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What does it mean to say you "know" something? And, more importantly, how do you gain that knowledge in the first place and how do you capture it, retain it and retrieve it when needed? Without spiraling into an existential discussion on the "nature of knowing," it is critical to understand that not all knowledge is created equal and so not all knowledge can be retained and retrieved in the same way.

Why is capturing mission-critical knowledge so important? In the electric power generation industry the answer can be easily summed in a number: 2.5 million. That is, 2.5 million customers without power as a result of a worker who erroneously disabled two levels of relay protection that cut off power to 2.5 million Floridians in late February, 2008.

Here's another number: 575 million. That's the estimated dollar cost of industry-wide employee attrition per year. That works out to $90 million due to worker retirement and $485 million due to non-retirement attrition. And finally, one more number: 45. That's the percentage of the total workforce within the electric and natural gas utility industry that will soon reach retirement age. If having nearly half of an industry's workforce nearing retirement isn't enough of a wake-up call, consider also that the average age of the power generation industry workforce as a whole is nearing 50.

So, why is knowledge management (KM) so important? Because the opportunity cost of letting knowledge walk out the door without capturing it first is too high-and getting higher. Organizations that don't employ effective KM processes to safeguard existing mission-critical knowledge will ultimately pay the price in reduced competitiveness, reduced market share and reduced stock prices.

The American Public Power Association (APPA, 2005), in The Aging and Retiring Workforce: New Challenges for Public Power, detailed how the aging and retiring workforce would affect the electric power generation business. The report showed the following:

• 50% of the respondents indicated that more than 20% of their workforce would be eligible to retire in the next five years.
• 63% of respondents identified "skilled trades" as among the utility positions with the most likely retirements over the next five years.
• 52% of respondents indicated that vacancies among the "skilled trade" positions would be among the most difficult to fill.
• 64% of respondents believed that retirements would create either a moderate or very significant challenge to their business.

If the KM challenge arising from retirement attrition sounds bad, it is. But perhaps even more challenging is the difficulty in attracting and retaining qualified engineers. In today's high-tech economy, the best and the brightest engineering students are more interested in working for companies like Google than in working for the local utility. The fact remains, however, that without the folks at the local utility, Google's servers wouldn't serve anyone and search engines, along with everything else, would flicker and go dead. Even the back-up generators need engineers to run them.

One way to drive the importance of the KM challenge home is to measure the return on investment (ROI) for knowledge management systems (KMS). Measuring ROI for KMS is itself a long-term project not a short-term benefit. Feldman estimated that knowledge workers spend from 15% to 35% of their time searching for information. These workers typically succeed in finding what they seek less than 50% of the time. Feldman also found that 90% of an organization's accessible information is used only once. That's a lot of time (and money!) spent on not completing core job responsibilities.

Although all these numbers look impressively daunting, the biggest KM challenge of all is convincing decision-makers in the electric power generation industry that the problem is real and growing. DiFrancesco and Juliano state, "The power generation business faces a critical strategic choice: continue to rely on the strategies and tools of the past, or recognize the competitive advantage that can be gained by developing strategies to manage the new reality" (2004, ¶ 23). Silverstein stated, "The central issue is that the attrition rate has exceeded the rate at which people are getting educated and coming into the ranks" (2006, ¶ 2). According to a study performed by Sierra Energy Group, about 57% of all electric power generation organizations have a strategy in place for managing the impeding shortage of qualified workers. That is considered small, given the fact that the positions that will experience the most retirements during the next five years are also those that will be difficult to replace (Silverstein, 2006, ¶ 5).

Organizations within the electric power generation business must develop a knowledge-creation process (Figure 1). Nonaka and Nishiguchi (2001) state, "For knowledge to be created organizationally, knowledge within a particular individual needs to be shared, recreated, and amplified through interactions with others" (p. 19). While knowledge can take on many forms, tacit and explicit knowledge are the two generally recognized forms of knowledge (Nonaka, 1994). Explicit knowledge is articulated, easily documented, shaped and codified and can be expressed in formal and systematic language (Choi & Lee, 2003). Referring to the electricity industry, Bishop said, "The power generation industries traditional training programs address the `explicit knowledge' contained in written documents, technology manuals, policies and procedures. Tacit knowledge held in a worker's mind is harder to capture and transfer to new employees" (2005, ¶ 4). Explicit knowledge represents the type of knowledge that is often captured in documents, libraries, written policies and procedures, files, manuals, and databases.

