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Selasa, 05 Juni 2012

knowledge management tool


Knowledge management

The management of knowledge of the latest management concepts, which developed the literature that related to it on the quantity and quality .The past years have witnessed a growing interest by the business sector to adopt the concept of knowledge management. What is the meaning of the knowledge of management?
Knowledge management is the processes that help organizations to generate and access to knowledge, choice, organization, use and dissemination, and transfer important information and expertise possessed by the Organization, which is necessary for administrative activities such as making different decisions, solve problems, learning, and strategic planning.
What is knowledge?
Class Polanyi (1966) knowledge of two basic branches:
1. Tacit knowledge (tacit)
2. Virtual knowledge (explicit)
Both the Nonaka and Takeuchi (1995) that the intangible assets as ethics, mental photo for the organization intuition, metaphors, and insights into the most important assets that should take care and attention because it is the added value to the daily operations of the organization.

1.    Tacit knowledge
Related to tacit knowledge skills (Skills) Know-How, which is in fact found at the heart and mind of each individual and which are not easily moved or transferred to others.
 These may be technical or cognitive knowledge.

2.    Virtual knowledge

The information relates to virtual information are stored in the archives of the organization, including (manuals related to Politics and procedures, documents, standards of operation and operating) and mostly that individuals within the organization can access and use and can be shared with all staff through seminars, meetings, books.

Polanyi made a distinction between two types of knowledge when he said "we know more than we can say" "We can know more than we can tell”
In an explicit reference of course to difficult to put the state of knowledge implicit in the words spoken.
Supplement to the issue of knowledge management. Knowledge is the product of multiple items, and most important of which:
1. Information
2. Data
3. Capacities
4. Trends
1. Data
Data set of objective facts that are not  interrelated are highlighted and delivered without the provisions of the initial advance. becomes Data  information when it is categorized, fix it, analyzed and placed in a clear framework and concept of the recipient.

2. Information
Information is in fact data gives credibility and are submitted for the specific purpose. The information is developed and promoted to the position of knowledge when it used to do or For the purpose of comparison and evaluate the results prior and specific, or for the purpose of communication, or participate in a dialogue or discussion. Information is data showing the framework and content of clear and specific and that does not could be used to make a decision. The information can be provided in various forms, including written form, image, or a conversation with another party.

3. Capacities
Knowledge next to the information you need for the capacity to make information from the data obtained to be converted into information you can use and benefit. God has given some individuals the ability to think creatively and the ability to analyze and interpret information and then act based on what is available from the information. If it is not available to the individual’s capabilities and core competencies to deal with the information then we can say that one of the main pillars of knowledge is missing.

4. Trends
Above all this that knowledge has strong relationship with trends. It is in fact the trends that drive people to the desire of thinking, analysis and action. Therefore, trends consider the main element to manage of knowledge and that by stimulating the curiosity of individuals, and find the desire and motivation them for creativity. This sure is lacking many of the organizations???
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Great Leaders Have Clarity & Self-Knowledge to Bring their People to the Right Path


Leaders are different from managers although sometimes both traits are present in one person. A manager makes sure that the company systems and employees are working, the data is converted into information, and the information is given to those who will make decisions about them within a framework of time and a budget. He or she is focused on administratively or personally doing tasks properly. He or she also solves problems to keep these tasks going properly. A leader, on the other hand, focuses on guiding the organization and people to do the right things.
Clarity and self-knowledge are needed for a leader to direct and motivate people to the right path. Self knowledge includes the talents, skills, strengths and weaknesses of the leader and his or her people, including the managers. These are all used to efficiently and cost-effectively attain the vision, mission, desires and plans of the organization or project. Clarity is needed for the desires and plans to be carried out in the way it needs to be done. They work together so that there is no confusion, and the strengths and weaknesses are used or made up for by those who are skilled at it.
The need to know these things is further emphasized when the leader is stretched to do more than the plan to get it to work, and when changes are happening within the company and to the economy. The most important skill that is used by the leader is communication. Good communication gets the message to the right people and makes them want to do what is needed in a proper manner plus it makes them feel good. Bad communication makes people feel attacked or used and not appreciated so the results or feelings are usually not good either.
The skills of clarity and communication can be learned but self-knowledge is something you seek for yourself because many of the items here are not all learned from school or experience. Some are innate talents that were never given the opportunity to come out before. Different or extreme situations can show a person a different side to himself or herself. Some leaders are better at extreme situations than others. The great leaders can handle people, situations, and money all at the same time while others can only handle some. The important thing is that what needs to be handled is done properly.
Doing things properly includes making money and using it well. Whether the leader is handling a business or an organization like a foundation or charity, money is used to keep the business running, for the benefit of a charity, and for profit. The proper use of money includes using it to make more, to produce the desired result, and for the benefit of the charity involved.

