Competitive Intelligence as a Sustainable Long Term Competitive Advantage

Table of contents

Abstract

Table of figures

List of tables

List of Abbreviations

1 Introduction
1.1 Topic
1.2 Goals of this thesis
1.3 Introduction

2 Fundamentals
2.1 Competitive Intelligence
2.1.1 Sub-groups
2.1.1.1 Internal Knowledge Management / Counter Intelligence
2.1.1.2 Competitor intelligence
2.1.1.3 Market Intelligence
2.1.2 CI evolution phases
2.1.3 The concept of “weak-signals”
2.2 Business Intelligence
2.3 Sustainable Competitive Advantage

3 Model Setup and Assumptions

4 Industry-specific requirements for CI
4.1 Industry classification
4.2 CI activities
4.2.1 ISIC 10
4.2.2 ISIC 20, 21
4.2.3 ISIC 25, 51
4.2.4 ISIC 26
4.2.5 ISIC 35
4.2.6 ISIC 62
4.3 Quantitative results
4.4 Overall result of the analysis (Thesis part one)
4.5 SMEs and CI activities

5 Legal frameworks and their influence on CI in Europe
5.1 Relevance of law for CI activities
5.2 Effectiveness of law in international environments
5.3 EU-specific legal frameworks
5.3.1 In general
5.3.2 The structure of European criminal law
5.3.3 The division of legislative power in the field of law relating to economic offences
5.3.4 Unfair competition
5.3.5 Data protection
5.3.6 Intellectual property rights
5.3.6.1 Community patent
5.3.6.2 Community design
5.3.6.3 Community trademark
5.4 Implications of globalization for protective effect
5.5 Implications of the law for CI activities in Europe
5.6 Legal filter of CI activities
5.7 Actual unenforceability because of public attention

6 Strategic decision making based on CI
6.1 Importance of CI for strategic purposes
6.2 Scenario Planning as a combination opportunity
6.2.1 Scenario Planning as a strategic tool in brief
6.2.2 Scenario Planning as strategic tool for CI
6.2.3 Identification of key influencing factors
6.2.4 Interim result
6.3 Achievement of a sustainable CA
6.3.1 Scenario Planning as tool to create a CA
6.3.2 CI as sustainable competitive advantages
6.3.3 The fit of CI and Scenario Planning creates CA
6.4 Overall result of the analysis (Thesis part three)

7 Discussion and Outlook
7.1 Conclusion
7.2 Managerial Implications
7.3 Limitations
7.4 Implications for research

Bibliography

Books

Journal articles

Internet / Electronic publications / others

Abstract

“Integrity without knowledge is weak and useless, and knowledge without integrity is dangerous and dreadful.”

Samuel Johnson (1709 – 1784)

Nowadays knowledge is the economic basis of each company. One needs to know the product, the technology behind it, but also the customer, the competitor and other circumstances that influence the business^[1]. The scientific term for the necessity of information gathering and its transformation into applicable knowledge is Competitive Intelligence (CI).

This thesis focuses on three questions regarding CI which are linked in a model. Firstly it gives an overview about the most important types of CI. Based on three types, namely Market Intelligence, Competitor Intelligence and Internal Intelligence, it raises the question if there are industry-specific requirements and general key aspects of the activity. The focus group consists of 15 multinational companies from 6 different industries which were analysed with respect to information gathering and types of CI activities.

Secondly the thesis considers legal aspects. It asks how effective international treaties and European laws are in terms of criminal prosecution of unfair competition and protection of intellectual property rights. The considerations are limited to those facts that might be taken into account for CI actions. In addition it analyzes if the results from the first part of the thesis are legally allowed or if some activities are legally questionable.

Thirdly it looks at the strategic relevance of the legally gathered information. Therefore it assesses the opportunities of CI activities for strategic implementation based on the existing strategic tool “Scenario Planning” and proves that the fit of CI and Scenario Planning has potential to create a sustainable Competitive Advantage (CA).

Table of figures

Figure 1: Overview of the hypothesized relationships of existing analyses and the hypothesis from the third part of the paper.

Figure 2: Classification of obtained information.

