KM Implementation

Modern enterprises are inundated with information, and in most of the organizations the volume of data has been increasing at a rate of 35 percent to 50 percent each year. Companies today process more than 60 terabytes of data annually, which is 1,000 times more than a decade ago. Most of the data collected today by the companies is unstructured (as opposed to in structured databases) and captured in word processing documents, spreadsheets, images, and videos, which often makes it difficult to retrieve or interpret. Despite the buzz around “big data,” most organizations are focused on challenges of storing, protecting, and accessing massive amounts of data, which are primarily the responsibilities of the IT unit. In general, most organizations have underexploited the opportunities that could be made possible from exploiting such data. Only a few CIOs and other IT executives reported that their organizations are generating significant business benefits from the stored data.

Studies show that on average, data in organizations grows at a rate that nearly doubles the volume of data stored every two years. The highest growth rates were primarily observed at research universities and hospitals. Contrary to the expectation of increased decision-making opportunities based on the volume of data, most organizations are still in the aspiring stage of generating business value from the data. For a better understanding of the challenge in producing business value from the information in the organizations, it is helpful to understand various segments of the data sources.

1. Growth of Structured Data

As companies invest heavily in enterprise resource planning systems, customer relationship management systems, radio-frequency identification tags, and other technologies, the amount of data collected per transaction is multiplying. For example, companies collect data on inventory levels, transportation movements, and financial transactions enabling them to communicate more accurately with customers, accelerate supply chains, manage risks, and identify business opportunities. Increased structured data can be a double-edged sword: increased granularity creates opportunities for analytics that could lead to improved business processes and customer service, but duplicated and conflicting data can undermine service delivery resulting in conflicts over whose data are more accurate. A large percentage of stored data serves no useful purpose in practice because management has not specified how it will be used or who will make what decisions on the provided data.

2. Explosion of Unstructured Data

Documents, images, videos, and e-mail make up a significant percentage of the data stored in most organizations. This growth is the result of many factors such as increased regulatory requirements. Some organizations are finding that unstructured data collected through social media enabled greater sharing of information and knowledge. However, realizing business value from this unstructured data typically requires indexing and reorganizing of some information.

At the tactical level, IT units can take the lead in ensuring safe, reliable, cost-effective data storage and access, but that will not necessarily lead to business success. In order to achieve the maximum value from data, senior management must commit to three practices:

• Identify the "sacred data": Information about customers, sales orders, inventory items, employees, and so forth constitute most of the data. This information can provide different opportunities for different segments of the business. By scoping the “sacred data,” management can clarify how the business will set the parameters for the organization’s enterprise architecture on which IT can build.

• Define the workflows that will use unstructured data: To derive business value from the unstructured data, management needs to define the workflows that create, retrieve, change, and reuse documents, messages, images, and other unstructured data. In particular manual or automated processes need to be defined for adding the “metadata”—tags that categorize unstructured data.

• Use data to refine business processes: deriving benefits from the information available is an iterative process. Improving business processes and service can lead to richer data allowing innovation and efficiencies.

Source: Compiled from Beath et al. 2012.

Extracted from: Becerra-Fernandez and Sabherwal (2014) pg.325

Please note, the below links are to external website, please proceed with caution!

No. 1: World Bank: Behind the IT Transformation

Amidst the World Bank's recent management brouhaha, a more significant event went overlooked-the bank's dramatic transformation from a hierarchical source of low-interest loans to a decentralized organization that uses knowledge-management technologies to fight poverty and disease in developing nations. It wasn't easy. In order to create a working knowledge management system, the bank's information infrastructure and communications network had to be overhauled.

No. 2: Southern Co.'s IT Aids Post-Katrina Recovery

Southern Co., the energy company that produces electricity for much of the Gulf Coast region, was preparing for Hurricane Katrina even before the 2005 storm struck. Southern had taken steps to meet worst-case scenarios, such as building an enterprise content management platform to ensure that engineers could get immediate access to design plans of electrical substations and other power equipment. As a result, the electricity distributor restored service to its Mississippi customers within 12 days of the hurricane, instead of the initially estimated 28.