Is it easier to be a great leader now? Do you know what talents to develop to become a better one? You can do it!
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Thrust of Business Intelligence: A Primer


The field of business intelligence (BI) deals with ways to muster information in order to support the objectives of an organization in a fluid environment. Although the term “business intelligence” was introduced in 1958, the moniker was hardly more than a dreamy notion at the time.

In the absence of digital tools, the concept had scant impact on the practice of commerce. To fulfill its potential, the domain would have to await the advent of computer systems.



Rise of Digital Platforms

The mainframe computer began to make inroads in the business environment during the 1960s. Even so, the hardware was too expensive and the software too primitive to make much of a dent in any but a few isolated corners of commerce.

A case in point was the record of payments received by an insurance firm from millions of customers. Another sample was the coordination of bookings by an airline through a network offices spread around the globe.

If the computer were to spread its wings, the hardware and software had to become a lot cheaper and suppler. In this light, a watershed was the advent of midsize machines during the 1970s.

Another wave of equipment burst forth during the following decade: the rise of the personal computer. The uptake of affordable machines throughout the organization led to the proliferation of digital systems for storing and analyzing data.

Yet, there was a big barrier standing in the way of further progress. The initial wave of equipment took the form of stand-alone machines. In the absence of electronic links, the isolated rigs could only work on a particular task in piecemeal fashion.

Islands of Computation


At the low end of the product line, a desktop computer could be used for basic functions in the office, factory or studio. An example lay in word processing or spreadsheet analysis.

At the high end of the range, beefy devices known as workstations were deployed in a number of additional niches. A case in point was product design within an engineering department or scientific analysis in a research lab.

On the other hand, the cost of hardware and the dearth of software held back the digital revolution. To bring up an example, the practitioners in business intelligence had to rely for the most part on manual schemes for monitoring the marketplace, spotting key trends, and so on.

Even simple tasks had to be mediated at every step by human minders. An example was the offline analysis of sales figures on a desktop machine, after the data had been copied onto a diskette from the archives of a corporate mainframe. Another sample was the manual extraction of salient statistics from a paper document purchased from an external vendor of market research.

If the field of business intelligence were to flourish, then a fresh breakthrough would be needed. To this end, a seminal advance was the release of the World Wide Web in 1991.

Rollout of the Information Highway


The advent of the Web, along with graphic interfaces for browsing materials, set the stage for the torrid growth of the information highway. As a result, the Internet entered the mainstream of business as well as the society at large. The digital network would come to serve as the groundwork for personal interaction as well as commercial activity.

The attractions of cyberspace led to the mass linkup of offices, factories and other sites to the global infobahn. Amid the groundswell of connectivity, access to the Net became a hallmark of modern culture at home, school and work.

The power of digital platforms burgeoned during the 1990s even as their cost plummeted. Against this backdrop, the practitioners of business intelligence began to rely more heavily on virtual tools to support their activities.

On one hand, the software aids designed for business applications were still patchy and clunky. For this reason, computer systems could do little more than access raw data in online warehouses, perform statistical analysis in offline mode, and plot the results on pretty charts.

As an example, a digital system could be used to obtain sales data from internal storage or download market reports from external sites. Yet, the fetched items had to be studied and evaluated for the most part by human analysts.

By the dawn of the millennium, the Internet turned into a standard medium for communication among individuals as well as organizations. Thanks to the meshwork of connectivity, the stage was set for the next wave of business applications.

Another trend at the time was the rapid spread of database systems based on open source software. As a result, a data warehouse was no longer just a luxury for giant corporations but a necessity for myriads of smaller firms.

Digital Tools in the Mainstream of Commerce


The upgrowth of databases, along with the tools to manipulate the contents, led to a couple of notable changes in the field of BI. In the past, the domain had been the backyard of a small band of mavericks in the consulting industry. But now the tiny squad ballooned into a vast army as hordes of newcomers swarmed into the field.

