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Knowledge Management can sometimes seem like a difficult term to define. There are several different approaches to the topic which cause the confusion. One definition is a range of systematic processes and practices used by a business to manage the knowledge in an organisation,  distributing that knowledge and helping with the adoption of insights and experiences. It is interest of businesses to stop people re-inventing the wheel all the time.

Another problem is the definition of Knowledge. It can be facts, ideas, opinions, principles, theories and frameworks. Knowledge can also be something that people aren’t aware of but exist in the common knowledge of a subject.

One thing that is clear is that Knowledge management is a technological solution or a manual. It is centred around the complete processes of finding where knowledge is currently hidden, capturing the information and helping spread it to everyone who needs it.

The term Knowledge Management seems to have started being used around 1991. In 1999, the term personal knowledge management appeared to express the systems and processes that solo individual can use for their benefit. With the increasing computer power of mobile devices, personal knowledge management processes and application will be come more widespread.

Lets look at why a customer leave a service over the other service provider? The main reason is price, the more lucrative the price offer the more chances prevail that customers would leave a connection. It’s noticed that 60-80% of the customers leave due to lesser tariffs.

The second main reason is the kind of customer service provided and how customer is treated by the customer support personnel. Many a times when a complain is raised they are not resolved within expected time and customers services representatives are not able to meet the demand and expectations of the customer issue, they just try to close the issue rather than solve it. Hence in frustration customer migrate to other service provider where customer services are better and they are listened carefully. Here frustration is the primary cause of churn.

The third main reason of customer jump to another service provider is the quality of service being provided, for example if there is lot of network disturbances and call drops, a customer would get irritated and look for better service providers which can give disturbance free service. People would go for better quality.

The fourth main reason for the customer churn is the changing technology, the next generation is knowledgeable and fast moving with the trend, they have economic power and want to posses newest and latest features, which can provide them the whole world of features in their mobile. The moment they find that there is something more in another service provider’s features they quickly migrate.

Added with this, the telecom companies are witnessing falling ARPU (average revenue per user). It looks like subprime lending, where an economically poor customer like (milkman, washer man, vegetable vendor, rikshawala, loaders etc;) is given connection without understanding the long term customer profitability to the company. Here a customer takes a connection but makes restricted calls added to this the price is cheaper per call. In this situation, though the customer base is huge they fail to take ARPU higher. The huge customer base itself is economically weaker just like subprime customers in the banking industry.

Where does knowledge management fit in for the telecom companies? Earlier companies were trying to collect, capture, replicate enterprise, employee and business knowledge capital. However, now that customer is the prime asset, companies are trying hard to capture the customer data. Though there are business intelligence tools, one department uses one tool the other another. Whereas knowledge management can be applied through out enterprise through streamlined processes facing customer services area like billing, fault repair, new campaigns, complaints, self service, cross sell and up sell. When knowledge management processes are aligned with the customer processes, companies would be able to understand the customer better and know the customer lifestyle and behavior in a more meaningful way. Once the company understands the customer better it would be able to serve it better. In the scenario of better service customers will remain with the service provider for long. Knowledge management will also allow companies to provide personalized services to the customers, as needs and wants of customers differ from one customer to another.

If companies fail to capture the customer data through knowledge management processes, they would fail to get into the lives of customers and hence fail to provide services suitable to them. The wrong services and messages would only enhance frustration and churn.

Article Source: http://EzineArticles.com/?expert=Madhu_Bala

* prepare KM strategy
* implement knowledge sharing tools for both tacit and explicit knowledge
* document good practices and what did not work
* map all the existing knowledge in the organisation – tacit and explicit
* make knowledge sharing a policy of the organisation

KM is directly linked with people rather than technology. Technology is just a supportive tool for boosting KM. Effectiveness of the KM lies under the competence of the staff, institutional support and the motivations. And, KM is an ongoing process as Knowledge is constantly tested, updated, revised, and sometimes even obsolete.