Figure 3: Overview of internal CI activities in the aviation industry

Figure 4: Marginal utility of CI Levels

Figure 5: Three-tiered test model

Figure 6: European patent system 2009

Figure 7: Community Design

Figure 8: Interrelation of CI and Scenario Planning (part one)

Figure 9: Interrelation of CI and Scenario Planning (part two)

Figure 10: Detailed structure of thesis (part three)

List of tables

Table 1: Overview of industry classification in accordance with ISIC standards

Table 2: Overview of the quantitative results of thesis part one.

List of Abbreviations

illustration not visible in this excerpt

1 Introduction

1.1 Topic

CI is the strategic foresight of the company environment. There exists the misconception that information equates to intelligence^[2] but information is factual^[3] whereas intelligence provides the factual connection for one specific question. Intelligence needs an analytical process that uses the fragmented information, filters it and transforms it into useful knowledge^[4]. Based on intelligence, a company can verify its strategic decisions and orientation^[5]. Benefits do not only occur because of the quality of the available knowledge but also the short reaction time. CI claims to provide the required information when the first “weak signals” appear. This would increase the decision options and thus could lead to a sustainable CA.

The importance of CI has risen during the last three decades from a seldom observed practise in only a few organisations to becoming a generally accepted and required part of business culture^[6].

1.2 Goals of this thesis

CI is a highly business oriented subject. Most of the invested interests are CI divisions, consultants that are looking for companies without their own CI departments or organisations that specialise in CI. There are also some organisations like the German DCIF and the international SCIP that promote CI on a professional basis, but also educationally. Market researchers, strategy consultants, departments for knowledge management and corporate management take advantage of CI. The existing analyses correspond to the needs of these stakeholders^[7]. They either regard a single company^[8], a sole industry, CI as a whole, CI in specific environments^[9] or espionage as delimitation to CI^[10]. There exists no comparison between industries. Wright et al.^[11] examined CI practises in the UK retail banking sector. Krummenast^[12] investigated the supportive affects of CI for chemical firms. Schweyer^[13] analysed CI resources in law firms and Desai and Bawden^[14] tested CI in the pharmaceutical industry. One could easily continue this list, but no cross-industry comparative analysis has been done until today.

The research on CI with regard to legal frameworks focuses very much on the boundaries between CI and espionage. Richardson and Luchsinger^[15] examine the influence of the Economic Espionage Act of 1996 on CI and corporate information and Crane^[16] defines when CI gathering becomes industrial espionage. Scientists with business backgrounds like Meissinger^[17] focus on potential dangers for trade secrets or describe only national law and its influence on CI like Lux and Peske^[18]. Scientists with legal background like Tiedemann^[19] are able to address the whole field of law relating to economic offences including national and international legal frameworks, but without a connection to implications for CI activities. No comprehensive overview exists about international law which has an effect on CI in Europe.

The importance of rapid response in strategic decision making processes within the organisation lies in its demonstrable contribution to sustainable CA and superior profitability^[20]. The effects of CI on strategic decision making has already received some attention in scientific papers. Attaway^[21] confirms the importance of CI for short and long-term strategic planning. He acknowledges the supportive character of CI for strategic decision-making, planning and implementation and its function for early warnings. Fahey^[22] addresses in his paper how to build a bridge between the many outputs typically generated by intelligence professionals and the analysis requirements of those responsible for developing and executing strategy. Also Gilad^[23] discusses the conditions under which a company needs to organise its intelligence activities. He proposes a strategy aimed at ensuring the effect of CI on decisions. But there is currently only one scientist, Kenneth Cory^[24], who has discovered a connection between CI and sustainable CA. He provides guidelines for analysing which activities are more likely to result in a sustainable CA and thus have a tangible effect. In summary the impact of CI on corporate strategy was examined as well as the impact of CI on sustainable CA. The impact of the fit between CI and influencing factors of Scenario Planning on sustainable CA was not assayed yet. Figure one gives a schematic overview about the modelling of part three.

illustration not visible in this excerpt

Figure 1: Overview of the hypothesized relationships of existing analyses and the hypothesis from the third part of the paper.

Source: The author.

As shown all three subjects of the thesis are more or less known in the literature but not evaluated in the same way. This lack of systematic approaches was picked up in this thesis. It develops a method to standardise information about specific industries and the value of CI. Due to the increasing importance of the legislation, relevant international treaties and European laws and regulations will be considered and analysed with regard to their implications on CI as well. The last part addresses the systematic use of CI as a tool to provide factors of influence for Scenario Planning. At the same time it tests if CI supports the creation of a sustainable CA.

