Journal of Knowledge Management Practice, January 2001

Digital Communities @Work TM

A Concept Describing the Next Wave in Human Capital Management

Hakan Altintepe, A.T. Kearney, Inc

ABSTRACT

In this article, the author aims to bring clarity to a long overdue mystery around the management of human capital. First, he lays out a widely used approach, which describes how most Fortune 1000 organizations are managing their most valuable knowledge assets. Then, he identifies and elaborates the fundamental shortcomings of this approach. Finally, the author suggests a practical and innovative solution for large organization to better harness the potential of their human capital. The author believes that the concepts introduced in this article will stimulate the thinking of executives to establish an upper hand on the rapidly emerging strategic issue of human capital management.


EXECUTIVE SUMMARY

During the past two decades as dependency on critical business knowledge has increased, many Fortune 1000 organizations have adopted a fairly standard, top-down approach to human capital management. According to this approach, the corporate management is responsible for determining what knowledge to capture, how to organize it, who to grant permission for access. Employees, on the other hand, are responsible for creating the critical business knowledge. The whole system depends upon a simple expectation that employees contribute their knowledge to corporate systems for the benefit of their whole organization.

This standard approach to human capital management reveals striking conceptual similarities to the socialism. The socialism is an idealistic system that was originally developed to accelerate wealth creation for the benefit of a whole community. It assumed that people work hard and allow their production given to others. However, it failed to achieve this goal due to its fundamental defects and unrealized assumptions. In this paper, the author asserts that the standard approach suffers similar defects. The socialism came to an end when its perfect execution by communist governments could no longer justify its shortcomings against free-markets. He extrapolates that even a perfect execution of the standard approach cannot succeed, as innovative organizations search for and adopt alternative means for the better management of their human capital.

Fortunately, recent technological developments and changes in competitive business environments has created a significant opportunity for large organizations to better manage their human capital: digital communities that adopt free market principles will be most suited to establish a frictionless environment for the knowledge exchange, and therefore, for the growth of human capital. In simple terms, the Digital Communities @WorkTM refers to an innovative business concept that will create digital communities of practice or interest at large organizations, by leveraging the Intranet and Enterprise Information Portal (EIP) technologies. Digital communities will stimulate collaboration and knowledge exchange among employees and members of the extended enterprise. The Digital Communities @WorkTM will most likely to lead to a new intranet-based, killer application that will push the effectiveness of human capital management to the next level. Particularly, the resulting communities will represent the collective brainpower of a whole enterprise by accelerating collaboration among employees to a new measure never achieved before.

What differentiates digital communities from today’s collaborative environments is that they will adopt free market principles to acquire, organize, distribute, and evaluate knowledge; and reward members based on their contributions. These communities will no longer treat knowledge as a public good. They will set aside a credible budget to compensate members proportional to the value of their contributions. The size of the compensation budget will depend on the productivity of the whole community. Digital communities will create a constructive competition within efficient markets; similar to those already established for physical goods that only citizens of the free-market nations are privileged to enjoy today.

Digital communities will lead to a new kind of corporate brainpower that will exponentially increase as more employees become better connected with others. In the end, organizations that successfully nurture these communities will create an unequalled corporate intelligence, and thereby, outperform their competition.

Although digital communities will prove to be invaluable to large organizations, their implementation will be nontrivial, and it will require a major paradigm shift in the way executives view how knowledge be acquired, captured, organized and distributed within their organizations. Furthermore, enterprises, which decide to nurture digital communities, will need to overcome significant challenges in developing complex analytical infrastructures to manage the balance of demand and supply of knowledge through comprehensive, flexible, and efficient incentive programs.

Fortune 1000 executives will significantly benefit from carefully evaluating the benefits and the risks of digital communities, and from preparing their organizations for this emerging opportunity.


INTRODUCTION

Demand for knowledge enabled products and services are burgeoning, and competitive pressures in business markets are increasing. The role of knowledge as a strategic differentiator is becoming clearer in all sectors. The management of human capital, where corporations’ most valuable knowledge assets reside, has been receiving a significant executive attention at most Fortune 1000 organizations.  Effective use of knowledge assets has become a universal necessity to succeed.

Unfortunately, most Fortune 1000 organizations are still uncertain about whether they are able to maximize returns from investments on their human capital. Why? Because, conventional wisdom and traditional financial tools employed throughout evaluations of investment options offer little relief when something as ‘sacred’, and puzzling as human capital is involved. In the absence of adequate tools and frameworks, executives prefer to remain conservative rather than freewheeling, despite their awareness of the lucrative opportunities that are systematically sacrificed. These executives are looking for clear answers to the following basic and common sense questions:

Ø      What is my ROI on human capital initiatives, and how does it stand against my competition?

Ø      How do I make sure that every dollar I invest in knowledge assets is best allocated for the highest financial return?

Ø      In today’s knowledge economy, how can I become as prudent and informed with my investments on knowledge assets as I am with capital spending on my physical assets?

Ø      What financial opportunities am I forfeiting due to managing knowledge assets at arms length?

One of the most significant bottlenecks of today’s human capital management is the contribution of knowledge by employees into corporate systems. As far as tacit knowledge that resides in the minds of employees is concerned, most Fortune 1000 organizations rely upon a similar approach: create massive databases, expect employees to contribute insights, and distribute those insights to authorized employees at zero cost (a public good approach). Isn’t this analogous to how socialism tried to create wealth, and failed?  Socialism assumed that people would work hard and share their production with others. In reality, lack of ownership and competition severely inhibited creation of wealth in their communities. By the same token, zero-cost access to other employees’ insights diminishes the excitement and motivation needed to create valuable knowledge and share it with others. Today, many Fortune 1000 enterprises are far from unleashing the full knowledge potential of their human capital.

In his article, we will together explore alternative and innovative remedies for this universal bottleneck. First, we will develop an analytical framework to assess the significance of human capital at Fortune 1000 organizations. Using this framework, we will highlight the major shortcomings of standard management practices applicable to human capital, today. Next, we will analyze the knowledge value chain at large enterprises to find out why standard management practices cannot yield the optimum performance. Finally, we will suggest an innovative approach to unleash the full potential of the employee knowledge.

ASSESSMENT OF HUMAN CAPITAL

Knowledge is a prominent, present-time strategic economic driver

From prehistoric hunter tribes to the digital communities, mankind has been witnessing an astonishing economic evolution. During this journey, every time a strategic economic driver emerged, the indisputable judgment of the natural selection promoted those who best converted new drivers into competitive advantages to leaders of a new era. For example, physical strength was a crucial characteristic, and hence an economic driver, in the prehistoric age. Back then, strong hunters were, hence, very influential, and held ruling positions in their communities. By the same token, ‘land’ during the agricultural age, and ‘transportation capability’ during the colonial age emerged as strategic economic drivers, providing unequalled competitive advantages to those who controlled them.

Natural resources such as oil, gas, steel and chemicals gained strategic importance during the industrial age. Nations that acquired prominent control over these resources dominated the rest of the world economically and politically until technology replaced physical resources, and became the next strategic economic driver.

During the last three decades of the past century, enterprises such as Microsoft, Intel, and Merck started differentiating themselves through acquisition and capitalization of the knowledge rather than the physical resources. This trend led to technological innovations in software, space technology, semiconductors, computers and electronics. Consequently, knowledge emerged as the next strategic economic driver. A new breed of information savvy organizations pushed the titans of the industrial age into sidelines, and become the leaders of the emerging technology age.

