Keywords: Technology intelligence systems; System toolbox; Knowledge management; ...... Interacts with Business Strategy to Anticipate Technological Trends.
Pre-publication draft: Mortara, L., Kerr, C.I.V., Phaal, R., Probert, D.R., 2009. A toolbox of elements to build technology intelligence systems. International Journal Of Technology Management 47, 322-345.
A toolbox of elements to build technology intelligence systems -----------------------------------------------------------------------------------------L. Mortara, C. I. V. Kerr, R. Phaal, D.R. Probert Centre for Technology Management, Institute for Manufacturing University of Cambridge
Abstract: In response to the need to achieve a consistent view on how to organise technology intelligence (TI) activities, a generalised framework to support the creation of TI systems was developed by Kerr et al. [2006]. This paper generalises the structure of TI systems by observing and abstracting from real life examples. As a result, a toolbox of system elements is proposed, which can be used to structure and characterise any TI system. The different choices of system elements can be attributed to the model’s four modes of searching: Mine, Trawl, Target and Scan. With the exception of the Trawl mode which features just connector elements, all the TI modes are supported by management, source connectors, repositories of information and search elements. All these elements can be either people’s roles, activities or characteristics, or physical infrastructure. TI social networks are eminently important elements for any TI system; a reasoned overview on how companies can build their own TI networks is presented. Keywords: Technology intelligence systems; System toolbox; Knowledge management; Scouts; Gatekeepers; Technology listening posts
A toolbox of elements to build technology intelligence systems.
1
Introduction
Technology intelligence (TI) provides an organisation with the capability to capture and deliver information to develop an awareness of technology threats and opportunities [Kerr et al., 2006]. The industrial interest in developing effective TI capabilities has increased in recent years as a response to the boost of technological global competition and the need for continuous innovation. While historically some academic research has focussed on empirical studies [Utterback and Brown, 1972] or on the generation of processes for TI [Ashton, 1991; Ashton and Stacey, 1995], recent academic interest has followed the industrial need to deepen understanding of TI activities. Lichtenthaler [2003; 2004a; 2004b; 2007] concentrated on TI processes and on the co-ordination of TI activities in multinational organisations; Savioz et al. [2001; Savioz and Blum, 2002;] explored how TI activity can be implemented in SMEs. Interest was also directed towards the investigation of the interaction between top management and the TI activity [Savioz and Tschirky, 2004]. Bucher et al. [2003] investigated the role of TI in evaluating disruptive technologies in firms via the analysis of a case study example. Shehabuddeen et al. [2004] reviewed existing technology management tools and processes which may support TI, while the employment of TRIZ-based techniques was suggested by Schuh et al. [2003]. Other studies reviewed the sources of information for intelligence in general [Ghoshal and Kim, 1986] and for TI in particular [Lichtenthaler, 2004b; Brockhoff, 1991; Ashton et al., 1991; Ashton and Stacey, 1995; Reger, 2001]. Literature has also identified some elements used to create TI systems: for example gatekeepers [Allen, 1977], intelligence brokers [Kerr et al., 2006], listening posts [Gassmann and Gaso, 2004; 2005], scouts [Brenner, 1996; Tibbets 1997], and technology analysts [Porter, 2004]. However, there is a perceived need for a consistent view on how to organise TI activities [Gassmann and Gaso, 2005]. The work herewith described aims to contribute to this academic gap and is directed to understanding the operational aspects of TI, providing clarification and practical tools for companies in the implementation of efficient TI capabilities.
2
Background to the research
This work started with the development of a conceptual TI model [Kerr et. al, 2006] which was created to frame, define and explain TI, based on a broad ranging literature review. The model links the TI activity to its organisational context, explaining that its role goes beyond the simple knowledge management and information processing: its purpose is to provide ‘intelligence consumers’ (i.e. decision makers) [Bernhardt, 1994] with analysed, contextualised and purposeful intelligence. Focussing on the relationship between the decision makers and the ‘intelligence brokers’, Kerr et al’s. [2006] model provides three layers that explain how TI activities can be viewed and described. (1) The framework level highlights the relationship between decision makers and information providers. It explains that TI is part of a wider (Business) intelligence system which also includes markets and product/competitor intelligences. The framework maps the information requirements and knowledge gaps of the decision makers, linking them to the actual data sources through the business intelligence activities. (2) The process level of the model illustrates how decision makers input guidance to TI operatives, identifying information needs. On the other side, information is disseminated back though the intelligence cycle. Six phases lead to the capture and delivery of the information. The Co-ordination phase assigns tasks, generates ideas for sources and refines the search goals with the decision makers. Search, Filter and Analyse phases form a subordinate cycle within the process that is repeated until a satisfactory level of
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A toolbox of elements to build technology intelligence systems information is acquired. Then, investigators Document their findings and Disseminate intelligence. (3) The system architecture layer (Fig. 1) relates to the information searching phase of the process. Two modes (Mine and Trawl) are directed internally within the organisation, while the other two (Target and Scan) are used when information is sourced outside the organisation. The modes can be briefly described as: - Mine: the searcher is aware that the information has been gathered and where it is. - Trawl: the searcher is not aware of where the information is kept or if it has been acquired at all. - Target: the searcher knows what to look for, outside the company boundaries. - Scan: the searcher has not previously identified which information to acquire. Figure 1: about here This paper expands the understanding of how companies can operationalise these different modes of searching for information, by proposing an approach to understanding what roles and infrastructure can be used for operating the Mine, Trawl, Target and Scan modes. A large portion of the information is accessed through social network connections. Researchers working on in the field of social networks have long since highlighted the importance of weak ties [Granovetter, 1983], i.e. relationships that enable the connections between different social groups, to reach the most innovative information. In this research, the theory developed by Stephenson [1999], who highlighted the elementary structure of social networks, has been used (Fig. 2). The basic cell of a network revolves around a ‘hub’, where knowledge is contained. The ‘pulse-takers’ are the elements in contact with anyone else in the network via the shortest route and the ‘gatekeepers’ the elements that allow the interconnection between hubs. Networks are glued together through bridges of trust. Figure 2: about here Adapting Stephenson’s [1999] model, at a high level (macroscopic view – Fig. 3) a company can be viewed as a knowledge hub but at a lower, more detailed level (intermediate view – Fig. 3) the hub interfaces with the environment via external gatekeepers (e.g. the departments which have external connections). The path for reaching the gatekeepers often passes through the organisation pulse-takers (e.g. cross organisation activities). If this model is taken to an even more detailed level (Microscopic view – Fig. 3) the organisation can be seen as built up of multiple networks glued together and based on single individuals, where internal gatekeepers provide the exchange across organisation boundaries, while individuals who always know ‘who knows’ are the pulse-takers. Figure 3: about here One can build social networks which are ‘highly clustered’ [Uzzi and Dunlap, 2005], i.e. constituted by people who are very similar (e.g. they have the same background, the same interests, they mostly know the same people, etc.) or diversified [Uzzi and Dunlap, 2005] where people belonging to different clusters are connected, often by virtue of the action of a broker.
