3.1.1. The R&D function in the lead¹

The R&D function has always maintained a close link with digital technologies, compared to the company’s other tasks. Not only are these technologies designed quite extensively by R&D, but they have sometimes been designed first for R&D and then extended to a wider audience. The world of R&D therefore has a more daily, and in a way “natural”, relationship with these technologies.

For years now, R&D has been experiencing the use of a wide range of digital tools. This is the case for those that enable a very fast and low-cost flow of information: messaging, the Internet, electronic databases, online scientific journals and specialized social networks. Scientific monitoring, literature reviews and cooperation between researchers are greatly facilitated.

By accelerating computation and reducing the resources required to perform a test, digital tools increase the efficiency of R&D. They also make it possible to make the results more reliable, because the experiments have been replicated over a larger number of tests and computer-aided design (CAD) tools leave less room for error than hand-operated drawings, etc. But these tools also transform the way of working and support the development of new skills and innovations.

Collaborative tools make it easier to work with others and remotely. In internationally fragmented R&D networks, in multi-organizational R&D partnerships, these tools are valuable. The development of online virtual communities, specialized social networks, wikis, Internet forums, etc., provides new spaces for the exchange of ideas, inspiration and learning.

Digital equipment is also changing the way we work, because of the new possibilities it opens up in terms of prototyping. This is particularly the case in software development. Tools such as 3D printers make it possible to materialize ideas at a fairly early stage and very easily. It is now possible to test the ergonomic character of an object, check its compatibility with another, etc. Other technologies such as virtual reality and augmented reality make it possible to project a user into experiences of using a product at intermediate states of realization, facilitating very rapid feedback from customers.

Finally, digital technologies offer many possibilities to involve customers in design processes: crowdsourcing platforms, remote data collection and use, physical or virtual prototype testing, etc.

3.1.2. Marketing challenged by digital transformation

In the marketing function, which is essentially open to new ideas, “digital marketing” has become very important. It consists of promoting products and services and interacting with the consumer through the available digital technologies. It has become an essential component of a marketing strategy.

Digital marketing concerns both operational sales activities (prospecting by emailing and other means of electronic promotion, online sales) and strategic brand policy activities (use of social media, brand blogs, etc.), as well as customer loyalty (community animation using chat tools, mobile applications, “in-store” interactions by digitizing the point of sale).

Even more profoundly, the development of digital technology is changing interaction with consumers and potentially creating a new paradigm (Quinton, 2013). The digital world makes more data available to consumers who can easily compare product performance and prices. With one click, they can switch from one sales site to another and have the product delivered to their home as soon as possible.

The development of social networks disrupts consumer relations with brands, from a simple conversation between the service provider and consumers to a multitude of exchanges between customers themselves on forums, through co-creation, brand communities, communication via mobile phones or online games, etc. (Iglesias and Bonet, 2012). Shared dissatisfaction with a product or service can affect a hard-won brand image. This phenomenon requires new skills that the actors in the marketing department do not always possess.

From a more global perspective, the market can be seen as a carrier of symbolic resources that allow consumers to tell their stories by building their identity. However, digital technology affects the relationships that individuals maintain, through the products they use, with others and with themselves.

Belk (2013), a North American marketing professor, is at the origin of an extended self theory which postulates that beyond a core self, other elements (objects, people, places, ideas, experiences) gravitate towards the person’s history and define it. In this context, a smartphone, a computer or any other digital object can fall within this status and constitute an extension of oneself. Belk questioned the relevance of the notion of the self in a digital world. He identified five major changes that also have an impact on marketing:

• – the dematerialization that the digital age has extended to the entire sectors of the economy, particularly cultural goods (music, films, books, etc.);
• – reincorporation, which allows an individual to appear in various forms, with the use of avatars in video games, as well as in blogs or social networks;
• – sharing with a circle of acquaintances whose scope has considerably expanded with social networks that allow individuals to be in contact with others who are geographically very distant;
• – co-construction of the self, linked to the intensification of sharing (especially with photos of an object that you would like to acquire) that allows an individual to obtain rapid feedback and thus to reassure her/himself about his/her choices or perceptions;
• – distributed memory, because everyone’s life is now delivered by Google in small pieces that fit together more or less successfully.