During the early phases of the technology age, due to practical, organizational and economic reasons it was appropriate to top-down manage the business knowledge. This led knowledge to be created, exchanged and retained primarily among a few elite in each organization such as executive managers, lead scientists, and executive sales people. The rest of employees were merely expected to execute the decisions or innovations initiated by the elite.

Since then, the advent of personal computers, the Internet and the electronic delivery of information enhanced the importance of knowledge to a new level that all ranks of employees now accumulate, process and generate insightful information. Today, all employees, rather than a few individual stars, constitute the new corporate brainpower that impacts the corporate bottom-line. Knowledge, which is concentrated in employee networks, has become a prominent economic driver, signaling that we have reached a new milestone in our relentless economic evolution: Today, we are welcoming the digital age!

Historic trends shed a significant light into future events. Therefore, I predict that only those enterprises, that can convert employee knowledge into competitive advantages, will lead in the digital age. In the remainder of this section, we will review emerging trends in valuation of large enterprises, and uncover clues that either support or reject this prediction.

Intangibles rather than tangibles compose most of the market value of today’s enterprises

Market value of an enterprise can be described as the total market value of all underlying tangible and intangible assets. Tangible assets consist of economic resources such as cash, receivables, investments, properties, plants, equipments, etc. We can easily identify and appraise tangible assets. Intangibles, on the other hand, are very hard to identify, categorize and appraise. In this article, we group corporate intangibles into five main categories, i.e., human capital, intellectual property, customer assets, business relationships and organizational assets.


Figure 1.           Market value of an enterprise consists of tangible and intangible assets, i.e., human capital, intellectual assets, organizational assets, customer assets, and business relationships

Prior to the digital age, price-to-book ratio was a common measure for corporate valuation, as companies mainly leveraged tangible rather than intangible assets to generate earnings. In 1980, the Price-to-Book of largest companies in the U.S. was 1.2[1]. Today however, the Price-to-Book has reached 9.9x[2]. In other words, the premium that market is willing to pay for an enterprise beyond its book value increased roughly from $0.2 to $8.9 for every $1 worth of tangible asset[3]. This 4350% increase in the premium manifests an immense appreciation of corporate intangible asset[4]. In fact, market to tangible book ratio for large U.S. enterprises average about 12.2, indicating that intangible assets constitute more than 90% of the overall market value of U.S. enterprises[5].

Large corporations’ ability to create, store, disseminate, and use knowledge is the foremost driver of the spectacular appreciation of intangible assets

Knowledge-based industries, particularly in science and technology sectors, have been growing faster than most other industries. During the last 10 years, industries that have leveraged knowledge as one of their primary resources have not only transformed the economic structure in the U.S., but also in many other countries. For example, recent reports indicate that the international trade in the knowledge sector is growing five times faster than in natural resource intensive industries, reaching to $3.5 trillion in 2002[6]. Furthermore, the Market-to-Book ratio averages at 14.2 among highly knowledge-based companies, whereas this ratio remains to be only 3.5 among industries that moderately depend on knowledge.

Table 1.            Intangible assets consist of a larger portion of the market value in knowledge-based industries[7] then the rest of the economy

Industry

Dependency on Scarce Knowledge

Market Value

($ MM)

Price to Book

Network Communications

High

 $733,803

22.3

Computer Software

High

 $808,167

19.0

Semiconductors

High

 $605,875

12.2

Pharmaceuticals

High

 $853,078

9.8

Medical Products and Equipment

High

 $116,760

7.8

Telecommunications

Medium

 $1,175,630

4.3

Retail

Medium

 $305,611

4.1

Motor Vehicles and Parts

Medium

 $146,675

2.1

Textiles

Low

 $5,778

1.6

Airlines

Low

 $33,316

1.5

Utilities

Low

 $253,245

1.3

Energy

Low

 $3,467

1.3

Table 1 illustrates a trend that intangible assets in knowledge based industries such as network communications, computer software, semiconductors, pharmaceuticals, etc. are more valuable than intangibles in other industries. This finding leads to the conclusion that knowledge-based intangibles like human capital constitute a significant portion of all corporate intangibles, which already account for most the market value of large enterprises.

The total worth of human capital at Fortune 1000 organizations is estimated between $1.0 trillion - 3.1 trillion 

The book value of corporate equity includes all tangible assets after liabilities and a portion of intangible assets that are not homegrown, but acquired through merger and acquisitions. These intangibles, called goodwill, make up on the average 27%[8] of the book value of corporate equity among large enterprises. To find out the total value of intangibles among Fortune 1000, we subtract from the total market value of corporate equity the total book value of these firms, and then add the goodwill value to it. Consequently, we estimate that intangibles that contribute to the market value of Fortune 1000 organizations be worth $10.4 trillion as of December 1999, see Table 2.

Table 2             The total intangibles among all Fortune 1000 companies is estimated to be $10.4 trillion in 1999[9]

Total market value of fortune 1000($ trillion)

$12.5

Book Value ($ trillion)

$2.9

Intangible Assets not on Books ($ trillion)

$9.6

Intangible Assets on Books (27% of Equity)($trillion)

$0.8

Total Intangibles ($ trillion)

$10.4

In Figure 1 we have defined intangibles as the collection of five asset subcategories such as business relationships, customer assets, organizational assets, Intellectual assets, and human capital. The value distribution of these subcategories within overall intangibles differs in each sector. To determine the total value of human capital within Fortune 1000 organizations, we estimate the distribution of each subcategory per sector. Our distribution criterion is the perceived importance of each asset category to the sustained value proposition of firms in that sector. Subsequently, we calculate the weighted average of asset category distribution based on the market value of each sector.

Table 3             Based on the best guess estimate of a small number of management consultants, intangibles are almost evenly distributed over five asset subcategories at Fortune 1000 companies

Sectors

Market Value Distribution

Business Relationships

Customer Assets

Organizational Assets

Intellectual Assets

Human Capital

Basic Materials

3%

30%

20%

30%

5%

15%

Capital Goods

2%

20%

20%

30%

10%

20%

Conglomerates

5%

20%

20%

20%

10%

30%

Consumer Cyclical

4%

30%

20%

20%

10%

20%

Consumer/Non-Cyclical

5%

30%

20%

20%

10%

20%

Energy

4%

30%

5%

20%

30%

15%

Financial

14%

20%

30%

10%

20%

20%

Healthcare

11%

20%

10%

20%

25%

25%

Services

19%

10%

20%

20%

20%

30%

Technology

27%

20%

20%

10%

20%

30%

Transportation

1%

25%

15%

30%

10%

20%

Utilities

2%

30%

10%

20%

10%

30%

All Companies

100%

20%

20%

20%

20%

20%

After adding a +/- 10% uncertainty band around the above results, we can roughly estimate that human capital may account for 10-30% of all intangibles. Consequently, human capital at Fortune 1000 organizations may be worth between $1.0 trillion and 3.1 trillion.

Figure 2.           Human capital constitutes a significant portion of the intangibles, estimated to be between $1.0 trillion - $3.1 trillion.