Setting up the content-management system presented some challenges, including matching data from one legacy system with a second one. The former system was a database with text data related to drawings, but no images; the latter contained drawings without the related text.

No 3: Dow Jones Makes Headlines With Content Management

With readers flocking to the Internet, newspaper publishers have been forced to invest more dollars in pushing content to their Web sites. For Dow Jones, that presented a series of challenges, including a constant grapple with the content management and delivery tools needed to serve a growing subscriber base.

No. 4: Shuffle Master Puts its Money on a Portal

Shuffle Master, the manufacturer of automatic shuffling machines and chip counting products, had been relying on a fragmented sales and order processing infrastructure that was making it difficult for company employees to find integrated and reliable business information. For example, sales forecasts were issued several times each quarter, but were of limited value to salespeople trying to meet their quarterly goals because the numbers were stale by the time they were issued.

The solution they came up with: Build a portal that could pull data on demand from more than 60 databases. The challenge they faced: How do you build a powerful portal on a midsize company's budget?

No. 5: Pratt & Whitney: Help Yourself

Pratt & Whitney airline engines are constantly transmitting information about the status of their parts. Down on the ground, data recorders at the manufacturer, which builds and maintains these engines for carriers such as Delta Air Lines and United Airlines, capture this information and compare it to optimum levels in order to ensure the ongoing health of the engines. Streams of data are made available in a flash through a Web portal. But as the manufacturer found out, portals are only effective if they deliver something that users want.

Extracted from: https://www.cioinsight.com/c/a/Case-Studies/5-Big-Companies-That-Got-Knowledge-Management-Right

Context: A major international consulting organization wanted to document lessons learned from its major projects. This represented a first step toward becoming a learning organization. From a scan of what other similar companies were doing, their competitive intelligence led them to select the implementation of an after action review (AAR) in the form of a project post mortem. The AAR was a new procedure and it was initially piloted with a group of experienced consultants. Project managers who became experienced with the post mortem were subsequently asked to become resource people for those willing to learn and try it out. A new role of knowledge journalist was created in order to have a neutral, objective person who had not been a member of the original project team who could facilitate the post mortem process and capture the key learning outcomes from the project. Finally, the post mortem was added as an additional step to be completed by all project managers before they could officially check off that a project has been deemed formally completed.

Knowledge Processing Steps

1. Knowledge capture/creation/contribution An after-action review process is created within the organization such that at the end of each project, a meeting is held to have project team members contribute ideas as to what could have been improved.

2. Knowledge filtering/selection During the meeting, the facilitator helps establish criteria for lessons learned such as was it a factor beyond the control of team members (in which case nothing much can be done in the future to mitigate against this event). Project team members must reach a consensus on the criteria that will be used to decide which lessons learned will be documented and why.

3. Knowledge codification The meeting notes are transcribed and the KM team (including the knowledge journalist) along with the project team agrees on how the lessons learned will be written up (e.g., format, length, classification tags for future retrieval).

4. Knowledge refinement The KM team then improves upon the original text of the lessons learned (e.g., sanitizing or removing information that can identify the project and/or the people involved, abstracting so that the lessons to be learned are more generalized and therefore applicable to more than one specific context).

5. Knowledge sharing The existence of the lessons learned are publicized and made available to others (may be organization-wide, may be to specific targeted groups).

6. Knowledge access The lessons learned are stored in a database with adequate metadata or tags that will enable easy access and retrieval (e.g., tagging by the type of lesson such as “poor team communication,” by date, by type of project and other meaningful tags).