3
Methodology
In order to test the theoretical model [Kerr et. al., 2006], it was compared to practice in 14 UKbased organisations [Mortara et al., 2007], eight of which were investigated in greater detail. The investigation employed a case-study approach [Yin, 1994] with semi-structured interviews based
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A toolbox of elements to build technology intelligence systems. on the framework. The only criterion for the selection of the case studies was that organisations had a strong interest in keeping abreast of technological developments. The researchers contacted individual TI operatives within each organisation, who could help them identifying and interviewing other TI operatives and decision makers. Due to pragmatic reasons, e.g. size of the company and of the TI system, availability of the companies, the number of interviews varied across the cases. In eight cases out of 14, multiple interviews took place. A review of these eight detailed case studies is given in Table 1. Table 1: about here The researchers used the interview protocol summarised in Table 2, with questions addressing the specific company’s TI systems, the individual roles played by the interviewees in the TI system and the model [Kerr et al., 2006]. Table 2: about here For each company the TI activity was outlined in a descriptive way and elements which allow each of the four modes of searching information were listed (see highlighted questions in Table 2). Cases were cross compared and criteria were generated in order to show similarities and differences between the elements. After the analysis, the interviewees were asked to check each case report.
4
The toolbox structure
The toolbox represents a generalisation of the different components (or elements) that can be used to build a TI system. It captures real practice and explains, at a level deeper compared to the TI model [Kerr et al., 2006], how companies operationalise TI systems. The most pressing questions for the researchers were: “What infrastructure does one need to create a functioning TI system? Who has a role in TI systems?” In order to provide clarity for those who analyse, structure and design a TI system, the researchers clustered the elements observed according to emerging criteria, although it is recognised that other organisations of the elements observed might be possible. The first of these criteria was imposed by the model and so the elements were grouped according to the four modes for searching information (i.e. Mine, Trawl, Target and Scan) as they were observed during the comparative analysis of the case studies. The elements were also grouped according to their function within the searching mode, i.e. according to what these were used for. The elements observed were employed for: - Storing the information: In all the cases observed, information comes in different forms, but in general it could be argued that it is gathered either in ‘published’ form (e.g. journals articles, patents, reports, web publications, books, proceedings) or it is reached via verbal communication (e.g. networking, meetings, presentations, conferences). - Connecting to information: ‘Connectors’ create a link between searchers and the information they seek (internally or externally). When information is not yet acquired it is located in ‘external sources of information’ such as, for example, a technical journal. Hence, the organisation cannot own the repository of information itself (e.g. technical journal) but can create a connection to it (e.g. by subscribing to the journal database). Connectors are also used to reach and link with internal concealed repositories of knowledge (Trawl mode). - Searching the repositories: Used to find the most significant information within the repositories. - Co-ordinating the TI activity: Organisation of the search processes for the different modes.
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A toolbox of elements to build technology intelligence systems This classification can be expanded, for example by including, together with the categories “People” and “Infrastructure”, other types of elements such as “Processes” which enable each of the modes of searching information. The combination of these criteria resulted in the template shown in Fig. 4. Within this structure, similar elements (same mode/nature/function) were clustered together and a generic definition was given. For example, for the Mine/infrastructure/repository of information, a list of diverse solutions for knowledge management were observed, such as data warehouses, electronic databases, personal electronic devices, corporate libraries, etc. All these were clustered together as ‘physical repositories’. Figure 4: about here. A detailed description of the toolbox is given in the following paragraphs, proceeding from mode to mode. Examples are given, extracted from the case studies observed (see Table 1). Often a single person covers different roles with regards to the TI activity. Similarly, the same tool is sometimes used for different tasks. Consequently, the toolbox reports the same element in different positions. For example, periodically each technology group in Tech-consult (the technology consultancy observed) creates roadmaps that are used as a reference document to identify new technological developments in their area. In this case, the roadmaps were seen as ‘enablers for the identification of new technologies’ among the ‘Target /infrastructure/coordination’ elements. However, roadmaps are also used by intelligence operatives to identify who in the company might be interested in information found with the Scan mode. So, roadmaps can be also classified as ‘enablers for the identification of information users’ among the Scan/infrastructure/coordination elements. This is the case, for example, of the scouts of the European technology outpost of Imaging, who use the roadmaps produced by the main business units to identify interested interlocutors based in the US headquarters. Mine and Trawl modes concern internal knowledge, hence knowledge management best practice applies to TI, as observed by previous studies [Savioz and Blum, 2002].
4.1
Mine
In the Mine mode the searcher knows that the information has already been acquired by the organisation and where it is. Table 3 summarises the generic elements which are used for this mode. Co-ordination Knowledge Managers: The role of these operatives is to co-ordinate the mining activity. They organise the corporate knowledge system in order to maximize its potential. In Tech-consult, a technology manager was appointed to organise the knowledge base resources which have been generated over fifty years, to make it available in the best form for retrieval. His efforts include capturing people’s tacit knowledge, re-organisation of internal repositories and fostering the creation and maintenance of individuals’ social networks. Table 3: about here Competence Directories: Corporate yellow pages (e.g. Tech-consult has a directory called ‘who knows’ which is a guide to staff expertise listing people according to their core knowledge), organisation charts or personal web-pages. They help in organising and identifying repositories of intelligence information.
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A toolbox of elements to build technology intelligence systems.