 

 

 

 

 

 

 

 

 


CURRENT STATE OF HUMAN CAPITAL MANAGEMENT AT FORTUNE 1000

A skeptical audience may challenge from an academic or scientific perspective some of the assumptions we employ in above framework to appraise human capital. However from a practical perspective, this model provides valuable insights into a common perception that human capital is one of the most valuable corporate assets in today’s fast paced, technologically advanced business world: customers always demand better, cheaper and faster services and products, whereas skilled employees are hard to retain. Still, most Fortune 1000 organizations deal with significant challenges to exploit their human capital to its fullest extend. In the following section, we will elaborate these challenges, and estimate their impact on the corporate operating earnings.

Human capital is one of the most underleveraged corporate assets

Since the birth of modern economic principles, relentless quest for shareholder value creation has been a significant challenge for executives. In this regard, various financial tools, such as Return on Asset (ROA) and Return on Investment (ROI), have been employed to determine how to allocate corporate resources in means that maximize the shareholder value. The primary weakness of these tools has been their dependency on the accurate appraisal of assets, investments and associated returns. In the old economy, when most of critical resources were physical and easily appraisable, this handicap did not evoke any concern. Today however, traditional financial tools are inadequate when it comes to appraise intangibles. Especially, human capital is even harder to appraise compared to other intangibles. Who can estimate the value of competitive information that resides in the minds of the sales force? How much increase in revenue could be realized, if a management-consulting firm knew what its consultants collectively knew? What percentage of a yield increase could a manufacturing firm achieve, its engineers in two identical factories, which are located in two different states, shared their process improvement ideas.

Frequently, it is difficult to demonstrate returns that are directly attributable to the better management of human capital. Hence, executives are commonly reluctant to directly allocate precious corporate resources to grow this precious asset. Instead, they often rely upon volunteers to spearhead initiatives that aim to nurture human capital. This long-lasted systematic management oversight, therefore, curtails the growth of human capital with respect to what it could be, such that human capital has become one of the least leveraged corporate assets, today.

Fortune 1000 firms significantly under-invest in growth of their human capital

To make an insightful assessment of the adequacy of current investments on human capital, we need to understand what human capital is comprised of, and what portion of it can enterprises practically nurture through implementation of systems, processes and administering necessary organizational changes. In our opinion human capital consists of two major knowledge components, which contributes to the operating profits of enterprises:

1.      General knowledge assets, those acquired prior employees’ joining the workforce,

2.      Business knowledge assets, those acquired on the job.

We can assume that general knowledge assets are prerequisite to join a company, and they are ubiquitously available throughout the workforce. Therefore, we should note that only the business knowledge assets could grow through improved collaboration among employees and through a better management of human capital.

The average annual salary among Fortune 1000 organizations was around $44,500 in 1999, whereas the average starting salary was estimated as $25,000. If annual salary is an indicator of employee’s value proposition, we calculate that human capital consists of 56% of general knowledge, and 44% of business knowledge[10]. Here, we can assume that recently graduated employees possess only general knowledge, and they acquire business knowledge on the field while performing the assigned job functions.

To understand common investment practices among Fortune 1000 companies, let’s look at their 1999 annual financial statements and extracted their capital spending and the value of their fixed assets. As shown in Error! Reference source not found. on page 11, the annual capital spending among these organizations ranged between 17% and 38% of all fixed assets, with a weighted average of 22%. If Fortune 1000 organizations made similar investments on business knowledge in their human capital, their investment would reach to $100-300[11] billion, annually.

Even though it is difficult to size how much Fortune 1000 organizations invested in human capital in 1999, various sources[12] stated that corporate America spent less than $10 billion on systems, processes and change management to manage and grow its human capital. Furthermore, another $60 billion was spent on employee training[13]. This combined $70 billion investment on human capital is well below what is needed to bring investments on human capital to an equal footing with capital investments.

Table 4             Fxed assets and capital spending data for  select organizations[14].

Company Name

Fixed Assets ($BB)

199 Capital Spending
($ BB)

Investment Rate (%)

Ford

 $276.2

$42.3

20%

GM

 $274.7

$29.0

25%

Sears

 $ 37.0

$ 6.5

16%

Wal-Mart

 $ 70.3

$36.0

17%

Intel

 $ 43.8

$11.7

29%

AMD

 $ 4.4

$ 2.5

25%

Microsoft

 $ 37.2

$ 1.6

36%

Oracle

 $ 7.3

$ 1.0

38%

Coca Cola

 $ 21.6

$ 4.3

25%

Pepsi

 $ 17.6

$ 5.3

21%

Bank One

 $269.4

$ 3.3

18%

 

 

 

 

 

 

 

 

Consequently, we conclude that Fortune 1000 firms have so far addressed only a miniscule portion of the business knowledge resident in their human capital. Current knowledge management investment levels are well below what is ideally needed to maximize the return on human capital[15], supporting our earlier assertion that human capital is one of the most underleveraged assets in Corporate America.

Leasing rather than institutionalizing the knowledge in human capital has become the norm

Enterprises leverage the business knowledge in two different ways depending on where this knowledge primarily resides. If critical business knowledge solely resides in the minds of employees, enterprises utilize it by ‘leasing’ human capital through salaries, bonuses, perks, etc. In this case, enterprises gain access to knowledge as long as employees are part of the organization. When employees switch to another firm, they take their knowledge with them, and their new firm becomes the beneficiary of it.

Alternatively, enterprises may choose to institutionalize the business knowledge by extracting it from employees and capturing it in corporate systems. Once knowledge is institutionalized, corporations can access it whenever and wherever needed.

Institutionalization of employee knowledge is a complex, expensive, and financially risky undertaking requiring significant upfront investments in systems, processes, and change management. Limited availability of financial and managerial resources to overcome these challenges have led large firms to favor leasing the human capital rather than institutionalizing its business knowledge. These firms have focused primarily on the acquisition, retention and training of skilled employees by investing into employee training programs, recruitment, and retention plans. Consequently, little has been done to extract and claim co-ownership for the business knowledge in human capital.

The concept of leasing knowledge rather than institutionalizing constitutes several fundamental problems. First, as employees become empowered by the knowledge they possess, it becomes harder to satisfy them to stay. Consequently, the cost of programs aimed to retain experienced employees, the cost of knowledge that is lost due to departures, and the cost of increased need for industry hires add all up, unfavorable impacting the operating earnings. Second, lack of institutionalization creates a conflict of interest between knowledge workers and the enterprise. The former agree to share knowledge only if they are adequately compensated, the latter wants freely to distribute information to those who can make use of it and generate corporate value. This conflict eventually prevents a frictionless exchange of knowledge among employees, and curtails the growth of human capital. Finally, knowledge that only resides in the minds of a small number of employees is underleveraged: knowledge holders and seekers experience difficulty in finding each other. Also, the manual steps of the tacit knowledge exchange needs to be repeated during each exchange, requiring additional time and effort.

Sub-optimal management of human capital may cost Fortune 1000 organizations up to  $50 billion - $110 billion, annually

Ideally, if human capital were fully leveraged, every employee would have access to what the rest of his or her organization knew. Unnecessary duplication of work would be reduced, innovation would flourish, and the whole organization would function as one creative mind. The collaborative networks of employees would functions as corporate neural networks, where the collective value of the network exceeded the aggregate value of its components. Fortune 1000.

