Knowledge management in Hewlett - Packard services

I suggested the following theme: Improving Knowledge Management and Knowledge Sharing practices for GDIS APJ ASIA PACIFIC & JAPAN in order to  Improve quality and TCE TOTAL CUSTOMER EX

vietnam national university, HANOI

hanoi school of business

Doan Anh Tuan

Knowledge management

in Hewlett-Packard services

master of business administration thesis

vietnam national university, HANOI

hanoi school of business

Doan Anh Tuan

TABLE OF CONTENTS

ACKNOWLEDGEMENTS

ABSTRACT

TABLE OF CONTENTS

LIST OF ABBRIVIATIONS

LIST OF TABLES

LIST OF FIGURES

INTRODUCTION

NECESSITY OF THESIS

SCOPE OF WORK

METHODOLOGY

CONTRIBUTION OF THESIS

CHAPTER 1: THEORETICAL FRAMEWORK

1.1 DEFINING KNOWLEDGE MANAGEMENT (KM)……… 3

1.1.1What is knowledge? 3

1.1.2Managing knowledge 7

1.1.3.Relationship between Knowledge Management and Information Management 10

1.1.4.The duality of Knowledge 12

1.1.5.A final definition 14

1.2 HOW TO IMPLEMENT KM SUCCESSFULLY?……… 15

1.2.1 The value of Knowledge Management 15

1.2.2 KM in practice 17

1.2.3 Perceived need for KM 21

1.2.4 Key success factors 22

1.2.5 Managing the change 24

1.3 MAKING THE BUSINESS CASE ……… 27

1.3.1 How to measure KM impacts 27

1.3.2 Is KM profitable? 30

2.1.THE MARKET OF IT OUTSOURCING SERVICES 37

2.2.IT OUTSOURCING SERVICES IN HP 39

2.2.1 HP Services: A complete portfolio 39

2.2.2 Strategy and challenges 43

2.2.3 The Delivery organization 45

2.3 KNOWLEDGE MANAGEMENT IN HP 4

2.3.1 HP – a best practice organization? .49

2.3.2 Development of KM in HP Consulting 51

2.3.3 KM in HPS today 53

2.4 DIAGNOSTICS 57

2.4.1 Results from interviews 57

2.4.2 Results from other sources 64

2.4.3 SUMMARY 70

CHAPTER 3 RECOMMENDATIONS 3.1 RECOMMENDATION 3.1.1 KM STRATEGY 76

3.1.2 KM Organization 79

3.1.3 KM PROCESSES 81

3.1.4 KM CULTURE 83

3.1.5 KM TECHNOLOGY/SYSTEMS 85

3.1.6 KM MEASUREMENT 87

3.2 ACTION PLAN DISCUSSION AND CONCLUSION 91

APPENDIX 1

APPENDIX 2

APPENDIX 3

LIST OF ABBRIVIATIONS

Management

LIST OF TABLES

TABLE 2.1 : DISTRIBUTION OF INTERVIEWEES AMONG DIFFERENT POSITIONS

AND ORGANVIZATION ENTITIES 35

TABLE 3.1 : ADDITIONAL RESULTS FROM THE SHAREPOINT USAGE SURVEY 66 TABLE 3.2 : NEED FOR IMPROVEMENT OF KM - FACTORS 66

LIST OF FIGURES

FIGURE 1.1: THE HIERARCHY OF EXPERIENCE AND LEARNING (SOURCE:

BELLINGER [13] 6

FIGURE 1.2 : KNOWLEDGE MANAGEMENT VS INFORMATION MANAGEMENT 11

FIGURE 1.3: THE THREE DIMENSIONS OF HPCI'S KM PROGRAM (SOURCE: HP INTERNAL KM MATERIAL) 14

FIGURE 1.4 PERCEIVED IMPACT OF VARIOUS KM ACTIVITIES 21

FIGURE 1.5 : APQC’S MODEL FOR SUCCESSFUL IMPLEMENTATION OF KM 26

FIGURE 1.6 : APQC’S KM MEASUREMENT FRAMEWORK 28

FIGURE 2.1 : INFRASTRUCTURE SERVICES SPECTRUM 38

FIGURE 2.2 : IDC LEADERSHIP GRID: EUROPEAN MANAGED SERVICES MARKET 3

FIGURE 2.3: EXTRACT FROM FY05 THIRD QUARTER RESULTS FOR HP SERVICES 42 FIGURE 2.4 : HPS CUSTOMER ENGAGEMENT ROADMAP 47

FIGURE 2.5 : PRINCIPAL COMPONENTS OF THE HPCI KNOWLEDGE NETWORK 56

FIGURE 3.1: APPRECIATION OF SHAREPOINT FOR DIFFERENT USAGES 67

FIGURE 3.2: POSITIONING AND PERCEIVED KM NEEDS FOR GDIS ENTITIES 73

FIGURE 3.3: SUGGESTED KM IMPROVEMENT FRAMEWORK 75

FIGURE 3.4: THE FOUR-STEP APPROACH OF THE KM METHODOLOGY 83

INTRODUCTION

 Necessity of the thesis

Can one really manage knowledge? Knowledge is something intangible and hard to define Yet it is what drives the modern economy Companies have since long optimized their products in terms of price, quality, production costs and positioning in the market Now they struggle to leverage their last differentiating asset: the sum of the know-how of their experts, product developers, marketing managers, engineers and sales force, what they call their “corporate knowledge base”

No sector is more dependent on intangible assets that the service sector, because services are in reality nothing else than capitalized brainpower Therefore, service organizations were back in the 1990es the first to study how they could best leverage their corporate knowledge Within the IT world, companies that had been managing information started to manage knowledge – claiming that with help of smart systems they would be able to capture and store human ideas and know-how