Therefore a three-tiered model was developed which is able to combine these issues and

- To identify industry-specific differences in CI activities
- To identify important legal frameworks that have an impact on CI
- To identify the contribution of CI to a modern strategic decision making process.

1.3 Introduction

How can a company create a CA and thus build a foundation for sustainable success, increasing market share and above all a return on investment (ROI) which is attractive for investors? In “boom times” companies can be successful without a clear concept of how to create a CA. This success is hardly sustainable because the economic cycle will naturally face a weakening economy. The situation is even worse if managers make decisions based on some generic strategic recommendations. Only if relevant information about the specific circumstances is available, can a strategic decision be developed that might lead to a CA. This information can hardly be found in the past. In business the past is not a predictor of the future^[25], for some industries not even an indicator.

CI professionals claim to deliver the required information. To analyse the benefit of CI in terms of creating a CA one has to define the scope of it, which is difficult, because the scientific world relies on a confusing number of different definitions^[26]. No single definition has achieved worldwide acceptance, but most of those that have emerged over the years have only semantic changes in language and emphasis. This thesis will give CI structure and define the scope of it in chapter two.

Historically Porter was a pioneer in the field of CI. In 1980 he defined “Competitor intelligence” as the development of a response outline for the competitor. This should include answers to the following questions:

1. How confident is the competitor about his current situation?^[27]
2. What will be his next steps and future strategies?
3. What are the weaknesses of the competitor?
4. Which action will force the competitor to react in the most effective way?

These questions are still an important part of the subject, and there are companies that still focus on information regarding their competitors^[28]. Nevertheless most of them look at the entire competitive business environment. Knowledge about customers, the market, suppliers, distributors, regulations and consumer demographics^[29] are considered as important to develop a recommendation which does include a large number of influencing factors and thus will be as comprehensive as possible. This thesis will deal with the subject in chapter 2.1.1. From that point on the author will create an overview with industry-dependent knowledge and influencing factors with a general validity.

Most of the definitions somehow address legal and ethical boundaries^[30] to distinguish CI from spying. These boundaries are not easy to identify. There is sometimes a fine line between the legitimate tactics of CI gathering and industrial espionage^[31]. Peripheral activities are easy to classify – legally gathered information with no ethical reason to take offence is so-called “white information”. Information gathered through industrial espionage is known as “black information” and is obviously illegal. Between these two there is “grey information” which belongs either to one or the other area, depending on the ethical obstacle that a company establishes for itself.

An example of grey information gathering would be if a recruiting team is encouraged to search for new employees that worked for a competitor with the aim to pick his brains.^[32] The opposite action is equally problematic. It is considered as unethical if somebody does an internship to gain an insight into relevant strategic actions and to provide this information to third parties.

Another example of illegal and unethical business espionage is a company sending an employee to apply for a job at a competing firm solely for the purpose of retrieving information^[33].

A more detailed overview about questionable tactics is provided by Hallaq and Steinhorst^[34].

illustration not visible in this excerpt

Figure 2: Classification of obtained information.

Source: The author.

The influence of the legislation will probably increase. National intelligence services will be used more frequently to ensure the same chance of success of national companies in foreign markets.^[35] Moreover the European Union will have to consider stricter regulations to protect industrial secrets and intellectual property rights (IPR). Therefore the thesis will deal with the subject of law and regulations in chapter five.

CI is not practiced as an end in itself. One needs to avoid actions that end up on paper in a drawer. To review the practical use of CI the author will extend the work of Gausemeier, Plass and Wenzelmann^[36] who defined influencing factors on strategic decisions in terms of Scenario Planning by aligning his outcomes with those from the first part of the model where influencing factors were defined and filtered with regard to legal requirements.