Explicit and Tacit Knowledge

While knowledge can take on many forms, explicit and tacit knowledge are the two forms important to knowledge management processes. Explicit knowledge is articulated and codified and can be expressed in formal and systematic language. Explicit know-ledge represents the external manifestation of data and information that can be captured in documents, libraries, written policies and procedures, files and manuals (Figure 2).

In contrast, tacit knowledge consists of a technical dimension, often referred to as know-how, and a cognitive dimension that includes schemes, mental models and beliefs. Tacit knowledge is deeply rooted in individuals' actions, experiences and involvement within a specific context as well as in the ideals, values, or emotions he or she embraces. It is, therefore, highly personal, hard to formalize and difficult to communicate and share with others. It is also considered to be the fundamental type of knowledge upon which organizations are built (Figure 3).

For instance, imagine a piece of equipment in a power plant, say a motor on a pulverizer drive, needs repair. Joe, a young engineer, decides to search a database for an equipment repair manual, an example of explicit knowledge, to determine how best to proceed. But also imagine Joe discovers the motor has both been upgraded and already has a history of repairs. Joe concludes it would be faster and more efficient to find the specific worker who performed the repairs in the past or who was in charge of the upgrades.

Joe gets the upgrade and repair log and discovers George is the man he needs. George, however, has been transferred to a different plant. In a phone consultation, George tells Joe to listen to the equipment. Listen for what? Joe asks. Well, George says, if it is making a low hum, you need to do abc. But if it's more of a buzz, you need to do xyz. And, if it is making a knocking sound, for Heaven's sake turn the damn thing off.

Obviously, the tacit knowledge held in George's mind is at once valuable to the task at hand and difficult to access, replicate and apply. George's knowledge and experience -- his knowledge of exactly what to listen for -- is difficult to transfer to Joe, or to any other engineer, through a written repair log. (Perhaps an audio file of the different sounds would help, but even that would assume the exact same sound would be made during each repair scenario.) Simply articulating and recording tacit knowledge and storing it in a log file or database does not mean it will do the next worker much good. Indeed, for tacit knowledge to be effectively shared, it must often be passed person-to-person through hands-on learning and mentoring.

George's knowledge should have been captured and shared before he was transferred to another plant because as difficult as it is to search for the right nugget of knowledge in a database, it is much more difficult to search for the right nugget of tacit knowledge held in an employee's head when employees are scattered across a regional, national or international organization. And when employees cannot readily find the right expertise, they must spend both time and effort (i.e. money) searching for the answer.

Employees who leave an organization take mission-critical knowledge with them. This knowledge may be lost forever if a process is not in place to capture and transfer it to their successors. According to Qu and Pao, "employees who follow them in the job take a longer time to ramp up, important insights disappear, and the company's ability to act with intelligence and agility can be significantly handicapped causing the organization to lose its competitive advantage."

Tacit knowledge involves both cognitive and technical elements and is based on action, experience, and involvement in a specific context (Mooradian, 2005). The cognitive elements refer to an individual's mental models consisting of beliefs, paradigms and viewpoints while the technical component consists of concrete expertise, crafts, and skills that apply to specific contexts (Politis, 2003). Nonaka & Nishiguchi (2001) define tacit knowledge as "highly personal and hard to formalize, making it difficult to communicate or share with others" (p. 14). Tacit knowledge represents the type of knowledge that is often embedded within the individual. Tacit knowledge is subjective and hard to formalize and communicate (Keskin, 2005). Existing employees may feel obliged to be willing to share their tacit knowledge to new employees out of gratitude for their long employment or simply because they feel sharing is "the right thing to do."