This thesis discusses Knowledge Management (KM) in one of the world‟s largest IT service corporations: Hewlett-Packard Services Late entrant into the market of IT outsourcing and managed services, HP Services has managed to become a global trendsetter, alongside IBM, in only a few years Growing and thriving in this highly competitive market requires adaptability, and HP Services has changed quickly and adopted highly advanced collaboration techniques to streamline their global service delivery organization Knowledge Management is a part of the daily working language, but is it practiced efficiently? We hope to give the answer in this thesis

 Scope of work

The fieldwork for this thesis was carried out at HP Asia Pacific Pte Ltd The mission was to study the current practices of Knowledge Management within the delivery organization of outsourcing services in APJ (Asia Pacific & Japan), and if

necessary propose and implement improvements that could impact positively on the business performance The thesis is for the MBA degree at Hanoi School of Business, Vietnam

An important, although small, part of the study was to understand the business context The IT Outsourcing services market is highly complex and in continuous change Understanding this market and HPS‟ current situation and positioning will help understand how KM can be applied effectively A short assessment of the managed services and IT outsourcing markets as well as HPS‟ position, its service offerings and current challenges is therefore presented in chapter 2.2 and 2.3

 Methodology

Description of the mission

HP Services is an organization exposed to constant changes, as much in the highly competitive market of IT services as in the value proposal to clients and the way the contracted service products are delivered These ongoing evolutions call for

a constant rethinking of how productivity can be increased, while at the same time keeping a satisfactory level on quality and customer satisfaction

In this context, knowledge management is seen as one of several tools to help organizations improve their performance At the same time, as we have seen,

KM is a vast area with many possible types of activities at different levels HP Services‟ Delivery organization for IT outsourcing and managed services had identified KM as a target area of possible improvement, but needed to find out if, where and how KM techniques and practices could be improved and exploited effectively in order to improve the organization‟s performance

Therefore, when I joined HP Vietnam (a part of HP Asia Pacific Pte Ltd), of which, the Quality & Process department in Global Delivery Infrastructure Services

(GDIS)6, APJ (ASIA PACIFIC & JAPAN) region, it was clear that the problems

need to be attacked I suggested the following theme:

Improving Knowledge Management and Knowledge Sharing practices for GDIS APJ (ASIA PACIFIC & JAPAN) in order to

 Improve quality and TCE (TOTAL CUSTOMER EXPERIENCE) on

outsourcing projects

 Assure compliance with external and internal KM standards

 Increase efficiency of service delivery

 Assure effective communication and sharing between “closed” silos

6

For a detailed description of the HP Services organization, see chapter 2.3

I also suggested spending a considerable amount of the time on establishing

a comprehensive understanding of the current situation This meant doing a thorough mapping of existing KM practices, both within GDIS and elsewhere in HP Services Such a mapping process would ensure that whatever proposal was made would be consistent with existing activities and leverage present best practices This proposal was accepted by the Quality & Process manager, who saw a thorough understanding of the current state as a necessary step in order to convince higher level management to invest in the improvement proposal

Assessment of the current state of KM

The first and, as it turned out, most important part of the mission was the mapping of current KM projects and needs within GDIS Three main questions were asked during this stage:

1) What KM initiatives are already in place and how are they linked? Is there

an overall KM policy/strategy?

2) What are the perceived needs for KM improvements?

3) Where and how can KM improvements help enhance delivery performance and what are the gaps between perceived needs and real improvement potential?

The needs for improvement were analyzed from two different perspectives:

a) Requirements imposed by the business and organizational contexts

b) Internal demands for improvement

In this phase it was seen as very important to get not only an overview over current KM initiatives, but also to hear what people in different parts of the organization thought about the current situation and where they felt needs for improvement This approach was a direct result of theory, since as we saw in Chapter 1, culture and people are key aspects of KM In order to make employees take ownership of a KM solution, it is therefore of uttermost importance that the suggested improvements answer to an experienced need

For this reason, qualitative interviewing was chosen as the main vehicle for information gathering since it would allow people to come up with independent ideas at the same time as it would allow for a higher freedom of expression compared to surveys However, a survey was also used for system mapping, since this concerned mostly technical information which was more neutral standardized in nature All together, the following five sources of information were used:

1 Qualitative interviews (22 interviewees)

2 Survey on KM system usage (63 answers in 1 month)

3 Complementary informal conversations with selected persons (10 to 20 people)

4 Search for information on the intranet

5 Study of external best practices through literature (see chapter 1)

The qualitative interviews were carried out after a using a set of questions given in the interview checklist in Appendix 1 The questions were grouped along 6

KM dimensions inspired by Mathi [10]: Strategy, Culture, Processes, Organization, Technology/Systems and Measurement All in all, 22 such interviews with an average duration of 1 hour were conducted The interviewees were chosen along two criteria:

a) People with strategic positions relative to KM, and b) People whose views would represent as much of the organization as possible The names of persons to

interview were given by colleagues GDIS being a geographically dispersed organization, most of the interviews was conducted in English and by telephone A few interviews were conducted face to face and some of these were done in Singapore The interviewees were categorized according to function, type of position, seniority (mean seniority =10.3 years) and whether or not they had background from other similar companies (Compaq: 4 persons, IBM: 1 person, EDS:

1 person) Interviewee information is provided in Table 1

Table 1: Distribution of interviewees among different positions and organization entities

