health, ecology, etc.).

In addition, commercial companies can also offer responsible technological innovations. The Fairphone company already mentioned is an illustration of this. The challenge is therefore to identify the conditions for the emergence and production of these responsible technological innovations within market organizations. Based on the definition of social or responsible innovation, they seem to us to be as follows:

• – to identify an unfulfilled social need, sometimes not put on the agenda by public authorities;
• – to reason outside established structures and concepts;
• – to put the issue of economic and financial profit on the back burner;
• – to link the social and technical dimensions.

Thus, as we have seen, the first step is to identify an unfulfilled social need, sometimes not even put on the public agenda. However, if the need is not put on the public agenda, it means that, to identify it, it is necessary to reason outside established structures and institutions. Moreover, if the need is put on the public agenda but is not met, it probably implies that it is difficult to satisfy this need in established structures and institutions. In this second case too, reasoning outside established structures, institutions and concepts seem necessary. Secondly, as we have seen in the social and solidarity economy sector, social innovation is also characterized by putting the search for profit on the back burner (Oosterlynck and Moulaert, 2014). Finally, it is necessary to link the social and technical dimensions, as social innovation is based on the interweaving of the two (see Table 5.3).

5.2.2.2. Responsible technological innovation, a vector for democratizing organizations?

As mentioned above, a whole field of research is concerned with social innovation as a vehicle for democratizing society (Klein, Laville and Moulaert, 2014). Therefore, the transposition of this perspective to work organizations could imply that some social innovations related to technological change could make work organizations more democratic. Two elements and examples seem to us to support this point.

First of all, a dialogue with employee representatives, an essential element of corporate democracy, can in some cases allow forms of social innovation linked to technological change. Oosterlynck and Moulaert (2014) thus give the example of a dialogue with social partners on the dissemination of new information technologies (see Box 5.8).

Secondly, social innovation in some cases implies the active participation of workers in its production, and this is just as true in the case of responsible technological innovations. Organizational learning theory thus reflects a movement to integrate knowledge from work practice into organizational processes. It is therefore a vertical upward movement, which ensures that innovation responds to a need and consists of both a technical and a social dimension. Thus, an operator can innovate by developing new work tools or technologies, which can eventually be integrated into work procedures, and which other operators, in turn, will have to use or apply. This theory is thus based on the premise that workers are best able to develop innovations that meet their own work needs. Similarly, in the case of technological innovation to meet societal needs, it is sometimes workers who have had to deal with difficult situations who propose to their organization an innovation to meet these types of situations. Such participation may, in some cases, take the form of intrapreneurship, already mentioned in Chapter 3, when employees develop social innovations within their own companies (see Box 5.9).

Finally, social or responsible innovation is a form of change that combines a technological dimension with a social and societal dimension. In this way, it responds to some of the criticisms made by some researchers in the human and social sciences against technology. The development of responsible technological innovations requires the participation of different groups of stakeholders, including work organizations (e.g. companies), as producers and beneficiaries of these innovations. Indeed, the latter can contribute to organizational democracy through the development of dialogue and participation of employees and their representatives.

5.3.1.1. A prescriptive model for change management

Among other things, researchers have proposed prescriptive change management models. Thus, Philips (1983) starts from the observation that there are three key factors for successful organizational change: the quality of the new strategic vision, the development and dissemination of the skills required for this strategic vision and organizational support (leaders, managerial line, etc.). He thus derives a four-phase planned change management model (see Figure 5.1). A first step is to build consensus within the organization on the need for change. This can be done, for example, by offering training on socio-economic change, by leaders speaking out or by setting up small groups of influencers convinced of the need for change and responsible for disseminating this conviction to those around them. The second phase aims to launch a movement of commitment towards a specific change: the definition of the strategic vision and of the resulting organizational vision in particular. The third phase consists of defining and implementing actions to enable change: training if new skills are needed, changes in operating and working methods or job creation or reduction, for example. Finally, the fourth phase should make it possible to consolidate the new organization, for example by institutionalizing the new rules.