Fortune 1000 organizations could enjoy two types of tangible financial benefits, if they succeeded in establishing, so called, corporate neural networks. First, these enterprises would experience an improvement in productivity through reduced repetitive tasks, increased innovations, and better decision-making. Second, they would reduce the total employee cost through more effective training programs, retention programs, and lesser recruiting costs as a consequence of improved job satisfaction and lower employee turnover. Clearly, it is very difficult to practically quantify the size of potential savings due to higher institutionalization of employee knowledge. To resolve this challenge, I will call upon the art of the management consulting rather than attempting to employ the science of financial analysis. Based on my previous consulting experiences with Fortune 1000 organizations, I suggest that a 3-6% productivity improvement and a 1-2% reduction in total employee cost constitute a rough but reasonable guess.

Table 5 illustrates a framework to estimate the annual value of productivity improvement and potential savings in total employee cost. First, the worth of business skills assets that are imbedded in human capital is calculated, and their contribution to overall operating profits is estimated by evenly distributing earnings over all underlying assets. Second, the operating profits attributable to human capital and total employee compensation are added to calculate the overall output value of the workforce. Third, 3-6% of the employee output and 1-2% of the overall employee compensation is calculated to find out the productivity gain and the savings opportunity in employee costs attributable to better management of human capital, respectively. Finally, this analysis reveals that Fortune 1000 organizations might be forfeiting $50-110 billion in operating profits due to sub optimal level of human capital management, and inability to established well connected, collaborative employee networks.

The significance of this analysis is not in the absolute accuracy of its final number, but in the directional accuracy of its inference providing sufficient evidence that Fortune 1000 organizations have a lot to gain from better management of their human capital through establishing effective and efficient collaborative networks within their organizations.

Table 5             Frtune 1000 enterprises may be collectively forfeiting $50 billion - $110 in operating profits[16].

 

Conservative Estimate

Aggressive Estimate

Total market value of Fortune 1000  ($ trillion)

 $12.5

 $12.5

Book value ($ trillion)

 $2.9

 $2.9

Intangible assets not on books ($ trillion)

 $9.6

 $9.6

Intangible assets on books ($trillion)

 $0.8

 $0.8

Total intangibles ($ trillion)

 $10.4

 $10.4

Ratio of human capital to all intangibles

10%

30%

Value of human capital ($ trillion)

 $1.0

 $3.1

General knowledge assets (56%)

 $0.6

 $1.7

Business knowledge assets (44%)

 $0.5

 $1.4

1999 Corporate operating profits ($ billion)

 728

 $728

Profit attributable to human capital

 $60

 $181

Employee compensation (salary, benefits, exec. comp. in $ billion)

 1,258

 $1,258

Productivity improvement opportunity

3%

6%

Productivity improvement annual value proposition ($ billion)

 $40

 $86

Savings opportunity on employee cost ($ billion)

1%

2%

Employee cost savings opportunity value proposition ($ billion)

 $13

 $25

Aggregate value proposition ($ billion)

 $50

 $110

In the digital age, the effective management of human capital plays ever increasing role in differentiating the leaders of the competitive markets

A significant trend in the new economy has been a rapid shift from traditional business models to e-businesses. In general, e-business implies that external parties interact more directly with internal enterprise systems. For example, customers order directly from a company’s website, in addition to check the status of their order against an operational database. Furthermore, online stores capture valuable customer data to establish personalized customer relationships.

Technology increasingly replaces the human touch in traditional customer-supplier interactions. However, it is that human touch which typically compensates for inadequacies in formal procedures and systems by surrounding them with human competence--the expert who knows “how things work round here”. e-Business strips away this safety mechanism. How effective can the enterprise be in interactions with customers and suppliers with no intermediaries masking its systems and processes anymore? The only solution is to incorporate that expert knowledge into online systems and business processes. Therefore, institutionalization of human capital becomes vital when interacting with suppliers and customers online. Furthermore, e-business expands the competitive arena and demands faster reaction times to business events. Both of these trends require greater inventiveness and improved competitive intelligence—both leading to greater need for institutionalization of human capital.

Furthermore, as the pace of business increases, employees are expected to locate and absorb critical knowledge more quickly to compensate for the ever shortening shelf life[17] of the critical business knowledge on customers, organizations, markets, regulations, and technology.  Unfortunately, physiological limitations of humans have already been reached, and employees are complaining about the information glut they have to deal with. Effective management of human capital could provide them the necessary tools to improve their ability to timely access high quality information with minimal effort.

In summary, as the significance of human capital in competitive markets increase, even minor improvements in its management can account for major achievements. Firms that adopt state of the art management practices for their human capital are more likely to become the leaders of the digital age.

THE KNOWLEDGE VALUE CHAIN

Findings presented in previous sections suggest that Fortune 1000 organizations are experiencing serious challenges in getting the best value from their human capital. This section articulates how the business knowledge in human capital contributes to corporate bottom-line.

Knowledge holders, knowledge seekers and the corporate management are three main players involved in knowledge value chain

From generation until its impact to the corporate bottom-line, insightful information goes through a six-step value chain as shown in Figure 4. First, employees accumulate insights and they become knowledge holders. Insights can be acquired anywhere and anytime, as simply as from a recently read article, a conversation with colleagues, an observation at work, etc. Second, knowledge holders externalize their insights by sharing them with coworkers. Third, knowledge seekers consume the insights they receive. Fourth, these insights improve the productivity of the knowledge seekers, by enabling them to deliver better results and/or complete their tasks more quickly. Fifty, enterprises consume the improved productivity. Each improvement causes myriad other improvements within the organization, as the output of one employee often becomes an input to others. Consequently, the ripple effects of each individual improvement collectively improve the overall value proposition of the organization.

It is interesting to note that although holders, seekers and management lead the various stages of the knowledge value chain, none of these parties have an end-to-end visibility over it. For example, holders can supply the content and control its quality. However, in the absence of direct feedback, they are unable to determine what content and quality knowledge seekers actually demand. Similarly, neither knowledge holders nor seekers have an understanding of how the improved productivity of seekers creates ripple effects within the corporate value chain, and impacts the bottom-line.

Limited visibility by all participants to the overall knowledge value chain necessitates specialization among them. Ideally, since knowledge holders are topic experts, they should be determining how to best respond to a quest for a particular insight by seekers. Knowledge holders are the only group that thoroughly understands how particular insights improve their own productivity; hence, they should be able to decide what insights they actually need. Corporate management has the overall understanding of how seekers’ output is consumed within the corporate value chain, until it delivers a tangible result. Hence, the management should appraise each productivity improvement, and guide knowledge holders to provide most valuable insights.

If the above-described specialization were observed, the management would first define the desired output of seekers. Seekers would then decide what insights they need to best deliver this output. Then, management would devise the necessary tools, incentive programs, and guidelines to extract the needed insights from knowledge holders. Consequently, holders would produce what seekers needed.

Figure 3            Knowledge goes through multiple steps, called value chain of knowledge, from generation to delivery of tangible bottom-line results

 

 

 

 

 

 

 

The throughput of the knowledge value chain depends on three factors: velocity of knowledge exchange, community liquidity and knowledge liquidity

When we acquire a piece of knowledge, we usually improvise it in our mind, and we develop new insights; or throughout our discussions with others, we collectively gain insights that were not apparent to anybody before. This phenomenon illustrates a basic distinction between human capital and tangible corporate assets: knowledge appreciates, rather then depreciates, when it is consumed. Therefore, an effective way of growing human capital is in fact nurturing a community where knowledge exchange is encouraged, facilitated and stimulated. We identify three factors for communities to accomplish these objectives.