Although the interview checklist in Appendix 1 was followed for all the interviews, the interviewees were encouraged to talk freely around the subject in order to capture any ideas or points uncovered in the questions For this reason, not all the questions in the checklist were asked during each interview Moreover, answers were often outside the scope of the question In spite of these lack homogeneity in the answers, certain tendencies were spotted and extracted from the interviews to form the statistics given in Appendix 2 Here, a certain number of common assertions are given, some answers to direct questions, others spontaneous statements given by several persons For each assertion, each interviewee was attributed “agree” or “disagree” in the case there were strong indications of the subject‟s opinion on the particular question In the case no such indication was found, the answer was set to “no opinion” This homogenization effort provided a useful tool in spotting differences in needs and opinions about KM between

different departments and different occupational categories

In addition to the qualitative interviews, the survey on a particular KM technology deserves a presentation The survey concerns the KM tool called SharePoint, a web-based Microsoft application intended facilitate collaboration between virtual and remote teams (teams in which the members work out of different geographical sites – see chapter 2.4.2 for a more detailed presentation of the tool) The survey was distributed to owners of SharePoint sites through a general message to all managers in GDIS 63 answers were received, a number that

is quite good for a survey, but low compared to the believed number of sites7 In addition to strictly administrative and quantitative information, a few questions related to content quality were added to the survey, e.g the number of documents which content was thought to be useful for persons outside the core user community The answers that were obtained here are interesting, but care must be taken in their interpretation since the site administrators would not always be familiar with the content in documents of which they are not the owners Nevertheless, the SharePoint survey provides a relevant complementary source of information for the evaluation of the current state of KM in GDIS

 What‟s KM and the role of KM

 KM assessment in HPS

 KM improvement; action plan & recommendation

to comprehend the complex world we have created

In the business world, as in society, managers compete to feed new products into customer segments that they would have characterized as saturated only a few years back The mounting competition leads to increased pressure on price and quality, and as margins are dropping, product developers and marketing experts look for new ways to differentiate, striving to satisfy needs that are unknown even

to the customers themselves This self-justification of production is only one of many signs that humanity has definitively left the modern (technology-driven) era for post-modernity, a time with fewer truths, but with one intangible but fundamental virtue; the concept we call knowledge

So how can we define this knowledge around which the new society circles? Semantically, three main definitions seem to be prevailing1:

1- The fact or condition of being aware of something (i.e science, art, technique, truth or fact) with familiarity gained through experience, reasoning or association

2- The range of one‟s information or understanding

3- The sum of what is known: the body of truth, information, and principles acquired by mankind.[

[ Definitions extracted from Merriam-Webster Online Dictionary: (http://www.m-w.com/)]

We see that „knowledge‟ is traditionally either related to personal awareness and skills or to the sum of all existing truths that are known by or accessible to all human beings However, the apparition of the Knowledge Management (KM) concept has slightly altered the use of the word in order to make it encompass the sum of information and working practices that allow a company to produce valuable products and services We are talking about “company knowledge”, a notion first introduced in the beginning of the 1990-ies

Wilson [31] argues that such a use of the word is contradictory, since

“knowledge involves the mental process of comprehension, understanding and learning that go on in the mind and only in the mind” Talking about “knowledge”

as a company asset is therefore said to be meaningless Rather, what can be stored, treated and evaluated by a company is knowledge that is articulated, i.e spoken or written down by the “knower” This is, according to Wilson, equivalent to what we normally call “information” – a concept that is closely related to communication and which companies have been managing for decades through various Information Management (IM) practices (for a definition of IM see chapter 1.1.3)

Essers & Schreinemakers [16] agree with Wilson that an acceptable demarcation

between information and knowledge 2 is semantically AND referentially impossible However, Essers & Schreinemakers justify the new utilization of the word

„knowledge‟ by the clear difference in objectives and guiding principles between

IM and KM There was a need for a new term, and „knowledge‟ fitted the need Such an argument can be seen as highly post-modern in the sense that if taken to the extreme, it would allow words to have any definition as long as the meaning is common and useful to all appliers inside a closed community3

Practical, we might think: Knowledge is different from information because we want it to be! The truth is, however, that knowledge continues to have several different meanings depending on the context Nevertheless, there seems to be an agreement in the KM community that the distinction between information and knowledge is related to the amount of experience and brainpower necessary for the interpretation, combined with a certain difference in the dependency on context for meaning to appear Bellinger [13] adds wisdom to the hierarchy and thus ends up with the diagram in Figure 1 He further states that:

 Information relates to description, definition, or perspective (what, who, when, where)

 Knowledge comprises strategy, practice, method, or approach (how)

 Wisdom embodies principle, insight, moral, or archetype (why)

2

Knowledge seen as an „object‟ that can be captured, shared among individuals and stored in knowledge repositories This usual way of using/defining knowledge dates back to early KM pioneers like Ikujiro Nonaka who published his first research on “organizational information creation” in Japanese companies in the 1980ies

Figure 1: The hierarchy of experience and learning (source: Bellinger [13])

Another tentative comes from Davenport & Prusak[6], who, while admitting to the difficulty of giving a precise and covering definition, acknowledges the same need to distinguish knowledge from information They therefore end up with a far more complex “working definition”:

“Knowledge is a fluid mix of framed experience, values, contextual information, and expert insight that proves a framework for evaluating and incorporating new experiences and information It originates and is applied in the minds of knower In organizations, it often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms.” (Davenport & Prusak [6], p 5)

This definition distinguishes knowledge by its complexity and by its relation to the intellect and to the activity and community that creates it, thus to a certain extent uniting the statements of both Bellinger and Essers & Schreinemakers

1.1.2 Managing knowledge

As we have seen, the emergence of Knowledge Management as a discipline

is based on the recognition among companies that intelligent application of internal know-how is a key success factor This trend is not new4 Managers have always sought, used, and valued knowledge implicitly, for example by hiring experts and people with experience What is new is the explicit acknowledgement of the need to manage and invest in knowledge with the same care paid to getting value form other, more tangible assets

4

The recognition of the importance of knowledge in the new economy can, according to Infed (http://www.infed.org/biblio/learning-organization.htm) be traced back to Donald Schon, who, as early as in the beginning of the 1970ies, provided a theoretical framework linking the experience of living in a situation of an increasing change with the need for learning He called this the learning society and later projected his findings on the firm, resulting in emergence of the term the learning organization

