Keywords

1 Introduction

There have never been as many disruptions as those observed the past 20 years with the increased diffusion and adoption of information and communication technologies (ICTs). New ICT based innovations emerge every day both in the public and the private sector, as well as in everyday life. All businesses are actually impacted by ICTs, and not just because of the new technologies themselves: indeed, ICTs are at the origin of new customer behaviours, new business models, and new markets. Even more: there are now new ways to achieve innovations that were not imagined before the invention of the Internet, open source development and open data, peer to peer, wikis, social networks, copyleft and the like. Thus, both the internal and external environments of organizations are impacted by information technologies [26, 38]. While each company defines its own strategy to cope with these changes, many companies have difficulty to define and implement a proper innovation strategy, use inadequate approaches, and are not mature in terms of innovation practices. In most cases, the competition requires the use of ICTs to enter on dominant markets. In order to cope with these problems, companies are increasingly trying to take a systematic and proactive approach to realizing innovation [44]. Many companies are turning to assess their innovation process and determine key improvement actions [8]; others start concrete actions through open innovation [6, 7, 46] or creativity techniques [2] to improve their innovation capacity.

Some works have already demonstrated the benefits of using maturity models [2]. However, there are still many open questions about innovation-specific features of maturity models. Taking these issues into account, the research presented in this article is part of an effort to identify effective innovation maturity models driven by ICTs, and support their use in organizations. We believe that understanding existing innovation maturity models is a key step towards this goal. Therefore, the core research question of the paper is “what are the salient features of ICT centred innovation maturity models?” Starting from a collection of innovation maturity models selected from scientific as well as practitioners oriented literature, we provide a classification of their main characteristics that we use as the key building block of a structured analysis framework. A comparative analysis is then presented, considering (a) general purpose maturity models, and (b) innovation maturity models proposed at industry level.

The article is structured as follows. Section 2 introduces maturity innovation by defining the main concepts of maturity models of innovation. Section 3 describes the innovation maturity models selected for the review for the comparative study, and proposes a systematic description of their salient features. Section 4 reports measures and validation instruments for the considered maturity models. Section 5 discusses the findings and its practical implications. Research perspectives for future work conclude the paper.

2 Related Work

As shown by [49], although innovation and especially the ability of organisations to innovate has raised the attention of many researchers, there is no consensus on its definition. While Link and Siegel [28] consider innovation as the implementation of a new idea leading to a change that creates value. Wang and Ahmed [47] have a more organisation centric view. They call “innovativeness” the ability of organizations to innovate, more precisely, innovativeness is “the overall internal receptivity to new ideas and innovation that is demonstrated through individuals, teams and management, and that enables the formation of an innovative culture” [47]. Carlson and Wilmot [5] have a slightly different definition. For them, innovativeness is founded on the concept of innovation, the process of creating and delivering new customer value in the marketplace [5]. For [43], innovation capacity refers to the continuous improvement of the ability to generate innovation in order to develop new products that meet customer needs. Considering business practices, many researchers made use of maturity models that focus on a set of constructs suitable to stimulate innovation capacity at firm level, thus provisionally overcoming the challenges associated to establishing a semantic definition of innovation. Yet, the various models available in the literature [33] represent a set of concepts of the state of the art related to best practices in an area of activity such as CMMI for software development [41]. Furthermore, it can be argued that most of them draw their origins in the work of Crosby [10, 20] and they are heavily inspired by the CMMI maturity model (Capability Maturity Model Integration) by SEI (Software Engineering Institute). Indeed, using a maturity model helps an organization to assess the current state of its processes and to plan for improving its practices [42, 48]. It serves for assessing organizational practices processes implemented and support their improvement. The use of the concept of maturity is thus adopted in various fields both in research and business practice such as, e.g., systems engineering, purchase, service [11], Research and Development processes [3], assessing innovation capability [13, 16]. According to [22], the maturity grids can be applied to all processes of all companies to get higher performance. Organizations evolve, change to achieve the most mature large as possible at a given time. Thus, we argue that the innovation capacity of a process or activity can be evaluated depending on different levels, which similarly to the CMMI can be classified, e.g., as initial, managed, defined, quantitatively managed, optimizing [17, 35]. Therefore, strengthening an organization’s innovation capacity requires a combination of different measurements, in order to improve critical points and progress towards a higher maturity level [13].