Repositories (Internal sources of information) The information acquired through intelligence activities is stored in repositories, available for future reference. Two main types of repositories contain information according to whether it is stored in an explicit or tacit form. Tacit information - Human knowledge: In their quest for information, intelligence operatives process and archive in their memory a great deal of information. In this instance, operatives act as ‘human repositories’ who can retrieve information on request. It is known that experts are able to organise their knowledge around key concepts and are consequently capable of “flexibly retrieving important aspects of their knowledge with little attentional effort. Experts’ knowledge cannot be reduced to sets of isolated facts or propositions but, instead, reflects contexts of applicability.” [Bransford, 2000]. As a result, the information retrieved from a human repository, especially if this is an expert, is generally elaborated with strong elements of analysis. The localisation of the information stored this way can be more difficult than if it is in the physical repositories. Its identification often requires a Trawl step before mining [Mortara et al., 2007]. Useful tools to identify knowledgeable individuals are the competence directories described in the section above. Infrastructure for explicit intelligence - physical repositories: For example digital databases publicly available for consultation by internal users such as digital corporate libraries, or data warehouses. Systems employed by the companies observed to manage information varied; examples were Lotus Notes® (software that allows users to create and update shared databases), SharePoint® (portal server that allows users to search for and connect to information from multiple internal systems), PersonalBrainTM (software for organising and linking documents and webpages). When information is privately kept, it is mostly stored in personal computers or in case of hard copies, in personal archives (e.g. diaries, personal notes, private libraries, copies of reports and articles). Information can be stored ‘raw’ (if it has been directly collected from sources of information) or ‘elaborated’ (if it contains the analysis by the intelligence operative). The raw information, especially if it is obtained by specialised technologists, is generally quantitative and extremely technical. In this state, information is kept in local repositories (either personal or of the technical group) as it is generally meaningful just for the owners of the information. The ‘elaborated’ information can take, for example, the form of notes to remind the intelligence operative about the reason of the collection. Alternatively, internal intelligence reports, funding proposals, newsletters or abstracts are archived in intranet repositories accessible to a wider internal public. Search elements Knowledge processors: Both people and infrastructures, can access and manage databases, extracting pertinent information on request. They allow browsing and retrieval of any type of data on the basis of taxonomies, i.e. hierarchical organizations of concepts. Librarians or filing experts retrieve information on request. Infrastructures encompass database management systems and data mining systems such as Google DesktopTM (desktop search application) or other similar software. Some tools are more sophisticated than others, allowing the recognition of patterns through the analysis of statistical data. Analysts of knowledge: Individuals who provide reasoned (in contrast with the processors) information abstracts on request but are usually not aware of experimental conditions and the intended aim. Librarians and the staff who manage a literature databases help with information search in Tech-consult, Telco-service and Print2. They select a series of relevant information sources and pre-filter potentially relevant literature on behalf of enquirers. As the majority of information is managed electronically, ICT (Information Communication Technology) networks, in the form of intranets, are fundamental infrastructures for the management of the information and for the connection to the internal sources of information (repositories).
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A toolbox of elements to build technology intelligence systems 4.2
Trawl
The search for intelligence in internal sources (repositories) can be difficult, especially when it is not explicitly organised in identified repositories, but is kept in people’s memory or in personal storage. Trawl is the mode of searching used to reach concealed repositories of knowledge. This is typically achieved through the deployment of interpersonal links (internal social networks). For this reason, the only elements observed in the case studies were connectors (Table 4). Boundary spanners (Connectors to internal knowledge) Intermediaries of knowledge: People who can connect others to knowledge, or, in other words, people who know ‘who knows’. This role is rarely appointed to someone, but some categories of people, by virtue of their everyday work or their personal characteristics, might find themselves in this position. The librarians of Tech-consult help with many information quests; they are able to help searchers in finding colleagues who have previously been interested in similar topics. Table 4: about here Internal gatekeepers: Individuals who cross the boundaries within the company are key elements in the search for hidden information. People who operate across departments or teams or across different geographic areas can provide information links. At Tech-consult, it is common practice to talk among colleagues, asking for advice and suggestions and disseminating informally the outputs of projects. It is commonly believed that networking skills are fundamental for staff, so much so that new employees are also judged on the basis of how much they communicate with others. In Telco-service, decision makers use preferential, personal, trusted internal sources of reference (i.e. technology consultants, individuals with whom they particularly feel to be on the same wavelength) who are asked for their opinion when decisions have to be made. Through this personal network decision makers can reach other knowledgeable individuals within the company which they personally do not know. An example of process for Trawling is shown in Fig. 5. Figure 5: about here Internal social networks: Internal social networks are structured patterns of personal contacts among employees (e.g. inter-personal relationships). Several types of networks can be equally useful, from personal trustworthy contacts like friends, colleagues and acquaintances to communities of practice. Finding those who have access to information via the shortest route (i.e. the company’s ‘pulsetakers’ [Stephenson, 1999]) may provide useful. As a method to identify these people, a survey across the company is suggested by Stephenson [Watters, 2006], asking questions like: "Whom do you go to for a quick decision?" "Whom do you hang out with socially?" "To whom do you turn for advice?" "Whom do you go to with a good idea?" "Whom do you go to for career advice?". Imaging provide occasions for knowledge exchange by organising weekly meetings where scouts report their latest networking activities, the people who were met and the technologies observed. This promotes communication, exchange of information and network creation among colleagues. ICT networks: Including intranet, e-mail and telephone are widely used for Trawling. Competence directories: As illustrated for the Mine mode, can be used to support the search. Broadcasting communication: Mailing list messages requesting information and contacts support Trawling. For example, in Print 2, an internal chat room/mailing list promotes debate where people can post problems and the subscribers can reply with solutions.
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A toolbox of elements to build technology intelligence systems.