3.1.3. Factory 4.0

Obviously, “factory” does not spontaneously rhyme with digital technologies. However, industrial activities, although considered more traditional, are not to be outdone. The notions of the factory of the future, industry 4.0 or even the connected factory, became very popular at the end of the 2010s. They constitute one of the European Union’s strategic axes, together with the “Horizon 2020” and “Factories of the Future” programs. In general, the idea of stopping the deindustrialization of developed countries is nowadays a necessity, and digital technologies are called for as a reinforcement.

Without being the only ones concerned, the manufacturing industries will be profoundly affected. According to the Fédération des industries de la mécanique (2015, p. 21–22), ICTs (Information and Communication Technologies), which pave the way for the connected and digital factory, should make it possible to deliver:

“– continuous, instant and integrated communication of information relating to production processes (design, manufacturing, logistics and maintenance) and manufactured products;

– the simulation of the product, process, workstation and even the factory, logistics and supplier chain;

– self-diagnosis and self-adaptation of production processes and equipment and continuous product monitoring” (authors’ translation).

To meet these needs, the Boston Consulting Group, an international strategy consulting firm, has identified nine technologies that are transforming industrial production (Gerbert et al., 2015):

• – Big Data and analytics: the presence of sensors on machines and products facilitates the collection of large datasets from many different sources. With appropriate processing and analysis tools, this data makes it possible to optimize the production chain by identifying in a very detailed way the problems that arise in relation to an increased knowledge of customers’ habits and preferences;
• – autonomous robots: manufacturers in many industries have long used robots to tackle complex tasks, but robots are evolving to be even more useful. Advanced robotics now makes it possible to create robots that are cheaper, more autonomous, more flexible and capable of greater cooperation with humans;
• – simulation: 3D simulation of products, materials or processes extends to the entire production chain. Real-time data acquisition offers the possibility of refining models to better reflect reality and allow operators to optimize machine settings;
• – horizontal and vertical integration systems: information systems facilitate integration and communication within and between companies, functions and services, and between companies in order to automate value chains;
• – Industrial Internet of Things: with the multiplication of sensors on machines and products, even unfinished ones, machines can know the production history of the object, the corresponding final demand in order to respond in a fully automated way or through global control of the manufacturing process;
• – the cloud: cloud storage is already widely used for software and data management. As its performance improves, data and machine functionality will be increasingly deployed in cloud storage, making it easier to share large amounts of data;
• – additive manufacturing: beyond the production of prototypes, 3D printing already enables the production of complex parts, spare parts and even customized tools in small series. The speed and accuracy of printing should increase and allow, in some cases, large-scale production. In addition, efficient and decentralized additive manufacturing systems will reduce transport distances and available stock;
• – augmented reality: this technology, which is still in its infancy, will be able to support a wide range of services, from sending instructions to repair a damaged part on a mobile device to providing real-time information to operators on the operation of an installation or even training;
• – Cybersecurity: with the increase in connectivity (presence of sensors generating data, communications within and outside the company), the need to protect critical industrial systems and manufacturing chains against threats is increasing and cybersecurity is becoming a major challenge for industrial companies.

Factories are therefore also deeply concerned by digital technology, whether it concerns, to use a few illustrations, prototyping (rapid prototyping and printing of unit products via 3D printing), manufacturing (simulation before starting production, collaborative robotics, Internet of Things, etc.) or maintenance (preventive maintenance by anticipating the replacement of parts or systems through Big Data, remote maintenance of industrial machines, etc.). On the periphery of production, traditional activities such as logistics are at the forefront of modernity with voice recognition, which is used in order preparation or automatic goods movement systems (automatic conveyors, guided carts, etc.).

But to meet their industrial challenges, companies are not relying solely on digital technology, as in the case of the Fonderies de Sougland, an SMI based in northern France for nearly 500 years that combines digital technology, reorganization and employee empowerment (see Figure 3.1). This case – it is far from being isolated – also shows that digital transformation is not only for large high-tech companies.

3.1.4. e-HR

No activity escapes the “digital revolution”, including those areas that were seen by non-specialists as less technical and less likely to receive significant contributions from digital technology. This is the case for the human resources role.

