Exploiting Participatory Design in Open Innovation ... - Semantic Scholar

Exploiting Participatory Design in Open Innovation Factories Valerio Bellandi, Paolo Ceravolo, Ernesto Damiani, Fulvio Frati, Jonatan Maggesi and Li Zhu Computer Science Department Università degli Studi di Milano - Crema, Italy {valerio.bellandi, paolo.ceravolo, ernesto.damiani, fulvio.frati, jonatan.maggesi, li.zhu}@unimi.it Abstract— In this paper we describe a methodology and a set of tools that support the exploitation of ideas, suggestions and proposals coming from different sources, internal and external to the organization (e.g. customers and employees). Items extracted from incoming message flows are used as a basis of a participatory design process. In this context, we discuss the design principles of an environment we call Open Innovation Factory, supporting collaborative design of new products and services. Index Terms—Open Innovation, Innovation Factory, Collective Knowledge

I. INTRODUCTION Traditionally, large firms relied on internal Research and Development (R&D) to create new products. In many industries, large internal R&D labs were a strategic asset and represented a considerable entry barrier for potential rivals. According to conventional wisdom, large firms with high R&D capabilities would outperform smaller rivals [1]. This process, in which large firms run internal processes for discovering, developing and commercializing new technologies, has been labelled as a closed innovation model. Although closed innovation worked remarkably well for a long time, the current innovation landscape has changed. Due to labour mobility, abundant venture capital and widely dispersed knowledge across multiple public and private organizations, enterprises can no longer afford to innovate on their own, but rather need to engage in collaborative innovation practices. As a result, a growing number of organizations have moved to open innovation models where they employ both internal and external processes and sources to develop new technologies [2]. External actors’ involvement is a key difference between Open Innovation (OI) and traditional research and development. Today, most companies adopt OI processes in order to exploit inflows and outflows of knowledge for accelerating their innovation dynamics [2]. For our purposes, a major aspect of OI is bringing research and development closer to collaborative design. In this paper we show how knowledge items extracted from incoming knowledge flows can be proposed to a team composed of multiple participants, each capable of proposing values for design issues and/or evaluating these choices from her own specific perspective.

In our collaborative approach, the outcome of an OI process can be regarded as an agreement between team members, to be reached via negotiation and communication. In other words, OI triggers a participatory design (also called consensus design or collaborative problem solving) process, which is essentially the mediation of a conflict that involves many parties. Our technique is composed of two steps: firstly, incoming flows are mined to extract knowledge items to be used as “stimuli”. Then, stimuli are fed to a recommender system in order to generate useful recommendations (seeds) to be presented to the innovation team, fostering collaborative development of new products or services. Periodically, partial results (e.g., terms extracted from on-going discussions) are fed again to the recommender system, reseeding the collaboration. The contribution of this paper is the design of the overall software environment (called the Innovation Factory – IF) that supports our methodology. The IF is composed by a synchronous wiki-based Virtual Product Designer, a tool for the automatic extraction of innovative concepts and ideas from internal and external sources, and a set of recommender services used for recommending (i) people that can join the innovation team, and (ii) contents that could help in the definition of the new product or service. The IF will be developed within the ARISTOTELE FP7 research project1. The project aims at relating the learning process to the organizational one as well as to the innovation process management. In particular, the project focuses and relies on the three main processes that are traditionally identified in the organizational contexts: organizational processes (marketing and communication, human resources management, business), learning processes (group training sessions), and social collaboration processes (spontaneous formation of groups within the organization). The paper is organized as follows. Section II defines the link between OI and Collaborative Design. Then, Section III describes IF methodology and Section IV introduces the IF design principles. Finally, Section V describes the IF interface, and Section VI draws our conclusions.