4.3
Target
When identified, new technologies are investigated through the Target mode. For this mode, which is the one that the majority of systems observed developed to a greater extent [Mortara et al., 2007], coordination, connectors to external sources of information and search elements are employed (Table 5). Table 5: about here Co-ordination Co-ordinators of Target activities: Individuals responsible for the management of resources and to interface with the rest of the intelligence system and the organisation. People in this position usually have proven technical expertise and also an understanding of the corporate technology management policy. One of their primary responsibilities is to interface with the decision makers to identify technology gaps for investigation. This can be done through understanding and interpreting the explicit decision makers’, and by refining the specifications of the information required. In Print 1, the technology director and the technology manager coordinate the Target activity by delegating to a team of technologists the task of investigating new technologies. Each week, the director organises meetings that involve the whole technology group to learn about new developments and to steer the search. He also reports to the board about new findings and technologies which may represent new opportunities or threats. Enablers of the identification of key technologies: Roadmaps are popular choices, house-ofquality types of matrices are also used, watch lists (updated lists of technologies already identified as potentially important for the company’s future) and tripwires (mechanisms that auto-detect and report changes in key fields). Connectors to external sources of information External gatekeepers [Allen, 1977]: “Individuals that span the boundaries between the company and the surrounding environment, conducting high level communication between fellow workers and people external to the organisation”, are the people that connect the company to the external sources of information. Usually, for the Target activity the gatekeepers are widely recognised as experts in their technological field. In the position of a gatekeeper, several types of people can be found from technology consultants to sales agents. Networks of personal contacts: The Target mode performs the search on the basis of preidentified information to be gathered. The external gatekeepers provide connection with primary sources of information through relationships (external social networks). Examples of the external sources of information for Target [Mortara et al., 2007] (technical knowledge hubs, in Stephenson’s [1999] words) are academic departments, research centres, technical workshops and seminars, technical and scientific conferences, tradeshows and exhibitions, customers, advisory bodies, suppliers and collaborators and even other industries through benchmarking activities. For example, Food&Drink exchange information on best practice on how to transport liquids with other chemical companies. ICT networks: In addition to the social networking, information can be obtained through the search of external repositories such as databanks, databases of academic papers, patents, other companies’ websites, technical journals, technical reports, technical services of advisory bodies, blogs or books. In all these cases, sources are often reached via internet connections or by using the telephone, fax and e-mail.
Search elements Technical (field) experts: Experts possessing a vast knowledge relevant to their discipline have a central role in any TI system observed. Their role in information gathering activities can be easily understood considering the study by Bransford et al. [2000] who show the way in which experts
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A toolbox of elements to build technology intelligence systems learn. They organise their knowledge in ways that reflect a deep understanding of their subject and hence can identify features and ‘meaningful patterns of information’. As a result, they can be extremely fast in tracking and understanding implications of information for the business, hence can filter and analyse very effectively. Mech has appointed twenty technologists across the whole organisation as gatekeepers, in charge of gathering information about new technologies in their sectors. They were selected for their past track record of enthusiastic contribution towards change, not only for having had exceptional ideas, but also involving and encouraging others to adopt the changes. The selected gatekeepers were not just technologists and engineers very close to the technologies identified as potentially very relevant to Mech, but also in a position capable of implementing them. They had direct contact with customers and suppliers, and in general with their business sector, so that they could provide reliable information, mainly focussed on other companies activities. Technical specialised analysts: Technical personnel with a specific background and competence, who can evaluate and analyse highly technical information. Patent analysts who can collect and appreciate patent-related issues are of particular importance. For example, Print 2 hires a specialist to look for new technologies for liquids, by subscribing to technical services. Information is prefiltered and periodically reported to a project/product review committee. Print 2 also appoints an external patent analyst to perform searches on what types of technologies are filed by competitors and what trends in technology can be observed through patent analysis. A similar search is also done focussing on technology for relevance to customers. Common language: It enables and reinforces the exchange of both technical information and information needs across the business. Mech organises training for the gatekeepers where a common language is developed to foster information exchange. Subscriptions to external field specific services: A very common way of obtaining information from the outside is receiving periodical newsletters or mailing lists. Some services provide bespoke responses on demand. Examples found were technical databases of journals, patents, external intelligence services (e.g. NERAC, Ovid). To develop their network, gatekeepers use the services of intermediaries (or brokers) of knowledge [Hargadon and Sutton, 1997] (e.g. technical consultancies, networks and field associations, technology transfer offices and incubators). 4.4
Scan
The Scan mode, used to capture non previously identified information, presents similar elements to the Target (Table 6) with a few contrasting differences highlighted below. Table 6: about here Co-ordination Co-ordinators of Scan activities: Generalists (see Scan’s Search elements), as required by ‘active Scanning’ [Lichtenthaler, 2004a], co-ordinate the Scan mode. Co-ordinators are rarer for the Scan mode as it is often a solitary activity [Mortara et al., 2007]. In Imaging’s technology outpost, activities aiming at discovering new business and technological opportunities are co-ordinated by two scouts who combine technical and technology management skills. Their role is to establish directives for the whole TI activity (including Scan) as well as to manage collaborations with third parties. Enablers for the identification of information users: In contrast with the Target mode, roadmaps, house-of-quality type of matrices and organisational diagrams are used to identify people potentially interested in new information. Connectors to the external sources of information External gatekeepers: People who provide the connection between the company and the external sources of information. They can be categorised as scouts, recruiters/handlers or pathfinder [Kerr et