Ø      Maximize velocity of knowledge exchange

As long as we cannot simply physically tap into each other’s brains, tacit knowledge sharing remains to be a complex process. During the initial step of this process, the knowledge needs to be articulated, organized and externalized by the holder. Then the holder and seeker should be able find each other to initiate an exchange. Finally, the seeker needs to absorb, reorganize, and articulate the knowledge to make use of it. All these steps take time and effort. Moreover, since knowledge is highly perishable, the exchange has to be completed before its shelf life expires, adding another degree of complexity to the whole process. By automating certain steps of this process, knowledge communities should speed up knowledge exchange among their members.

Ø      Maximize community liquidity

Improved community liquidity means seekers have better access to more holders than they previously did; or conversely, holders have improved access to more seekers. Liquidity becomes especially important in extremely fragmented exchange environments, such as knowledge communities. No knowledge is exactly comparable to another, since it is can come in various breath, depth, and quality. Knowledge communities should help seekers easily find an appropriate holder or even to choose which holder to deal with. This type of liquidity provides new exchange opportunities and is valuable to both holders and seekers.

Ø      Maximize knowledge liquidity

Knowledge liquidity is a special kind of liquidity because it results in the exchange of information that would not otherwise have exchanged. Some knowledge is very difficult to exchange, often because it may have a limited audience or very short shelf life. This type of knowledge may go without being exchanged, and never generate value. Knowledge communities can resolve this liquidity problem by quickly aggregating holders and seekers who would not have found each other in a timely manner or at all.


Figure 4            Liquid exchange of supply, demand and incentives among suppliers, consumers and the sponsor of human capital is the most important requirement for effective Management of Human Capital

Consequently, knowledge communities that are able to achieve maximum exchange velocity, community liquidity and knowledge liquidity have the strongest value proposition to foster human capital by improving the throughput of the whole knowledge value chain. Figure 5 illustrates the interactions between the participants and their roles within the knowledge value chain. As the community liquidity, knowledge liquidity, and knowledge velocity improves, the supply-demand-incentive circle accelerates, boosting the throughput of the knowledge value chain.

THE STANDARD APPROACH TO HUMAN CAPITAL MANAGEMENT

Most large organizations, such as Fortune 1000 companies, have conceptually adopted quite a similar approach to manage the business knowledge in their human capital regardless of industry, geographic location, or size. In this section, we will first describe this widely adopted approach, which we call the Standard Approach, in detail. Then, we will elaborate why the Standard Approach does not satisfy the fundamental requirements of creating liquid knowledge exchanges, and therefore, is incapable of harnessing the full potential of human capital.

The Standard Approach is widely adopted by most Fortune 1000 organizations

In the corporate field, employees produce ubiquitously and continuously valuable business insights, which can be simple or sophisticated, trivial or unique, haphazard or well organized. Enterprises aim to harvest this production by capturing it in forms of intellectual assets. During this process, the tacit knowledge residing in employees’ mind is transferred to an explicit, physical medium, and the ownership of the knowledge is transferred from the employee to the enterprise.


Figure 5      The Standard Approach to human capital management

As shown in Figure 5 the Standard Approach to human capital management includes five main tasks:

Ø      Employees create knowledge

Ø      Enterprises provide rules, guidelines and infrastructure to capture the knowledge

Ø      Enterprises organize it according to corporate knowledge map

Ø      Then they to distribute it to authorized recipients

Ø      Recipients consume this knowledge, consequently they innovate, and possibly, create new knowledge, reactivating the cycle.

Knowledge is a strategic competitive advantage, and hence, enterprises establish extensive rules and guidelines to control and regulate its capture. Employees are expected to share their insights with the rest of their organization within those rules and guidelines. Knowledge specialists are tasked to identify, capture and organize contributed knowledge in forms of corporate assets. These dedicated agents establish quality standards, and develop a knowledge map (taxonomy) of the whole organization. Furthermore, specialists recommend rules and guidelines to the executive management in order to regulate authorizations specifying who can access to what information.

Authorizations are determined based on the management’s or knowledge specialists’ view on how knowledge is used within the organization. For those who are viewed by the corporate management as the target recipients, the knowledge becomes a public good: they are authorized to access information at zero cost to them. Figure 6 illustrates the Standard Approach employed by most Fortune 1000 organizations.

The Standard Approach relies upon a heavily centralized management, and does not adequately leverage decentralized community members

Earlier, we have discussed that none of the participants, i.e., holder, seeker and the management have an adequate, end-to-end visibility into the knowledge value chain. Hence, we emphasized the importance of an ability-based specialization among participants. Instead, the Standard Approach employs a different type of specialization based on management’s need to control how knowledge is created, distributed, and consumed. This strong interest in control encourages a centralized management for the business knowledge in human capital. Moreover, some organizations are reluctant for adopting advanced technologies, such as intranet infrastructures, enterprise information portals, and document/content management solutions. In the absence of these technological capabilities, a centralized management remains to be a safe choice.

The need for control and absence of technology should no longer provide grounds for justifying a purely centralized management for the business knowledge in human capital. During the early stages of the technology age, when most critical business knowledge was concentrated among a few elite such as scientists, executives, and sales persons, it was important to have a heavy control on knowledge to avoid unwanted leakages. Today however, since knowledge sources are distributed throughout the workforce, a heavily centralized approach is no longer appropriate. Also until recently, it was not possible to provide access for all employees to a centralized depository and have them use powerful search and analytical engines to leverage corporate information sources. Therefore, a centralized body was needed to gather information, classify and determine who needs what to facilitate proper distribution. Again, due to rapid proliferation of IP technologies, desktop computers, peer-to-peer file exchange technologies and business software applications, these limitations do no longer exist.

When we compare the Standard Approach described in Figure 5 against the functioning of liquid knowledge communities illustrated in Figure 4, we find out the following inefficiencies with respect to the roles and responsibilities of each participant:

Ø      Due to lack of feedback channels, knowledge seekers have limited ability to communicate their demands on content and quality to the corporate management and knowledge holders. Furthermore, they have limited ability to influence the quality of content.

Ø      Knowledge holders are not adequately compensated for their time and efforts to externalize (documenting) their knowledge. Also, available incentives usually do not cover the loss of personal power due to making a scarce knowledge available to others

Ø      Corporate Management cannot determine the link between the value of content and quality, and the bottom-line impact. Centralized management usually has limited ability to provide targeted incentives based on content and quality that is needed by seekers. Finally, corporate management, through knowledge specialists attempts to evaluate the content quality despite of their limited understanding of it[18].

The Standard Approach suffers from the same fundamental defects that brought socialism to an end

It is interesting, and simultaneously alarming, to discover a strong resemblance between the fundamentals of socialism and the management thinking behind the Standard Approach. In short, socialism is a fundamentally defective idea that was well carried out until its accumulated shortcomings made its survival impossible. Among others that are open to debate, mismanagement of its human resources was the most significant of those shortcomings.