Wu (2000) stated, "Organizations that can leverage technology to exploit their data will realize the benefits by creating a competitive advantage. The competitive advantages are in the form of identifying trends, unusual patterns and hidden relationships that a competitor may not realize." Creating a comprehensive, mission-critical knowledge management system benefits the organization by keeping its secrets, core processes, and knowledge within the organization. The loss of mission-critical knowledge may result in unacceptable operational, functional, or financial harm to the organization. The electric power generation industry must distribute the mission-critical knowledge among all employees involved in operations, maintenance, engineering, and support functions.

The International Atomic Energy Association (IAEA) deployed a process to identify and capture the undocumented mission-critical knowledge of employees nearing retirement (p. 18):

• Identify critical "at risk" knowledge and skills, particularly those associated with impending attrition.
• Evaluate the risk associated with losing critical knowledge and skills and focus on areas of greatest risk.
• Develop, implement, and evaluate actions (documentation, mentoring, coaching, training, reengineering, sharing expertise, etc.) for managing risk.

There are three basic components in every successful knowledge management initiative: knowledge creation/capture, knowledge sharing/transfer, and knowledge integration/use. Knowledge creation and/or capture refers to the process in which knowledge is acquired by an organization from outside sources or created from within. Knowledge sharing/transfer refers to the process by which knowledge is transferred from one person to another, from individuals to groups, or from one group to another group. Knowledge transfer increases the value of knowledge within an organization by maximizing knowledge. As Lavergne and Earl put it, "Knowledge transfer is a dynamic process of complex interactions between players who seek to understand and identify the reality and act upon it."

Finally, the integration is when the value and meaning of the knowledge is recognized and applied when and where needed to further the goals of the organization. Knowledge use is often referred to as knowledge utilization, knowledge application or knowledge implementation. For an organization's knowledge management processes to succeed, they must be effective in all three aspects.

The electric power generation industry faces a staffing crisis. To keep pace with anticipated growth over the next five years, the industry must add 3% - 5% annually to the workforce. Achieving this goal will prove difficult as the industry averages an annual attrition rate of 10% and anticipates a shortage of engineers, craftsman, electricians, mechanics, and other skilled trades.

Knowledge Workers Recruitment and Retention

Organizations must both recruit talented future employees and retain experienced current employees. Organizations must also ensure that strategic workforce efforts safeguard existing mission critical knowledge and develop employee capability. Knowledge identification and capture, job shadowing, mentoring, apprenticeship, documentation processes, procedures, and standards help identify and mitigate knowledge management risks.

Developing essential skills in future employees is a priority. The power generation market competes with other industries and technology-based career paths for talented future employees. Because skill development for many positions must begin at the undergraduate or graduate level, a student considering a career in the power generation industry must often decide to enter a power program years in advance of entering the job market. A student's perception of the power generation job market is critical as he or she considers the number of potential job openings, the challenges and career progression opportunities, salary, job security, and a work-life balance. The industry must proactively position itself as an "employer of choice."

The university infrastructure necessary to support a growing power generation industry work force is weakening. Many universities have discontinued industry-focused programs and often no longer teach formerly required courses. Major universities that do offer industry-related courses do not have enough faculty members to fill the anticipated needs of the industry. The power generation industry must play a more prominent role in revitalizing the educational programs needed to sustain industry growth.

Employer of Choice - Corporate Citizen

The power generation industry must embrace a social vision that defines corporate citizenship as both a moral responsibility and an economic necessity. Successful, world-class organizations understand that good corporate citizenship strengthens the organization. Power generation industry organizations must adopt a social vision that guides the development of citizenship strategies and "puts a positive face on the industry." Successful organizations will distinguish themselves from competitors through progressive employment practices, excellent customer service, minimal environmental impact, and by taking a measurable, active role in their communities.

Succession Planning

The power generation industry must address the long-foreseen aging of its workforce. The sustainability of the industry's competitiveness requires a renewed effort to understand how talent is used and leveraged. The industry must create a strategic workforce gap analysis plan starting with a proactive evaluation of the critical workforce capabilities needed over the next five years and the creation of maps that identify talent gaps before they arise.

According to the Department of Labor, estimated retirements in the power generation industry for 2006 were just 4.4% while non-retirement attrition was 19.4% (Kamph, 2008, p. 27). Kamph (2008) stated, "Eighty-seven percent of companies do not have a goal for limiting non-retirement attrition" (p. 23). Participant interviews revealed that at least 73% of participants' organizations have no succession plan for limiting non-retirement attrition.

