Category: Knowledge Management

Knowledge is variable; the data can be identical, but the knowledge is always different. The past 25 years have seen knowledge management evolving, underpinning that knowledge is our most strategic asset and should be managed as it is “the most important guarantor of sustainable competitive advantage” (Easterby-Smith & Prieto, 2008).

Knowledge and its management must evolve over time as one could have a vast knowledge base but in a volatile environment with increasing complexity, businesses are subject to the Innovator’s Dilemma. The failure to adapt to new technologies, listen to customers, suppliers, and employees, and improving their competitive advantage is caused by either the lack of new knowledge, or knowledge that is held locally either within a person, team, or department but not transferred or managed efficiently if at all (Christensen, 1997).

Ikurjiro Nonaka developed the SECI model to highlight knowledge management and transfer and focuses on 2 types of knowledge: tacit and explicit. Explicit knowledge is ‘visible’ knowledge which is rational, and readily and easily passed onto other. Tacit knowledge is held in the knowledge holder’s mind and needs a middle step in processing the knowledge before it is passed on, making it subjective. Nonaka also notes when reviewing the model with Takeuchi that each type of knowledge can be converted, and be viewed as a continuous improvement process, moving the model into a clockwork spiral. The foundation of this model is the notion of ‘knowledge conversion’ and how once can convert tacit knowledge to explicit and vice versa.

When executing the model, it can be an inexpensive method of mapping different types of knowledge, mapping how to transfer the knowledge at a high-level view and can highlight ‘quick wins’ for the company. The source and trainer of the knowledge being transferred can determine the effectiveness to the new recipient. In saying this, the model does not consider that there may be lack of motivation or fear for an employee to share their knowledge as Holste and Fields highlight in their work (Holste & Fields, 2009). This can create a supply failure where the source of the knowledge and/or the facilitator might be someone who understands the process but is unable or unwilling to facilitate the transfer of it. This creates a failure at the first point; the origin and movement of the knowledge. Kaplan argues that transferred knowledge can hold bad habit and cynicism, and one must be aware what is being transferred as although knowledge exchange can be monitored, it cannot be measured (Kaplan, 2008). One also needs to be aware of the recipient of said knowledge and their learning styles. Not everyone will learn the same, with some taking more in by doing the process, or seeing it, or reading it.

Although the model can act as a roadmap of knowledge, it does not specify what knowledge needs to be transferred, nor the resource or time to execute. “Knowledge is a perception obtained from experience, reasoning, direct perception, and learning” (Bhatt, 2008). This could potentially create an abundance of knowledge being transferred, some of which could be less imperative and therefore diluting the effectiveness of the knowledge and skills which the company should be focusing on. The model holds no indication as to who makes the judgement as what knowledge is worthy or imperative to share.

The benefit of this model is the ability to see knowledge that can be shared intra-organisational. The movement of knowledge from individual tacit to organisational explicit offers massive potential for value creation. This is the key behind whether a business is stable. This can be done in the form of standard pieces of work or processes and can be seen in the cases of continuous improvement, sharing best practice. It creates a homogeneous culture and process within an organisation.

An insight between open and closed innovation can be seen in this model. In order to utilise knowledge, one needs to recreate it. Replication is easier in explicit form as there is a formalised process, usually written down, and there is little room for miscommunication. Many times, this can come from outsourced business advisors who will create a formal process to make uniform within the business. Tacit knowledge is usually gained by mastering or doing a process and can be difficult to cover to explicit as Polanyi states “we can know more than we can tell” (Polanyi, 1966). Bider and Jalali also introduces a new type of knowledge in the adapted SEA model, embedded knowledge which comes from well-known ‘good regulator theorem’ (Bider & Jalai, 2014). As the model was first proposed in the 1990’s, it is clear from the author’s research on the subject that there is a diverse pool of knowledge types, and that tacit and explicit may not encompass all types.

Glisby and Holden argue that Nonaka’s SECI model was developed in case studies where there was Japanese cultural practices notes that these practices do not occur worldwide, and therefore the model may not be suitable for other cultural or geographical environments (Glisby & Holden, 2003). Even within the same organisation, employees can be from different backgrounds or educational levels and therefore they do not have the homogeneity that the model assumes all recipients and knowledge holders to have.

Although Nonaka’s model can be effective if utilized correctly, it is difficult to trace whether the theory was born after consulting case studies, or whether the case studies were used to support the theory.

“Identifying and developing talent globally is the strength that makes leadership a competitive advantage for Scotiabank” – (Scotiabank, 2019).