Many researchers attribute this new trend to the globalization of the economy As Devenport & Prusak [6] rightly recognize, “companies now require quality, value, service, innovation, and speed to market for business success” They continue by stating that “a business firm that thrives over the next decade [is one that] knows how to do new things well and quickly” Wickramasinghe [30] calls this increase in the importance of knowledge to companies a “paradigm shift” in which knowledge is accepted as “central to organizational performance” In this situation, acquiring control over the existing knowledge is seen as a vital first step Former HP CEO Lew Platt expressed the feelings of many managers when he said:

“If HP knew what HP knows, we would be three times as profitable” [6]

Managers and researchers seem, therefore, to agree on the importance of knowledge as corporate asset in today‟s economy However, there are many different opinions on the ability of corporations to manage knowledge effectively This diversity is linked to the complexity of corporate knowledge, for as many

authors state,“…knowledge is not neat or simple It is a mixture of various elements;

it is fluid as well as formally structured; it is intuitive and therefore hard to capture

in words or understand completely in logical terms Knowledge exists within people, part and parcel of human complexity and unpredictability Although we traditionally think of assets as definable and “concrete”, knowledge assets are much harder to pin down.” (Devenport & Prusak, [6])

This complexity explains to a certain extent why KM practitioners have a hard time defining the knowledge they claim to be able to manage It also explains why so many critics have been raised against this newcomer on market of management practices Many skeptics have argued that KM is just another

“management fad” that will fade away in the same way as other “fads” and trends like Total Quality Management (TQM), Business Process Reengineering (BPR), Enterprise Resource Planning (ERP) and Organizational Learning All of these have certainly worked for many businesses, but there is a common understanding today that “off-the-shelf” management solutions of this type will at best need a high degree of customization to work As a strong carrier of this point of view, Wilson [31] states that: “KM came along just as they (the IT firms) were being hit by a wave of scepticism over the possibility of IT ever delivering more than problems”

In Wilson‟s opinion, IT firms like IBM were thus able to sell old IT solutions under

a new name, turning “Groupware” or “Personal Information Management” systems into “Knowledge Ware”

Indeed, the popularity of Knowledge Management has decreased since the concept was introduced in the 1990ies This change, while by some seen as the beginning of the end for KM, is by others interpreted as a natural next step indicating that KM as a tool for improving management practices has finally reached maturity In this regard, Brown & Duguid [15] define KM as “bottom-up” and based on “practice” as compared to the since-long practiced Reengineering which is “process” based and inherently “top-down” By recognizing the “inventive, improvisational ways people actually get things done”, Brown & Duguid [15] argue that KM helps managers find the balance between practice and process, thus

enabling both the creativity and structure needed for a corporation to succeed in the marketplace In this way, KM is becoming “integrated into normal operations of business”, as King [20] formulates it

This change of status has several implications Firstly, KM projects are now expected to show the same hard value return as other business deals, an aspect which is treated separately in chapter 2.3 Secondly, KM responsibility is shifted from corporate KM groups into the local business units, thus being “diffused throughout the organization” to use a wording from the consulting branch of IBM [25] Finally, there is a spreading recognition that technology cannot alone solve the problem of helping companies leverage their knowledge Where in the 1990ies companies made huge one-time investments on collaboration tools and knowledge database systems, the same companies have today come to see KM as a continuous process closely linked to the willingness of people make information and knowledge flow easily within the organization

This last point, which consists in including soft components like culture, people and organizational aspects in order to achieve success in a KM program, is highly emphasized in the literature The Economist Intelligence Unit [29], for example, states that: “Technology can help unlock knowledge, but corporate culture

is more important Understanding who knows what, and how people use different types of information as part of their work, is just as important a part of good knowledge management as having the latest business technology.” Similarly, Smoliar [27] suggests that: “The origins of knowledge management are far more firmly rooted in the psychological legacy of organizational communication than they are in the technological legacy of information management systems” He concludes that since knowledge transfer depends on interaction rather than communication, the next necessary step beyond KM should be Interaction Management Mathi [10] goes the same way, by identifying as many as 5 (almost) equally important key success factors for KM, of which technology is only one (see

section 1.2.4 about KM key success factors) Finally, Davenport & Prusak [6] agree that culture is important for successful KM and make their point by confirming that

“…information technology is only the pipeline and storage system for knowledge exchange It does not create knowledge and cannot guarantee or even promote knowledge generation or knowledge sharing in a culture that doesn‟t favour those activities”

1.1.3 Relationship between KM & IM

In order to make it clear what KM is and what KM is not, it is important so look at where theorists situate KM as compared to traditional Information Management As seen in chapter 1.1.1, theorists like Wilson see no difference between KM and IM simply because they see no difference between information and knowledge as used by among KM practitioners Others, like Essers & Schreinemakers [16], see the difference mainly in the objectives and guiding principles behind the two different disciplines

When searching through literature on the subject, the general opinion seems

to be that although many KM activities are very close to IM, KM generally incorporates a much wider spread of practices than IM Further, the general opinion seems to be that the two management disciplines tend to drift further apart as KM is leaving the all-technology focus in advantage of a more holistic perspective where culture and process is seen as equally important In practice, Information Management is a collection of technologies that assist in the capture, indexing, and dissemination of organization information The technologies in Information Management might include search tools, portals, document management tools, content management tools, relational databases, etc As such, Information Management should be viewed as an enabler of Knowledge Management, but it is not part of Knowledge Management itself Thus, one can have an outstanding set of

IM tools, but have little knowledge management Conversely, one can have Knowledge Management in a company, without using any IM tools However,

ultimately, a large company probably requires a robust IM infrastructure to enhance its KM efforts Gartner Group – a leading consulting company in the KM field, states:

"Information access is the element that links IM and KM A key tenet of KM is that providing people access to information and to the knowledge of others will improve decisions and work processes, will enhance learning and, generally, will encourage people to become more creative and innovative However, KM requires information access to be implemented within a framework of strategy, business objectives and cultural change; conversely, when separated from these additional KM elements, information access is simply part of IM." (Gartner Group [17], 2000)