Indeed, in human resources departments, the challenge is twofold. On the one hand, as with other support roles, it is a question of taking advantage of the facilities offered by new technologies and the cost reductions they allow. Thus, many start-ups now offer digital services to automate some of the tasks assigned to the HR function (e.g. CV pre-selection, administrative management of employees). The progress made in the field of HRIS (Human Resources Information Systems) therefore makes it a cost reduction lever today. But, on the other hand, it is also a question of modernizing the company’s image and thus attracting and retaining young talents, accustomed to using digital tools. These two issues (reducing HR role costs and at the same time attracting candidates and retaining employees) may seem contradictory. We illustrate them by referring to the effects of digital technology on some key recruitment and training activities (see Table 3.1).

3.2.1. Technological change and organizational structure

The study of the succession of technological changes in the 19th and 20th Centuries in the Western world identifies two phenomena that highlight the profound links between technological change and organizational structure. First, the structure of an organization affects its organizational capacity; but, as a result, the need for innovation also encourages organizations to focus on certain organizational structures.

Caron (2010) identifies several stages in the history of technology between the 16th and 20th Centuries in the Western world. He shows, in particular, that between the years 1830 and 1960, four main categories of actors emerged and had to coordinate themselves around technological research: companies, trades, engineers and universities. In particular, since the 1880s, the emergence of large companies has profoundly changed the technological landscape. Indeed, these companies have developed planned research strategies, and policies to appropriate the knowledge produced, by the patent filing system. In the United States, Edison is the embodiment of this movement (see Box 3.1).

The French automotive industry is a second example: the brothers André and Édouard Michelin, Armand Peugeot and Louis Renault, created great industrial empires based on innovation (the dismountable tire for Michelin, for example) and greatly contributed to the development and dissemination of innovations to the general public. These two examples show the important role that companies have played in technological change.

The success of large companies in the field of technological innovation depends largely on their ability to limit the risks inherent in R&D activity, as well as to monetize the knowledge produced. The process of national and then international concentrations of companies in certain fields, such as synthetic chemistry, is an illustration of this. Caron (2010) explains that, from the end of the 19th Century until World War I, companies in the technological sectors tended to group themselves into national and then international oligopolies, in order to pool research efforts and the knowledge and innovations produced. These large groups or companies, such as Bayer in Germany, opted to create integrated research laboratories alongside the establishment of partnerships with public laboratories. This internalization of research allowed them to have groups of employees dedicated to producing knowledge and to controlling the dissemination of this knowledge. Thus, this strategy was accompanied by massive patent filings to protect the knowledge produced, or by scientific publication strategies aimed at disseminating knowledge on behalf of the company. Caron (2010) and Chandler (1992) give the example of General Electric’s laboratory (see Box 3.2).

The example of General Electric, or more generally the fact that many companies set up internal research laboratories dedicated both to fundamental and applied research at the beginning of the 20th Century, clearly shows the role of the company as an actor of technological change and the importance of the organizational structure in this role.

Beyond the internal laboratories at the beginning of the 20th Century, companies have also gradually adopted other organizational structures more favorable to innovation, of which we give two examples here: the network structure and the extended enterprise.

The network structure dates back to the 1980s. This type of organization is based on the decentralization of tasks and institutionalizes the operation in business units, to the detriment of hierarchical functioning. These business units benefit from the proximity of the field (market, for example), as well as from the ease with which knowledge and innovations can be disseminated between units. Several studies have shown the usefulness of this type of organization in the field of innovation (Tsai, 2001). However, this represents a reversal of the pyramidal hierarchical organization common in the 20th Century and therefore requires an adaptation of human resource management practices, with, for example, the mobility of researchers between units (Gilbert et al., 2018).

The extended enterprise goes even further than the networked enterprise by setting up inter-company cooperation systems: co-design, co-development and co-production. In these systems, companies pool resources (material, human, financial, for example) and coordinate to produce together. The advantage of this model lies in the fact that companies focus on their area of excellence, and join up with external partners on elements of the value chain that are not part of this area (Defélix and Picq, 2013). It is highly developed in sectors that require multiple skills or that are involved in several fields of activity (interdisciplinary): the automotive industry or aeronautics, for example. The extended enterprise can also refer to the involvement customers in a product’s design before it is launched on the market: this is the case today with many start-ups that, using crowdfunding, offer individuals the opportunity to receive a test version of the product and to give their opinion on it. Finally, this extended enterprise system is similar to the notion of open innovation, in which companies rely on an entire ecosystem of both internal and external R&D (Gilbert et al., 2018). Like the network structure, the extended enterprise requires an adaptation of management practices, for example, in terms of skills and knowledge management or legal matters.