Furthermore, the main objective of maturity models is to improve the quality of the processes by assessing processes and improving their weak spots. The maturity models account for a well balance between standardization and flexibility of innovation processes related in order to change the business environment and meet to requirements of stakeholders. However the relevance and diffusion of maturity models, the salient features and characteristics of innovation within these maturity models have been little investigated from a systemic perspective. Thus, in what follows we detail the results of a review of the literature, which leads to the selection of more than 50 maturity models and specific characteristics. Among those models, we then choose those that are specifically dedicated to innovation management.

3 Innovation Maturity Models in Research and Practice

The use of maturity models in companies has intensified and it has recently expanded in various fields. This expansion gave rise to several maturity models, both from the research and the practitioner community. In this article, we consider sixteen maturity models selected for discussion here that are particularly relevant to the assessment of innovation capacity proposed in the literature. To analyse these maturity models, they have been grouped into three categories on the basis of the community producing or else using them. Furthermore, the following characteristics with regards to the objective of the research were defined:

  • Concept of maturity levels,

  • Process areas or items,

  • Focus on innovation in general, open innovation, or innovation and IS/IT.

The results of the analysis of the literature are presented in Table 1a (showing models from the research community), Table 1b (showing models from the community of practitioners), and Table 1c (showing hybrid models), where the selected models are described considering: Model name, Process areas or dimensions, Type of innovation, References.

Table 1a. Analysis of innovation maturity models (research community)
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Table 1b. Analysis of innovation maturity models (community of practitioners).
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Table 1c. Analysis of innovation maturity models (hybrid models).
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The selection of the models from the research community (shown in Table 1a) usually is based on the presence of relevant literature that supports the model and the usability for innovation managers and practitioners. Whereas for the models coming from the community of practitioners (see Table 1b), the selection considers the use of the model by the company creator or the client companies to improve innovation capacity.

Yet, as for hybrid models in Table 1c, both the criteria for research and practitioners communities are considered.

Notwithstanding each model, either from the research or the practitioners community, has its own structure, most models are based on the original concept of maturity as already defined in the CMMI model [36], representing an assessment of maturity of the whole organization. In CMMI models [21] with a staged representation, there are five maturity levels (initial, managed, defined, quantitatively managed, optimizing) that consist of a predefined set of process areas; each of the five maturity levels captures performance expectations, practices or activities performed collectively to achieve the objective of that process area. Similarly, for every model considered at the state of the art there are certain process areas determined for each maturity level that an organization must implement in order to achieve a given maturity level. Thus, it can be argued that innovation maturity models have taken the same principles.

Taking these issues into account, Table 2 shows a relative similarity among the levels considered by state of the art maturity models. Indeed, the five maturity levels of the first CMMI model inspired most of the subsequent models. Furthermore, some models have taken the five maturity levels of CMMI. For others, they adopted their own terms to designate levels of maturity. The number of models studied levels of maturity varies from 3 to 6. Noting that the IMM model (B) does not have adopted maturity levels.

Table 2. Maturity levels of models
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4 Models’ Structures and Validation

As shown in Sect. 3, measuring the maturity of innovation capacity, its determinants or processes/practices may vary from one model to another. Different authors propose assessment models and representational capacity to innovate that we have summarized Tables 1a, 1b and 1c. Indeed, the areas as well as the dimensions of different models are very heterogeneous, thus resulting in various models’ structures. Yet, all models agree on a set of key factors suitable to improving a company ability to innovate; in fact, it depends on firstly understanding the innovation capability of a given organization and what is needed to that organization to improve it, even if the constructs considered by the various models are different. According to the models considered in previous Section and shown in Tables 1a, 1b and 1c, thirteen main dimensions have been identified: culture, risk perspective, collaboration/open innovation process, partnership capacity, climate for innovation, processes and practices/organization, individual capabilities, knowledge, learning and competencies/people, ideation and product development, innovation management, requirements engineering/customer focus/continuous delivery, quality management, leadership/strategy and intent/vision and strategy, infrastructure/tools/resources and organizational support.

Each factor promoting innovation is defined by sub factors or practices under represent the activities or business processes. For example, between ideation/generation concepts and individuals/organization/culture, there is a link because a culture of innovation facilitates the emergence of new ideas. We find the interactions between all dimensions/factors. It exists therefore a synergistic effect that enhances the company’s innovation capacity. The analysis of the factors/areas and processes of the innovation assessment models thus shows a clear trend of the complexity for assessment the innovation capacity as multi-criteria that have relationships between them. It also demonstrated similarities in the form of a list of factors/process areas that allow assess innovation capacity and trigger an improvement plan.