By defining information access as the common denominator between IM and KM, this definition solves the demarcation problem and provides a very useful distinction which helps explain why KM has become so widely acknowledged The common frontier is even more precisely defined by the classification of typical KM&IM activities under strictly IM, KM or both (Figure 2) As a conclusive remark we can say the IM is an enabler for KM

Figure 1.2: Knowledge Management vs Information Management.(Source: Gartner Group [17])

1.1.4 The duality of knowledge

As the discussion in chapter 1.1.1 indicates, there have been many attempts

to define knowledge following the apparition of KM as a distinct discipline in opposition to plain Information Management Indeed, as we have seen, knowledge

is not a simple object, but manifests itself in a myriad of ways, some documented, some not This debate is far from finished, and many researchers argue that the lack

of clear demarcation lines for what can and cannot be called knowledge is linked to

a general failure to recognize that some aspects of knowledge cannot be successfully articulated, abstracted, codified, captured or stored

Hildreth & Kimble [18] agree with this viewpoint and argue that there should be a clear distinction between hard knowledge, knowledge that can be captured, structured and stored in databases, and soft knowledge, knowledge that is basically “what people know” Clearly linked to the more and more frequently recognized culture dimension of KM, the soft knowledge is often identified as tacit,

ie Understood without being expressed, whereas hard knowledge is called explicit since can be expressed fully and clearly The „tacit‟-„explicit‟ terminology is often encountered in KM literature and dates back to Polanyi, who described tacit knowledge as “the idea that certain cognitive processes and/or behaviours are undergirded by operations inaccessible to consciousness” (Wilson [31]) Tacit knowledge can thus be identified as “what we don‟t know that we know”; it is

“hidden even from the consciousness of the knower”

If such is the case, tacit knowledge in organizations is in practice unmanageable, since no one is clearly able to identify it! Davenport & Prusak [6] try to solve the problem by suggesting that knowledgeable people in organizations are generally known to be so Their tacit knowledge can therefore be “codified” simply by identifying who the experts are and ask them to solve problems that need

to be solved However, this solution would not be logically valid since in order to identify which expert to contact for a given problem, we need to know who knows

what, and hence the knowledge would no longer be tacit! In addition to this clear dilemma, Davenport & Prusak [6] go even further by claiming that “patterns of tacit knowledge” actually can be captured and stored in a repository!

It is understandable that such philosophical impasses make life hard for practitioners who try to make executives agree to invest in knowledge management

KM simply has too many meanings and implications This “terminological ambiguity”, which “often require a host of adjectives to make clear exactly in what sense [the term KM] is being used” (Hildreth & Kimble [18]) has lead to important critics towards those who promote KM as a discipline However, it must be understood that KM is by no means meant to be just a set of easy rules that that can

be applied straightforwardly for guaranteed better business performance Quite on the contrary, KM is indeed a philosophy, a way of living in which increased openness and a genuine willingness to capture and share knowledge are guiding principles But KM is more than just culture and common belief, it is also hard facts

In addition to facilitating the necessary cultural change, KM practitioners should also provide a framework of tools and processes to facilitate implementation of the high level principles In fact, the three dimensions, Culture, Technology and Process, must be equally emphasized, with the means adapted to the “clients” and to the type

of knowledge at hand For example, Hildreth & Kimble [18] affirm that soft (or tacit) knowledge can only be shared through direct interaction, while hard (or explicit) is more efficiently distributed through the use of technology

These three “KM-pillars” (People + Process + Technology – see Figure 3) are often mentioned in literature, sometimes padded with additional dimensions such as Strategy, Measurement and others (see chapter 1.2.4 for a full discussion of key success factors for KM) What seems to be universal, though, is the acknowledgement that a balance between „soft‟ and „hard‟ means is crucial for success of KM programs The Economist Intelligence Unit [29], for instance, states that: “Successful KM is about shifting culture and behaviour – technology is an

important element, but is subsidiary.” Wickramasinghe [30], on his side, claim that

“the design and implementation of a KMS (Knowledge Management System) [is] dependent on an appropriate technological infrastructures as well as a supporting culture and organizational process” Finally, as we saw in chapter 1.1.2, Davenport

& Prusak [6] also acknowledge the importance of multidimensionality in KM by emphasizing the importance of favoring culture in the processes of knowledge generation and sharing

Figure 1.3: The three dimensions of HPCI's KM program (Source: HP internal KM material)

1.1.5 A final definition?

We have seen in the above chapters that Knowledge Management is used and defined in many different ways according to the need and the standpoint of the person who tries to define it However, on order to practice KM, we need to have a

definition that is simple and allows companies leverage their knowledge in a best way possible Consequently, we adopt the tactics of Davenport & Prusak [6] and decide on a “working definition” of Knowledge Management Using HP as the reference company, we adopt the HP definition repeated by Jones & Pace [3], and created by a “cross-HP virtual team charted to recommend how HP can most effectively manage our collective knowledge” back in 2000 Their definition was:

“At HP, we define knowledge management as the process of identifying, capturing, leveraging and creating knowledge to deliver value to customers.” (Jones & Pace [3], 2001)

1.2 How to implement successfully

Having looked at the theoretical aspects of Knowledge and Knowledge Management, it is now time to identify how KM can be implemented successfully

in order to provide real value to organizations We will first identify the fields in which KM can add value, followed by a deeper discussion of how to achieve the related improvements

1.2.1 The value of Knowledge Management

From the discussion in the previous parts of this chapter, we understand that KM has appeared as an answer to companies‟ demand for new management methods to help them achieve differentiation, market share, increased volume of sales, higher profitability

However, KM does not seem to be capable of adding such value directly to the firm King [20] states that KM creates “improved decision making and organizational behaviours that positively influence overall performance” Davensort

& Prusak [6], on their hand, describe KM as capable of providing companies with a