These new and more cooperative ways of working towards innovation require significant coordination and cooperation capacities. The different groups of actors involved in the development of the project (engineers, researchers in companies, researchers in laboratories, customers, etc.) will have to coordinate themselves around a project of which they do not necessarily have the same vision or knowledge. The work of the sociology of translation, and, in particular that of Star and Griesemer (1989), has focused on this very issue of coordination around scientific research work. They stress the importance of having “boundary objects”, objects in the broad sense of the term (standards, reference systems, work programs, concepts, physical objects), which will enable agreement, coordination and work sharing around an innovation. In particular, these boundary objects must be sufficiently flexible so that each group of actors can maintain its own vision of the project, and sufficiently robust to allow for delegation and work sharing. This notion underlines the importance of adopting less streamlined working methods, leaving room for flexibility and uncertainty in the production of scientific innovations.

Finally, companies have also adopted new ways of working, as more conducive to innovation. These new ways of working may also have led in some cases to the adoption of new types of organization. We give here the example of CAD, developed, in particular, in the book edited by Cadix and Pointet (2002) (see Box 3.3).

These various examples therefore highlight the role of the company in technological change, as well as the profound interdependence between technological change and organizational structure. The school of structural contingency (Lawrence and Lorsch, 1967), among others, provides a clear understanding of this interdependence. According to this school, the environment (competitive, strategic, economic, etc.) is a decisive factor in the structure and performance of an organization. Thus, a particularly competitive environment requiring strong innovation capacities may encourage organizations to adopt the structures and processes mentioned above: creation of internal laboratories, network structure, extended enterprise, digital design tools, etc. From then on, it becomes easier to understand the mimicry and ultimately the homogenization of the structures of so-called innovative companies.

3.2.2. Technological change, and financial and human resources for innovation

Beyond the organizational structure, the question of the financial and human resources that organizations allocate to innovation should not be neglected. In fact, these expenses can be considerable. Thus, in 2012, OECD companies spent US$752 billion on R&D, which corresponded to more than two-thirds of the total R&D expenditure (OECD, 2014). In the same year, Chinese companies spent $224 billion on R&D, one-fifth of OECD spending. These expenses were mainly allocated to experimental research and to a lesser extent to fundamental research.

The OECD has carried out numerous studies on the link between R&D spending, technological change and growth. According to this organization, investment in R&D and employee training is a necessary condition for global growth. Moreover, the most developed economies tend to be more R&D intensive, due to their proximity to the “technological frontier” (the most advanced level of technological research), which requires their industries to innovate to make further progress.

However, investments in R&D and training have rather long-term effects, which can weaken them in times of crisis. For example, during the Great Depression of the 1930s in the United States, patenting declined (OECD, 2015). Similarly, R&D spending decreased during the 2008 crisis, except for the companies that invest the most in R&D globally, which maintained their efforts during the crisis.

In this context, the OECD is particularly interested in public policies aimed at supporting companies’ innovation efforts. These policies acknowledge that the costs and uncertainty associated with R&D, as well as the payback period and the non-rivalled and non-exclusive nature of R&D, can be a barrier to business investment in this area. They also acknowledge that companies’ R&D efforts can benefit a country as a whole, by contributing to the dissemination of knowledge and innovations, and because of their potential economic benefits. In France, for example, which is one of the most generous countries in terms of indirect support for R&D³, this includes the Crédit d’impôt recherché (a research tax credit) (see Box 3.4), and PhD contracts in companies (CIFRE; see Gilbert et al., 2018). On average, in the OECD, direct and indirect government funding of R&D represent between 10% and 20% of business R&D expenditure.

Business expenditure on R&D can take a wide variety of forms, from providing premises for researchers to purchasing machines, the hiring of research staff, financial support for public research, etc. Whatever their form, they give a good idea of the role of companies in technological innovation and the importance they attach to the subject.