Another outcome was the development of nifty tools for analyzing data. Prior to the upsurge of digital platforms, the practitioners in BI used to claim that keeping tabs on trends in the marketplace was the crux of their work.

However, the task of environmental scanning took a back seat as the years wore on. Thanks to the profusion of hardware platforms as well as software tools, the manipulation of internal data moved to center stage.

In this milieu, the workers in BI turned their focus inward. With increasing frequency, monitoring the environment was an elusive function that was given short shrift in practice.

By the dawn of the 21st century, any mention of external scanning was largely an empty gesture during a zealous bid to secure a consulting contract. If the concept was trotted for a particular project, the real reason was to titillate any senior executives who happened to stop by during a sales presentation.

Roundup of Business Intelligence

During its infancy, the field of business intelligence was the preserve of a small band of practitioners who dealt almost exclusively with external trends in the marketplace. Given the dearth of digital tools, however, business intelligence was scarcely more than a feeble afterthought within the larger realm of marketing strategy.

On the other hand, the outward bent was turned on its head amid the flowering of digital platforms throughout the enterprise during the 1990s and beyond. The groundswell of internal applications was driven by low-cost hardware as well as open source software. The platforms in the latter category spanned the gamut from online media and database packages to operating systems and analytic tools.

And so it came to pass that the realm of BI flourished in terms of technical capabilities as well as fielded applications. The community of practitioners burgeoned, along with the ensemble of customers and the intake of revenues for services rendered.

In contrast to its original purview, however, the field gradually turned inward to focus on internal activities rather than external events. By the turn of the millennium, the practice of business intelligence became more or less synonymous with the management of information within the enterprise.
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What is Risk


What is Risk

Project Risk Management
Risk is an inherent factor of virtually every human endeavor. Human beings naturally consider risk and reward as part of the decision-making process. The consideration is not always formalized and may occur at a subconscious level.
The Concept of Risk
Risk is all around us; it plays a part in virtually everything that we do. It can be very difficult to predict and assess risky outcomes accurately.
‘Risk’ as a word originates from the French word Risk meaning ‘daring’.
Risk is a measure of the probability and consequence of not achieving a specific project goal. It therefore depends on both the likelihood (probability) of an event occurring and on the consequences (impact) if that event should it occur. Risk is therefore a function of the event, the probability of it occurring and the effect if it occurs. This relationship is sometimes known as the first level equation for risk and can be expressed as
Risk = f(event, uncertainty, consequences)
It is prudent to consider risk in terms of the second level equation for risk:
Risk = f(event, hazard, safeguard)
In this consideration, something – or the lack of something – causes a risky situation. The source of danger is a hazard and the mitigation or defense against the hazard is a safeguard .
Risk acts like a barrier to the development of effective strategy. Risks are evaluated in some way, and if the risk is perceived as being greater than some minimum threshold level, the organization shies away from encountering it; proceeding is too risky. However, effective risk management allows the risk to be controlled to such an extent that there is no longer any need to shy away from it, so that the risky application is able to be pursued ahead of the competition.
The impact of a risk and the probability of it occurring can be considered in terms of the exposure of the organization and the organization’s sensitivity to a particular risk profile. Exposure is a measure of the vulnerability of parts of the organization to risk impacts. Exposure arises when any asset or other source of value for the organization is affected by changes in key underlying variables resulting from the occurrence of a risk event. An organization is exposed to risk when a realized changes in a variable within a given time scale will result in a change in one or more of its key performance indicators. Exposure is therefore a measure of the vulnerability of an organization to stated risks. An organization’s sensitivity to risk is a function of three elements. These are the significance (or severity) of the enterprise’s exposures to the realization of different events (that is, sensitivity to such items as changes in competition, weather conditions, etc), the likelihood of the different events occurring, and the firm’s ability to manage the implications of those different possible events should they occur. Sensitivity is therefore a measure of likelihood and impact, modified to some extent by the ability of the organization to manage these variables.
Risk management is not only about competitor advantage in terms of approaching ventures that contain high risk levels. The organization that is able to develop an effective risk management program, within the limits of its own sensitivity and degree of exposure, is the one that can take good commercial decisions. Having mastered the risks that put the others off, the successful risk management organization is in a much better position to take advantage of risky ventures in the marketplace.
It is possible to say that risk is the distribution of possible outcomes in a firm’s performance over a given time horizon that are due to changes in key underlying variables.
The use of risks to create value is changing. The profile of risk management and the risks defined by organizations in decision making are also changing. As more risks come within the decision-making boundaries of an organization, the risk management system becomes more sophisticated and refined.
So risk is inevitable and can be good. There is therefore a need for some effective way of managing this risk to make sure that is effectively addressed and used. It is always unclear what will happen in the future; and opportunities and threats can be forecast with different degrees of accuracy. However, in general terms, the decision maker acting under conditions of risk would be most concerned with the following questions:
• What can go wrong with the project?
• What possible outcomes do we face as a result of these risks?
• Where do these risks and consequent outcomes originate?
• Do we have any control over these risks and if so are we using it?
• Are the risks and consequent outcomes related to any extent?
• What is the degree of exposure of the organization to these risks?
• How sensitive is the organization to each degree of exposure?
• Do these risks affect the achievement of the overall strategic objectives of the organization?
• What response options do we have?
• What contingencies or emergency responses are in place?
• Can we match the worst case scenario?
• If not which scenario reaches the limit of our response abilities?
• What is the potential reward associated with each risk?
• Are we prepared to accept a risk and corresponding outcome that is beyond our limits to absorb?
The Human Cognitive Process - Pattern Recognition and Attention
Decision making and risk are elements of the human cognitive process. People make decisions in relation to perceived rewards and risk. The decision-making process is largely dependent upon perceived rewards and risks. Perception of risk varies from person to person and in relation to the potential effects of the risk event. Most aspects of the human cognitive process make a subjective evaluation of risk.
Bounded Rationality
The approach to information processing is known as bounded rationality . It is based on the philosophy that a being will generally opt for rational behavior within constraints. Most cognitive processes will be based on reasoning, and therefore logical and rational outcomes, based on pattern recognition and learning will be naturally preferred to illogical and irrational ones.