“sustainable advantage”, allowing them to stay in the lead on “quality”, “creativity” and “efficiency” It seems, therefore, that the value of KM is indirect rather than direct, since there is no direct link to improved business results Conversely, KM

places itself in the beginning of the chain, enabling improvement in such areas as Decision making, Organizational behavior, Innovation, Quality and Effectiveness (King [20], Wickramasinghe [30], APQC [9], Bellinger [13]) These factors will in their turn, directly or indirectly affect sales revenues, market share or profitability,

at least on middle term basis The challenge of making the link between KM investment and hard returns is discussed further in chapter 1.3

Another interesting point made by Davenport & Prusak [6] is that the value that KM can provide is to some extent linked to the size and geographic dispersion

of a company They state: “The stock of knowledge in a global enterprise with scattered offices and plants and a complex mix of products and functions are vast, but that potential boom is part of the problem How do you find what you need?” Getting knowledge to the right person or connecting the right people in a global corporation is certainly a challenge, and with the number of global companies growing, we should expect to see increasing deployment of KM solutions among these companies in the future

Another key area in the future is for companies to sustain competitive advantage through innovation According to this line of thought, enterprises facing the risk of losing their innovative edge will turn to Knowledge Management as a key enabler to boost its knowledge creation and "disruptive innovation" processes Hewlett-Packard technology watchers Jones & Pace made the following forecast in 2001:

“Over the next two years, most enterprises will continue to improve their ability to store, index and retrieve information, using technologies such as portals, document management, Intranets, and sophisticated search mechanisms By late 2002, most companies, will have solved (or have a plan in place to solve) the "info glut" problem (how to capture, store, deliver and find information), and made it much easier for users to find internal information” (Jones & Pace [3], 2001)

If this theory holds, the attention should therefore now be turning towards creation of new knowledge in order to foster innovation According to Jones & Pace [3], KM as an enabler for innovation will “become increasingly vital as enterprises realize they are losing their ability to create disruptive technologies The Institute for the Future states „as they exist today, large companies across industry sectors and geographies do not have climates conducive to disruptive innovation‟” Likewise, Brown & Duguid [15] make the link between KM and innovation by saying that “in the delicate art of balancing practice and process [in KM] lies the means both to foster invention – by allowing new ideas to spark – and to further invention – by implementing those same ideas”

1.2.2 KM in practice

A number of studies have been made since the beginning of the KM era in order to pinpoint the characteristics of best practice KM Since KM is such a vast and diverse field, every company will have a different approach according to its specific needs and business characteristics KM activities that succeed in one company might therefore, although organized in exactly the same way, fail in another Let us look at one example

Brown & Duguid‟s article from 2000 describes a typical technical support

KM initiative for customer service representatives who fix Xerox machines The article describes how a local group of a dozen service representatives created a common knowledge pool by sharing experiences informally – creating a

Community of Practice (CoP) where storytelling was the main vehicle for knowledge transfer between persons This was a bottom-up approach, very

efficient for solving technical problems on a local basis, but the knowledge stayed within the group and was therefore not leveraged on a company level To resolve

this, Xerox initiated the Eureka project, creating a database (knowledge repository)

to preserve resourceful ideas over time and make sure they were transferred across

the company A rigorous content validation and codification process was

established in order to assure that only relevant information was kept and to avoid duplicates Since the submitter‟s name was attached to the tips he submitted to the

database, he earned recognition for active participation both from managers and

other service representatives The result has been highly positive, and by 2000 this

KM initiative was estimated to have saved the corporation $100 million

Although this example is a quite simple one with a very specific type of knowledge (technical) and a homogenous audience, we recognize many typical KM elements and activities (highlighted in the text) In order to facilitate the study of

KM practices in companies, it is useful to regroup such terms under five core groups (the following list is consolidated from several different authors, e.g Davenport & Prusak [6], Jones & Pace [3] and others):

 Knowledge Generation / Capture: This includes creation of new knowledge through R&D activities, capture of tacit knowledge (people write down, talk about or show others what they know Typical activities are after action reviews, and lessons learned processes), and location of information that is transformed into knowledge for a specific case (i.e reuse of a sales proposal document for a deal with a similar client in another region, storytelling, etc.)

 Knowledge Codification / Coordination:Implies classifying and preparing knowledge for effective storage or reuse This includes activities and tools such as Content Management, Knowledge Maps, Taxonomies (Classification rules), etc Some codification activities involve adaptation like abstract writing, key word definition etc

 Knowledge Storage / Retention: Policies, processes and systems to help a company retain and store its knowledge Document repositories is one type

of system for knowledge storage, often, but not always based on database platforms, but can also be a paper based archive Another classical

knowledge retention policy is making sure that knowledgeable people stay within the company

 Knowledge Sharing / Transfer: All activities that enable exchange of knowledge between two or more people or that allow knowledge to be accessed easily by others, i.e collaboration tools, intranets, training sessions, search engines, Communities of Practice (CoPs), facilitated transfer of best practices, expert locator systems, etc

 Knowledge Reuse / Leverage: Implies all activities intended to promote research for and reuse of existing solutions, most often included in business processes or simply a part of the company culture

We see that KM includes activities on many levels Some companies develop along all these axis, while others follow just one or two However, they all call it

“Knowledge Management” Wickramasinghe [30] tries to establish some order by separating Total Knowledge Management (all activity groups) from plain KM (mostly technology) An interesting attempt, but one which has not been widely adopted

Returning to our list, the reader might argue that we have included typical

IM activities like document management, content management etc This is intentional, and is linked to the fact that we consider both IM and KM as being part

of the scope of this thesis – partly due to lack of a clear distinction in many organizations and that IM and KM problems often are related This is the case with

HP Services as we will see later

Now, having classified KM activities into five types, we wish to have an idea

of what kind of activities companies actually practice In a study published by AMERICAN PRODUCTIVITY & QUALITY CENTER in 2003 (Leavitt [9]), the following seven specific approaches to managing knowledge were assessed:

1 Communities of Practice (CoPs)

2 Facilitated best practice transfer

3 Expertise locator systems

4 Content management systems

5 After action reviews

6 Lessons learned

7 Decision support systems

What is interesting in this study is that it actually evaluates the impact of the various KM activities on business results Only a few of the 40 assessed organizations (sponsors) actually measured this impact, so in the final report only 5

“best practice” organizations are studied in detail (partners)5

Figure 4 shows the perceived impact of the various KM activities among the partner organizations (since many different measures make up the perception of impact, the scale 1-7 is without caption) We observe that Communities of Practice (CoP) is by far the most successful activity for the partners, followed by decision support systems, best practice transfer processes and after-action reviews

Figure 1.4 : Perceived impact of various KM activities (Source: APQC [9])

Off course the seven KM activities mentioned above are only examples of

typical KM initiatives There are many others, indeed, since KM is more a working

concept than an actual management practice, companies have freedom to put the

KM label on whatever activity they feel fit the idea of managing their knowledge

This lack of a clear definition can become quite of a problem, since it leads to

misunderstandings concerning scope, cost and implications of such activities.

5

The five selected partner organizations for the APQC study were : Caterpillar, Halliburton, Ford, IBM and

Schlumberger

1.2.3 Perceived need of KM

A recent study conducted by The Economist Intelligence Unit [29] reveals

the motivations behind KM investment in large western-European organizations It

shows that executives see KM-systems as more important than all other IT

investments for achieving the company‟s strategic goals KM technology is even perceived as more important that CRM applications, supply chain systems and ERP solutions The main benefits these executives see from KM are:

 Improved customer relationship/loyalty (65%)

 Better visibility of internal business processes and performance (46%)

 Faster, sounder decision making (44%)

 More effective product/service development (41%)

68% also agree on the statement “Our IT systems generate large volumes of data, but insufficient actionable information is generated from data” Furthermore, 40% think that in order to make better management decisions in the years to come, IT-investments must “make it easier to analyse and drill down data” We clearly see that the “info glut” problem mentioned in section 1.2.1 is far from solved! Finally, 50% of the participants agreed that the main obstacles to achieving efficient flow and use of knowledge within the organization consisted of internal barriers to the cross-departmental sharing of information and knowledge This indicates a cultural and organizational misfit that must be addressed if the forecasted KM investment is

to become efficient

1.2.4 Key success factors

If we try to extract the success factors form the Xerox presented in section 1.2.2, we might come up with the following list:

 There must be a good balance between practice and process, i.e between bottom-up and top-down Here the initiative started as bottom-up and was extended through a top-down approach that took care not to disturb the initial community-feel

 There must be a good balance between, or „soft‟ and „hard‟ KM – as here between the original stories and the codified and validated versions that finally found their way to the “hard” database

 The people aspect, of how to make people contribute to and reuse content must be addressed seriously

 It is important to (at least try to) measure the impact of the KM initiative This helps to make management understand the importance so they provide continued funding and support

If we go to the literature, many authors list what they mean are the key factors for successful KM Davenport & Prusak [6] provide nine factors: 1) A knowledge oriented culture, 2) Technical and organizational infrastructure, 3) Senior management support, 4) A link to economics or industry value, 5) A modicum of process orientation, 6) Clarity of vision and language, 7) Nontrivial motivational aids, 8) Some level of knowledge structure, 9) Multiple channels for knowledge transfer

Under the title “Characteristics of successful KM programs”, AMERICAN

PRODUCTIVITY & QUALITY CENTER (Leavitt [9]) sites six different success

factors that apply to APQC‟s the best-practice KM partners: 1) Their KM program

objectives are focused on the objectives of their organization 2) They track KM‟s impact on business results 3) They use the language of the firm to define and measure KM 4) They have successfully marketed KM to the organization 5) Each has a KM core group that serves to coordinate and facilitate the activities in support

of business goals 6) KM program leaders have been involved since the inception of

KM in their organization

Bixler [14], an academic specialized in KM, give the following “practical,

critical success factors” for KM: 1) Strong unified leadership, 2) Align KM with

mission and business needs, 3) Cohesive and engaged team, 4) Understand current problems and issues, 5) Collaboration and communication, 6) Innovation, 7) Understanding and appropriate use of current technology, 8) IT infrastructure, 9) Workflow and change cycles, 10) Security, 11) Establish metrics, 12) Reliability and integrity, 13) Accessibility and portability, 14) Cost-effectiveness 15)

Interoperability

Finally, we will site a recent study by Mathi [10] on the German automobile

profile systems group Metzeler Starting out with a hypothesis of five key success

factors, he sets out to measure the relative importance between them The results

show the following ranking (values on a scale from 1 to 5):

1) Measure of KM success (value = 3.4)

2) Strategy, Systems & IT infrastructure (value = 3.3)

3) Culture of persuasive knowledge sharing (value = 2.9)

4) Effective & Systematic Processes (value = 2.9)

5) KM Organization (value = 2.6)

There are some interesting observations to draw from these results Firstly,

we observe a clear top-down vision through the high perceived importance of measuring outcomes and defining a clear strategy backed up by technology The result is not surprising since almost 50 % of the interviewees are managers or top executives What is surprising, however, is the relative lack of importance these same managers and executives give to funding KM initiatives and investing in an adequate organizational support structure! This lack of perceived importance has concrete negative effect, recognized by the author as contributing “to the lack of vision on how KM could be integrated into the business” in organizations “strapped

of funds and resources” Conversely, one of the author‟s recommendations for success of future KM initiatives is a “high priority given to the initiative at the very top of the hierarchy” This aligns with Davenport & Prusak [6] who identify senior management support as one of their key success factors