First and foremost, Scotiabank is extremely dedicated to helping develop leaders. Ultimately, strong leadership within any business is a competitive advantage that can help deliver positive results. Scotiabank has operations in over 50 countries, and these platforms help identify and develop necessary talent from around the world. This is the particular strength that helps Scotiabank develop a competitive advantage.

Globally, we strive to equip our Scotiabank family with the knowledge and tools to access any necessary information and data. Working with our global partners, we are able to harness onto a vast amount of potential information and knowledge being shared by our partners worldwide. Using our collaborative knowledge, we can assure that our employees, clients, shareholders and the community as a whole, is treated with integrity, respect, and insight into their financials. Finance is an essential part of our everyday lives, and being able to put across complicated information and data in a simple and understandable way, is our ultimate goal. This way, our customer and employees are not frustrated with the complex knowledge being fed into our company. This is efficient and effective and can overall help solve any problems and provide both our clients and employees with the best customer service solutions.

Knowledge Management and Organizational Culture

Scotiabank is committed to helping our clients. We value diversity, inclusion and network. This means that any visitors will feel like they belong. Scotiabank is dedicated to sharing knowledge and providing financial services. With our highly trained employees, you will quickly gain knowledge and guidance you need to succeed. Our culture believes in empowerment, accountability and openness. We also invest in others, actively contributing to the communities in which we work. We value all information that is brought forward, shared, collected.

Gruber and Duxbury (Duxbury & Gruber, 1999) concluded that an environment that supports knowledge sharing has characteristics of rewards structure, recognition for knowledge sharing with peers, openness/transparency, trust, and communication. Within Scotiabank, we strive to maintain a healthy relationship with both our employees and clients. We don’t hoard information but share it with those most interested. We can not have any resistance within out company, or else this stall any new knowledge from entering and being retained. We must be transparent and open to knowledge sharing.

Knowledge Management Strategies

Scotiabank’s goal is to apply, distribute, and store knowledge. Our company depends on the effectiveness of knowledge sharing. We want to make knowledge more visible and easily accessible to both our employees and clients. We’re striving to create a more two-way exchange of knowledge between both the individuals and as a collective, with an interactive social aspect of creating and sharing data and knowledge. We will use local network and internet to collect information and dismiss any information that is not useful. That we do not experience a system overload of information. Our banking operations globally, are trying with all our capacity to capture, manage and construct suitable information within our organizational knowledge, in order to help improve the quality of our management and operations. Our strategies will address any issues and find solutions to encourage prompt decision making both suitable for our staff and clients. Our culture strongly supports our knowledge management tools and methods. Our company provides training and opportunities to gain further knowledge. We encourage our staff and even our clients to gather as much information as possible, in order to have a clear view of their financial future.

Knowledge Management Tools

In order to ensure that our knowledge management is working, we will use specific tools to help simplify and deliver information in a timely and effective manner. This will help our company plan, control and formulate strategic activities in the best way to achieve our companies desired objectives. Our tools derive from the knowledge management tools and techniques manual (Asian Productivity Organization, 2010).

Document Libraries Leading to a Document Management System

The purpose for this tool is to ensure efficient and effective access to information. This way it can make it easy to recognize key knowledge and develop appropriate information assets to support them. Our Knowledge Library systems will be easily backed up and regularly updated. Documents contained will be organized through many categories, but easily and quickly accessed and used by our employees. Public records for client’s interests will be documented and statistically recorded by number of views. Components within this tool includes spreadsheets, text documents, calendars, links, search engines, excel documents with any financials.

Knowledge Bases

Scotiabank and our employees hold an abundance of two specific types of knowledge: tacit knowledge and explicit knowledge. We strive to hire as many employees that hold incredible tacit knowledge, that being ‘personal’ knowledge. This valuable knowledge is only attained through verbal communication with the person holding the specific information. Our staff are incredibly knowledgeable, and we create an atmosphere where clients are not afraid to ask for advice or guidance in relation to their financials. This helps create new knowledge and encourage knowledge sharing among our staff and cliental.

Social Network Services

Social networking is an extraordinary way to build our network and business. Scotiabank’s social networking services help find people who are looking for the appropriate financial tools and guidance they are seeking. If they have a need that Scotiabank can help with, being able to reach out through of social networking tools come in handy. It makes communication quick and easy. Our social networks also make it easy to quickly share valuable information that we know our clients would like to know. We would be able to share content like links and relevant resources that not only reach our clients, but future clients as well.

Advanced Search Tools

Visiting our website can sometimes feel intimidating with the amount of information being thrown out at the forefront. However, using an advanced search tool, we can make it very easy for our employees and clients to search for specific information they seek. Using specific phrases and words can make it easy to quickly find the information you are looking for.