Risk Forecasting and Analysis

Risk Forecasting and Prediction Momentum
Bounded rationality therefore uses knowledge of past events to assess a current risk in making a decision. This assumes that acceptable outcomes from the past will continue to be acceptable outcomes during the current evaluation process.
This is the concept of risk forecasting . In relation to risk forecasting, we can generally say that it is:
• based on experience. Experience gained in the past is used to analyze and forecast what might happen in the future.
• As much subjective as objective based.
• Possible to subject it to complex modeling as in chaos theory, although it is not restricted to complex mathematical modeling.
• An area that is perhaps best evaluated using a combination of modeling and subjective approaches.
• based on using data from past experience in order to allow extrapolation as a basis for predicting future trends.
In other words, what happened in the past and is happening in the present will continue in the future unless something happens to change it – known as prediction momentum.
In developing a forecast, a decision maker uses a two stage process. The decision maker infers what the future is like before the proposed action, and also infers what the future will be like after the proposed action. This is of course not an exact science. The future is uncertain, and the decision maker may make wrong assumptions and inferences. In addition, even in the most careful predictions, some unexpected mutation may affect the predictions.
Various forecasting techniques can be used and each has strengths and weaknesses.
Some important considerations are given below in relation to forecasting.

Accurate data.
Any forecasting technique is only as accurate as the data used in developing and operating it. Most organizations store formal records and most individuals retain relatively accurate records and memories of their own experiences. If the more accurate the data is, the more accurate the prediction.

Time limits.
Generally, the accuracy of any prediction model is a function of the time scale that is required. The longer the time scale, the more difficult it is to make accurate predictions. More and more variables and mutations come in to the equation as time continues.

Cost.
Detailed and complex forecasting is a labor-intensive Endeavour. It can be very expensive to provide all the resources that are required. If fewer resources are provided, the overall accuracy of the prediction could be reduced.

Vision.
Intuition and bias are powerful influences on any forecasting application.
It can be very difficult to erase them from the equation completely. Vision is an important attribute.