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A toolbox of elements to build technology intelligence systems. al., 2006]. While scouts and recruiter/handlers are deliberately appointed to search for weak signals and follow a more formalised approach, pathfinders serendipitously find information and make the connection with the company’s needs. Scout and handler/recruiter activities could be, for example, performed by managers in the search for new start-up business with whom to partner. As scouts, they participate at events and trade fairs where start-ups present their technologies in different fields, or consulting databases/reports about small companies activities; as recruiters/handlers, they communicate the company’s needs to organisations which typically work with start-up companies. In Print 2 a strategy director explores new market opportunities for expanding the business in line with the vision expressed by the board. The most interesting business opportunities identified (both from a market and a technical perspective) are selected and developed in business proposals. The strategy director provides ‘blue sky’ information as a scout, for example by participating at conferences, searching the web, contacting interesting SMEs; as a recruiter, by networking with venture capitalists and intermediaries, informing them of Print 2’s technical interests. Internally, he has also the handler role by communicating to interested stakeholders what was discovered. External social networks: Scan gatekeepers link with organisations that function as intermediaries and connections to other sources of information or other networks. Intermediaries are typically external companies which provide specific services to support innovation [Howells, 2006] but they can also be individuals who behave as knowledge brokers [Hargadon and Sutton, 1997], i.e. people who facilitate the transfer of knowledge between groups or communities [Cillo, 2005, Uzzi and Dunlap, 2005]. By tapping into the intermediary networks, a company can exponentially grow the number of contacts whilst maintaining and increasing selectivity. Examples of these are venture capitalists, regional and national technology networks which offer services for the connection between industry and academia, regional, national, EU development agencies. Hence, a company can be connected with external sources of information either directly to other hubs of knowledge (such as university centres) or indirectly through the intercession of the ‘environment pulse-takers’, in Stephenson’s [1999] terms by or intermediaries of knowledge (Fig. 5). When Targeting, the company connects directly to a specific knowledge hub if it is recognised as a significant potential primary source of information (e.g. a start-up). However, it is almost impossible to review, identify and to have contacts with every hub of knowledge. So, for the Scan mode, the network connection is preferentially made with the intermediaries, or secondary sources of information, which can both direct the information towards the company but also diffuse the company’s requirements in the environment. In this way the company can manage to receive selective information about the most interesting contacts in the external environment by deploying a limited amount of resources, through the intercession of the intermediaries. The TI activity can be driven by the company (information users) with the top-down approach or by the intermediaries (information brokers) who can proactively provide information before it is needed (bottom-up approach). Companies ask intermediaries to look for specific information while intermediaries independently look out and send updates. In the example in Fig. 6, by connecting to three intermediaries, the company achieves secondary connections with eight primary sources of information. Social networks with intermediary 1 and intermediary 2 are clustered as they both reach Start-up A. Intermediary 4 allows the connection to the network of intermediary 3, allowing to reach with secondary contacts 5 information sources. Imaging has developed criteria for evaluating the value of an intermediary, including: geographical coverage, technical coverage, network span, network density, capability, reputation, motivation and working style. Figure 6: about here Technology listening posts [Gassmann and Gaso, 2004; 2005]: Decentralised company facilities in specific geographic areas typified by centres of excellence in scientific research and industry and/or identified as innovation clusters [Porter, 1990], are often set-up by global companies. Scouts and recruiters/handlers usually have their operational basis in the listening posts. Imaging has created a technology outpost in Europe with specific location selected according to networking potential and practicality including the presence and reputation of local universities, presence of a
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A toolbox of elements to build technology intelligence systems community of venture capitalists, density of technological start-ups and SMEs, presence of other companies with relevant business, practical issues of people relocation and accessibility. Search elements Generalists: In contrast to the Target mode where experts and specialised analysts are employed, non-specialised analysts are the search elements for the Scan mode. While generalists can acquire more than a superficial knowledge of a wide range of topics, experts usually have a deep understanding of a limited number of topics. Bransford et al. [2000] suggest that in general experts are considered people who have the ‘answer to all the questions’. This perceived status might influence how experts feel towards the exploration of new and unknown knowledge fields: often they consider this a threat for their ‘expert’ status. However, experts who are ‘accomplished novices’, i.e. “skilled in many areas and proud of their accomplishments, but they realize that what they know is minuscule compared to all that is potentially knowable” [Bransford, 2000], continue to learn even though they may have spent long time recognised as ‘experts’ in their field. Hence, experts could also be generalists as long as they associate their deep knowledge skills with the capacity to broaden the remit of their knowledge. Often people with such skills are referred also as ‘T-shaped people’ in literature [Amber, 2000]. Technical generalists: Non specialised personnel with a general technical background can evaluate and analyse technical information. In Imaging, about 25 scouts are based in a technology outpost to look for new technological opportunities. They come from different cultures and involve people with different and complementary skills and competences, ranging from science and technology, to design, art, cognitive sciences, medicine and artificial intelligence. Attraction infrastructure: In order to receive information, with reference to the ‘bring-in’ approach of the Scan mode [Kerr et al., 2006], companies promote their willingness to hear from outside about new technologies, relevant information and ideas. Examples of such attraction elements include website calls for technological inputs and collaboration, corporate venture capital activities [Ernst et al., 2005], surveys and business plan competitions. Two multinational companies in the energy and FMCG sectors have setup corporate technology venture activities that invest in start-ups which might become useful to their future activities. While giving the chance to learn about new information, without specifically looking for it, this type of infrastructure has the drawback of being unselective, attracting also unsolicited and potentially inappropriate information. 5
Proposed use of the TI toolbox
The toolbox could be used to identify TI modes in which a company has invested significant resources and those which are weaker. Breaking down the complexity of the TI systems, using a blank diagram, it is possible to evaluate each mode by entering people and infrastructure involved in TI activities. The same individual or group may carry out multiple functions and may be placed in more than one box in the diagram even if tasks are carried out in combination with other responsibilities. Empty boxes indicate areas in which the company could expand or improve its activities. By reviewing the current state of the system and comparing ‘empty’ or ‘unpopulated’ areas of the map with the generic elements listed in the toolbox, a company could identify possible ways to improve and fill the gaps. In Table 7, an example from one of the case studies (Tech-consult) is reported, showing the map of their TI system (Fig.7). The overall aim of the TI system is to support its members’ present and future needs. In Tech-consult the gathering of information is a continuous activity performed in parallel with other day-to-day tasks within each technology group. Decision Makers: The technology groups’ managers (TGM) are the decision makers to whom information is fed by the group intelligence.