Socialism assumes that people work hard and allow their production given to others for the benefit of the whole community. Similarly the Standard Approach assumes that employees work hard, and allow their knowledge, or per se production, given to other coworkers for the benefit of the whole organization. However, employees generally do not agree to share their knowledge, if they are not adequately compensated for their efforts to do so and for the loss of power they experience once their knowledge is shared. Relying on excessive rules, regulations, and enforcements, the Standard Approach merely succeeds in capturing the well-defined byproducts of everyday business functions at bare-minimum quality. It does not create a sense of ownership among employees towards their community, or generate a sense of accountability for delivering high quality insights. Consequently, enterprises end up leasing rather than owing employees’ knowledge, as it remains to be resident only in their minds.


Table 6             Socialism was doomed by the absence of autonomy and competition.

Socialism was doomed by the absence of autonomy and competition. This same fate will befall the Standard  Approach.  This is because knowledge communities based on free market principles will flourish and drive traditional communities into despair.

Socialism assumes that private property and ownership creates greed. By the same token, the Standard Approach does not recognize individual ownership of knowledge assets, and treats knowledge as a public good that is distributed to an authorized audience at zero cost. Consequently, free access to knowledge diminishes competition among employees to create, innovate and market their own individual intellectual assets within their respective organizations.

Socialism mistrusts the power of free markets. Until its grand failure, socialism has relied upon stringent rules and regulations to perform the tasks that are best performed by the free markets e.g., demand and supply management, pricing and quality control. So does the Standard Approach. Corporations employ rules and guidelines to capture, organize and distribute their knowledge. End users have often little, if no, say in what knowledge is needed, what quality is sufficient, and what value should be obtained from accumulated knowledge.

Having highlighted the shortcomings of the Standard Approach, we also need to emphasize its strengths to be fair. In its early years, Socialism thrived since certain economic achievements such as development of large infrastructures, heavy industries, and public transportation facilities exceeded the capabilities of any individual or commercial entity, and required involvement of a central authority. Today, corporations need a centralized authority to establish appropriate technological, legal, political and cultural infrastructures before they can leverage their human capital. Furthermore, certain knowledge-enabled assets such as white papers, trademarks, patents, etc. requires coordinated efforts of multi-disciplinary and multi-functional teams. In all these cases, involvement of central authority is required.

However, management of knowledge that resides in the minds of employees is a completely different beast. As a consequence of sole reliance on socialist principles in human capital management, enterprises are continuously failing to establish employee communities, where exchange velocity, community liquidity and knowledge liquidity could be maximized. Socialism was doomed by the absence of autonomy and competition; unfortunately, the future of the Standard Approach does not seem to be any brighter.

AN INNOVATIVE WAY TO HARNESS HUMAN CAPITAL: THE DIGITAL COMMUNITIES @ WORK

Today’s large organizations need to blend two fundamental concepts with their existing human capital management practices to improve their return from it. First, these organizations need to cultivate user-friendly digital communities, which successfully attract, engage and retain members, as well as facilitate knowledge exchange among them. Second, these communities should adopt free market principles, i.e., treat knowledge as an economic, rather than, a public good. We call the concept, which combines digital communities and free market principles, the Digital Communities @WorkTM.

Why digital communities?

In simple terms, a digital community is an Intranet application that facilitates collaboration and knowledge exchange among employees and members of the extended enterprise. It may include various features such as bulleting boards, threaded messages, document depositories, feedback boxes, etc. Also, it allows members to voice their suggestions, compliments or complaints. Subsequently, the application provides members with necessary tools and information to continuously improve their community.

Digital communities enable employees to tap into minds of thousands of coworkers by pooling their knowledge regardless of the distance between them. When entirely new information flows between previously unconnected groups of people, new ideas, concepts, philosophies, and more practically, solutions to common business problems emerge. Moreover, community members are never left on sidelines; on the contrary, they are part of the creative process that continuously shapes these communities. Consequently, they feel a strong sense of ownership, professional satisfaction and enrichment through having access to most insightful and current information and expertise.

Why free market principles?

Communities embrace a set of fundamental laws, called principles, to define their identity and to structure interactions among members in a way that supports the longevity of the whole community. We have earlier stated that most Fortune 1000 companies adopt socialist principles today in order to create collaborative environments within their organizations. As proven by historic events, free-market principles constitute a superior system for wealth creation through stimulating liquidity of exchanges of goods and services between utility seeking customers and suppliers. In this regard, knowledge exchange is no different than exchange of physical goods and services, as it also occurs between holders and seekers to enhance the utility of both parties. As a direct consequence of this analogy, free-markets rather than socialism provides a better system for stimulation of knowledge exchange in digital communities and for unleashing the power of knowledge in human capital.

Two characteristics of knowledge particularly dictate why free-market principles are needed to harness human capital through digital communities:

1.      Knowledge is perishable. What is the value of business intelligence that is a second, a day, or a month old? How much is a real-time vs. delayed stock quote worth? How quickly does the value of business opportunities depreciate in time? How rapidly does knowledge of market trends, technology understanding and management practices depreciate?

All these questions underscore the fact that knowledge is perishable, and it has a finite shelf life.  Particularly, there are two main factors that determine its shelf life:
a) accuracy, i.e., how long are the key relevant factors, which were present when knowledge was first originated, preserved:
b) uniqueness, i.e., how long can the holder enjoy a monopoly power over the knowledge.

As it is the case with any physical perishable good, a particular knowledge has to be consumed by seekers before its shelf life expires. Therefore, it is very important that collaborative environments, such as digital communities, can maximize liquidity in the community. Free-market systems are proven to be superior over socialism in creating liquid markets.

 

2.      Knowledge needs collaboration to appreciate. Collaboration not only enables more people to benefit an existing knowledge, but also stimulates creation of completely new insights. In other worlds, knowledge assets appreciate rather than depreciate as they are consumed. Hence, digital communities need to improve liquidity of knowledge exchange in order to boost the value of human capital. Once again, free-market principles suit better to digital communities to ensure liquidity in the community.

A rough analogy between financial capital and knowledge assets clearly illustrates the significance of liquidity in digital communities. As we all know, the financial capital depreciates by time through inflation, whereas it appreciates when invested. In other words, financial capital has also a shelf life, and it results in creation of new capital when put in use. Liquidity of financial capital is a very important phenomenon in modern economies. During the last 200 years, modern economies have established autonomous and liquid capital markets that have efficiently matched available capital funds with profitable projects competing for funding. As a matter of fact, many scholars believe that the hidden engine behind the recent technological innovations in the U.S. is the enormous size of available financial capital. Socialist economies, on the other hand, have lacked this autonomy and competition. They were not effective in identifying profitable and innovative projects. Consequently, their societies were unable to create enough wealth to sustain them.

By the same token, liquidity in collaborative environments, such as digital communities, plays a very instrumental role in knowledge based wealth creation. Therefore, digital communities should embrace free-market principles to ensure liquidity of knowledge exchange. In digital communities, knowledge should be treated as a good that can be exchanged for the right price[19], determined by the demand and supply in the community. Knowledge holders should be compensated for their efforts to produce knowledge. Seekers should incur a cost[20] for the knowledge they consume. The corporate should allocate a budget to each employee to cover the cost of consumed knowledge. The amount of this budget should depend on how much the corporate values employee’s output. Corporate management should act as the market maker, and facilitate exchange of knowledge between holders and seekers.