Intuition and Bias
Intuition and bias are major determinants in how successful forecasting models are in both application and outcome. In most real applications, the decision maker looks at a prediction model and then makes a decision based on his or her intuitive reasoning.
Intuition is a combination of experience and extrapolations forward. It is an example of pooled interdependency within the cognitive process. By using experience, the decision maker can look at all the data and information that have been stored in his or her long-term memory, and also at the pattern recognition information that is arriving in relation to the current situation. He or she can then combine the two and project the situation forward to decide on the best course of action. The extrapolation from known to unknown often includes large areas where definite information is lacking. Intuition can be both individual and organizational. Companies store and use collective experience in much the same way as individuals.
Bias is the tendency for a person or group to misinterpret data or observations because of their own perceptions or outcome preferences. A marketing team may truly believe that their company’s product is better than it actually is because they have been committed to selling it for a long period of time.

Risk Handling
So risk is all around us and it is essential for the propagation of enterprise and innovation. There will always be an element of risk in any enterprise, and this characteristic is not going to go away. The key factor is to manage risk.
This is done by deciding what level of risk is acceptable and what level is not acceptable. Risk that is not acceptable is transferred or reduced in some way.
Once the residual risk is at an acceptable level, it is managed so as to ensure that it does not affect the performance of the project and/or of the organization as a whole.

Risk Assessment and Control
There are different types of risk. Risks also have different characteristics. People often assess these characteristics as part of the risk analysis process. While this assessment is often subjective, it can involve highly complex objective analysis. Total elimination of risk is rarely achieved and is often impossible. Therefore, the assessment process acts as a means of evaluating the risk that remains so that some kind of monitoring and control system can be set up. This concept forms the basic elements of a risk management system.
Risk management is a strategic approach. Risk assessment and control have to form a part of a long-term operational process. Risks have to be calculated and analyzed in advance and then monitored against performance to identify where risks are changing and how effectively they are being managed. There is a tactical element involved as well, since responses may depend on the specific nature of the occurrence. However, it is important to realize that a risk management strategy should be developed in detail for a project before the project actually starts, the strategy being implemented as early as possible in the life cycle of the project.
Risk assessment is part of the collective risk analysis process. Risk analysis involves the determination of the probability of individual risky events occurring, and also of establishing some measure of the potential consequences of each event occurring, together with some kind of monitoring and control system to assist with the management process. Risk handling is the process of dealing with risks. It is not sufficient to identify and analyze the risks; the risks have to be handled in some way in order to reduce the likelihood of individual events occurring. Risk feedback is an essential section in the process. Feedback is the process where the results of occurred risks are analyzed and any results and items for use in future strategies are fed back into the system. Risk analysis, handling and feedback are often referred to collectively as risk control.

Elements of Risk Assessment
Risk assessment is about identifying and assessing all potential risk areas within the project. It is probably the most difficult phase of the project risk management process. Risk has been defined previously as a combination of uncertainty and constraint. Constraints are generally difficult to remove, but it is important that they are recognized and understood.
The essence of project management is planning, forecasting, budgeting and estimating, which implies that very little in the project is certain. Thus, determining the uncertainty in a particular project could just about include every aspect of that project. This is highly impractical because the cost and time required to carry out such an assessment would be prohibitive; common sense must therefore be applied to ensure that the process of risk assessment is restricted to attempting to select only those areas of the project with the most severe constraints and the greatest uncertainty.
It is nevertheless important to remember that the process is in fact an iterative one and that risk assessment is only complete when the assessors and project manager are satisfied that all undetected risks are insignificant.
The assessment process allows the risk taker to develop a risk typology. This can be based on probability and impact or on safeguard and hazard. The impact is the severity of the effect on either the budget, the schedule to project completion, the quality of the work, or the safety of the project. Whether the severity of impact of the risk or the probability of the risk occurring at all is high or low is a matter for the judgment of the risk assessor and the project manager.