1.2.5 Managing the change

As the discussion in the previous section indicates, implementing large scale (Total) Knowledge Management in companies requires a true organizational change Many authors acknowledge this and emphasize the importance of managing this change consciously and effectively APQC [9], for instance, recognizes that each of

their partner organization selected specifically for their KM success have

“successfully managed change in the creation, implementation, and sustainment of their KM programs” Another link between KM and Change Management is made

by Carnall [4], who asserts that

“…if an organization is to achieve long-term benefit of learning which is undoubtedly achieved through change then appropriate processes are needed In fact we need convergent systems designed to capture and create knowledge We need to secure a convergence of the IT infrastructure‟s capacity to capture knowledge, the management structure and the systems design focused on the encouragement of learning, and corporate development processes aimed at achieving learning and applying it in new circumstances.” (Carnall [4], p 165-166)

This paragraph not only shows that a conscious change management process is indeed necessary when implementing KM, it also affirms one of the main hypothesis of underlying the creating of the Knowledge Management discipline, namely that KM is a necessary means for effectively capitalizing on the perpetual change process organizations today are undergoing

Now, in order to carry out this change effectively, there is a need for a framework Almost every respectful consultancy company provides such a structural model for how KM should be implemented Any change management model would indeed suffice, but for convenience, we here present in Figure 5 APQC‟s roadmap to KM results (from [7]):

Figure 1.5: APQC’s model for successful implementation of KM (Source: APQC (AMERICAN

PRODUCTIVITY & QUALITY CENTER) [7])

The importance of a knowledge sharing culture has been emphasized in many sections so far in this report Why this element is seen as so crucial is certainly linked to the fact that company culture is perhaps one of the hardest parameters to change in an organization Managing such change demands

“openness, learning, good communication and the recognition of people‟s needs”

(Carnall [4], p 234) Resistance to sharing knowledge is natural, especially in

task-oriented organizations, and is simply linked to the facts that “knowledge is power” Having people share their knowledge means making them give up some of their

personal power Similarly, achieving a learning culture can be difficult because of

resistance to new knowledge, linked to the fact that “…our self-esteem is based on what we know and how we‟ve done things in the past” (Davenport & Prusak [6], p 102)

1.3 Making the business case

“If you can‟t measure it, you can‟t manage it!” is a well known proverb in modern management theory Although KM was for long exempted from the same requirements of measurable success and reliability as other types of projects, times have now changed According to IBM [25], “…in the tougher economic climate, knowledge management projects are under increased pressure to prove themselves Also, business managers are under increased pressure to provide „hard‟ justification,

by using return on investment (ROI) or other financial metrics.” At the same time,

KM become “more integrated into the fabric of the organization”, basically

“becoming everyone‟s job” KM thus competes with other tasks for normal employees, making managers ask for proof of the value of this activity

In spite of this development, few organization measure KM activities Others that do measure, fail to employ the results Mathi [10], for instance, reports that

“most of the KM initiatives fail due to ineffective use of inbuilt measures” In this section we look at how KM measurement can be carried out Further, we look at the results of KM assessments for some of the companies that do measure KM actively

1.3.1 How to measure KM impact

The “soft” nature of many KM activities, like knowledge sharing and CoPs, make the inherently difficult to quantify However, more and more companies try, often with the help of consultants One such consulting firm, APQC (AMERICAN PRODUCTIVITY & QUALITY CENTER), states: “The intangible nature of knowledge itself has caused some KM practitioners to assume that the impact of

KM would also be intangible APQC (AMERICAN PRODUCTIVITY & QUALITY CENTER) has not found that to be the case The impact of KM is measurable.” (APQC [7])

With such requests measurability and profitability from KM practicing firms

in mind, IBM recently presented a framework for building the KM business case

(IBM [25]), while APQC (AMERICAN PRODUCTIVITY & QUALITY CENTER)

has launched their KM measurement framework (APQC [7]) Many other

consultancy firms and KM specialists suggest similar approaches These methods basically encourage managers to try and trace how KM investments (inputs) relate

to quantifiable business value (outcomes) In Figure 6 we see the APQC (AMERICAN PRODUCTIVITY & QUALITY CENTER) model

Figure 1.6: APQC’s KM Measurement Framework (Source: APQC [9])

The model is a four step approach, where the added value is to encourage managers to set up measures on each of the four points in the chain Typical measures are [9]:

 Input: Direct labour, Contract labour, Contracted/outsourced services,

Participation costs, Travel and meeting costs, Technology investments

 Process: Number of users, Number of contributors, Average call time,

Repeat work orders, Application usage, Participation counts, System reliability, Usage frequency

 Output/Outcome: Cost savings, % of satisfied customers, Cost of poor

quality, Revenue saved, Client satisfaction

With such result, APQC (AMERICAN PRODUCTIVITY & QUALITY CENTER) claims that best practice organizations manage to calculate the return on investment (ROI) on their KM outlays In order for the result to be as realistic as possible, APQC (AMERICAN PRODUCTIVITY & QUALITY CENTER) advises companies to:

 Be cautious and rather underestimate than overestimate

 Keep it simple with understandable measures and easy to use technology

 Use existing metrics and measures as far as possible

This method is useful because of its general nature However, some “soft”

KM activities are difficult to quantify, even at input and process levels One of the most used KM activities of this type are Communities of Practice (CoP) Etienne Wegner (referenced in HP Community Handbook [2]) suggests a solution by

“following the stories” He calls this method systematic anecdotal evidence It can

be put down to 5 main steps:

1) Gather stories about successes and failures in leveraging a community

2) Follow each story and express the gain provided by a community to

one person or one business unit (time saved, cost saved, reduced risk, etc.)

3) Estimate the chances in % that the same information could have been

found elsewhere What is the % of the asset that came directly from the community?

4) Estimate in % the confidence of the truth of the answers to question 2

and 3

5) Calculate a conservative estimate of the value of the community by:

Community value = gain * community-generated % * Certainty %

This method resembles closely to the method developed by MetrixGlobal and described by Anderson in [12]