A particular form of means allocated by the company to innovation can also be identified: human resources. Again, this support can take many forms. The creation of internal laboratories, already mentioned and now well established in large companies, is of course one of them. More innovatively, some companies seek to take into account the fact that employees themselves can innovate, sometimes outside any established circuit, any institutionalized structure. They will then seek to stimulate and encourage this creativity, which can take various forms. At Google, for example, since 2004, employees have had working time (one day a week) dedicated to developing their personal ideas and projects related to Google’s overall business. This system was linked to an internal collaborative platform, Google Labs, allowing exchanges on projects and ideas. Two of Google’s most profitable projects were born from this device: Gmail and Adwords. Even if the reality of this 20% rule is subject to debate, the fact that Google communicates on the subject and that this device has such a media success clearly shows the need for companies to record and make visible the innovation potential of employees. At Orange, an international system allows employees in each country to submit their innovation ideas (service, product or organizational) on a platform for expert evaluation. This system was then extended, as in other companies, by an internal incubator system (see Box 3.5).

Intrapreneurship schemes are increasingly developing in all areas where companies need to innovate. Intrapreneurship refers to schemes that allow employees of a company to carry out an innovative project while maintaining their salary status. These measures have two complementary objectives: to capitalize on a potential for innovation (employees) and to retain employees with innovative ideas who may be tempted to develop them in a less restrictive framework than that of large companies. They must therefore have several characteristics: selection of the most promising ideas, creation of a space and ecosystem conducive to new ways of working, more agility and proximity with regard to small businesses and provisioning of means and resources specific to large companies. They therefore represent costs for the company. However, the success and dissemination of such schemes illustrate the importance for companies of encouraging innovation among their employees. The example of Crédit Agricole, a major French bank, supports this point (see Box 3.6).

Finally, this section highlighted the major role played by companies and organizations in technological change. Two elements were particularly highlighted: the organizational system, and financial and human resources. We also stressed that the search for technological change has an impact on organizations, particularly on organizational structures.

3.3.1. Prescriptive and assistive technologies

More specifically, the same technology can be used as a prescriptive tool or as an aid tool, and the effects on employees can therefore differ significantly. Thus, the same technology can become a control or empowerment agent.

3.3.2. Technological ambivalence: the same technology for empowerment and control purposes

This blurring of the distinction between prescriptive and assistive technology may explain why the same technology may be used by organizations for empowerment or control purposes. More precisely, it also illustrates the fact that, as indicated in the introduction, a technology refers to all the techniques, procedures, methodologies, equipment and discourse enabling implementations. This means that a technology can carry several possibilities of implementation.

This phenomenon, described as technological ambivalence, has been studied, in particular, by Ellul (1988), as discussed in Chapter 1.

Technological ambivalence also exists within organizations. In this case, the “negative effects” will refer to the prescriptive dimension of the technology and the notion of control, and the “positive effects” to its dimension of decision support and the notion of empowerment. Thus, the same technology may be used for prescription purposes or as a decision-making aid, which will have very different effects on the social entity.

Several authors have taken an interest in technology as an instrument of workers’ alienation, in a sometimes Marxist approach linking mechanization, capitalism and the appearance of the proletariat. Marx thus made a distinction between craftsmanship, production and manufacturing. Machines are used in production and manufacturing. In the factory, this mechanization is accompanied by a dispossession of the worker: the worker has his/her labor power, but not the means of production (which therefore refers to the notion of capitalism). Marx then denounced the fact that, in capitalist labor, the worker loses both individual freedom and know-how, in favor of a fragmentation of tasks allowed and accentuated by the machine. Weil (1951) repeated this analysis but introduced a form of ambivalence. Having had experience working in a factory, she established a link between mechanization, Taylorization and worker alienation. The machine is indeed a cornerstone of the rationalization of work, by taking on certain categories of tasks faster than humans, or even by participating in the organization of human work, as in the case of chain work. Besides, mechanization is accompanied by a fragmentation of work, which is segmented into small tasks, each worker being deprived of the vision of the finished product in favor of a much more fragmented vision. This fragmentation constitutes a form of alienation; the worker can only be aware of the physical difficulty of their work, and no longer of his/her meaning. However, this Marxist-style analysis is sometimes mixed with much more optimistic statements about technology. Indeed, the philosopher sometimes proposes as a horizon and as a solution a more complete mechanization of tasks, allowing the worker to be free from all the chain work and the most physically demanding tasks. This apparent contradiction is a good illustration of technological ambivalence: the machine can be considered as a tool of human alienation, but progress in mechanization could, to some extent, contribute to the worker’s empowerment, avoiding the most fragmented and painful tasks.