Elements of Risk Control
Risk control involves the thorough investigation of the entire project and will include reviewing the project’s plans, documents and contract to identify all possible areas where there may be uncertainty or ambiguity about what is proposed or the method through which objectives are to be achieved. The constraints inherent in the project must underpin all these investigations and should be considered. The performance of individual sections or activities where risks have been identified is then monitored to ensure that risk is being minimized and to gauge the magnitude of any changes in the risk status of the activity.
Risk control is particularly important in monitoring the evolution of risks.
Because risks change over time in terms of probability and impact, it is imperative that any such evolutions are monitored and controlled. In modern business, rabbits can grow into sharks if you don’t watch them carefully!
Risk Identification
Risk identification requires different approaches and considerations by different people within the project. Any person’s perception of risk depends on numerous factors, including:
• where the individual is in the organization;
• the power level of the individual;
• the immediate area of authority of the individual;
• the responsibilities of the individual.
The risk itself, as an occurrence or event, will have a source and an effect.
For any given event, there could be numerous potential sources and numerous different effects. Control requirements will vary depending on the critical of the risk element and on the relative power and importance of the activity as part of the greater whole.
Some risks are more controllable than others, in that people can make varying efforts to try to avert them. Some events can be prevented to some extent, such as avoiding car crashes by regularly maintaining a vehicle. Others, such as accidents caused by other drivers, are very difficult for an individual to prevent.

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Small Business Knowledge Management


Small businesses use knowledge management every day, perhaps without even realizing that they're following knowledge management processes that are much more formalized in many larger companies and corporations. Small business knowledge management is something that's largely been overlooked by software developers who cater to the bigger organizations and create programs that allow them to gather, organize, analyze and share business knowledge. But even without software programs designed specifically for small businesses, these smaller organizations can and should still use a process of knowledge management to maximize their business' potential.

Small businesses don't have the same amount of operating capital, and obviously can't spend the dollars on software and other business helpers that a huge multinational corporation can. But there are solutions out there for every size of business to help with knowledge management and those should be taken advantage of. A small company that follows a good process of gathering, storing, organizing, analyzing, sharing and leveraging knowledge has a much better chance of becoming a larger and highly successful business than one that doesn't take advantage of the valuable information it's faced with every day.

Small Business Knowledge Management is on the Upswing

Larger companies and corporations have only recently formalized the process of knowledge management as they've realized just how crucial it is to a successful enterprise. Top companies have always used it, but they might not have had a formal process for it or even had a term for it. But today, it's clear to most companies that information is a basic building block of a good business and is one of its most valuable assets. Using it properly can make the different between failure and success, or between maintaining and excelling.
Small business knowledge management processes haven't been quite as quick to catch up, at least in part because the same resources aren't available to most smaller companies (and maybe because they don't understand the large benefit of knowledge management). But just like corporations now often have a formalized process of knowledge management and consider that one of their core business practices, small businesses should focus on this too to take advantage of the valuable data that's already at their disposal.

So What is Knowledge Management?Small businesses that see this as something only corporations can afford to do are shortchanging themselves and their employees. And chances are, at least if the company is somewhat organized and efficient, there's a small business knowledge management process at work, though it might not be considered a business process at all.

A company that gathers sales figures from the last year and tries to compare the quarters to find trends is using a form of knowledge management. Because they may not be using all the numbers needed and may not be analyzing the information in the right way, their process of handling knowledge might not be efficient or good, but there is a process there. By deciding to follow certain steps and really hone the way data is gathered, handled and analyzed, a company can get the most it can out of those numbers and make more accurate conclusions. This helps with goal setting and, most importantly, the achievement of those goals.

A Poor Small Business Knowledge Management Example

In an example to illustrate the importance of the process, this company doesn't have a standard for knowledge management. They're trying to figure out how to improve sales on Product X. They look at the last year's sales figures on the product to find clues about how to improve the numbers. Because they don't have a standard in place, they may not have figured out the best way to find other numbers that can help them analyze the sales numbers and put them in context. For instance, sales around Christmas are higher so they assume that the holidays boosted sales. In this case, they're correct.

But sales during the quarter after Christmas hit a serious slump. They assume that it's because people are spending less after the holidays and so they decide that they'll scale back their marketing on that product during the beginning of each year and pay extra to market less expensive products. They might be correct. But if the slump was deeper than usual because they had a product shortage and they don't have that information when they're analyzing the data, they've made a mistake. They could market the product and see sales improve next January because they'll also take steps to make sure enough of Product X is available to meet the demand. This is the type of small business knowledge management mistake that is common, because companies don't have a more structured way of organizing and analyzing all the data to see those important connections.

Small Business Knowledge Management Software

By investing in software that will automatically pull all those necessary numbers together so that one aspect of the business (sales) can't be analyzed without taking everything else that's relevant into account (manufacturing, production problems, strong competition, returns for defective products, for example) then the correct conclusions can be drawn from the information available and the small business knowledge management process becomes a vital part of creating success in the future.