2 Fundamentals

2.1 Competitive Intelligence

As already mentioned there are several common definitions for the scope of CI. In general, CI can be described as “the systematic gathering, analyzing, storing, disseminating and protecting of specifically tailored information to the decision-making and planning processes^[37] for both operating and strategic managers”^[38], but this definition is not exhaustive. The variety of definitions could be a reflection of a process of steady change within the business environment and amongst the players. The initial focus on competitors^[39] was enlarged to a comprehensive analysis of everything that influences the business of a company. As the thesis will show in chapter four, the extent of CI activities varies depending on the industry. Competitor Intelligence, Market Intelligence and Internal Intelligence are the most important sub-groups and will be addressed more specifically in the following sections. In addition the literature knows Technical Intelligence^[40], Retail Intelligence, Marketing Intelligence, Competitive Sales Intelligence^[41], Political Intelligence, and Partner Intelligence^[42]. In terms of process description it is a strategic, tactical and/or operational method to collect, analyse and process accurate, relevant, specific, timely and actionable information^[43] and thereby a tool for the continuous and coordinated monitoring of the competitive environment. The different levels of continuity and coordination are explained in section 2.1.2.

Sources of information can be very diverse. Industry meetings, trade fairs or carefully combined public information on industrial trials are traditional sources with high yield^[44]. Reverse engineering is a reasonable method to gather technical information. Joint-ventures with technology leaders^[45] may be interesting opportunities too, but with extreme effort. Since the Internet became an open source of information, companies use Google Alerts, Twitter.com, Twitter Search, Twitturly.com, BIT.LY.com, Quarkbase.com, Howsociable.com, socialmention.com, Facebook.com and Domaintools.com among others as low-intensity ways to keep an eye on the actions of other market players^[46]. Electronic communication through blogs, wikis or email has increased the amount of publicly available information tremendously^[47]. Moreover company web pages give access to speeches of employees, annual reports and a summary of press releases. These are all primary sources, whereas complete “CI-reports” are secondary sources which are created from CI consultants or institutions. Other popular secondary sources are trade journals and newsletters with in-depth company profiles^[48].

This fragmented data and unrelated signals, events and perceptions^[49] go through a systematic (technology-based^[50] ) analysis to create and update applicable knowledge^[51] in order to improve the business performance and thus the ROI^[52].

Many definitions centre also on ethical and legal selection of the method^[53]. It is considered as the legal opposite to espionage.

2.1.1 Sub-groups

CI is a contextual analysis which can comprise different areas of interest. To understand the aims and prerequisites for every type of information a categorization is helpful.

Therefore the most common categories will be mentioned in the following:

2.1.1.1 Internal Knowledge Management / Counter Intelligence

Internal Knowledge Management, also known as Counter Intelligence^[54], is the defence of attacks through knowledge protection tools and strategies as well as the coordinated knowledge exchange within groups of employees. Knowledge can be subdivided into knowledge which is embodied in products, documented knowledge, experience knowledge and social knowledge^[55].

Between 60 to 80% of the value added in technology driven companies is directly linked to knowledge.^[56] It is the only resource that increases if it is used and internally shared. The experience of employees has a special importance for a company. The more knowledge-based a position is the more dependent is the company on the abilities of the respective “key-employee”. If he or she leaves there would be a huge loss of know-how. Additionally it causes a high risk if the former employee joins a competitor. To ensure access of all relevant employees to the company’s enormous pool of knowledge is one goal of internal CI activities. This specific part of Counter Intelligence, which focuses on experience knowledge, is also known as HUMINT^[57] (“Human Intelligence”).

A challenge for companies is to manage the fact that employees often lack the motivation to share their knowledge. However the more sophisticated task is to define a formal method to find facts^[58].

To achieve reasonable results companies make considerable efforts. The following overview gives an impression of the major activities of only a single company solely with regard to internal CI.

illustration not visible in this excerpt

Figure 3: Overview of internal CI activities in the aviation industry

Source: The author.

Didactical Conferences for the expert community of a company support the network activities amongst the company’s specialists. Periodical conferences are organised with randomly changing relevant topics that are presented by the respective most experienced employee. That specialist knowledge is transferred to a larger group of engineers and process managers.

Innovation training does not transfer knowledge horizontally but vertically. It addresses the problem of high staff turnover. It is a tool to transfer know-how from very experienced employees to young engineers that recently joined the company. Doing so the company is able to continuously spread the knowledge amongst the colleagues and at the same time creates heterogeneous teams, which are generally considered as productive and good for the working atmosphere^[59].