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A toolbox of elements to build technology intelligence systems. Mine: A central library, available to members and staff, acquires printed and online material, including books, journals, proceedings, theses, standards, and patents. Specialised staff abstract and tag the new literature with keywords and perform searches on behalf of enquirers. Intelligence results are reported periodically to the TGM and kept in intranet digital archives. However, a great part of the organisational knowledge, including past intelligence information, is mainly held by individuals. There is an archive of past projects consisting of formal hardcopy reports but it is poorly used, obsolete and difficult to search or update. An attempt to transform the archive into an electronic system is ongoing, under the supervision of a knowledge manager. Individual technology groups have their independent on-line archives disconnected from the rest of the organisation. Trawl: Tech-consult encourage informal parent-child relationships, whereby experienced employees introduce the younger generation to their own knowledge and personal networks. The library staff is often in the position to connect who is looking for information to those who have already gone through similar searches. A guide to staff expertise listing all employees by their core knowledge is available to staff and members. Target: In each group, technology managers (TM) are the TI coordinators and identify new technologies important for the future of their area. They delegate responsibility for learning more about each topic to individual technology group members. A matrix is produced on annually, in collaboration between the industrial support teams and the technology groups. On the matrix, current or desired technology expertise is matched against industrial needs. In some of the groups, local roadmapping exercises provide guidance on future technological needs. Everyone in the company is encouraged to build and make use of personal networks to obtain information. Most employees have developed personal networks and a record of information. Specialised technologists search for information through field-specific sources and personal contacts. The most common sources of information are universities, industrial partners, technical literature (e.g. patents and academic journals), newsletters, conferences and specialised technical services. A patent office searches for information on new technologies, how they work and whether they can be acquired by the company. Figure 7: about here Scan: Identification of unknown technologies with the potential to change the industry is carried out by a single individual who belongs neither to a technology group nor to an industrial support unit. This scout connects people interested in the development of long term strategies both internal and external to the company, through a social network, formed during 25 years of experience. The technology groups organise forums twice a year to which representatives from academic, industrial and government organisations are invited. The meetings provide an opportunity for discussion about the needs of the industry in the future years. A questionnaire is sent to the attendees in advance to select the most important technology areas to discuss. A yearly survey of the most recent technical publications is carried out by the library. Areas of Weakness: Scan is the least developed mode: a single individual with extensive company and technical experience performs this function alone, Scanning for new opportunities and future trends. The whole company relies only on his varied and well developed personal networks, representing a substantial risk for the firm. The loss of the scout could result in a cessation of the Scanning, if his networks are not transferred successfully to others in the organisation. The infrastructure which complement Scan (i.e. a peer review of the current understanding about new technologies and a yearly survey of the most important subjects and books published) cannot substitute for his activity. To improve this mode, considering the series of elements described in Table 6, the current scout could co-ordinate a group of other less experienced technical analysts and scouts and to involve them in his networks. For the Mine mode, different repositories of information can be listed, many of which are locally kept by the technologists. These are not accessible to everyone and especially to those in the other groups. Search elements could help the organisation to look into the digital archives, but much
Mortara et al., 2009
A toolbox of elements to build technology intelligence systems information is still kept in hardcopy form and is difficult to search. Tech-consult is very active in accumulating information on a wide set of technologies, so substantial resources are required for knowledge management. Using the elements available in Table 2, adopting search elements which can search in all the networked information repositories connected to the Tech-consult network, could be a possible improvement to the accessibility of information kept in local archives. Areas of strength: Personal networking is encouraged at all levels; this facilitates the internal exchange of information (Mine and Trawl) and the increasing of the links with the environment (Target and Scan). The library services and the patent office provide a valid support for all the four modes. Target is well organised with several technology managers coordinating the identification of new interesting technologies. Table 7: about here 6 Summary The research described in this paper addresses the gap identified by both academic and industrial audiences of how companies could set up TI systems. Through cross comparison of companies’ case studies [Mortara et al., 2007] and building on Kerr et al’s [2006] theoretical model], this paper proposes a generalised set of elements (toolbox) which can be used to map and characterise any TI system. It has been presented with an example of how it could be used, with data relative to one of the case studies observed. The toolbox is intended as a structure which could help both scholars and practitioners to approach the analysis of a TI system and to identify its strengths and areas for improvement. The toolbox proposes a classification that may be used as a template for the capture of new, currently unidentified elements. However, other organisations of the elements observed might be possible. The different choices of elements were attributed to the four modes of searching Mine, Trawl, Target and Scan [Kerr et al., 2006]. The categories suggested include the nature of the elements (e.g. people and infrastructures) and their functions (e.g. co-ordination, search, connection, storage). In both cases, other elements could be added which haven’t been included in this version. For example, the nature category could include other types of elements such as the ‘processes’ which enable each of the modes of searching information. The toolbox shows how systems are designed to connect the company’s decision makers to the repositories of information, either internal or external sources. With the exception of the Trawl mode which features just connector elements, the TI modes are supported by three types of elements, namely management, sources connectors and search elements. They can be either people’s roles, activities or characteristics, or infrastructures. Networks have a dominant role in any intelligence system. The paper proposes a model developed combining Stephenson’s [1999] model of social networks with the observation of practice. The model suggests that a company can be seen at a different level as a knowledge hub which is characterised by a subsystem of elementary network cells connected through gatekeepers. The internal search of information (of the internal knowledge hub) with the Trawling mode makes use of pulse-takers and internal gatekeeper connectors. Target uses links with primary sources of information via the external gatekeepers, while Scan provides the connection with a large number of non pre-identified sources of information across the environment through the link with secondary sources of information (intermediaries). Further work will be directed towards improving the understanding of TI social networks, with particular focus to the role of intermediaries. As the research is based on a limited number of case studies, further empirical data is needed to test and validate the toolbox. Words: ~6,910
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A toolbox of elements to build technology intelligence systems.
7 Acknowledgements The authors wish to thank Dr. Shehabuddeen who contributed to develop the foundations of this work and the companies for their support and collaboration. The study was funded by the Engineering and Physical Sciences Research Council (EPSRC) under the Innovative Manufacturing Research Centre (IMRC) grant.
8
References
Allen, T.J. (1977) Managing the Flow of Technology. Cambridge, MA: MIT Press. Amber, D. (2000 ) Researchers Seek Basics Of Nano Scale. The Scientist. Ashton, W. B., Kinzey, B. R. & Gunn, M. E. J. (1991) A structured approach for monitoring science and technology developments. Int. J. Technology Management, 6, 1/2, 91-111. Ashton, W. B. & Stacey, G. S. (1995) Technical Intelligence in business: understanding technology threats and opportunities. Int. J. Technology Management, 10, 1, 79-104. Bransford, J. D. B., A. L. Cocking, R. R. (2000) How people learn: Brain Mind, Experience & School, Washington DC:The National Academic Press. Bernhardt, D.C. (1994) ‘I want it fast, factual, actionable – tailoring competitive intelligence to executives needs’, Long Range Planning, Vol. 27, No. 1, pp.12–24. Brenner, M.S. (1996) Technology Intelligence and Technology Scouting, Competitive Intelligence Review, 7, 3, 20-27. Brockhoff, K. (1991) Competitor Technology Intelligence in German Companies. Industrial Marketing Management, 2091-98. Bucher, P., Birkenmeier, B., Brodbeck, H. & Escher, J.-P. (2003) Management principles for evaluating and introducing disruptive technologies: the case of nanotechnology in Switzerland. R and D Management, 33, 2, 149-163. Cillo, P. (2005) Fostering Market Knowledge Use in Innovation: The Role of Internal Brokers. European Management Journal, 23, 4, 404-412. Ernst, H., Witt, P. & Brachtendorf, G. (2005) Corporate venture capital as a strategy for external innovation: an exploratory empirical study. R & D Management, 35, 3, 233-242. Gassmann, O. & Gaso, B. (2004) Insourcing Creativity with Listening Posts in Decentralised Firms. Creativity & Innovation Management, 13, 1, 3-14. Gassmann, O. & Gaso, B. (2005) Organisational Frameworks for Listening Post Activities. Int. J. Technology Intelligence and Planning, 1, 3, 241-265. Ghoshal, S. & Kim, S. K. (1986) Building Effective Intelligence Systems for Competitive Advantage. Sloan management review, 28, 1, 49-58. Granovetter, M. S. (1983) The Strength of Weak Ties: a Network Theory Revisited. Sociological Theory, 1201-233. Hargadon, A. & Sutton, R. I. (1997) Technology Brokering and Innovation in a Product Development Firm. Administrative Science Quarterly 42, 4, 716-749. Kerr, C. I. V., Mortara, L., Phaal, R. & Probert, D. R. (2006) A conceptual model for technology intelligence. International Journal of Technology Intelligence and Planning, 1, 2, 73-93. Lichtenthaler, E. (2003) Third Generation Management of Technology Intelligence Processes. R&D Management, 33, 4, 361-375. Lichtenthaler, E. (2004a) Technological Change and the Technology Intelligence Process: a Case Study. J. Eng. Technol. Manage., 2, 1331-348.