At the very least, a small business needs to carefully examine the data that's available, the data that could be gathered to help analyze these types of situations and the conclusions that are made from the data so they can have a better understanding of the data and put it to much better use.
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The MBA Rush


Its rather unfortunate that in India only MBA degree seems to provide a launching pad to take one's career to a different orbit. All other professional degrees require a much longer gestation period. Therefore, every top-grade B-school gets huge number of applications even from professional degree holders such as Engineers, Software Professionals, Doctors. Chartered Accountants, Cost Accountants , Lawyers. Hotel Management Graduates etc. The Indian scene has now started following the global trend where people are coming back to an institution after working for a few years because pre and post MBA position differentials are significant.
Other than this pre-post difference in terms of money and responsibilities, work experience soon teaches you that "doing your job" and "getting job done" are two different competencies. While all other professional degrees teach you only the first, MBA teaches you both, the first and the second because a Managers job is to get work done.
The moment you become responsible for somebody else's work you need knowledge of management. For example, a salesman doesn't so much need any knowledge of management; he can deliver good results on the strength of his product knowledge, persuasive ability; energy, enthusiasm, intuition and common sense. However, a Sales Manager or Team Leader needs knowledge of management because he is required to coordinate activities if others and is also responsible for others performance. Appreciative intelligence, energy, persuasive ability, intuition and common sense can certainly serve a non-MBA manager well, but a structured knowledge of MBA does provide the manager a perspective that remains applicable across situations an people. There are many high performing managers who may not be MBA's as they have learnt all the nuances of management through their rich experience that cannot be substituted by anything, however, the MBA learn many of those tricks of the trade faster as they have a perspective that help them to join all the dots to clarify the picture.
MBA's are also emerging as a community, not yet professional enough to be registered by a single association with a common code of ethics. This community is highly networked and reasonably powerful. Currently, the community identity is defined by the institution from which one graduates, but we notice initiatives where alumni of many institutions are networking to create a larger MBA community, The rush for MBA is also to join such a prestigious community.
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Knowledge Management Process


Knowledge management is the concept of taking data and turning it into useful and applicable knowledge in a business environment. There is no one specific way that this done, and there's really no one specific definition of the process or the concept. The ideas are more general, though there are many specific benefits of knowledge management that can be named as well as some specific steps that must be included, no matter how simple or complex an organization's concept of knowledge management is. The knowledge management process can have a few steps or dozens, but those steps fall into the falling basic categories:
  • Data Capture: Raw data must be collected somehow before it can be turned into knowledge, or wisdom as the last step in the process is often called.
  • Data Storage: There has to be a place to keep the collected information. Data storage for most businesses and even individuals today is digital, but even a filing cabinet is a data storage solution.
  • Data Organization: Once the data is collected it has to be organized into some kind of a useful structure.  For instance, a piece of paper that contains raw data like sales figures numbers, number of employees, prices of products, employee attendance numbers and last quarter's profits is full of raw data, but it's a collection that's not organized and can't be easily used in this format.
  • Data Analysis: This often melds in with the organization step, as the act of organizing data often requires analysis. Once the data is analyzed, then it's more likely to be knowledge than just raw information because the way the information works together and things like cause and effect become more obvious. Patterns become obvious, and those can be used to illustrate general concepts. This turns the information into useful knowledge.
  • Knowledge Sharing. At this point, the raw data has become useful knowledge or wisdom. While this is an improvement over raw, unorganized data, it's necessary to determine the best way to share this wisdom with employees to make it truly useful on a daily basis, and to use it to reach organizational goals.