7. Knowledge learning Some of the lessons learned are incorporated into an employee orientation session and others into a project management-training course. In this way, the material is used to enable role playing and to provide themes for group discussion. An example would be a lessons learned that addressed attitudes that were not compatible for good teamwork. Another project team may decide to use some of the documented lessons learned for storytelling sessions where participants are asked to take on the perspective of another team member. In this way, the team members acquire some pseudo experience in “walking in someone else’s shoes,” which should afford them a different view on the events that occurred.

8. Knowledge application A project manager embarking on a new project calls up the lessons learned from similar projects from the organization’s lessons learned database. A quick scan of the sorts of things that went wrong in the past help the manager to prepare a risk management and contingency plan for these known challenges. At best, the same mistakes will not be repeated (which is not to say that human creativity being what it is, new ones will not arise!)

9. Knowledge evaluation A few people in the organization access the same learned lesson but find that the lesson is neither quite relevant nor valid in their particular contexts. They contact the KM team to have additional tags added to this documented lesson—tags that indicate the specific situations in which this is a valid lesson as well as the specific conditions under which the lesson is not to be applied (an example may be subsidiaries where the workforce is represented by a union and other subsidiaries who are not unionized).

10. Knowledge reuse/divestment The KM team performs its annual cleanup of the lessons learned database and finds that some can be replaced by newer and more comprehensive lessons. A few lessons are no longer relevant due to changes in the organization, changes in the business environment, or both (e.g., technology issues with an older version of software that are now moot with the newer version being used).

Extracted from Dalkir (2017) pg.60

Interviewee 37 (name coded in order to protect anonymity) works in a large government department and has been responsible for the implementation of knowledge management in the past five years. His own area of expertise lies in project management—he has over twenty years’ experience managing large-scale (over $10 million) infrastructure projects that typically required on average ten years to complete. One of the major catalysts for implementing KM was the lack of a good handover process—“the passing of the baton” when one project manager (PM) left and another took his or her place. Some turnover was reasonable in such long-term and complex projects. The trouble was that while each PM had the necessary training and skills, there was often little time to overlap with the incumbent PM in order to get rapidly up to speed on the specifics of that particular project.

The purpose of the structured knowledge elicitation interviews with senior PMs was to identify the types of tools and techniques they used to ensure that there was solid continuity in the management of these large infrastructure projects. Some PMs were scrupulous and disciplined and kept detailed records (primarily paper-based) while others found ways of embedding the knowledge about the project within the project itself (primarily digital annotations). The departmental KM team had recently introduced facilitators to carry out project debriefs and KM journalists to convert paper narratives into digital annotations, and they were in the process of setting up videotaping sessions to accommodate those PMs who were more comfortable with verbal rather than textual communications.

An excerpt of the interview with PM #37 follows:

Q:

How many project handovers have you been involved with to date? (an icebreaker question to help the interviewee feel comfortable and to begin talking)

A:

Over 20 at least—it seems to be getting worse actually—when I first joined the department as a PM we were careerists—we made sure to hang around until the job got done—not like these younger mavericks—jumping from one project to another—even jumping ship and going to work for another department! (subject getting off topic—starting to get a few things off his chest—prepare to cut in with next question)

Q:

What were some of the hardest challenges you faced in doing a handover?

A:

The stuff you can’t write down! I mean everyone spouts the same stuff—budget overrun, risk assessment figures off, and on and on and on. … the real stuff—we all know it in our gut but ****ed if I'm signing my name to it! (he has quickly started discussing tacit knowledge to be transferred during a handover and his lack of comfort in documenting this in any way—the best way to dig deeper without increasing his level of discomfort is to reassure re. anonymity of interview at this point and ask for an example in order to elicit substantive knowledge)

Q:

Absolutely—it is certainly not the place to start assigning blame or signing names to statements—and yet, as you say, this is the content that is important for the next PM to know. What would be an example?