5.3.1.2. Contingency factors for change management

However, this type of prescriptive model overlooks the fact that a change management strategy is contextual, in the sense that it also depends strongly on the type of change involved (Pettigrew, 1987; Weick and Quinn, 1999) and that there are alternatives to planned change. There are many types of organizational changes. Table 5.5 represents a non-exhaustive attempt at an overview that provides examples of dimensions that structure organizational change.

The first dimension concerns the extent of the change and its reversibility. Some changes, such as a change in managerial culture or a massive reorientation of the organization’s activity, affect several departments and lead to in-depth organizational renewal. Conversely, other changes are less important: reorganization of a team, marginal modification of a work process. The extent of the change then determines the strategy to be adopted. Van de Ven and Poole (1995) thus distinguish situations of change that concern a single entity of the organization (a department, a site, for example), and situations that concern several or all entities. In France, the example of the social crisis of the late 2000s at France Télécom illustrates a change strategy that is not adapted to the scale of the targeted changes (see Box 5.10).

The second structuring dimension concerns the place given to individuals in change. Thus, some changes are decreed by the company’s management (see Box 5.10) and imposed on individuals without their participation: this is therefore a prescribed change (Van de Ven and Poole, 1995). On the other hand, some organizations seek to involve employees in change, through working groups or collective workshops to bring forward proposals. However, it is still necessary to distinguish between situations where the results of these collective reflections are really taken into account to define the facets of change, and those where employee participation is only illusory, in the sense that it does not influence the path of change (see Box 5.11).

The third dimension refers to a distinction between situations where change is thought of as primarily technical, and those where it is thought of as primarily human. Indeed, as we have pointed out, while, change is often both technical and human, organizations tend to strongly separate the two dimensions. Thus, a company that decides to change its main working tool can promote the “tool” vision, focusing on technical aspects, and, for example, on the operational and technical prerequisites for the implementation of the tool, or on the contrary a “human” vision, focusing on individuals and highlighting, for example, the need for training and individual and collective support. Moreover, this primacy given either to the tool or to the human can influence all stages of the process (see Figure 5.2).

Thus, when choosing the tool, the company may focus on technical considerations (technical specifications, functionalities, version changes envisaged, for example), or be more interested in what the tool will change for individuals, in terms of autonomy, skills implemented or daily activities. Then, when the tool is installed, the technical dimension focuses on compliance with the technical specifications or interfacing with the other tools. On the other hand, organizations that focus on the human dimension will pay attention to the challenges of training and coaching individuals, and will seek to listen to them in order to better understand the obstacles to tool implementation. Finally, tool assessment may also depend on the preferred dimension. Thus, indicators related to the productivity or use of the tool (functionalities used, number of bugs in the tool, for example) can be mobilized, or on the contrary indicators referring to people’s perception and experience with the tool or their well-being and autonomy.

The fourth dimension refers to the factor that triggers change: the need to adapt to market developments, economic problems, as well as changes in management teams, employee proposals, etc. Van de Ven and Poole (1995) thus make the “generating force” of change a differentiating factor between four ideals of organizational change, and identify four types of generating force: institutional or regulatory changes, competition and the market, internal organizational conflicts, and the collective and consensual definition of new objectives. Indeed, the triggering factor of change strongly influences the discourse held on the necessity and legitimacy of change, which constitutes a key element of the change management strategy, as we have seen (Philips, 1983). Box 5.12 thus returns to the rhetoric of the need for change in work organizations.