The Purpose of the Knowledge Management Process

The entire point of gathering data, storing it, organizing, analyzing it and sharing it is so that the company can use vital business information to see what needs to be done, what needs to be improved, what can be eliminated, what needs to be maximized and what's possible in the future. The knowledge from this information processing cycle can be used to reach goals, whether those goals are more sales, more clients, less waste, more employee productivity, a better public image or almost any type of goal a company could have. Knowledge can be used to further those goals if it's gathered and processed correctly.
The knowledge management process has not always been something that companies have focused on, at least not in a formal way. Few people in a company several years ago would have used the term "knowledge management." But companies that were successful have always practiced knowledge management whether they called it that or not. Gathering data and turning it into useful information and shared knowledge has always been crucial.
An Example of the Knowledge Management Process
To illustrate the process, consider that you and another person want to pool your money to purchase something at a store. You'll need to know how much money you have and how much the item costs. You write down $20, $10 and $5. That is data that you've stored by writing it down. Those numbers mean nothing, because they're raw data with no context. Once you have these numbers, you have gathered data but it's essentially useless.
Now the data must be organized. You make it clear that the $20 is what the item costs, and that you have $10 to contribute and your friend has $5. Now you must analyze the data. This leads you to see that you don't have enough money to purchase the item, and that your friend needs to contribute another $5 in order to make it possible. You pass that information to share the knowledge. Now your friend also knows that it's necessary to add $5. What started at as 3 raw numbers has now become useful knowledge that helps in setting a goal.
While that's a very simplistic example, the basic steps are followed in every knowledge management process.
An Organization's Knowledge Management Process
A company can't set sales goals (resulting from wisdom rather than just guesses) without proper knowledge about past sales, trends, potential obstacles and which items sell best and why (data that's organized to have relevant meaning). Likewise, a company that wants to improve employee productivity can't do so without understanding that productivity in the past and looking at knowledge that would suggest what has worked and what hasn't.
While the idea of a knowledge management process might sound complicated in general terms, when you look at the specific steps it becomes something that people and companies do every day without even realizing it. By nailing the process down and following the steps deliberately, more associations between data are readily made and goal-setting and results can be improved even more.
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Nonaka and Takeuchi Model

Modelling knowledge management is one big issue for those who are in charge of gathering information, documents, professional experiences and know-how at a corporate level.
Nonaka's and Takeuchi's relevant work should allow you to understand easily and clearly how knowledge may be dealt with, transforming tacit knowledge into more explicit forms. This is one of the most famous model existing, maybe the easiest and the clearest.
"The Nonaka and Takeuchi KM model focuses on knowledge spirals that explains the transformation of tacit knowledge into explicit knowledge and then back again as the basis for individual, group, and organizational innovation and learning." (K. Dalkir)

First step: Socialization (tacit-to-tacit)

Much knowledge, perhaps 80%, lies in people's brains. The aim for the knowledge worker is to find ways to collect this tacit knowledge. Socialization consists of sharing knowledge through social interactions.
People hold indeed know-hows, secrets, personal skills that will never be shared if none work on it. It is very important to try to gather this knowledge by socializing, that is, using face-to-face communication or better, share experience directly at work through 2 roles: the tutor and the apprentice. It involves arriving at a mutual understanding through the sharing of mental models.That way, there will be little risk that the know-how of your company leaves at the same time of employees' retirement.
Socialization is a very effective means of knowledge creation, maybe one of the easiest but nethertheless the more limited. It is also very difficult and time-consuming to disseminate all knowledge using this mode only.

Second step: Externalization (tacit-to-explicit)

The process of externalization (tacit-to-explicit) gives a visible form to tacit knowledge and converts it to explicit knowledge. It can be defined as "a quintessential knowledge creation process in that tacit knowledge becomes explicit, taking the shapes of metaphors, analogies, concepts, hypotheses, or models" (Nonaka and Takeuchi, 1995). In this mode, individuals are able to articulate the knowledge and know-how and, in some cases, the know-why and the care-why.
An intermediary is often needed to execute this process. For instance, we can consider a journalist who is the typical person able to interview knowledgeable individuals in order to extract, model, and synthesize in a different way (format, lenght, ...) and thereby increase its scope (a larger audience can understand and apply this content now).

Third step: Combination (explicit-to-explicit)

Combination is the process of recombining discrete pieces of explicit knowledge into a new form.
No new knowledge is created at this step. It is rather to improve what we have gathered so far, to make synthesis or a review report, a brief analysis or a new database. The content has been basically organized logically to get more sense, consolidated.

Fourth step: Internalization (explicit-to-tacit)

The last conversion process, internalization, occurs through diffusing and embedding newly acquired and consolidated knowledge. In some way, internalization is strongly linked to "learning by doing".
Internalization converts or integrates shared and/or individual experiences and knowledge into individual mental models. Once internalized, new knowledge is then used by employees who broaden it, extend it, and reframe it within their own existing tacit knowledge.
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