A:

Well … in one infamous case … the team just dissolved … everyone went their own merry way … and the supervisor was so concerned about not losing face with the PM that he just waited too long before saying anything … the disasters just snowballed from there. … (at this point, true tacit knowledge is beginning to surface and this part is particularly important to document as the type of PM handover knowledge to capture—next, we need to know how it was handed over)

Q:

How did you manage to talk about this situation with the incoming PM?

A:

I shared my hard-earned wisdom and grey hairs with him! (Laughing)—I told him to forgot about “no news is good news”—no news is unacceptable—don’t wait for the formal briefings—keep your nose in it at all times—talk to everyone—walk around—get a feel for the morale and ask questions—just keep asking everyone the same question and you call the shots—get them in for a meeting the minute you sense there that something is off. … (interviewee is not in full-blown tacit mode—a number of terms will need to be pinned down in later follow-up interviews—need to capture good memorable sounds bites such as “no news is disastrous news!!” and define feelings such as “feel the morale” and “get a sense that something is off”—next in the interview template is a set of questions to assess how open the person is to new methods of doing handovers, e.g., videotaping)

Q:

Sounds like the sorts of things that have to be learned the hard way—what is the best way of getting the new PMs up to speed? Do you prefer to leave them some documentation or to meet with them face-to-face? How about this new initiative of videotaping PMs and leaving the clips on the intranet? (up to this point in the interview, the subject was very relaxed, intent, and engaged, and appeared to be very comfortable; upon hearing this question, his level of agitation increased—he leaned forward, appeared to scowl)

A:

Those oddballs—listen some people have too much free time on their hands—this isn’t the place for paparazzi—we are serious folks and we don’t need a bunch of tekkies pestering us— they don’t know what we do—all I need is a good heart to heart to put the fear of … to get my points across—that’s it that’s all—we don’t need anything fancy here. … (definitely not open to new ways of transferring this knowledge)

Q:

Of course the best way is to meet face to face—but do you have the time to go over everything? You must have to refer to some documentation as the projects span so many years.

A:

Well yeah—I also give them my notes and all that—they can sift through and find out about all the details—but the real stuff is what I need to say to them—and that won’t be shown on YouTube any time soon!!!

Extracted from Dalkir (2017) pg.111

More often than not, KM practitioners find themselves facing an organization that is convinced they need KM but cannot say why. In one large business unit, the stakeholders repeatedly insisted that knowledge sharing was blocked and no one knew whom to turn to for expert advice. They were convinced that “KM issues” were preventing them from carrying out one of the major mandates that was to assess the environmental health of a particularly sensitive area. Upon conducting an audit, the results quickly aggregated into one very strong theme: that of information management. Most respondents felt that they were great at sharing knowledge but they just could not get their hands on the data and information they needed. Some data sets were found to be over fifty years old but also still critically needed to do trend analyses—and these old data sets were on a medium that no one had a reader for. One was eventually tracked down in an archive and the data was transferred to more modern media for preservation. A second data set was sitting in cardboard boxes because the scientist in charge of the project had retired. Actually, the boxes were originally in the scientist’s basement and his family contacted the company when he passed away, asking if they would like the boxes. The only drawback: the key needed to decode the data was nowhere to be found. A Library and Information Studies intern had developed the key as a classification and finding aid fifteen years earlier and no one had thought to make a backup of the key.

The knowledge audit results showed problems existed at the information access, preservation, and retrieval levels. Much like the old adage that one should “learn to walk before running a marathon,” this particular organization did not have a good sense of where the immediate needs lay. KM was relegated to a more long-term strategy recommendation and the action plan addressed more pressing information management concerns, which will in turn be needed to provide a solid infrastructure for knowledge management.

Extracted from Dalkir (2017) pg. 295

The knowledge audit and gap analysis phases of the KM strategy will help determine what the KM efforts should focus on within a given organization. While there are some high-level goals, such as efficiency or innovation, and some generic KM initiatives, such as implementing communities of practice or an expertise location system, each strategy will necessarily be unique. Every organizational context is different, so a “one size fits all” approach cannot work for a KM strategy. The audit or diagnostic phase ensures that the core characteristics of the organization are well understood and taken into account in proposing KM recommendations.