Collaborative Virtual Workspaces

The purpose of a collaborative virtual workspace is to make it easy to communicate and share knowledge with our global partners. Scotiabank has partner around the world and being able to network in a collaborative, virtual way, makes it easy to access the best skills and acquire knowledge anywhere in the world. This significantly reduces any travel costs and allows our employees to work wherever is most effective for them, as well as giving them access to information whenever they need it.

Overall, these easily implemented tools give us an edge and can help us with balancing our financial business process and our knowledge management methods. These tools ultimately help us generate new ideas within our company and gives us a competitive advantage over out financial competitors.

Knowledge, in simple terms, knowledge is data that have been shaped into a form that is meaningful and useful to the intended persons. It can also be defined as information that is specific, relevant and actionable.

Social Networks are dedicated websites and applications which enable people to communicate with each other through text messages, comments and using images. Facebook is a perfect example of a social networking site that connects us with family and friends online. WhatsApp on the other hand is an app that enables communication through voice and messaging.

Knowledge management and social networks both have a similar role of obtaining and accessing new information with the use of technology. Both require individuals to provide and create new content with the intent of sharing. The role of social network such as Facebook and WhatsApp in knowledge management in an organization will be to:

• • Increase visibility or increase brand awareness;
• • Improve performance;
• • Build collaborative networks;
• • Give content a purpose;
• • Show value.

Increase Visibility or Increase Brand Awareness

An organization may choose to use Facebook and WhatsApp to inform workers about its workflow and how to access various services/ query the knowledge base. The organization may also choose to inform the intended market what is on offer through adverts posted on Facebook or marketing images/fliers sent through WhatsApp to individuals and groups.

Improve Performance

When workers are informed through the social networks on how query the knowledge base in order to offer better assistance to their clients, the originations performance will be improved, thus creating a positive image of the organization.

The organization can use social media to get feedback through live chats , dedicated feedback forms on their overall performance in service delivery or a product. This feedback will lead to improved performance and customer satisfaction.

Form Collaborative Networks

An organization can use social media to come up collaborative networks for sharing ideas and solving various problems. This would also enable an organization to come up with a Q&A page where that knowledge can be easily accessed.

Give Content a Purpose

An organization can use social media to set up posts as contributions with a purpose. This would open a door to honest unbiased engagement with others.

Show Value

Organizations should use social networks to communicate to the stakeholders that knowledge management goes beyond simple accumulation of data and is instead connected with the act of leadership. Managers will basically manage the organization’s knowledge base, but its management should be placed in the hands of the employees who interact with it on a daily basis while performing their duties.

The trend of globalization has induced fierce competition among business enterprises within domestic and international markets. The primary quest for the technologies is not limited to the strategic value of an organization but also empowers the organization’s work context by utilizing its resources. The knowledge management process deals with the extraction of both implicit and explicit knowledge of the organization for improving the performance of the organization. However, Business Intelligence, on the other hand, gained its importance with constant enhancement in technologies and tools for extracting hidden knowledge and patterns.

Hence it can be argued that both Business Intelligence and Knowledge Management are complementary to each other for extracting and managing the knowledge. Thus government organizations must have an integration of both Knowledge Management and Business Intelligence processes for enhancing the performance of the organization concerning make organization decisions for the competitive environment and utilizing the tacit organizational knowledge. The paper focuses on how BI and KM integration affect the government business organization while discussing its implementation challenges. Current situation of understanding management strategic decision making and the role of knowledge must need to address before proposing any framework for a government organization.

The study will distinguish between personal and organizational knowledge, as well as whether education is playing a pivotal role in strategic development or not?

Keywords

Knowledge Management (KM), Business Intelligence (BI), Data Mining, Knowledge, Data Warehouse

1. Introduction

In the era of knowledge and technical innovation, it has been accepted that intangible assets of any business organization will be key to its success. Experience is supposed to be the most critical asset of any business organization, which has the most significant influence on competitiveness, strategic development, and growth. Further knowledge can be made accessible to all through the knowledge management process. In the context of business organization, knowledge management is use to acquiring knowledge and experiences it for strategic development.

It has claimed that in an organization, the knowledge not only embedded to document and repositories but also with enterprise routine, process, and practices. Thus, education is recognizing itself as one of the most critical assets of any organization. Knowledge is acquired through the processing of available data of organizations using data mining approaches. Data mining has the potential to use as a powerful tool for business intelligence but yet not fully recognized.