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A toolbox of elements to build technology intelligence systems Lichtenthaler, E. (2004b) Technology Intelligence Processes in Leading European and North American Multinationals. R&D Management, 34, 2, 121-135. Lichtenthaler, E. (2007). "Managing Technology Intelligence Processes in Situations of Radical Technological Change." Technological Forecasting & Social Change, 74, 1109-1136. Mortara, L., Kerr, C. I. V., Phaal, R. & Probert, D. R. (2007) Technology Intelligence Practice in UK Technology-Based Companies. Submitted to the International Journal of Technology Management. Porter, A. L. (2004) QTIP: Quick Technology Intelligence Processes. EU-US Seminar: New technology foresight, forecasting & assessment methods. Seville. Porter, M. E. (1990) The Competitive Advantage of Nations. , New York, The Free Press. Reger, G. (2001) Technology Foresight in Companies: From an Indicator to a Network and Process Perspective. Technology Analysis and Strategic Management, 13, 4, 533-553. Savioz, P. & Blum, M. (2002) Strategic Forecast Tool For SMEs: How the Opportunity Landscape Interacts with Business Strategy to Anticipate Technological Trends. Technovation, 22, 2, 91. Savioz, P., Heer, A., Tschirky, H. (2001) Implementing a Technology Intelligence System: Key Issues, Portland International Conference on Management of Engineering and Technology (PICMET), Portland (US). Savioz, P. & Tschirky, H. (2004) Technology Intelligence System: Benefits and Roles of Top Management. Bringing technology and innovation into the boardroom. Strategy, Innovation and Competences for business value. New York, Palgrave Macmillan. Schuh, G. & Grawatsch, M. (2003) TRIZ-based Technology Intelligence. European TRIZ Association Meeting TRIZFutures 2003. Shehabuddeen, N.T. & Probert, D.R. (2004) Excavating the Technology Landscape: Deploying Technology Intelligence to Detect Early Warning Signals. IEEE, International Engineering Conference. Singapore. Stephenson, K. (1999) Networks. IN DORF, R. C. (Ed.) The Technology Management Handbook. US, CRC Press - IEEE Press. Tibbetts, J. (1997). Technology Scouting, in W.B. Ashton and R.A. Klavans (Eds.) Keeping Abreast of Science and Technology: Technical Intelligence for Business, Columbus, OH: Battelle Press, pp.217–257. Utterback, J. M. & Brown, J. W. (1972) Monitoring for Technological Opportunities. Business Horizons, 205-15. Uzzi, B. & Dunlap, S. (2005) How to Build Your Network. Harvard Business Review, December 2005, 53 - 60. Watters, E. (2006) How to Tap Your Company's Hidden Network. Forget the IT Network. It's a Company's Human Infrastructure that Really Determines whether It Lives or Dies. Business 2.0 Magazine April 6, 2006. Yin, R. K. (1994) Case Study Research: Design and Methods, Sage.
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A toolbox of elements to build technology intelligence systems.
9
Figures
Fig. 1: System modes for TI [Kerr et al., 2006]
Gatekeeper Network Glue = Trust
Hub Pulse-taker
Fig. 2: Elementary structure of networks. Adapted from Stephenson [1999]
Macroscopic view
Intermediate view
Microscopic view
Fig. 3: Multilevel perspective of company’s internal network. Adapted from Stephenson [1999]
Mortara et al., 2009
A toolbox of elements to build technology intelligence systems
Physical repositories
Fig. 4: The structure of the toolbox OK Yes
Contact trustworthy references
No Do they know?
Redirection towards heads of research groups and the business units
Redirection towards contacts of contacts
No Do they know? Yes OK
Fig. 5: An example of Trawling process through the use of personal networks at Telco-service
Mortara et al., 2009
A toolbox of elements to build technology intelligence systems.
Intermediary 2
University
Company 2
Intermediary 3
COMPANY Intermediary 4
Start-up A
Company 4
Intermediary 1
Start-up
Company 3 Start-up
University
Start-up
Start-up University
Start-up
Start-up Start-up Start-up
Direct connection to information source
University R&D Centre
Connection to information source obtained through intermediary
University KNOWLEDGE HUB
Company 5 Start-up
‘PULSE-TAKER’
Fig. 6: Generic representation of company’s TI external networks adapting Stephenson’s [1999] model.
Mortara et al., 2009
A toolbox of elements to build technology intelligence systems BUSINESS INTELLIGENCE TECHNOLOGY INTELLIGENCE - SCAN Industrial support 1
Government agencies Regional development agencies European organisations Industrial partners International contacts….
Experienced multi-interest technologist
Industrial support 2 Industrial support 3 Internal networks
External Networks
Industrial support 4 Industrial support 5
Infrastructures
…
TECHNOLOGY INTELLIGENCE - TARGET
Library
®
Technology Group 4
Technology Group 2
Technology Group 5
Technology Group 6
Technology Group 7
Patent office
Universities Industrial partners Research centres Technical conferences….