For example, in a public utility company, an extensive audit revealed that while explicit knowledge was formally shared quite extensively, there were few if any opportunities to meet to share knowledge informally. As a result, the lessons learned were edited so as to not cause any undue alarm, and by the time these reached the eyes of the CEO, the reports all read a bit like “something terrible happened, we were not 100 percent prepared, we dealt with it, all is now back to normal.” In fact, the knowledge audit revealed that this organization worked exceedingly efficiently and effectively under normal operational conditions. In the context of an emergency, however, work teams no longer knew their roles, they could not collaborate in more dynamic, tacit ways, preferring to keep to “the book” or manuals and rules, and they often failed in carrying out their critical duties.

For this particular organization, an emphasis on tacit knowledge and informal ways of sharing this knowledge became a critical focus for the KM strategy. Employees were encouraged to meet and discuss project post mortems with peers before reporting more formally up the hierarchical levels of authority. Additional recommendations included short term training of teams so that they could better perform in crisis situations through role playing and simulations in the short term, beginning the journey to cultural change by encouraging employees to send anonymous emails directly to the CEO, and rewarding employees for taking risks.

Another organization, an international aid outfit, revealed quite a different focus for KM during the course of their KM audit. This organization had branches around the world and operated in a highly complex environment: multiple locations, multiple languages, and multiple stakeholders, including funding agencies, partners in the various countries, and a high turnover rate due to two-year mandates. The audit revealed that tacit knowledge was being well shared throughout the organization, primarily through informal contacts using Skype and occasional face-to-face meetings. A number of bottom-up or grassroots communities of practice had emerged on their own, further linking geographically dispersed workers around a common mandate theme. In fact, this organization’s evolution in KM terms mimicked that of the World Bank, which created over 100 thematic communities to better harness their expertise that they provided to third world countries.

The gap analysis showed that the critical KM missing in this organizational context was the formal capture and sharing of explicit knowledge. Meetings were often held without an agenda, attendees changed at the last minute, and the way of proceeding was quite chaotic to an outsider: the topics to be addressed were arbitrarily changed, priorities were suddenly announced, and discussions were very difficult to follow. Attendees often interrupted one another, there was no set time for the meeting to end, there was no one to chair or to take down the minutes. Employees explained that this was the “culture” of the place—where everyone was involved in everything and every decision was made by consensus. There was little systematic documentation of meeting results, very little reflection on completed projects, and what documentation did exist was often very difficult to track down. Reports were written for each project but the reports varied in structure and content as each was dedicated to an external audience. KM seemed to be invoked in order to fulfill very specific demands of external parties but rarely was the KM lens turned inward.

As a result, the organization had to focus KM efforts on the knowledge capture and codification side of things, to identify the types of knowledge they have and need to have, and how to render these more visible and therefore easier to access by others.

Extracted from Dalkir (2017) pg. 305

A large mining company was examining its predictive maintenance procedures. This form of maintenance relies upon scheduled parts changes and “tune-ups” that take place according to expected useful life spans of the various types of equipment used, as opposed to waiting until something fails and brings the whole operation to a costly stop. In the case of one particular type of valve used in the refinery, technological advances had resulted in the use of a new type of polymer that was just now available. The question was: could this new polymer be used to cap the valves? Could it withstand the high temperatures that the valve would be subjected to during operations? At first, this seemed to be an easy, almost trivial question. Engineers began looking for the equipment specification documents. These proved, however, more elusive than expected. When, after about six weeks, they were found, they were located not within the company but within the archives of a design firm that had been subcontracted to design that particular piece of equipment—roughly twenty-five years earlier. Unfortunately, nothing in the specifications helped answer the question. The use of a polymer would represent a significant cost savings but the team was reluctant to go ahead. The conventional wisdom said that “a slow dime is worth more than a fast penny,” in other words, we may save a few pennies now but if the polymer melts under the high temperatures, the whole refinery will have to be shut down, costing many, many, more dollars to the company. Finally, after about six months of searching, the HR department of the design company tracked down the original design engineer who had worked on the equipment. He was happily retired and playing golf in Florida but was still receiving a pension and that is how they found an address for him. Luckily for the mining company, this engineer was a bit of a pack rat and/or nostalgic: he had kept his original handdrawn specifications with his own annotations. It was by checking these annotations that he was able to confidently answer “no—the polymer would not be a safe alternative—metal should continue to be used.” The next question posed by the mining team was: now, where can we write down this valuable information down? Where is the company “book” where they can look this up when the next five-year cycle comes up?