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http://www.aristotele-ip.eu

II. COLLABORATIVE DESIGN AND OPEN INNOVATION Our approach relies on two interconnected pillars: Open Innovation and Collaborative Design. In the following subsections we provide the state of the art related to the two areas. A. Open Innovation A way to distinguish between traditional and open design process is looking at their approach to innovation. Traditionally innovation has been seen only as the result of a Research and Development (R&D) process. Today, the management community agrees nearly unanimously that improvements to classic R&D–based processes can only be carried so far. R&D resources are naturally limited in terms of funds to invest, and of qualified researchers to carry out the work. The paradigm of OI, then, has been proposed as a new model for the management of industrial innovation in the 21st century, in which firms work with external partners both to commercialize their internal innovations and to obtain a source of external innovations that can be successfully marketed. OI brought about a paradigm shift that works in two directions: (i) outside-in open innovation, which consists in reaching across organizational boundaries to access innovation capabilities of external players, and (ii) inside-out open innovation, which deals with scenarios where an organization holds a technology but does not have the channel to market. OI sources can be classified as follows: (i) internal sources, composed by ideas and suggestions on new products, functionalities, and services coming from company collaborative systems, (ii) external sources, composed by ideas and concepts coming from external sources. B. Collaborative Design The definition of OI must be made operational by specifying collaborative techniques to develop new services or products. In fact, like user-centred design, OI is widely recognized as being ill-defined or even “wicked” [3]. In contrast to R&D problems that scientists and engineers usually focus on, which are well defined and with all the necessary information, OI process has not been subject to exhaustive analysis and there is no guaranteed correct solution [3]. Particularly relevant to the notion of IF is the one of participatory design, described as “a democratic and participatory process” [4]. Participatory design involves users in the design process by empowering them to propose and generate design ideas, and exploiting different techniques to support communication and collaboration within interdisciplinary teams. A major connection between participatory design and OI is the capability of involving final users and customers in assessing the potential of technological novelties in real work practice. From the IF point of view, the notions of OI and collaborative design are complementary; in fact, collaborative design is triggered by an inflow of knowledge items, presented to a diverse innovation team, whose members are potentially capable of proposing values for design issues and/or evaluating these choices from their own specific perspective [5].

Fig. 1: The Seeding, Evolutionary growth, Reseeding model (Adapted from [9])

Collaboration within the innovation team fosters the emergence of a Virtual Product (see sub-section V.A) as a coevolution of an artefact by stakeholders (the innovation team members) who have a shared understanding of the innovation goals and of the means of achieving them [6]. Exploiting collaboration of innovation team members requires appropriate solutions for resolving conflicts among them. In our methodology, reaching an agreement on innovative solutions is not only based on technical criteria, but also results from compromises between actors through negotiation and communication. III. IF OPEN INNOVATION METHODOLOGY Our OI methodology relies on two fundamental concepts: the concept of Meta-design and the one of Virtual Product (VP). We define a VP as a conceptual definition of a new product consisting in the identifications of the requirements, functionalities, and the competences required to develop it [7]. In turn, meta-design aims at empowering designers to modify and tune the design process rather than passively following it. Some researchers stretch the meta-design notion to the point of leaving “the design of design environments to designers” [8], i.e. empowering designers to shape their own design environments. In our approach, meta-design means empowering innovation team members to act as co-designers, defining the scope and basis of their interaction at design time. In fact, our methodology extends the Seeding, Evolutionary growth, Reseeding (SER) stepwise process model [9], which describes the development of systems and information repositories that evolve over time (Fig. 1). The three steps that compose the SER model are the following: 1. Seeding: team members feed our Recommender System (henceforth called the ARISTOTELE Recommender System - ARS [10]) with items extracted from one or more knowledge inflows to obtain recommendations of external resources. In our IF, seeds come from external and internal knowledge inflows. Seeds do not necessarily have to be complete, since an under-designed seed engages users to use the system, and to extend and refine the innovation outcome.

TABLE 1: INNOVATION FACTORY DESIGN PRINCIPLES. DP

Description

IF-1 Support exploration: Searching digital libraries for related resources and thus being inspired. IF-2 Low threshold, high ceiling, and wide walls: Users should work on projects that grow out of their own interests and passions; which implies that creativity support tools need to support a wide range of different types of usage and projects. IF-3 Support many paths and many styles: Important for interdisciplinary design teams’ collaboration, in that they have different ways, skills and cognitive styles to externalize their ideas. IF-4 Support collaboration: Supporting the integration and iteration of the contributions of team members with their different strengths and talents. IF-5 Support open interchange: Supporting extensibility, exporting and importing from other c tools. IF-6 Make it as simple as possible: Providing the simplest ways to do the most complex things. IF-7 Iterate, iterate and iterate again: Rapid prototyping, playing with prototypes, and improving them. IF-8 Serendipitous meeting: Suggest, encourage new meeting, and get in touch different profile, workers with the objective to stimulate new relations. IF-9 Stimulate new ideas: using open innovations sources is possible to stimulate, encourage and define new ideas, new products.