A technical solution to store the know-how of employees is a platform with technical modules and process modules – a so called Learning path. Engineers have to create or update modules after every implementation of a new design or of an improvement process. One can ensure the usability of the platform through a user-friendly search function and a logical module structure e.g. a Wiki as a Web 2.0 application embedded in the intranet is a user-friendly possibility to edit^[60] the existing Internal Intelligence.

On the job knowledge transfers are rare but highly effective measures. It is used if an employee is in his last year before the retirement or if it is known that somebody will leave the company in six or nine months. To preserve as much know-how as possible a promising employee will follow the expert and learn from his actions all day long for approx. nine months. These costly and very exhausting transfers are only required to replace a high level key employee. The sample enterprise in the aviation industry has only two to three on the job transfers per year.

Beside pure internal knowledge protection there are also Counter Intelligence activities that protect the knowledge against external attacks. Internal Intelligence activities must reduce the vulnerability of the corporation’s CA and safeguard its assets from exploitation, theft and fraud^[61]. One has to secure information that competitors would want^[62]. To develop a measure catalogue one has to do a threat analysis and develop protection mechanisms. Such protection mechanisms can be divided into technical precautions, employee-related actions and targeted obfuscation of corporate strategies.

Examples of technical precautions could be communication networks which are bug-proof and tap-proof; internet-free computers, periodic changes of passwords and special encryption of important IT and communication devices^[63].

Employee-related actions are vital, because not only is the human factor the most important but also the weakest factor of Counter Intelligence which causes the biggest risk for a company^[64]. For example business trips contain in themselves the danger of intelligence theft through socializing with a business acquaintance from the competition^[65]. Measures are, for instance, the enduring promotion of team morale, data protection through raising awareness about the confidential handling of sensitive information^[66] and the prohibition of portable memory devices^[67].

2.1.1.2 Competitor intelligence

As discussed in chapter 1.3., Competitor Intelligence is the root of CI as externally-oriented business intelligence. In journals is it also known as “Strategic Intelligence”^[68]. It considers the process how a firm can collect information, including specific information sources and “benchmarking” techniques^[69] for evaluating the quality of their organizational resources relative to those of competitors^[70]. The aim is to collect and use information about relevant strategic steps of competitors, capacity-figures, main customer details, data about suppliers and strategic partnerships of the competitor to develop a perfectly adjusted own corporate strategy. Broader definitions consider Competitor intelligence as the aggregation of competitive information to facilitate strategic development and a CA^[71] and thus weaken the clear boundary between the generic term CI and the sub-group Competitor Intelligence.

2.1.1.3 Market Intelligence

Market Intelligence is also known as Tactical Intelligence. It is the ability to understand, analyze and assess the environment of a firm with customers, competitors and markets, and industries, that conduces strategic planning and help decision making^[72]. Taken in the literal sense it is comprised of all intelligence that is related to the market. Since market participants are part of the market^[73], too, market intelligence and Competitor Intelligence are not mutually exclusive. The early identification of market adjustments, new customer needs and upcoming trends and hurdles are prerequisites to a strategic analysis of the current market position. Based on these influencing factors a company’s board is able to build up market scenarios for the future. The supporting character of relevant market information for effective decision-making is very important and goes far beyond general market research. Therefore business methods in the field of future-oriented corporate management like Scenario Planning are used to utilize the collected relevant data^[74] to derive a market forecast from it^[75].

2.1.2 CI evolution phases

In this section the different levels of continuity and coordination in CI practice will be explained. In 2005 Michaeli developed a phase model that consists of four phases with increasing formal structures. Since then the model and the four phase names became generally accepted by the CI community. They are commonly used to describe the intensity of CI activities^[76].

illustration not visible in this excerpt

Figure 4: Marginal utility of CI Levels

Source: See Michaeli (2006): p. 6.

Lonely CI-Stars focus on ad-hoc-research^[77]. They are considered as reactive intelligence managers and have no continuous CI processes. Ad hoc analysis is performed on an “as requested” basis. It is focused on an event that is anticipated to impact the firm or its operations. A formal CI function is not necessarily required^[78]. The first active intelligence management is Guerilla–CI. One can characterize this level as subversive, unofficial and opportunistic^[79]. The benefit increases on that level and comprises unofficial actions and opportunistic behaviour. CI-islands arise out of established Guerilla-CI. They are structured, follow pre-defined formal processes and are in line with the central corporate management. The growing internal recognition and therewith the growing number of intelligence users generates strong benefit increase. CI-islands operate only in certain portions of the company like the Sales department or limited to geographical regions. The most comprehensive level is the CI Centre. These centres support strategic decisions, acquisitions and partnerships. Centres have an offensive rather than defensive attitude.