Extracted from Dalkir (2017) pg. 349

Transport Canada was a pioneer in the identification of critical knowledge that was at risk of being lost due to imminent retirements. They undertook a comprehensive pilot study in order to develop a toolkit for knowledge transfer for succession planning. Their initial questions were how to:

1. Identify critical human resources.

• Whom do others turn to in a crisis?

• Who are the subject matter experts (SMEs)?

• Who has long-term corporate memory?

• Who is doing a one-of-a-kind job?

• Who has a unique set of skills/knowledge?

• Who carries the ball on major projects?

2. Maximize retention.

3. Retain their critical knowledge.

4. Facilitate the transfer of this critical knowledge.

5. Expose the right people to that critical knowledge.

Some key lessons learned (Avoiding Knowledge Collapse—Proactive Solutions for Regulatory/Inspection Organizations. Government of Canada, Regulatory Inspection Secretariat, Transport Canada, March 2003) included:

• Buy in from senior management.

• Raise awareness, generate enthusiasm.

• Managers should take ownership of the process of KT.

• Human Resources (HR) personnel provide significant and sustained support to managers and SMEs through entire KT and succession planning process.

• Integrate KT and succession planning into the ongoing business planning process of the department.

Good practices that emerged included:

• Analyze your organization’s demographics to identify your vulnerabilities (where will the loss of personnel most seriously threaten the execution of your mandate?).

• Secure senior management support and funding (if possible, name a champion).

• Identify critical knowledge holders.

• Approach them to discuss what would motivate them to stay on.

• Prepare succession and knowledge transfer plans.

• To facilitate mentoring and one-on-one knowledge transfer; bring in a replacement before the SME retires whenever possible.

• Extract critical knowledge held by these experts, customizing your methods to fit your subjects.

• Work with IM/IT personnel and librarians in your department to choose your codification methods, information management software and retrieval tools.

• Encourage/facilitate strong CoPs to help disseminate tacit knowledge into the organization.

• Reward knowledge sharing.

• Involve retiring SMEs in the writing of their job descriptions and the selection of successors wherever possible.

• Provide extensive hands-on support to individual managers and management team.

The Transport Canada knowledge transfer toolkit consists of the following key components:

1. Stakeholder maps identified internal and external interactions with stakeholders and partners—personal and professional networks of SMEs.

2. Knowledge maps—conceptual representation of job tasks, key resources, how to obtain and reuse knowledge, summary of SME expertise

3. Task support systems—online tools to support specific processes and information needed to complete specific tasks—glossaries, demos, templates, references, resource lists, case studies, simulations, Computer Based Training (CBT) modules

4. Dashboard—single-stop shop, customized work tools to hold knowledge maps, stakeholder maps, task support, and other information such as answers to Frequently Asked Questions (FAQs), relevant legislation and regulations, calendar of events, scholarly articles, recent news, and useful tools

Transport Canada found that it was necessary to address both explicit and tacit knowledge and found that Information Technology (IT) worked best for explicit knowledge while Communities of Practice (CoPs) worked best for tacit knowledge. Other best practices included:

• Hire successors before incumbent leaves, if possible, to establish mentoring relationship.