More recently, the digitalization of companies offers us many examples of such ambivalence. For example, the use of electronic messaging, which has spread very rapidly and is now widely used in companies, can have several effects. Electronic messaging facilitates exchanges by shortening the time it takes to receive information. It has thus enabled telework to develop, whether in the form of cooperation between geographically remote sites or in the form of telework. Telework can be seen as an instrument for liberating workers, allowing them to work from a place of their choice, without being subject to the constant presence of their colleagues and superiors. But on the other hand, both sending and receiving emails can be tracked relatively easily, which then gives a particularly controlling manager the opportunity to check at what times the members of his/her teams work and process their emails. In France, for example, case law thus gives the employer the right to control and monitor employees’ activity on the Internet or via email, insofar as employees are informed of this. Similarly, many corporate computers today are equipped with remote communication software that indicates whether employees are “online” or not. From then on, it becomes easy for a manager to remotely check that members of their telework team have their computer turned on and are connected to the Internet at the times they are supposed to work. Geolocation gives other examples of technological ambivalence: used to manage a company’s fleet of vehicles, it can also be used to monitor where employees are located at a particular time of day. Finally, the rise of internal and external social networks is a good example of technological ambivalence, between empowerment and control (see Box 3.10).

This section has therefore illustrated the notion of technological ambivalence, and clarified it by applying it to the question of organization. We thus have examples of technologies that can be used for empowerment, as well as for control purposes, thereby completing the distinction between prescriptive and assistive technologies presented above.

3.4.1. Changes in the social entity and management methods

We have already highlighted in the first section of this chapter the profound interaction between the technological and organizational systems. Thus, we explained that certain structural forms, or forms of work organization, could more easily bring about technological innovation. However, beyond this phenomenon of concordance between the objective of the organization and its structure, the interaction between the technological and organizational systems also stems from the fact that the organization constitutes above all a social system, which can be modified by the introduction of a new technology. This is why this introduction is never self-evident: employees must take it on board, sometimes contributing to forms of diversion. The perspective used here to analyze the meeting of technical objects and employees is rather sociological. We will take up the subject from a more psychological perspective in Chapter 4.

3.4.1.3. The appropriation of technological change by employees

However, the organization’s adaptation efforts are not enough: in many cases, the introduction of a new technology within an organization also requires an effort of appropriation by internal actors (employees). However, this appropriation⁷ may ultimately lead to a form of misuse of the technology: new uses may appear, instead of the uses initially planned by the designers of the technologies.

3.4.2. Support for employees whose activities are threatened by technological change

Beyond this appropriation dimension, technological change is linked to social or societal change when it has an effect on activities and jobs, which has been relatively common during major industrial revolutions, as discussed in Chapter 1.

More recently, computerization and digitalization have also contributed to new replacements of human by machine, leading to a question, now very present in the public debate, about the potential end of work. Indeed, computerization and digitalization offer many opportunities for business automation. Advances in artificial intelligence, for example, which refers to the construction of machines that reproduce or imitate human reasoning and capabilities, make it possible to develop programs that can perform increasingly complex tasks, not just simple and repetitive tasks, such as the machines described by Marx. One of the particularities of current technological progress then lies in the fact that machines can nowadays supplant humans in their intellectual activities, and not only physical ones (Harari, 2018). Thus, artificial intelligence has many applications today, from visual recognition to automatic natural language processing. Some jobs are strongly affected by these technological changes, and two cases in particular arise: jobs that are likely to evolve and jobs that are likely to disappear. In both cases, the organization’s support of employees is necessary.

3.4.3. The actors of technological change in organizations

We highlighted the intertwining of technological and social change, the role of organizations, organizational polyphony, the need to support employees, etc. These different elements highlight the key role of certain actors inside and outside the organization:

• – the technological actors, first of all, who will design the technological change;
• – the decision-making actors, who will take the decision to introduce this change in the organization;
• – trade union actors, who will influence this decision;
• – employees and users, who will contribute to redefining the scope of this change through their appropriation;
• – finally, technological change is embedded, as we have seen in the organization, in a more global ecosystem, including, for example, consultants and start-ups.

Finally, this section summarizes the contributions of this chapter by specifying the outlines of technological change in organizations.