Does the Digital Communities @WorkTM make an economic sense?

The fundamental question that needs to be answered is whether allocation of compensation plans to stimulate knowledge contribution within Fortune 1000 organizations makes an economic sense. To search for possible clues, let’s look at the following financial model.

Our model consists of three main modules. The first module analyzes the financial data of all Fortune 1000 organizations, and ranks them based on each firm’s potential for benefiting from the Digital Communities @WorkTM. The ratio of a firm’s Market-to-Book (MTB) to the average of highest MTBs in its industry is used for this ranking. The lower the ratio is, the less the market values the firm’s intangible assets with respect to those of its competitors, implying that the firm is under leveraging its human capital. Besides the MTB, this module uses several industry specific factors to determine the benefit potential. Some of these factors include, dependency on innovation and creativity, the percentage of employees having access to corporate intranets, the perception about investments on knowledge assets, the willingness to adopt new technologies, etc. Once all 1000 firms are ranked, the model selects only the top 200 organizations, and analyzes them in four categories, each containing 50 Fortune 1000 organizations.

The second module creates a comprehensive model of the Digital Communities @WorkTM. Using current usage patterns of employees at corporate Intranets or at the Internet, the module makes assumptions[21] about many aspects of digital communities: How many members will an average community have? What will be the behavioral characteristics of knowledge seekers, and knowledge holders? What will be the distribution of quality of submissions in each community? How large a compensation budget is needed to pull supply in order to match it with demand? Etc.

The third module leverages the output received from the previous two modules. It calculates the potential improvement opportunity in annual operating profits due to implementing the Digital Communities @WorkTM. Furthermore, it estimates the annual budget of compensations, and the annual cost of running the communities. The module assumes that community management is outsourced to specialized service providers. The providers not only manage the day-to-day activities of communities, but also develop underlying technologies. Also they help executive managers initiate necessary change management activities to implant digital communities in their organizations. The hosting organizations are expected to have a corporate Intranet and a corporate portal, which are already accessed by a majority of the workforce.

Table 7             The Digital ies @WorkTM offers almost a 20-fold return on costs, and require less than 1.7% of salary pool to be diverted into the compensation budget

Top 200 of Fortune 1000 Organizations

            Number of Employees

Compensation Budget / Salary Pool

Annual Compensations ($ MM)

% Improvement in Operating Earnings

Annual Improvements in Operating Earnings ($ MM)

Annual Community Cost ($ MM)

Average of Top 200 firms

46,880

1.6%

$38.5

8%

$120.8

$5.2

Average of Top 1 - 50

40,561

1.7%

$33.9

84%

$162.0

$6.4

Average of Top 51 - 100

47,909

1.7%

$40.2

10%

$89.7

$4.3

Average of Top 101 - 150

41,632

1.7%

$34.7

6%

$69.6

$3.6

Average of Top 151 - 200

57,417

1.6%

$47.1

2%

$71.5

$3.9

Table 7 summarizes the model’s output for a mature digital community[22]. The model reveals that improvements in annual operating[23] earnings for Target 200[24] organizations average at $120 million after 5 years of being in operations. Top 50 firms with highest benefit potential could gain about $160 million, whereas other firms that leverage knowledge assets better might be able to realize  $70 million or more in improvements of their operating earnings. The model reveals that the annual cost of the Digital Communities @WorkTM would range between $3.6 million and $6.4 million, implying as much as a 20-fold return on cost.

Our model also indicates that the compensation budget does not need to exceed 1.8% of the overall salary pool of hosting organizations. In other words, these organizations do need to divert within five years less than 1.7% of their existing salary pools into digital communities to support them. The Digital Communities @WorkTM constitutes a new channel for organizations to compensate employees based on the merit of their knowledge contribution. Today, corporations expect employees to contribute knowledge into corporate systems, and they compensate them through salaries. It is fair to assume that this portion of the salary pool can be diverted into digital communities to compensate employees based on the value of their actual contributions, rather than based on management’s expectations. Consequently, compensation budgets will not constitute a financial burden to hosting organizations.

Successful blend of digital communities and free-market principles is likely to produce the next web-based “killer application”

Some of the earliest Internet-based community-like applications involved chat rooms, billboards, and multi-user dungeons as means of bringing people together. Typically, they were simplistic, text-based environments with severely limited ability to promote interactions among participants. Since the explosive growth of the Web, and the tremendous financial and technical resources being poured into its development, sophisticated tools have emerged that allow the creation of extensive, secure corporate Intranets to facilitate collaboration among knowledge workers. In this regard, enterprise portals are fast becoming the hottest new technology in corporate Intranet market. They offer a Web-like solution to distribute structured business information and consolidate business intelligence objects, e.g., reports, documents, spreadsheets, databases, etc., generated anywhere in the enterprise. According to Gartner Group, by the year-end 80% of technology savvy organizations will implement an enterprise portal, and spend tens of million dollars to further develop this technology.

Consequently, we would probably agree that ingredients necessary for establishing successful collaborative environments are already here: a mature web-based infrastructure, a variety of enabling technologies, financial resources and significant attention among executive management teams. Therefore, we assert that the next web-based killer application is the digital communities located on corporate intranets. These communities will treat knowledge as a perishable good with economic value rather than a public good. By delivering maximum velocity of exchange, community liquidity and knowledge liquidity, such communities will enable enterprises to realize the untapped potential of their human capital and result in substantial improvements in operating profits.

The path to establishing and nurturing digital communities is rewarding, but nontrivial

It is always a challenge to bring a concept to life, regardless of how sound its underlying rationale may be. Today, establishment of digital communities is a promising concept for human capital management at large organizations; and, it exhibits no exception to the above-mentioned rule. At most organizations, successful digital communities will flourish only if executive management teams change their organization’s attitude and habits regarding how employee knowledge is captured, organized, and distributed.

Executives need to re-evaluate their position regarding to the tradeoff between control and liquidity of knowledge

When it comes to knowledge management, control and liquidity are like to ends of a stick; more of one means less of the other. In theory, large organizations use control over their critical knowledge to minimize the danger of unwarranted parties’ access to it.  In reality, however, they fell short in articulating what information constitutes critical knowledge and what parties are unwarranted. As a consequence of this vacuum, individual decision makers take excessive measures either to be on the safer side, or to leverage the circumstance to gain political power within their organizations. Both of these motivations often contradict with the overall welfare of those organizations. As control over the amount of knowledge available, and the size of its audience is increased, lesser knowledge exchange occurs within organizations. The liquidity of knowledge exchange becomes severely inhibited, and organizations suffer.

Before establishing digital communities, executives need to demolish the artificial organizational barriers, inhibiting exchange of knowledge within their workforce. There are three important tasks that executives need to implement. First, they need to communicate to the rest of their workforce how important knowledge exchange is to the viability of the organization. Second, they need to establish taskforces, which analyze how critical knowledge is created and used within their organization. The work of these teams should reveal potential barriers that do not contribute to the overall welfare of the organization. Finally, executives need to lead the development of analytical frameworks for digital communities to monitor activities, and to develop guidelines that best manage the delicate balance between the control and liquidity.