Technology Group manager External Networks
Technology manager Team members
Fig. 7: Tech-consult’s TI system [Mortara et al., 2007]
Mortara et al., 2009
INDUSTRIAL NEEDS
Technology Group 3 TECHNOLOGY
Database
Technology Group 1
♦ ♦ ♦ ♦ ♦
♦ ♦
A toolbox of elements to build technology intelligence systems.
10
Tables
Table 1: List of detailed case studies Name
Sector
1: Print 1
Manufacturing, Printing, UK
2: Techconsult
Technology Consultancy, UK
3: Print 2
Manufacturing, Printing, UK
4: Mech
Manufacturing, Mechanical Engineering, UK
5: Food&Drink
Manufacturing, Food, UK
6: Telcoservice
Telecommunicati on Services, UK
7: Imaging
Manufacturing, Imaging, US and UK
8: Telcomanuf
Manufacturing, Telecommunicati on, UK
Mortara et al., 2009
Description & general information Medium size manufacturing company which sells inkjet equipment and inks to original equipment manufacturers in industrial printing markets. Technology consulting. The range of technologies is wide and covered by seven main ‘Technology Groups’, each specialised in different applications. The know-how in the technologies supports several industrial sectors, which are managed by ‘Industrial Support Groups’. World-leader in printing technologies and solutions. It manages subsidiaries and distributors worldwide. The company’s business revolves around two key technologies. Multinational supplier of mechanical parts to automotive and aerospace firms. The company has recently embarked on the implementation of a TI system, starting from one of the two business units. Part of a US-based multinational company producing drinks, owning multiple successful brands. Three technology groups, working loosely together, take care of aspects related to production and packaging of drinks. Four lines of business are supported by a technology office for research and innovation. Nine research centres share expertise in several technological areas. Across those the ventures manage the research budget. Multinational organisation with headquarters in the US and subsidiaries worldwide. The company revolves around four main businesses covering both traditional and digital technologies. Designs, develops and commercialises mobile technology digital radios for the security, military and utilities sectors. The products are based on a standard technology which has now reached a mature stage.
Interviews number 10
10
5
10
4
5
10
2
A toolbox of elements to build technology intelligence systems Table 2: Interview protocol.
Questions examples Is this model representative of the TI activity within your organisation? Are there missing dimensions? What would you change? Comments?
Theoretical Model (Kerr et al., 2006)
General Company’s TI system
Framework
Who are the stakeholders? What types of decisions are being made? What type of information is needed? How do you communicate these needs? How is TI system work valued? What sources are used? Why is TI important for your organisation?
Process
Describe your TI routines. How do you identify, coordinate, search, filter, analyse, document and disseminate?
System
How do you operationalise TI? (i.e. what specific activities are carried out?) What elements build your TI system? What do you use for Mine, Trawl, Target and Scan?
What are your role/responsibilities/tasks within the TI activity? What are the resources and constraints associated with this work? How do you advertise for or Individual role seek information? What do you do if you stumble across a technology that could potentially threaten or benefit your business? What do you do if you find of interviewee information that might be useful? How do you store it? Is there any mechanism for feedback on your activity? How is your work judged? Table 3: Generic elements for the Mine mode
MINE
Co-ordination
Repositories
elements
(Internal sources)
Knowledge managers
Human knowledge
Search elements Processors of
People
knowledge Analysts of knowledge Processors of
Infrastructure
Competence directories
knowledge Physical repositories
Internal ICT networks Libraries
Mortara et al., 2009
A toolbox of elements to build technology intelligence systems. Table 4: Generalised elements for the Trawl mode Boundary spanners TRAWL (Connectors to internal knowledge) Intermediaries of knowledge People Internal gatekeepers
Internal social networks Internal ICT networks Infrastructure Competence directories Broadcasting communication
Table 5: Generalised elements for the Target mode Co-ordination
Connectors to
elements
external sources
TARGET
Search elements Technical experts
People
Co-ordinators of Target activities
External gatekeepers
Specialised technical and patent analysts
External social Enablers for the Infrastructure
specific services
External ICT
Generic search tools
networks
Common language
identification of new technologies
Subscription to field-
networks
Table 6: Generalised elements for the Scan mode.
SCAN
Co-ordination
Connectors to
elements
external source
Search elements
Generalists People
Co-ordinators of Scan activities
External gatekeepers
Non specialised technical analysts
External social networks Enablers for the Infrastructure
identification of information users
Attraction External ICT networks Common Language Technology listening posts
Table 7: Map of Tech-consult’s TI system using the toolbox
Mortara et al., 2009
infrastructure
Pre-publication draft: Mortara, L., Kerr, C.I.V., Phaal, R., Probert, D.R., 2009. A toolbox of elements to build technology intelligence systems. International Journal Of Technology Management 47, 322-345.
TRAWL
Boundary spanners (Connectors)
P
Library, information service and patent office staff (help others with similar searches). experienced staff
I
Personal internal networks Parent-child relationships among staff “who knows” guide ‘Encouraging internal communication’ culture
MINE
P
I
Co-ordination
Knowledge managers
Knowledge Management team
SCAN
P
I
Internal Search Sources TARGET elements (Repositories) Technology Managers/ Group managers, Library & Project leaders, Information service P Consultants, staff Technologists, Patent office personnel Library and Information service, Hardcopies of reports, “Who knows” guide Patent office, Website, Technical literature Technical Literature database keyword Database, search Local technology groups’ databases
I
Coordination
-
-
Coordination Technology Managers (one or more for each technology group) Local technology roadmaps & cross linking maps of technology base with industrial support groups
External Source Connectors Gatekeeper: One very experienced scout networking with customers and development organizations to understand future trends Networks of one experienced scout External Source Connectors Everyone in the technology groups and in the industrial support groups
Search elements One generalist scout networking with customers and development organizations to understand future trends
Surveys of technological trends with peers Surveys of newly printed books by library staff Search elements Technology groups & Industrial support groups (experts and technologists) Patent officers
Personal networks of all the technologists and industrial support people at all Subscriptions to external levels, services: Journals, attendance Patent searches to conferences etc. (through patent office staff) and literature searches (through library staff)
Area less covered: potential weakness