• Include Knowledge Transfer (KT) in Results-based Management and Accountability Framework (RMAF).

• Document lessons learned, best practices, decisions made—include as much context as possible (include the whys, the justification, why alternatives were discarded).

• Focus on intellectual capital.

• Be proactive—don’t wait until key people retire.

• Promote intergenerational knowledge sharing (under 35, 35–45, and over 45) through communities of practice.

Extracted from Dalkir (2017) pg. 383

SOM (http://www.som.com) is a leading architecture, urban design, and planning, engineering, and interior architecture firm in the United States. Founded in 1936; SOM has completed more than 10,000 projects in over fifty countries. Most architectural and engineering firms operate in an environment filled with guidelines and regulations derived from best practices and standards that are often disseminated through the company’s intranet. SOM also has CAD (computer-aided design) libraries, drafting standards, employee directories, and social networks—in other words, bits and pieces of KM. So why did they need a KM model in addition to these piecemeal implementations? The model was necessary in order to have a deeper understanding of how KM contributes to the goals of the company. In this type of industry, as with many others, tacit knowledge consists of the creative and innovative knowledge—pretty much the polar opposite of the well-documented explicit knowledge such as guidelines and standards. A KM model helps SOM to harness both types of knowledge in order to perform efficiently, effectively, and competitively. A comprehensive easy-to-apply KM model can help decision makers and all employees. With it they can make the best use of tacit and explicit knowledge and apply processes to transform knowledge from one form to the other. A KM model, together with the KM process cycle discussed in the previous chapter, can be used by SOM as a checklist—to ensure that all key KM components have been addressed—not just addressed well but also addressed coherently, since KM components are highly interdependent and integrated with one another. In the absence of a model, the firm can continue implementing KM pieces in an ad hoc fashion but will rarely succeed in bringing the pieces together in order to better attain company goals and objectives.

A good KM model is a framework that positions goals, procedures, and enablers to help the firm capitalize on their valuable knowledge assets. With a KM model, everyone can understand what KM is expected to do for SOM, why they should share their knowledge, how they should share, and how they can assess the costs and benefits that result. The KM model will help ensure that everyone shares the same understanding of the role of KM throughout their career —from their employee orientation as new hires to their exit interview and knowledge handover at the end of their career. The SOM KM framework helps ensure that valuable knowledge is not lost when senior employees leave, that information and knowledge flows among departments, that work is not duplicated, and that errors are minimized. The company is better able to centrally gather, measure, and analyze how well they have met their goals. Finally, the KM model helps SOM leadership to better shape and support the firm’s business strategy. Each group within SOM needs to operate on this common KM framework in order to promote individual, departmental, and organizational success.

Extracted from Dalkir (2017) pg. 76

The World Bank has distinguished itself as a KM leader due to the swiftness with which it was able to transform itself into the “knowledge bank” within only four years (Pommier 2007). One of the major concerns that drove this transformation was being able to answer queries faster and better—by drawing upon the collective knowledge of the Bank. In addition, the Bank faced the challenges of multiple databases and repositories, different IT groups and tools, inconsistent information, and poor documentation and control. The World Bank thus developed their KM mission statement: to develop a world-class repository of their development experience and their cumulative knowledge.

One of the major success factors behind this rapid transformation was due to an innovative technique, storytelling, which just happened to be developed by one of their own employees, their KM champion, Stephen Denning. In fact, Denning came up with the idea of a springboard story based on his years of frustration at trying to “explain” KM and why they needed it to senior managers at the Bank. His idea was a story that would help the audience—managers and decision makers—use the story as a springboard to leap to an intuitive understanding of KM.

Here is the story Denning used:

A health care worker in Zambia needed an antimalarial preparation using only materials he had on hand. He sent a query via the World Bank’s website and he had a workable solution within 48 hours. He was able to harness the collective experience, expertise, and know-how of the World Bank to come up with the best possible answer in a timely way.