2.

Evolutionary Growth: team members use the IF to develop and extend the initial set of seeds according to their needs and ideas. This phase leads to the emergence of a VP, as a first incarnation of the OI process outcome. 3. Reseeding: it occurs when incremental changes, introduced in the previous phase, stop proceeding smoothly. During this phase, ARS is used again, feeding it with the VP requirements generated in the evolutionary growth step. Recommendations help team members to organize, reformulate, and incorporate incremental changes from the second step into the VP to support the next cycle of Evolutionary growth and Reseeding. Our OI methodology is loosely controlled, as the team itself decides if and when stop reseeding and, thus, release the VP. A. Support for Creativity Creativity has been studied over decades, and many researchers have tried to define the notion of creative process, person, and even product. One of the most influential creativity models in the 20th century is the one originally proposed by Wallas [11]. This model defines the creative process as involving the phases of Preparation, Incubation, Illumination, and Verification. Other creative process models exist, such as Osborn’s seven-step model [12], which share with our IF a common theme, namely the dualism between imaginative idea generation and critical evaluation. Creativity is a central theme in design and innovation research, since “design deals with making things while innovation deals with making new things” [13]. In our IF, we support creativity by increasing serendipity in the Seeding and Reseeding phase. The rationale behind this choice is that the larger the number of ideas produced, the greater the probability of identifying a fruitful innovation. Also, the collaborative nature of VP development aims at fostering interactions with other people. Using ARS for seeding provides a contact with artefacts that embody group knowledge and previous thinking, arranging informal ways for stakeholders to share experiences, in order to articulate their collective knowledge [14].

Additionally, bringing divergent viewpoints together and creating a shared common understanding will help team members to discover new insights and alternatives, and hence to solve problems more creatively. IV. DESIGN PRINCIPLES FOR THE IF Starting from the considerations exposed above, we are now ready to define the design principles used to set up IF’s collaborative environment to support the Open Innovation process. Collaboration, creativity, and serendipity are at the core of our IF. Work in [15] is particularly relevant to ARISTOTELE, as the authors explored computer-based tools that support creativity for interdisciplinary teams. They highlight the importance of supporting communication by developing a shared language and an understanding, as communicate and exchange creative ideas is an essential part of the creative process. According to them, a way to encourage communication is to provide lightweight tools to support polymorphic articulation of ideas. Another way to collect requirements is via focus groups. In 2006, the National Science Foundation sponsored workshop brought together 25 leading researchers to share their expertise on creativity support tools, to develop improved software interfaces that empower users to be more productive and more innovative [16]. They defined a set of design principles to guide the development of new creativity support tools. These principles are quite different from traditional ones as they focus on easy exploration, rapid experimentation, and adventitious combinations that lead to innovation. As results of the analysis on Sections II and III, in Table 1 we provide the list of design principles for an environment supporting Open Innovation, Collaborative Design, and the SER approach. V. INNOVATION FACTORY INTERFACE Design principles in Table 1 have been taken as basis for the definition of the ARISTOTELE Innovation Factory environment, under development by the SESAR Lab of the Università degli Studi di Milano. Figure 2 shows a mock-up of the interface, highlighting the three areas that compose it:

folder, allowing to develop a specific aspect or functionality of the VP. Therefore, a folder can contain one or more distinct sheets. The communication channels are described in [17] as “means to support communication between designers as well as between designers and administrators”. In our view, the IF itself acts as a communication channel: all innovation-related communication, negotiation, development, and social interactions are supported by the IF. More specifically, all the accessible folders, sheets, and widgets can be seen as a communication channel. A flexible mechanism will allow innovation teams to partition and locally configure communication. A. Virtual Product Definition

Fig. 3: Mock up of the IF user interface.

The data sources of OI considered by the IF are of three types: •

1. 2. 3.