3.4.3.1. Technological actors

Technological actors design technologies and, in this way, contribute to defining aspect of technological change. As we have seen, many technological actors are located outside the organization: researchers, engineers belonging to companies proposing technologies, etc. However, in some cases, technological actors are located within the organization itself. This is the case, for example, for IT services, which can develop new software or new internal technological solutions. For example, some companies have taken the gamble of developing their own payroll or training management software. However, internal technological actors may suffer from their lack of specialization and time to devote to research and innovation. This is why, as we have seen, some companies are trying to create conditions that encourage employee participation in innovation, such as intrapreneurship programs.

3.4.3.2. Decision-making actors

Decision-makers decide on the introduction of a new technology into the organization. This decision can be based on several types of rationality.

The search for productivity gains is regularly put forward as an argument justifying the introduction of a new technology. Thus, the massive computerization of companies and, in particular, of administrative work since the 1980s is largely in line with this logic (Pichault, 1990). Similarly, all automation technologies contribute to productivity gains.

However, other rationalities may also be at work. Thus, the fear of missing a technological milestone can contribute, as well as the desire to imitate competitors. Currently, some areas produce innovations very regularly, thus contributing to constant technological change. This is the case, for example, in the field of mobile telephony, which has seen a succession of touch screens, 3G, 4G, 5G, color screens, fingerprint reading or facial recognition, and soon flexible or foldable screens or personal assistant applications. This sector is just one example of the rapid pace of technological change. This speed and probably also the difficulty of anticipating change can lead organizations to fear that they will be overwhelmed by technological change that they would not have seen coming. This can then encourage decision-makers to introduce the vast majority of new technologies into their organization, without always questioning their meaning and contribution. Moreover, in a context of uncertainty, organizations have a strong interest in developing a form of mimicry, i.e. in aligning themselves with the behaviors of other organizations. As a result, if a large company decides to introduce a change, competing companies may tend to make the same decision. This is what neo-institutional theorists call mimetic isomorphism: DiMaggio and Powell (1983) explain that most forms of technological–organizational changes at the end of the 20th Century came not from a search for efficiency and rationalization, but from a process of homogenization of organizations. They point out that, in uncertain environments, when organizations’ objectives are ambiguous or the environment creates uncertainty (competition, technological change, etc.), doing the same as competitors in the sector seems the best strategy to adopt to limit the risks of failure. The disadvantage of this strategy is that the transferability of some changes is limited. As we have seen, the success of the introduction of a new technology depends largely on its adoption by users and therefore on the company’s context. Implementing a new technology for the sole reason that a competing organization has done so may result in a failed adoption.

Finally, the decision to introduce a new technology into an organization can meet several types of rationality and thus pursue different objectives.

3.4.3.3. Trade union actors

Once the introductory decision has been taken by the decision-making actors, the trade union actors can help to define the outlines and modalities of this introduction. In some countries, such as France, trade unions are required to be consulted when a new technology is introduced that could change working conditions.

However, the different unions in a company may have different strategies for technological change. This is a phenomenon described by Pichault (1990) for Belgium: some unions favor a negotiation strategy, others reformism, others opposition. However, whatever their strategy, unions generally agree on several types of demands: maintaining membership, avoiding deterioration in working conditions, protecting individual freedoms.

Several difficulties may arise for trade unions and decision-makers when discussing the introduction of a new technology. Firstly, it is often difficult to anticipate the effects of this technology on the volume of long-term employment and working conditions. Indeed, as we have seen, the same technology can finally be used in a very different way by different line managers, and thus lead to variable situations for employees. Secondly, the social entity may present very different demands regarding technological change: some employees will demand more efficient equipment, more modern software, more efficient machines, while others will be suspicious of the introduction of these new features. Therefore, taking into account the variety of these points of view is a major difficulty. Negotiating with trade unions on these issues can then provide some assurance that different points of view are taken into account (see Box 3.16).

3.4.3.4. Employees

As we have seen, the employees, agents and, more generally, the users who will use the technology will also contribute to redefining its outlines.

Through their use of the new technology, they will strongly define the outlines and limits of the technological change initially planned by designers and decision-makers. We have thus given examples of companies that, having implemented software, finally found that employees kept on working without the software. Conversely, in other cases, employees may themselves be drivers of technological change, introducing new ways of working into the company through new technologies, software or applications. For example, today, many employees whose organizations do not offer mobile instant messaging or file sharing services use external applications such as WhatsApp to coordinate, or Dropbox to exchange files. In this way, they contribute to introducing technological change into the organization.