The KM vision should be explained in organisational strategic terms rather than KM terms (examples are ‘ICIMOD will explore upstream-downstream relationships and to validate the supply of ecosystem services, including freshwater and carbon sequestration, and to conserve and manage biodiversity as a natural heritage, a resource for livelihoods and for ecological resilience. ICIMOD aims to help mountain people facilitate the development of appropriate policies and innovative and equitable compensation mechanisms for ecosystem services’, ‘ICIMOD wants to develop regional capacity and reduce mountain poverty to ensure the increased economic resilience of mountain people. By exploring sustainable livelihood options and enhancing innovative rural income generation strategies. ICIMOD will generate, promote and customise knowledge on equitable socio-economic adaptation strategies and methods to allay the effects of socio-economic and environmental change. ICIMOD also aims to monitor and analyse the poverty situation and its main drivers, and to develop policy-relevant data’), and in a manner that generates enthusiasm, buy-in, and motivates managers to work together toward reaching common goals as it always adds value to the existing knowledge by pooling the expertise together, building the relationships and collaborating among the useful knowledge to achieve the goal of the organisation.

Then, the challenge is to sort out the information within the organization that are valuable for obtaining the goal or moving towards the objectives of the organisation. And, KM should also secure the learning experiences of the individuals as when a person leaves an organization, she/he takes lots of knowledge about her/his job with her/him which are always valuable processes and procedures of the organisation. With all these and many more functions, KM adds a great value to the organizational efficiency achieving or moving towards its goals by

* Facilitating better decisions and processes
* Contributing to the intellectual capital of the organization
* Eliminating redundant processes, streamlines operations, and enhances employee retention rates

Lastly, KM is done not only for capturing or storing the existing knowledge but should be tied up with the strategic objectives of the organisation and embedded in everyday life, and implement as a part policy of the organisation.

Article Source: http://EzineArticles.com/?expert=Deependra_Tandukar

Top-down knowledge management has had limited success. KM will begin to show significant ROIs when the process is inverted. Centralized knowledge administration clearly produces higher-value knowledge — but centralized authoring retards growth. In the coming decade, the hard dollar value of knowledge will be recognized, and everyone — not just a small elite — will be responsible for generating the raw materials for corporate KM.

Bottom-up knowledge generation will have significant impacts on the way work, and workers, are perceived by corporations. Management will have to develop new incentives for knowledge workers to contribute high-quality content. For more traditional firms now adopting KM practices, decentralization of knowledge generation will be difficult, as it is antithetical to some ingrained management principles and habits.

The bottom-up knowledge capture trend will have a direct impact on technology. The technologies developed to capture and publish knowledge all have had to compromise one way or another between simplicity and specificity. Relatively unsophisticated techniques like text search are easy and cheap to apply; gather up a collection of documents and point a search engine at them, and in a simplistic way you’ve created a knowledge base — but the results are often not very specific.

Artificial intelligence techniques, by contrast, impose a great deal of structure on knowledge content, making it much easier to find the specific knowledge needed. Structure not only makes knowledge more useful, but also makes it easier to evaluate for accuracy and utility. But the knowledge is expensive to generate and maintain, and these techniques do not lend themselves to generalist authoring.

More advanced approaches incorporating pattern recognition and associative techniques such as neural networks, along with increasingly sophisticated textual and semantic analysis approaches, are enabling KM systems to capture knowledge in more intuitive ways. These technologies support decentralized authoring, not only by simplifying the way structure is imposed on the content but by allowing “authoring” to be a more innocuous, almost passive element of another task, such as solving customers’ problems or answering their questions about products. However, these newer technologies tend to be more expensive to license and implement.

The bottom-up knowledge trend is good news, then, for the technologies at the opposite ends of the spectrum — low-end search tools, which can provide cheap solutions requiring virtually no knowledge engineering, and high-end, high-priced solutions that allow effective knowledge capture to be seamlessly integrated into high-priority corporate workflows. The trend clearly is bad news for vendors relying on older, more labor-intensive structured knowledge representation approaches.

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