The pace and frequency of change (dimensions 5 and 6) are important and interrelated dimensions. Thus, some organizations, because of the sector in which they operate as well as intrinsic characteristics, have a culture of permanent and rapid change. Weick and Quinn (1999) refer to this type of change as “continuous change”. In contrast, other organizations are characterized by a change that is described as “episodic”, less frequent and with a shorter time frame. Weick and Quinn then suggest that two paradigms of change should be distinguished. The first, described as “Lewinian”, is based on the following assumptions: organizational inertia, linearity of changes and developments, progressive development and the pursuit of objectives. In this model, change results from an imbalance or external intervention that makes the original organization obsolete. Conversely, the second model, described as “Confucian”, is based on the following assumptions: cyclical and permanent organizational movement, permanent change and no organizational inertia. Thus, the first model seems more suitable for studying and leading episodic changes, and the second for continuous changes.

Finally, the characteristics of the organization constitute a dimension that strongly structures change (dimension 7). Thus, Mintzberg (1979) identified “contingency factors” affecting the structure of organizations and the distribution of power within organizations: age, size, sector of activity, etc. However, the structure and distribution of power, in turn, affect how change is approached (see Box 5.13).

The wide variety of situations linked to change therefore makes it difficult to formulate a single prescriptive model linked to a change management strategy. Moreover, a model such as the one proposed by Philips (1983) does not specify the content of phase 3 (“defining and implementing concrete actions related to change”), which seems to constitute the crucial phase of a change management strategy.

5.3.2.1. Managing unlearning and skills acquisition

We have listed the conditions for the emergence and production of technological innovations that respect individuals within organizations. The ability (collective and individual) to unlearn seems to be a common denominator under these different conditions. However, this requires that organizations manage their skills in a way that respects these cycles of unlearning and innovation.

The literature on organizational innovation highlights the importance of moving beyond pre-existing rules and procedures for the development of innovation (Alter, 2000). This is all the more important in the field of responsible technological innovation, which also challenges the usual codes of innovation. However, this “unlearning” contrasts with the current logic in work organizations. Drawing on Schumpeter’s work and the expression “creative destruction”, Alter (2000) shows how much innovation and adoption of innovation require breaking free from socially established rules. This is all the more true in the business world, where there are two contradictory injunctions represented by the need for innovation and renewal and the need to respect codes, rules and procedures. He thus gives examples where an innovation that was rationally interesting could not be deployed in organizations. Beyond the world of work, there are many examples of technological innovations whose deployment is contrary to established habits and rules (see Box 5.14).

These examples illustrate a phenomenon known as path dependence (Arthur, 1989). Arthur points out that in the field of the adoption of new technologies, yields are increasing, in the sense that the more a technology is adopted, the more significant its use is, therefore the more improvements it will benefit and the more other technologies will be added to it, which will reinforce the adoption of the first. He then examines the adoption of competing technologies and shows that, in many cases, the technology that ultimately wins the competition for adoption is not necessarily the most “effective”, but has benefited from sometimes minor circumstances that led to its adoption first, and has quickly become a dominant or even monopolistic technology. In addition to the example of the Dvorak keyboard mentioned in Box 5.14, he illustrates his point with the example of nuclear power generation in the United States. Nuclear energy can be produced with light water, heavy water, as well as gas or sodium. However, in the United States, the nuclear industry is largely dominated by light water reactors, a choice that dates back to the first nuclear submarine (1954), while gas-fired reactors seem rationally more suitable.

Path dependence is also present in work organizations, for at least two reasons. First of all, working requires relying on a number of tools, know-how and “ways of doing things”, which are all habits that are difficult to change. Thus, introducing a tool into an organization that requires changes in processes or work habits is always tricky and sometimes doomed to fail (see Box 5.15).

Secondly, as Alter (2000) points out, work organizations are based on a set of rules and processes that are difficult to challenge, which hinders innovation capacities. According to this sociologist, who partly takes up Schumpeter’s (1999 (1926)) work on the subject, the “entrepreneur”, i.e. the individual who wishes to propose an innovation in an organization, cannot be part of the rationalist aim of management, since he does not have previous experience or data enabling him to legitimize the interest of his innovation. In addition, the entrepreneur also faces individuals whose activity may be modified, or even threatened, by innovation. Therefore, it is in the entrepreneur’s interest to comply with the organization’s injunctions in the first instance, or even to conceal the potential effects of their innovation, until the latter’s interest is recognized within the organization. The entrepreneur is therefore always at some point in a situation of deviating from the organization’s rules: they must go beyond these rules, overcome them and probably sometimes unlearn them to be able to carry out their project successfully.