3.4.3.5. External actors

Finally, technological change places the organization in a broader ecosystem, including, for example, research laboratories, as well as consulting firms and start-ups.

Consulting firms promote the diffusion of technologies within companies, through their role as interfaces that give them access to different organizations and companies. They thus directly contribute to the phenomenon of mimetic isomorphism, by disseminating, for example, what they consider to be “good practices”, of which the adoption of new technologies can be a part. In addition to this dissemination role, they often also play a supporting role and, in this way, contribute even more to mimetic isomorphism, if they offer similar support services to the various client organizations.

As for start-ups, they now play a considerable role in the creation and dissemination of technologies, particularly in the IT world. Indeed, in this sector, technologies can sometimes represent a level of expertise that most organizations do not have: semantic analysis algorithms, for example, or machine learning algorithms, are certainly significant innovations, but do not, in themselves, carry out the instructions for use to disseminate their operations in the organization. As a result, it is mainly start-ups that position themselves at the interface between these technologies and the organization, by offering the latter new products or uses that incorporate the algorithms themselves. Thus, in most developed countries, start-ups are now multiplying in the field of Big Data applied to marketing, accounting, human resources, etc.

3.4.3.6. A multiplicity of actors

The list of these different actors clearly shows that technological change does not depend solely on the technological actors. A conclusive diagram summarizes the role of each actor and thus highlights that technological change in organizations does not stop with the design of a new tool by technological actors (see Figure 3.2).

Thus, the technological actors design a new technology, possibly in conjunction with external actors such as consulting firms or start-ups. But this new technology must then be the subject of a decision to introduce it into the organization, which is done by the decision-making (management) and trade union actors. In addition, these two categories of actors can participate in defining the rules for the use of the technology, for example, by refusing certain uses. Thus, as we have seen, a human resources department may wish to adopt a CV pre-selection algorithm, while refusing to allow this algorithm to replace human decision entirely. Finally, the new technology is then appropriated by the employees. However, this appropriation can, in turn, redefine the outlines of the new technology, as illustrated by the many examples given in the chapter. Finally, the technology as initially thought by the designers may be considerably modified during this process.

This plurality of actors already highlights the difficulty of driving technological change in organizations, whose different strategies will be discussed in more detail in Chapter 5.

The variety of actors corresponds to the notion of “technological democracy”, already mentioned in Chapter 2 (Callon, 2003). Sociologist Michel Callon thus deplores the fact that technology remains today mainly in the hands of researchers and engineers. This monopoly is accentuated by a distinction in the debates between the content of technologies, which remains the preserve of researchers and engineers, on the one hand, and the values, ethics and purpose of these technologies, which can be discussed by citizens and elected officials, on the other hand. However, the growing awareness of the secondary effects of the use of technology on the environment or democracy is gradually blurring this distinction, or at least calling for it to disappear. Callon thus gives the example of GMOs or nuclear waste, which have given rise to important debates within civil and non-technological society. The more recent emergence of algorithms that partly govern relationships to culture or consumption through their suggestions is also becoming a subject of debate, even for non-specialists (Cardon, 2015). Thus, citizens are increasingly convinced that technologies can have an impact on their daily lives, and as such judge it to be legitimate to ask for information and debate the very content of technologies. For their part, some scientists call for the production of scientific and technological knowledge to be more guided by moral and ethical imperatives. The graph above illustrates well that, when a new technology is implemented in an organization, this distinction no longer makes sense. Indeed, non-technological actors (decision-making actors, trade unions, employees, etc.) participate to a significant extent in the definition of the technology, its uses and outlines. It therefore seems illusory to think that the content of the technologies exclusively remains in the hands of engineers and researchers.

This then calls for another perspective, the socio-technical perspective. Trist (1978) points out that separate approaches to social and technological systems cannot be sufficient to reflect reality, given the profound interactions between these two systems. Therefore, from this perspective, the two systems must be viewed together. This perspective is relevant for understanding different levels (macro, meso, micro). Thus, the organization (meso-level) actually forms a system that combines a social and a technical subsystem: a socio-technical system (Trist, 1978). The optimization of this system then involves a joint optimization of the two dimensions, which cannot evolve one without the other. This is also illustrated in Figure 3.2.