The World Bank KM program was off and running. The World Bank transformed itself into a knowledge bank through its strategic goal of putting knowledge at the core of the World Bank’s work. The elements of this strategy included:

1. People: A focus on knowledge workers and connecting them via knowledge communities (communities of practice)

2. Culture: Shifting the culture from an individualistic focus to a team and knowledge-sharing culture

3. Accountability: Clear roles and responsibilities established for knowledge managers and coordinators

4. Technology: System to capture, organize, and disseminate knowledge to all stakeholders of the Bank

5. Process: Implement a series of small steps or quick hits and continually promoted awareness and buy-in through “relentless repetition”

The World Bank has implemented corporate portals, knowledge repositories (including image banks), a library of learning objects, video on demand and web casting content, a live database, an expertise location system, communities of practice (called”thematic groups”), after action reviews, peer learning, and field visits and site tours to enhance learning. The major focus was on the thematic communities to restructure the Bank. Today, there are about 123 thematic groups or communities of practice overseeing key areas such as poverty, community development, and rural information technology infrastructures.

A small KM Board comprised of five people oversees all communities of practice. This core KM team has overall coordination and facilitation responsibilities. They identify any synergies or redundancies among communities, they identify opportunities for cross-community knowledge sharing, they provide the link to organizational learning and corporate memory systems, and they assess the value of the outputs of each of the communities. A KM council is the governance body that provides overall KM policy formulation and has KM responsibility at the corporate level. In addition, knowledge sharing is one of the four key behaviors that are evaluated in performance evaluations. Usage and application of knowledge are behaviors that are rewarded—not numbers of hits or postings on the intranet site. This is the major contribution required from the Human Resources department. The World Bank spent roughly 3 percent of its total administrative budget on KM. Of this, less than 10 percent was on technology (web, telephone, email, and videoconferencing) and 2 percent was for the operating costs of the central KM unit. The rest went to financing the thematic groups and the knowledge support office (KSO).

Operational managers in the communities and the regions are responsible for implementing KM. Measurement, accountability, and budgets reside within the regions. Two major forms of support are required from senior managers: that community of practice leaders spend approximately 25 percent of their time on knowledge management activities and that communities are supported by KSOs that are best described as knowledge help desks.

The World Bank has established cost-effective, global connectivity with developing countries to facilitate collaboration between offices, extend operational and administrative information to staff at any location, and reduce the cost of doing business. For example, the Bank provides an electronic venue for dialogue and knowledge sharing among members of the development community. The Development Gateway is an Internet portal that supports knowledge sharing and interactions to address the digital divide and poverty. More than 13,000 staff in 80 countries are now linked together with high speed and high quality so that everyone has access to the same work tools and information. With the knowledge management system in place, the World Bank is able to provide not only new services but higher quality services.

A primary indication that the World Bank made effective use of its knowledge is the culture of organizational innovation and entrepreneurialism that was fostered partly as a result of knowledge management and sharing initiatives. Some of the key concerns of the World Bank, such as timeliness or speed of creation of new knowledge and access to knowledge-sharing methods and innovation, were also the focus of measurements undertaken. While it may be impossible to determine the contribution of KM with complete accuracy, as is the case with most intangibles, it is possible to talk about the contributing role of KM. In evaluating KM, a holistic approach was used in order to take into account human and social as well as technological critical success factors.

In 2000, the World Bank was found by the American Productivity and Quality Centre (APQC) to be one of the five global best practice leaders. By 2001, the World Bank received fourth place in the Most Admired Knowledge Enterprises Award and was recognized again in 2002, 2003, and 2004. The organizations in this study are recognized for their world-class efforts to managing knowledge that leads to superior performance. Knowledge sharing became a way of doing business at the Bank.

Extracted from Dalkir (2017) pg. 289