The higher the level the more intensive the efforts and the better the information potentially available. Nevertheless it is not necessarily the goal of a company to reach the highest level and to establish a CI-Centre. Every company has to calculate the investment-dependent marginal utility. For instance, this is influenced by the competitive environment, the industry, or the individual market position and thus by the necessity of different types of CI activities. An expected negative marginal utility on the next CI-level should be seen as a sign to remain in the respective CI-level.

It is difficult to find an appropriate method to calculate the utility of CI^[80]. There is often no direct correlation between the CI activity and the gained benefit (e.g. a new order, or a better pricing strategy). CI-audits are a good solution to on one hand check the quality of the CI-processes and on the other hand to verify the utility level through a past-experience analysis^[81]. This means the number of incorrect decisions should be reduced. Through a multiplication of prevented wrong decisions with the average costs one could calculate the utility of CI.

2.1.3 The concept of “weak-signals”

The concept of “weak-signals” goes back to Ansoff^[82]. It was an important discovery of early warning for the research team in the field. Ansoff proposes a dualistic approach to avoid strategic surprises. He claims an “after the fact responsiveness” and a “before the fact strategic preparedness”. If any inconsistencies within the trend line are noted one can react faster.

In this regard CI provides the “after the fact responsiveness” and serves as strategic radar to find such weak-signals. This would increase the decision options through temporally benefits and thus could lead to an advantage in comparison with competitors that react later.

2.2 Business Intelligence

Business Intelligence has two meanings. On the one hand it is used as synonym to CI^[83]. Reasons are miscellaneous. The demarcation to warlike activities and the better understanding of the strategic importance for the business are only two examples. On the other hand it is considered as IT-based management support that influences the operations indirectly^[84]. At first it was characterised by the analysts of Gartner Group. The aim of Business Intelligence is to support corporate decisions as technical corporate performance management tool. It can be used in nearly every department from Supply Chain Management to Controlling and serves as an analysis tool. Within Marketing it can be used to gain new customers or to support customer loyalty thereby reducing costs for data maintenance and advertising^[85]. Business Intelligence as an IT tool is somehow an assistive technology for CI.

To avoid any misunderstandings the thesis will mention the respective meaning if it speaks about Business Intelligence.

2.3 Sustainable Competitive Advantage

The title of the thesis links CI to sustainable CA. Therefore a short overview about sustainable CA as it is understood in the thesis shall be given.^[86]

A CA is an advantage over competitors gained by offering consumers greater value, either by means of lower prices or by providing greater benefits and service that justifies higher prices. Sustainability has traditionally been conceptualized as a condition where a firm’s CA resists erosion by competitor behaviour^[87]. A CA is more likely to be sustainable if it arises from activities that have more than one optimal configuration, because the differentiation advantage is difficult to retrace and hence it is less threatened by imitation or substitution^[88]. This is true for strategy-specific activities. They are based on several individual decisions that interact with each other and thus are difficult to imitate^[89]. Therefore these activities are more likely to represent sources of CA^[90].