Beatty and Visser (2005) defined organizational career development as:
A collection of resources and processes aimed at optimally aligning the career needs of individual workers with the mission, vision, and goals of their employers. An effective organizational career development program is completely integrated in all relevant business processes, particularly those in the realm of human resources, and enjoys full commitment and support from senior management. Activities include, but are not limited to: counseling and assessing; coaching; mentoring; training; hiring; and promoting. There is shared responsibility between the employee, HR staff, and management for delivering results in an atmosphere of openness and accountability (p.95).

An effective workforce analysis team communicates across organizational boundaries and includes representatives from engineering, information systems, human resources, operations, maintenance and other functions. The team operates within the strategic business planning group to forecast supply and demand up to five years into the future. Careful planning enables the team to perform just-in-time hiring in response to specific business needs and to avoid the wasteful practice of precautionary staffing.

The planning team helps control people costs by carefully linking human resource flows to the budgets of individual functional units while attempting to optimize the organization as a whole. The team's detailed plans reflect many variables including operations and workload forecasts, expected retirements, projected hiring needs, and future skill set requirements. The team uses up-to-date data and sophisticated attrition models to develop function-by-function labor supply information. These models incorporate, among other variables, age, type of work, and economic conditions. Demand is much harder to predict because it involves speculative variables such as operational, maintenance and workload schedules.

Human resources plans begin a year in advance and go through several iterations to adjust for changes in operational forecasts, the economy, and many other factors. The planning group conducts a large number of what-if scenarios and must be able to respond to changing conditions by revising plans on short notice. Nearly instantaneous scenario planning allows group and functional leaders to make timely, data-driven people decisions whenever required.

It is clear, however, that the loss of critical explicit and tacit knowledge from employee turnover is costly, and can result in a drop in productivity and loss of competitiveness in the power generation market. It is also clear that very few individuals in the industry understand the concept or fully recognize the importance of managing knowledge (either explicit or tacit) and its connection to competitive advantage. While it is certainly true that many organizations recognize that their primary sources of competitive advantage lies in the unique proprietary knowledge they possess, they have, for the most part, failed in transforming this knowledge.

Figure 1: Knowledge Creation

Figure 2: Explicit Knowledge Creation

Figure 3: Tacit Knowledge Creation

References

American Public Power Association 2005 Report. The aging and retiring work force: New challenges for public power. American Public Power Association, 1-24.

Bishop, W. (2005, May/June). Preventing knowledge loss as more utility workers retire. Utility Automation & Engineering T&D, 10(4), 16-22.

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DiFrancesco, J., & Juliano, J. (2004). Workforce renewal: A CEO's strategic imperative. Utilities Project, 102-104.

Keskin, H. (2005, September). The relationships between explicit and tacit oriented knowledge management strategy, and firm performance. Journal of American Academy of Business, 7(1), 169-175. Retrieved November 19, 2007, from University of Phoenix ProQuest.

Mooradian, N. (2005). Tacit knowledge: Philosophic roots and role in KM. Journal of Knowledge Management, 9(6), 104-113. Retrieved on November 13, 2007, from University of Phoenix ProQuest.

Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organizational Science, 5(1), 14-37. Retrieved on May 3, 2007, from University of Phoenix ProQuest.

Nonaka, I., & Nishiguchi, T. (2001). Knowledge emergence: Social, technical, and evolutionary dimensions of knowledge creation. New York: Oxford University Press.

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Qu, L, & Pao, S. (2005). Tools for tapping expertise in large organizations. In Rao, M (Ed), Knowledge management tools and techniques (pp. 365-377). Oxford, England: Elsevier Butterworth-Heinemann.

Silverstein, K. (2006, January). Getting in shape for the challenge ahead. EnergyBiz Magazine, 4(1), 19-22.

Wu, J. (2000, November). Business Intelligence: The Transition of Data into Wisdom. Retrieved on April 22, 2007, fromfrhttp://www.dmreview.com/portal_ros.cfm?NavID=91&EdID=2524&PortalID=17.