Organizations should empower employees to nurture self-monitoring communities

Like most successful societies, digital communities should be able to self-monitor themselves. Community members should determine what they need from the community and what constitutes the quality. Furthermore, communities themselves should be able to differentiate valuable contributions from non-value added stuff, as well as productive contributors from the free riders. Once these fundamental features of free-markets are imbedded, organizations can enjoy full benefits of digital communities.

Since most Fortune 1000 organizations rely upon a centralized knowledge management department to determine what constitutes value and quality, they will face a significant challenge, when turning to the whole employee base to perform these functions. Possibly, there will be strong resistance from those who prefer present way of managing the corporate knowledge. Another difficulty is that expectations from digital communities may rise too quickly for them to demonstrate their value.

Fortunately, digital communities can be established gradually, and in parallel to all existing knowledge management practices. To foster digital communities, Fortune 1000 organizations need to first establish necessary infrastructures in governance, management, and technology. Once these infrastructures are in place, employees can determine what role their community should play in the management of human capital. Clearly, not all tasks are suitable for digital communities, e.g., development of large intellectual capital projects, toolkits, methodologies or sensitive technologies. However, other tasks such as sharing marketing and customer information, developing practical approaches to frequent problems, bringing new employees up to speed, etc. can be accomplished by communities effectively. It needs to be seen what roles are most appropriate for digital communities. As digital communities demonstrate their value proposition, gradually they will also define these roles.

Executive management needs to view compensations paid to community members for their contributions, as an integral part of total employee compensations

Most of us agree that we are in a knowledge-based economy, where knowledge rather than physical resources play primary role in establishing competitive advantage in marketplaces. However, there exist a general resistance to make a direct payment to employees for their knowledge. This reluctance stems from the expectation that everybody should share his or her knowledge with others to begin with. As we have extensively elaborated before, this expectation is constitutes the basis of socialism, and there is real need to change this perception.

If all employees were compensated proportional to their contribution, Fortune 100 organizations could realize an exceptional increase in the knowledge throughput per employee. This improvement anecdotally would be similar to the difference between socialism and free-markets in their ability to create wealth. Cleary, placement of compensation plans to promote knowledge contributions cannot be implemented successfully, if organizations fail to identify the link between a particular content/quality and its tangible impact to the bottom-line. In the absence of these links, compensations may be counterproductive, or they may demoralize the whole community. Therefore, it is important to establish a comprehensive understanding of the knowledge value chain at hosting organizations and to support digital communities with comprehensive analytical engines that understand what constitutes a valuable insight and how much compensation is appropriate to externalize it within corporate systems.

CONCLUSIONS

Human capital is one of the most valuable and underleveraged corporate assets of the present time. For long, managers didn’t know how to invest in human capital and recognize associated returns. Furthermore, knowledge has been managed at large organizations according to socialist principles, where it has been treated as a public good, and has been distributed to an authorized group at zero cost. Socialism is not suitable for wealth creation; it is also not suitable for the growth of human capital.

Recent technological developments and changes in the competitive business environments created an opportunity for better management of human capital at large organizations. The digital communities that adopt free market principles is an innovative concept that is well suited to establish frictionless environments for knowledge exchange, and therefore, for the growth of human capital.

Although digital communities are invaluable to large organizations, their implementation is nontrivial, requiring a major paradigm shift in the way executives view how knowledge be acquired, captured, organized and distributed within their organizations. Furthermore, enterprises that decide to nurture digital communities need to develop complex analytical engines to manage the balance of demand and supply through comprehensive compensation plans.

This article concludes that executive managers at Fortune 1000 organizations will significantly benefit from carefully evaluating the benefits and risks of digital communities for their own organizations. Executives, who would like to learn more about the digital communities, are encouraged to contact the author to discuss the merits of concepts introduced here, and the means of implementing them.


About the Author

Hakan Altintepe has more than 11 years of extensive experience in knowledge management as both knowledge holder and seeker at large organizations. He is currently a manager with the New York office of A.T. Kearney, Inc., a leading global management-consulting firm. As a consultant, he has worked with some of the largest global organizations in the financial, retail, telecommunications and high technology industries. His functional expertise includes information technology management, e-business strategy, financial analysis, supply chain management, strategic sourcing, and organizational design. Prior to his career at A.T. Kearney, he has worked in marketing at Silicon Graphics, Inc., in software development at Nortel Networks, Inc., and in product development at Siemens A.G. in Erlangen, Germany. Hakan holds an MBA Degree from Carnegie Mellon University in Pennsylvania, and an M.A.Sc. Degree in Electrical Engineering from the University of Ottawa in Ontario, Canada.

For additional information regarding this article, Hakan Altintepe can be reached at 212-705-1247, or by email mailto:hakan_altintepe@atkearney.com.



[1] Source: The Book of Knowledge; Merrill Lynch; 9 April 1999

[2] Source: The Book of Knowledge; Merrill Lynch; 9 April 1999

[3] For the purpose of this analysis, we assume that the leverage ratio of an average Fortune 1000 organization has not significantly changed since 1980.

[4] For practical reasons we have not elaborated the impact of goodwill here.

[5] For practical reasons, it is assumed that market value and book value of tangible assets do not differ significantly

[6] The Measurement and Management of Intellectual Capital: An Introduction; International Federation of Accountants, September 1998

[7] Fortune 1000 database, www.fortune.com, April 15, 2000

[8]www.marketguide.com , May 1, 2000

[9] Market value information is retrieved from www.yahoo.com, yahoo finance on May 27, 2000. The book values are obtained from www.fortune.com on May 26, 2000 and they represent the book values as of year-end 1999.

[10] 56% = $25,000 / $44,500; 44% = 1- 56%

[11] $10.4 trillion * 10% * 44% * 22% = $100 billion; $10.4 trillion * 30% * 44% * 22% = $300 billion

[12] A.T. Kearney’s Executive Agenda by Steve Mecklenburg; KM Presentation by George Droger; Gartner Group predictions.

[13] Employee training increases the value of human capital the enterprise rents not owns, since after training the acquired knowledge is not shared with the rest of the organization, and solely possessed in the mind of the trained employee. For simplicity, we assume that money spent on training is an investment on human capital. In reality, it is additional lease paid in conjunction to employee salaries, bonuses, retention plans, etc to have access to employees’ knowledge as long as they stay with the firm.

[14] Information is obtained from www.marketguide.com.

[15]This statement assumes that cost of capturing business knowledge that resides in the minds of employees and transferring it to other employees occurs at zero cost. Clearly, this is not the case, and hence optimum institutionalization percent is somewhat below 100%. We will discuss this issue in detail later in this document.

[16] Source : www.fortune.com

[17] Shelf life refers to time before knowledge looses its insightfulness or becomes inaccurate.

[18] Knowledge seekers can determine the usefulness of a particular knowledge better than the knowledge specialist can do it for them.

[19] Price does not have to be in terns of a hard currency. It can be recognition, perks, benefits, etc. It is important that it has a well-defined utility value to employees.

[20] I don’t suggest a financial burden on the seeker, here. Rather, the cost should be a measure to make the seeker aware that he/she is consuming time and other corporate resources while consuming the knowledge

[21] Based on Media Metrix publications, IDC publications, Red Herring, Business2.0

[22] The model assumes that digital communities become mature after being in operations for five years.

[23] Before income tax, depreciation, amortization

[24] Refers to 200 of Fortune 1000 organizations with highest potential to benefit from digital communities