While innovation requires some form of unlearning, this seems even more true for responsible technological innovations. Indeed, these innovations require a double renewal, technical and societal, as we have seen. In the previous section, we listed the conditions for the emergence of social innovations: reasoning outside established structures and concepts; putting the issue of economic and financial profit in the background; and linking the social dimension to the technical dimension. However, these conditions require unlearning ways of working that are deeply rooted in most work organizations. Indeed, the question of economic and financial profit remains most of the time the main issue for profit organizations. Moreover, as the previous chapters have shown, the decoupling of technology and social issues remains common, and success in linking the two therefore requires an unlearning of this decoupling. Finally, responsible technological innovations are also characterized by the networking of a number of actors not used to cooperating, for example large multinationals with local workers, or multinationals with associations. This once again requires a review of pre-established patterns of cooperation between the different institutions. The intrapreneurs mentioned in Box 5.9 have therefore had to insist in some cases in order to convince their organization to set up new partnerships with these unusual actors.

However, unlearning is not necessarily seen as legitimate within work organizations, which are based on the rhetoric of building up skills rather than practices that challenge existing ones (Kuhn and Moulin, 2013). In fact, many factors can hinder “organizational unlearning” (Tsang and Zahra, 2008; Kuhn and Moulin, 2013):

• – the organization’s length of existence;
• – training seen only in terms of adaptation to the workplace;
• – very settled work routines;
• – rigid processes and rules.

Thus, it is sometimes difficult, if not impossible, for organizations to promote the unlearning of rules, routines and skills.

5.3.2.2. What kind of skills management?

However, unlearning is not enough: as Chapter 4 has pointed out, it is also necessary to be able to acquire and appropriate new skills (including knowledge, know-how and meta-knowledge; see Aubret, Gilbert and Pigeyre, 2005). Indeed, technological change is often accompanied by the emergence of new skills necessary to produce technological innovation as well as to seize it. Thus, as Chapter 4 noted, digitalization has gone hand in hand with the emergence of skills linked, for example, to communication on social networks or the use of digital tools. In addition, recent decades have seen an acceleration of change, leading to more uncertain predictions of the skills needed for work organizations. It then becomes necessary to disseminate interdisciplinary skills which are useful whatever the development of the organization (Aubret, Gilbert and Pigeyre, 2005). Two HR processes are particularly relevant: recruitment and training (Cadiz and Pointet, 2002).

Recruitment allows individuals with new skills to enter the organization. It is particularly suitable in situations where a skill is difficult to develop internally. For example, nowadays, organizations are trying to recruit data scientist profiles, knowing that data expertise requires a significant amount of training time and high expertise, which makes it difficult to develop these skills internally.

The link between recruitment and technological change is twofold: an organization may want to recruit people who can propose innovations, or people who have mastered new techniques to capture innovations. In the first case, recruitment involves an assessment of a person’s potential for innovation. This can be a particularly difficult exercise because the potential for innovation is not measured against the most traditional recruitment criteria (diploma, professional experience, etc.). This may then require organizations to renew their recruitment process and criteria. This explains the development of new recruitment tools, such as the escape game or the video CV, which allow candidates to distinguish themselves with atypical skills. Moreover, recruiting a person with high innovation potential is limited if the new recruit must then comply with the organization’s codes and requirements, which can, on the contrary, hinder the spirit of innovation (Alter, 2000). In the second case, recruitment requires the assessment of expertise, which is done, for example, through the diploma criterion. However, this criterion loses its relevance with the development of self-study movements, particularly in the field of computer science (many self-taught people learn code or new computer languages by their own means). As a result, other recruitment practices are developing, such as hackathons, which allow candidates to be assessed in real IT development situations (see Box 5.16).