3 Model Setup and Assumptions

In this chapter the basic framework of the analysis will be put forward. It is as follows. The population consists of multinational companies with at least 10,000 employees. Companies from six different industries were selected for the analysis and the results from seven detailed papers, six CI consultancy projects and two in-depth interviews are provided. The enquiry period stretches over three years, some data from papers was even older, but again verified before the use. In the first step the model considers all 15 multinational companies (C1 – C15). They will be grouped in specific industries (I1 – I6). The classification will be done in accordance to the International Standard Industrial Classification (ISIC). Countries around the world have used ISIC since 1948 to classify national activities. It is provided by the United Nations Statistics Division^[91]. The principle of ISIC is mutually exclusive. The fourth revision of ISIC is the latest version and will be used to tabulate the companies. The classification will be done with regard to section, and division. ISIC subdivides companies in the next place into groups and classes which the thesis does not do. Based on that grouping the thesis will analyse the respective CI activities in every branch of industry. The data is acquired from secondary sources that are either academic articles or data that the author received from companies or consultants about CI projects that were done in the recent past. The analysis includes the types of CI activities, collected information and generally performed practises. Afterwards a cross-industry analysis will show which CI activities are industry-dependent and which are standard. The heterogeneous set of information makes a classification of actions and efforts difficult. Therefore the thesis combines a qualitative result with a scale interpretation. The interim result will be a summary with the most important qualitative outcomes of the analysis and a table with the quantitative results. The table will consist of six columns and six rows. The three types Internal Intelligence (II), Competitor Intelligence (CoI) and Market Intelligence (MI) will be sub-divided into industry-dependent (II –D; CoI –D; MI –D) and essential industry-independent (II –I; CoI –I; MI –I) Intelligence gathering. They will be put in the available columns as column headings. Each row will contain the results of one industry analysis. The tabulated results will be a numeric value from “0” to “4”. “1” to “4” are linked to the CI-evolution phases that were discussed in section 2.1.2. An activity receives a “1” if the average company of the respective industry performs on a Lonely CI-stars level. “4” equates a CI Centre level. If there is not enough information provided to classify the activity, then it receives a “0”.

In the second step will be analysed if there are some information that cannot be gathered legally or if practises have to be excluded because they are illegal. Firstly the thesis will give a detailed overview of relevant legal frameworks. The legal structure is similar to the scheme in figure two. White information is protected through intelligent property rights whereas black information is prosecuted criminally through law relating to unfair competition. Secondly all data will be legally filtered. The outcome of the second step is the interim result from step one but reduced to those activities that a company can do without knowing violation of the law.

In the last step a comparison will be drawn between the outcomes of step two and influencing factors for Scenario Planning as an important strategic tool for the corporate decision making process to establish a sustainable CA. In reference to the scientific approach of Gausemeier, Plass and Wenzelmann^[92] the thesis identifies key factors for Scenario Planning. The consolidated findings of Cory,^[93] together with the defined content of section 2.3 will serve as criteria for the validation of the title of the thesis. The more data will be conforming the more one can agree on the hypothesis that CI is important to create a sustainable long term CA.

[...]

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^[1] Herring (2003): p. 6.

^[2] Caudron (1994): p. 35.

^[3] Kahaner (1996): p. 20.

^[4] Myburgh (2004): p. 48; Wilkins (2007): p. 20.

^[5] Kahaner (1996): p. 21.

^[6] See Fuld (2006), p. 5; Fleisher/Bensoussan (2007): p. 6.

^[7] See Badr et al. (2006): p. 31.

^[8] Pepper (1999): pp. 4-9.

^[9] Tao/Prescott (2000): pp. 65-78.

^[10] Hemphill (2002): pp. 501-511.

^[11] Wright et al. (2009): pp. 941–964.

^[12] Krummenast (2008): pp. 44-45.

^[13] Schweyer (2008): pp. 30-39.

^[14] Desai/Bawden (1993): pp. 327–339.

^[15] Richardson/Luchsinger (2007): pp. 41-45.

^[16] Crane (2005): pp. 233–240.

^[17] Meissinger (2006): pp. 15-22.

^[18] See Lux/Peske (2002): pp.109–150.

^[19] See Tiedemann (2010): pp. 3-9; 33-37; 111-120.

^[20] Day (1994): p. 37-52.

^[21] See Attaway (1999): p. 50.

^[22] See Fahey (2007): pp. 4-12.

^[23] Gilad (1989): pp. 29-35.

^[24] See Cory (1996): pp. 45–56.

^[25] Knilans (2009): p. 13.

^[26] Myburgh (2004): p. 48; See as examples: Kahaner (1996): p. 16; Michaeli (2006): p. 3; Calof/Wright (2008): pp. 717-718.

^[27] See for this and the following: Porter (1999): p. 88.

^[28] See Knilans (2009): p. 13.

^[29] See Knilans (2009): p. 13.

^[30] Source: Presentation from Capgemini, ACES Summer School@Capgemini 2007.

^[31] Crane (2005): p. 233.

^[32] Manta (2009): p.1.

^[33] Groom/David (2001): p. 13.

^[34] Hallaq/Steinhorst (1994): pp. 787-794.

^[35] See Michaeli (2006), p. 48.