Otherwise, for validation of maturity models, the Table 3 below shows methods of validation of each model. Most models have been validated by various methods. For example the model IMM (B) was validated by three different methods: workshops, interviews and surveys collected from broad engineering-procurement and construction (EPC) organizations.

Table 3. Types of validation for the models.
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Taking these issues into account, we propose to select only the maturity models from research based on a robust validation (through intensive interviews, survey methods, case studies or workshops) and implemented within companies (see Table 3). Yet, due to the relevance of information systems (IS) for innovation, two more frameworks are worth considering. These include the model CMMI-DEV for software [9], and COBIT V5 for governance and management of IT [25]. Indeed, CMMI-DEV is composed of 22 process areas. Among these areas, there is the area of “Organizational Innovation and Deployment”, its purpose is to select and deploy incremental and innovative improvements that measurably improve the organization’s processes and technologies. For COBIT V5, it is composed of 37 processes of governance and management, and each process describes its objectives, best practices, activities and deliverables. Furthermore, the process “Manage Innovation” is made up of six practices (creating an enabling environment for innovation, maintaining an understanding of the business environment, evaluating the potential of emerging technologies, evaluating the potential of emerging technologies, and monitoring implementation of innovations).

5 Discussion of the Results

According to [11], “The SW-CMM approach was based on principles of managing product quality that have existed for the past 60 years. A CMM follows the quality work of Crosby [Crosby 1979] where he observed progressing levels of maturity in an organization’s ability to anticipate, resolve, and eventually nullify quality problems.” For innovation models, we found that most models are based on the principles of CMM models (SEI) and partly some quality research including works of Crosby (1979–1986), TQM (1995–1998), ITIL (1980–2007) and ISO15504 (2005). The development of academic and industrial models in the time allowed integrating a multitude of factors or processes areas of innovation process or business innovation systems to assess the maturity of the innovation capacity, comparing levels of business maturity and implement improvement plan. Indeed the OIMF model (2011) took into account the work on the ICMM model (2009) and in the MOA model (2013) took into account the work on the I2MM model (2011). So there is a capitalization of knowledge anchored to the CMM original source as a “blueprint” actually evolving through different model instances as well as configurations for improving innovation practices and meeting the challenges of innovation imposed by a permanent change in competitive environment. Otherwise, we have also found that while maturity models are focusing more and more on open innovation, they still remain at a general level of description and to date there is no dedicated maturity model of innovation by technologies or IS except for a small part of the COBIT framework V5 devoted to innovation through technologies. Academic and industrial community seek to identify innovative levers adapted to the changing economic environment. However, the models proposed in the literature take more into account open innovation, to date, to our knowledge, there are no innovation models focused on the role of IS. Finding the right model of assessing the ability to innovate and thus able to analyze the management of mobilized resources for innovation in the current context where information and communication technologies plays a crucial role for innovation is an important challenge for research and businesses [1, 32].

6 Conclusion and Future Work

This research has presented a comparative study of maturity models for innovation based on an extensive review of both academic and practitioners oriented literature. Thus, this paper contributes to understand the key characteristics of state of the art maturity models, particularly with regard to the innovation they enable in a given company. As for the diverse levels suitable to improve innovation capacity, although some models adopt different levels of maturity, a common root has been identified in the five maturity levels of the first CMMI model. Furthermore, strengthening an organization’s innovation capacity requires a combination of different measurements/factors, in order to improve critical points and to achieve a higher maturity level. The assessment of the maturity of the innovation process is the first step on a path of continuous improvement. In particular, the study also revealed four basic observations:

  1. 1.

    The principles of CMMI model are widely used in the design of innovative maturity models.

  2. 2.

    Heterogeneous constructs or process areas are nonetheless characterising the diverse models emerging from both research and practitioners literature.

  3. 3.

    Capitalization of knowledge is a key factor in innovation maturity models over time.

  4. 4.

    Various practices of assessment methods and constructs can be applied to the validation of maturity models targeting innovation.

  5. 5.

    The models proposed in the literature improve increasingly take more account of open innovation; yet, to our knowledge there a few or none innovation models by IS.

In summary, the analyses presented in this article provide the basis for the design and development of a framework for innovation capacity maturity driven by information systems. In future work the authors intend to take advantage of the analysed models, in particular areas or topics for each model and assessments methods, thereby potentially enabling an automated assessment of innovation capacity, which can be used by managers in order to adapt their processes of innovation.