Work organizations may also choose to develop and disseminate skills internally. This then involves training aimed at developing the innovation potential of individuals or enabling them to appropriate new technologies without having to resort to external recruitment. Three training models stand out in particular: a vertical top-down diffusion model of skills (from top to bottom, through company training, for example), a vertical bottom-up diffusion model (from bottom to top, through reverse mentoring, in particular) and a horizontal diffusion model (by peers).

Some companies set up ambitious and costly training plans, sometimes based on internal trainers, particularly in large companies. This training can be useful in disseminating work rules and procedures. In the case of technological change, such training can be mobilized to support change, for example, in the case of the implementation of a new work tool (Aladwani, 2001). Training then becomes a means of encouraging employees to use the new tool (see Box 5.17).

On the other hand, training of this type does not seem to be well suited to developing the innovative potential of individuals. More recently, companies have experienced a development in reverse mentoring, which characterizes situations where individuals are led to train people who are higher up in the hierarchy or have more years of experience. This system is particularly well suited to the dissemination of skills considered new (e.g. related to new digital technologies), or to the development of the organization’s innovation potential. Indeed, the younger generations are considered to master these new skills more easily and to have a higher potential for innovation because of their new view of the organization than the older generations (see Box 5.18).

Finally, some topics and work environments are more suitable for the horizontal dissemination of knowledge through a system of peer-to-peer exchanges. This peer-to-peer diffusion experienced several transformations between the 20th and 21st Centuries, from communities of practice to networks of ambassadors and networks of collective competence (Alter, 2000). Communities of practice, like companionship, are made up of groups of individuals who work together or on the same subject, and are thus led to find together and share among themselves solutions to practical and concrete problems in their daily work. Networks of ambassadors are made up of employees who, on a given subject, will be identified as being able to help or train their colleagues (see Box 5.19).

Finally, innovation in work organizations requires a form of unlearning, all the more so when this innovation goes against the usual reference frameworks (pursuit of profit, efficiency, myth of technical rationality, etc.), as is the case for social innovation. However, this unlearning must go hand in hand with skills management to develop and disseminate the skills required to innovate and keep pace with technological change.

5.3.2.3. Strategies for managing technological change

To conclude this book, we mobilize the contributions of the previous sections to address the question of the management of responsible technological change and thus provide some recommendations in this area.

The contributions of the previous sections allow us to identify the specificities of technological change and how change management can take them into account (see Table 5.6).

Thus, the first dimension concerns the management of risks related to technological change identified in the first section of this chapter. The challenge for work organizations is to limit these risks or the effects of these risks on individuals. This involves, in particular, efforts to support employees, for example, by redeploying employees whose jobs may be lost, or by training employees to ensure that they have the necessary skills to cope with this change. The example of digital ambassadors mentioned above (see Box 5.19) illustrates how a company can try to ensure a good diffusion of digital skills. This also requires upstream reflection on the consequences of technological change for individuals and the social climate, and raising the awareness of the various actors on certain subjects: stress at work, discrimination and ecological degradation in particular. With regard to stress at work, it may be appropriate to put in place stress measures specifically related to technological change. In addition, involving expert actors in the fight against discrimination and sustainable development (internally, the diversity department or the CSR department, for example, as well as external consultants if necessary) from the outset of the change project can help to limit the risk of discrimination and ecological degradation. Finally, the risk of alienating individuals by technology can be avoided or reduced by taking into account the criterion of the room for maneuver left to individuals when choosing technologies and making changes.