Open Innovation Data Corpus (Light Blue Area). This zone exposes the main information coming from the open innovation sources (sub-section V.B). Virtual Product Designer (Grey Area). The synchronous collaborative tool that allows the developing of the Virtual Product requirements (sub-section V.C). Proactive Tools Area (Brown Area). This area contains a set of common and ad hoc tools that support the innovation process by providing suggestions and recommendations (sub-section V.D).

In the IF, innovation team members are empowered to perform collaborative development as well as to tailor their environment, communication, coordination, and all aspects of collaboration, in a more fluid way according to situated problems. We use a classical accounting model defining, in details, two different user levels (administrator and designer): •

•

Administrator: users enabled to start and setup a new innovation process. The main functionalities available of this kind of user are: o Select the OI data sources (see sub-section V.B); o Include personalized widgets (see sub-section V.C); o Involve designers in the project (see sub-section V.D). Designer: users involved in the innovation process and deputed to design the VP.

Moreover, in the IF we define two data levels: folder and sheet. The folder level characterises a new innovation process and, on setup time, do not impose a predefined structure on all design communities, but allow the sharing of specific features among selected employees. It is the collector of one or many sheets, which represent the editors where the employees design the VP. In particular, a folder describes an overall VP encompassing all the features and tools exploitable for its definition, while a sheet can be seen as a distinct area of the

Contributions coming from designers (for example a specialist or an innovation manager) that, manually, using their knowledge and skills, define specific requirements for a new product. • Contributions coming from users that send comments and ideas, which can be collected and transformed in requirements to be analysed. • Contributions coming from external sources, using software crawlers that analyse electronic resources and extract information (see Section V.B). Aggregating the gathered requirements, the new VP is modelled by aggregating different inputs, and relating them to other knowledge items of the ARISTOTELE models. This aggregation provides a conceptual definition of a product instance consisting of the desired requirements or functionalities and the competences required to develop it. The schema in Fig. 2 describes the general structure of a VP, showing how a set of inputs is linked with a set of competences. In fact, the VP is first linked to the inputs triggering its development (Req. 1, …, Req. Z), and then it is related to the competences (Comp1, …, CompN) necessary to support the proposed requirements. The aim of IF is to provide the specific recommendations that a team should follow in order to acquire the competences requested by a VP. In fact, the IF exploits the functionalities of

Fig. 2: General structure of a VP linking requirements and competences.

the ARS to compute recommendations [10], tailored to the innovation team memebrs that develops the product. The Virtual Product Designer (VPD), described in subsection V.C, is a service specifically devoted to the identification of the requirements most relevant for innovation, and to the associations of requirements to competences. This way the VPD outcome is a VP structured by descriptors that make it comparable with other data objects of the ARISTOTELE models. B. Open Innovation Data Corpus Our methodology considers knowledge inflows as the ideas’ repository of the IF. We recall that two types of sources are considered: 1.

2.

Internal. Data coming from sources inside the platform (e.g. internal forum or customer care log files); in the IF we define a set of automatic analysers designed to extract information from internal sources. External. Electronic data coming outside the platform, e.g. competitors’ web site, Twitter posts, etc.; usually crawlers that collect external sources are strictly goaldependent, and need an accurate configuration at startup.

When setting up a new IF folder, a set of data sources are selected by the current administrator. She also configures the crawlers, selecting the data sources to explore, and defining the crawler filter to specify the focus of the analysis. Regarding the internal sources, we initially define three types of data crawlers: 1.

2. 3.

Blog Crawler, which extracts tags from every posts or comments of a specific blog; during the setup phase it requires to select the employee’s blog hosted in the platform. Forum Crawler, which extracts tags from each post or discussion of a forum, and, to be configured, it needs the specification of the URL of the forum to analyse. Generic Data Crawler, which analyses generic files.

Regarding external data sources, each company that adopts the ARISTOTELE platform needs to implement specific software crawlers strictly dependent on the domains (and on the document formats) to analyse. Possible sources of external data will include: 1.

2.

3.

Competitor web sites. This source is important since it permits to monitor the competitor products. Data retrieved from them should represent the inspiration for new functionalities or requirements. Blog of trend setters/opinion leaders, which could help in defining new trends of the market, or new technologies that could be exploited to define new projects or update old ones. Technical or opinion forums. This source is an important point of discussion where many possible solutions or requests coming from the market can be identified.