^[36] Gausemeier/Plass/Wenzelmann (2009).

^[37] Fleisher/Wright (2009): p. 250.

^[38] Gilad/Gilad (1985): p. 54; Cory (1996): p. 48.

^[39] Porter (1999): p. 88.

^[40] Calof/Smith (2010): pp. 31-39. e.g. patent analyses, format related scenarios, technology potential analyses.

^[41] Agnihotri et al. (2008): p. 337.

^[42] Adams/Zanzi (2006): pp. 350–367; Krol et al. (1996): p. 28; Dickenson (2009): p.16.

^[43] Kahaner (1996): p. 16; Stauffer (2003): p. 3.

^[44] Stauffer (2003): p. 3.

^[45] Michaeli (2006): p. 44.

^[46] See Dickenson (2009): p. 16.

^[47] Britt (2006): p. 10.

^[48] Attaway (1999): p. 51.

^[49] Fleisher/Bensoussan (2007): p. 7.; See Grant (2008): p. 66.; Trim/Lee (2008): p. 732.

^[50] Heinrichs/Lim (2008): p. 95.

^[51] Schrader (2002): p. 6; Kunze (2000): p. 63.

^[52] Badr et al. (2006): pp. 29-30; N.A. (2009): p. 2; Price Waterhouse Coopers (2002): It found that the ROI from implementing a competitive intelligence effort will vary, but the average benefit from incorporating CI as critical knowledge into the strategic planning was a 20% faster growth rate of ROI.

^[53] Stauffer (2003): p. 3.

^[54] Schrader (2002): p.7; Michaeli (2006): p. 548; Myburgh (2004): p. 54.

^[55] See Boutellier/Gassmann (1996): p. 292 in: Gassmann/v. Zedtwitz (1996).

^[56] Pierer v. (2002) in: Davenport/Probst (2002): p. 5.

^[57] Michaeli (2006): p. 177-208.

^[58] Hendrichs in: Hannig (2002): p. 57.

^[59] Antonetti/Rufini (2008): p. 547-554.

^[60] Manchester (2007): p. 25.

^[61] Myburgh (2004): p. 55.

^[62] N. A. - Security Director’s Report (2009): p. 1, 11-13.

^[63] See Schaaf (2009): p. 185.

^[64] Schaaf (2009): p. 80.

^[65] See Schaaf (2009): pp. 109–120.

^[66] Michaeli (2006): p. 550-551.

^[67] Schaaf (2009): p. 114.

^[68] Schrader (2002): p. 7.

^[69] Komus (2001): p. 189.

^[70] Bisp et al. (1998): p. 56.

^[71] Rittenburg et al. (2007): p. 235.

^[72] Juntarung/Ussahawanitchakit (2008): p. 69.

^[73] See Weber et al. (2008): p.13.

^[74] See Weber et al. (2008): p.13.

^[75] See Pepels (2007): p. 13.

^[76] Romppel (2006): pp. 26-27.

^[77] See for this and the following: Michaeli (2006): pp. 5-7.

^[78] Attaway (1999): p. 50.

^[79] See Romppel (2006): p. 26.

^[80] Michaeli (2006): p. 23.

^[81] Michaeli (2006): p. 447.

^[82] See for this and the following: Kunze (2000): p. 44-45.

^[83] Michaeli (2006): p. 32.

^[84] Hendrichs, M. (2002): p. 219, in: Hannig ( 2002).

^[85] Sibold et al. (2006): p. 113.

^[86] Another resource-based approach is mentioned in journals which says that a competitive advantage is sustained if “it continues to exist after efforts to duplicate that advantage have ceased”: Barney (1991): p. 102; or rather if “competitors face significant challenges in acquiring, developing and using the resources underlying the value creating strategy”: See Mata et al. (1995): p. 495.

^[87] See Porter (1985): p. 20.

^[88] See Rodriguez et al. (2002): p. 136; Wade/Hulland (2004): p. 108.

^[89] Piccoli/Ives (2005): p. 749.

^[90] Porter/Siggelkow (2008): p. 37; Adner/Zemsky (2006): p. 227.

^[91] Source: UN Classification (2010), 22.03.2010.

^[92] Gausemeier et al. (2009): pp. 56-87.

^[93] Cory (1996): pp. 45–56.