The second dimension concerns the participation of workers in the production and diffusion of innovation. This point, discussed in the second section of this chapter, is divided into two sub-dimensions. Firstly, we discussed the notion of social or responsible innovation, and how this notion partly responds to the risks inherent in technological change. Therefore, one way for organizations to ensure responsible technological change is to integrate into the change process the principles of responsible innovation: to verify that technological change responds to a real need, that it has a human dimension and not only a technological dimension, or that the change process puts people at the center. This refers to Figure 5.2 and the distinction between a process that focuses on technical aspects and one that focuses on human aspects. Then, in connection with the notion of social innovation, we stressed the need for employee participation in change. We also pointed out (in the third section of this chapter) that, while organizations regularly issue injunctions for change and innovation, internal codes and procedures often stifle creativity. Therefore, ensuring employee participation in change may require flexibility in these rules, codes and procedures.

The third dimension concerns the notion of unlearning. In the third section, we pointed out that unlearning (of ways of working, as well as of codes and conventions) is an essential condition for technological change, but that organizations often see unlearning as a failure. Accepting the disappearance of certain skills seems to be both a difficulty and an important issue for organizations.

The fourth dimension concerns the management of technical skills. The management of technological change influences key processes such as recruitment and training. In the context of recruitment, it is a matter for organizations to recruit people with a potential for innovation or mastering new technologies. In both cases, this requires a reflection on the recruitment process and the mechanisms used to select applications: exercises to assess potential or the command of a rare technological skill. We have thus given the example of hackathons for assessing mastery of the most advanced computer skills (see Box 5.16). On the training side, in the same way, organizations can have two objectives: to develop the innovative potential of individuals, or to train them in new technologies. Once again, this may require mobilizing original training mechanisms differently from top-down company training: reverse mentoring, networks of ambassadors, etc.

5.3.3. An integrative scheme for the management of responsible technological change

Finally, the management of technological change, while taking up certain dimensions of change management in general, has specific features that should be kept in mind when setting up a strategy in this area. In this last section, we propose to combine the contributions of the two previous sections to propose an integrative model of responsible technological change management. We thus use Philips’ (1983) model, presented in Figure 5.1, adapting it to take into account the various elements mentioned above, and, in particular, to recall the risks inherent in technological change and the actions that organizations can take to limit them (see Figure 5.3).

Thus, in the case of technological change, the first phase, which corresponds to the construction of a consensus on the need for change, presents a risk (linked to the technicist ideology) of illusions about the validity of technologies and therefore of technological change. At this stage, the actions to be taken to limit this risk are aimed at ensuring that this change meets a real need and fully understanding the potential negative effects of the technology. Mobilizing the principles of social innovation can be a solution at this stage (technological change must meet a need, have a technical and social dimension, put people at the center).

The second phase refers to the definition of a specific technological change. This phase presents several risks related to the technology in question: this technology may be alienating, discriminatory or contribute to ecological degradation. In addition to ensuring that the technology meets a real need, involving experts in the fight against discrimination and sustainable development in the choice of technology can help to limit these risks.

The third phase corresponds to the definition of the actions necessary to support technological change. The main risk in this phase is to focus on the technical dimension rather than the human dimension (see Figure 5.2). To limit this risk, it is advantageous to carry out actions focused on individuals at work: training and support. Moreover, enabling unlearning seems appropriate to promote the acquisition of the skills necessary to appropriate a new technology.

The fourth phase, which we have added to Philips’ original model, is aimed at evaluating technological change. This assessment may be limited to technical aspects (productivity gains or the number of bugs in the tool, for example). Conversely, assessing a technological change that is more respectful of individuals and more sustainable may also involve assessing the effects of change on individuals (technostress, well-being at work) and individuals’ perceptions of change.

Finally, the fifth phase refers to the institutionalization of the new organization or the new technology. This institutionalization involves, among other things, the formalization of new rules, new procedures and new ways of working linked to the new technology. The main risk then lies in excessive formalism and in the definition of rules and procedures, leaving little room to maneuver for individuals, which again highlights the notion of alienating technology. To limit this risk, organizations must ensure that they maintain flexibility in the appropriation of technology.