After the data source configuration step, crawlers extract a list of incoming items (posts, documents, etc.) potentially related to innovation, according to the filter defined by the administrator. For each item of that list, tag extraction techniques are exploited to retrieve possible tags. The list of tags, ranked with its frequency, is presented in the light blue area of Fig., and represents the starting point of the methodology Seeding step. Each team member can select some tags, further analyse the associated items, invoke the ARS, and start to work taking the results as seeds. C. Virtual Product Designer In this sub-section we provide a description of the VPD, the synchronous collaborative environment that permits to develop (see Section II.B) new products or services. The VPD is a collection of wiki-style pages (i.e., the sheets) that can be edited by innovation team members in order to model the new VP. We adopted the wiki architecture as VPD base structure, because the wiki architecture matches many conceptual aspects of our methodology. In fact, the VPD leverages some features of a regular wiki, like for instance collaboration, rich context, openness, and dynamic links. Beside normal wiki functionalities, VPD extends wikis with specific development functionalities, using a macro-like system to change and evolve the system along with collaboration practice. As shown in the grey area of Fig., a VPD page consists of three parts, a header (Projects Bar), that indicates the current sheet and the user’s profile information, a VPD Editor, and a side panel, that shows the active environments and widgets in the whole folder. VPD provides a common collaboration context across the system where each team member can work while being aware of the activities of others. Beyond providing tools for content production like traditional wikis, VPD allows innovation team members to collaboratively modify and create seeds, and to evolve them continuously. An important aspect of the VPD is represented by the widgets, i.e. functional blocks that can be implemented and configured by the organization that adopts the ARISTOTELE IF. While our methodology favours diversity exploiting ARS functionalities [10], innovation team members with different cultural backgrounds will use different systems of signs, languages, devices and representations [18]. Communication is therefore needed to reach a common understanding. VPD is itself a mechanism to negotiate between divergent viewpoints regarding an object of interest. A mediation mechanism is not in itself a new idea; but open mediation mechanisms for inspection and evolution in the innovation process have not been fully explored. In our approach, the mediation mechanism is itself defined within a wiki page, and it is open to modifications. Instead of gathering data about the innovation team members culture, role and access device, and automatically customizing information for them, our open mediation mechanism goes beyond the “perfect personalization dilemma” [19] and enables team members to decide directly what is meaningful information and how to represent it opportunistically.

In other words, the VDP mediation mechanism works by allowing several users to access the same data page. The same data is accessed and modified by two or more designers, while the way of representing and interacting with data can be very different. The mediation mechanism empowers team members to create appropriate information representations for seeds, as well as to configure communication channels. For instance, a team member could be hindered by the chat widget while working on a seed during the Evolutionary growth phase, and decide to temporarily disable it. The widgets available for the innovation process are selected by the administrator (usually a Project Manager), which can choose among a set of standard components supplied with the IF. The widgets package that initially the IF will include is the following: •

•

• •

•

•

• • •

Chat. A classical tool for message exchanging is provided, that implements the feature of communicating with one or more designers in real-time or off-line mode, allowing to store the history of each discussion. File Browsing. This widget enables the capability of exploring files in the knowledge base, allowing to find documents using tags or other information (e.g. creation date, file name, etc.). Images Embedding. The widget allows to display an image exposing clearly concepts and features of the VP. Multimedia Video Embedding. The widget allows to embed videos in the VPD. The video screen can be resized, rearranged, played simultaneously or in a particular sequence to convey certain concepts. The result can be more powerful than static images. CAD Viewer. This widget allows to display a CAD file, exploitable when the new product is a real object. It permits to visualize and understand the shape of the object. External Files Linking. The widget allows to embed in the VPD external websites, PDF files, slides, and the like. Users can easily collect resources, and store and share them with other members. Combined with the Document Tagging widget, users can better organize and retrieve resources. This keeps IF lightweight and flexible, as resources are independent from IF. Document Tagging. This widget enables the feature of tagging documents, people and other elements within and in combination with the External Files Linking widget. Survey Administering. This widget allows to create, manage, and administer surveys and questionnaires to the designers. It will facilitate the decision-making process. Team Coordination. This widget provides functionalities to coordinate task and time of the designer team, specifying deadlines, assignments, and expected effort.

Thanks to its modular architecture, the IF is open to the integration of new functionalities; in fact, any organization

adopting the ARISTOTELE IF can define and implement new field-centric widgets. For instance, an innovation team set up in a Fashion House, that want to exploit customers’ messages as an external knowledge source, can develop a widget to manage and represent dresses shape, in order to enable the innovation team to discuss customers’ suggestions while manipulating 3D representations rather than using text messages only. It is important to note that the role of a widget is not clearly defined and can be specific of the current task and the needs of the individual innovation team member. For example, the communication channel is not atomically implemented by the chat widget, but several widgets can be exploited to define and enact a concrete communication channel. Currently, with reference to principles listed in the Table 1, VPD addresses in particular the following ones: • IF-1 Support Exploration: the activities of collecting, tracing, finding, and presenting data are addressed by the File Browsing widget. • IF-2 Low threshold, high ceiling, and wide walls: The possibility of expressing doubts or questions and the agile capability to plan activities are addressed by the Chat and Survey Administering widgets. • IF-4 Support collaboration: the structure of the VPD and the Chat widget support collaboration among team members. • IF-5 Support open interchange: this requirement is addressed by the technology widgets (e.g. CAD viewer and Images Embedding); in fact, the possibility to add a specific widget permits to open the IF to every kind of data. • IF-7 Iterate, iterate and then iterate again: the VPD is developed to implement the innovation methodology described in Section III. In fact, the possibility to use the innovation source tags as input for defining a new tag cloud, allows to iterate again and again the steps of our innovation process. D. Proactive Tools Area In this sub-section we describe the brown area of the IF shown in Fig.. The Proactive Tools Area (PTA) accepts in input the list of required competences returned by the VPD, and returns in output a list of suggestions specific of each innovation team member. In fact, the first requirement of IF is to define personalised suggestions that will cover all the competences defined by VPD. The PTA exploits the functionalities of the ARS, to compute ad hoc recommendations covering all the competences associated by VPD. ARS is therefore configured to return suggestions in terms of employees’ interactions, human resources, and electronic resources [10]. ARS is executed taking as stimulus the list of VPD competences, and as target the innovation team. First of all the ARS identifies competences related to the stimulus. Then, ARS returns a set of suggestions that are useful to acquire, for each innovation team member, all competences

related to the stimulus. Also, recommendations are computed based on the current VP definition at each Reseeding step. An automatic check will verify that all the employees composing the innovation team have been mapped on at least one competence. If some competences cannot be assigned, the ARS suggests additional innovation team members selected among the available HR capital. Of course, the composition of the innovation team can always be modified manually. The IF configuration of ARS can also define different cardinalities for particular competences, with the goal of having some competences covered by more than one team member. Finally, the associations between employees and competences are exploited to create customized suggestions tailored to VPD requirements and team members’ profiles. Summarizing, the PTA contains a set of suggestions, coming from the ARS, supporting the evolutionary growth phase of our methodology and, in general, the innovation process. Incoming knowledge items are generated and proposed to innovation team members in a proactive way. With a pre-determined frequency, current sheet contents are analysed, and associated tags are extracted using common knowledge extraction techniques. Then, starting from this set of tags, the competences associated are identified and used as stimulus to invoke the ARS. VI. CONCLUSIONS In this paper we outlined a methodology and a set of tools that support organizations in the exploitation of knowledge flows, i.e. flows of ideas, suggestions and proposals coming from external sources. We discussed how items mined from incoming knowledge flows can trigger a participatory “meta-design” process. Finally, we finalized our discussion to stating and describing the design principles behind our open Innovation Factory, a software environment developed at SESAR Lab, Università degli Studi di Milano. The IF supports collaborative design of new products and services, fostering creativity and diversity during the design process. ACKNOWLEDGMENT The research reported in this paper is partially funded by the European Commission under the Collaborative Project ARISTOTELE “Personalized Learning & Collaborative Working Environments Fostering Social Creativity and Innovations Inside the Organizations” under Grant Agreement n. 257886. REFERENCES [1] D. Teece, "Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy," Research Policy, vol. 15, pp. 285–305, 1986. [2] H. Chesbrough, Open Innovation: The New Imperative for Creating and Profiting from Technology. Boston: Harvard Business School Press., 2003.

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