With the proliferation of new technologies, data mining has experienced exponential growth and became an integral part of the Knowledge Management system. Data mining algorithms are applied to explore the underlying data of the business organization, and after processing, it determines the effectiveness of knowledge. The paper aims to find how government organization managers adopt both KM and BI processes in the public sector. The study aims to find out the interrelationship between Knowledge Management and Business Intelligence, and utilize it for strategic development and decision making.

In the government-based organization, there is an extensive amount of data that is used within the organization for business policy management, organization decision making, and growth & development of the organization.

With the increased amount of data, the correlation between data also changes; it means the relationship between the application system also changed this extracted knowledge can be utilized for decision-making business intelligence. Primarily in the Knowledge management process, the knowledge discovery process needs to apply data mining algorithms. Varieties of algorithms are available in data mining, such as genetic algorithm, decision making, neural network, and fuzzy logic. The fundamental purpose of the paper is to discuss the need to integrate KM and BI for exploiting structured & unstructured raw data, implicit information of the organization, and its challenges.

2. Literature review

Most researchers and practitioners agreed on the practical implication of knowledge as one of the critical assets of any organization. Knowledge Management and Business Intelligence are the two major areas of the researcher’s concern. Knowledge management is a tool for empowering the knowledge within the organization, and useful for decision making. However, Business Intelligence has affected the business world the most for transforming raw data into an experience. It can be used for prediction analysis. Dearth research has been performed to explore Knowledge Management, Business Intelligence, and its applicability within various application domains.

There is a need for a common platform for the organization where both employer and employee can share the knowledge.

A scheme for transforming Knowledge Management into Business Intelligence has specific parameters for implementing them to the organization for a standard workflow. However, the new or new solution cannot be added directly to the adoption purpose. Tacit knowledge plays a vital role in all the phases of any new innovative process and implementation of implicit Knowledge Management and can help handle new problems.

Memory is a model for linking individual knowledge to management. However, the management of tacit knowledge is a challenging task. Thus, there is a need for a common framework where tacit knowledge can be categorized into various degrees.

Both knowledge management and business bits of intelligence are different from each other in terms of standard foundation. Thus the interrelation between knowledge management and business intelligence needs to be explored. Simply an insight can be concluded that business intelligence is used for transforming data to knowledge. In contrast, Knowledge Management can be used as a tool for knowledge acquisition, knowledge sharing, and to create new awareness.

3. Knowledge management

3.1 Knowledge

Knowledge is defined as the mixed frame of facts, expectations, skills, and a combination of relevant information collected through experience, study, and reasoning, for enhancing the ability of decision making and evaluating the right context. However, data, information, and knowledge are the key terms which are the set member of knowledge management and may be used interchangeably. Several arguments were made by the researchers about these terms, and defined as:

Data can refer to unprocessed, unstructured collections of random facts; Information refers to structured and processed data having some sense to the user, whereas knowledge applies to the most refined and highly useful data for decision making and problem-solving.

Various researchers have proposed several classification methods for classifying knowledge. The classification of experience is helpful to the organizations for processing and managing their various available knowledge resources. The most widely accepted classification of knowledge is Explicit and Tacit knowledge.

Explicit knowledge contains the knowledge, which has already been processed in the form of visual, text, diagrams, tables, manuals, and specific documents. Acquisition of explicit knowledge is easy since it is in the form of a table, manuals, and document; so as easy to manage too.

3.2 Knowledge Management

Knowledge management is an essential part of any process management system and highly applicable to business organizations. It is an integral part of linking knowledge to business process management. Several authors have proposed various definitions of knowledge management. Knowledge management can be defined as the paradigm which is used for exploring knowledge resource, exploiting, and sharing all knowledge resource for enhancing the performance of any organization. Knowledge management provides a framework and tools for knowledge acquisition, sharing, and creating knowledge for aiding end users for problem-solving, and decision making.

The knowledge management system can be defined as the system for managing knowledge within the organization for creating, acquiring, and sharing of knowledge.

Figure 2: Overview of KMS

Researchers and practitioners have discussed challenges and barriers that may cause performance degradation using a knowledge management system.

3.3 Knowledge Management Models

Limited processes, procedures, and structured approach lead the development of a more structured approach for managing knowledge resources within an organization. Knowledge management modeling is used for creating and managing knowledge to overcome these challenges. Models provide an accessible presentation of a real system using its main features. Modeling helps give structured methods for understanding, implement, and evaluating knowledge management systems. However, researchers argued over the advantage and disadvantages of these models while applying the organization.

Generic Knowledge Management Models

Many generic models, methods have been developed by the researchers for enhancing knowledge management. Some of the well-known models are the SECI Model, knowledge map, Ontology-based knowledge management, Activity-based knowledge management, and knowledge management models.

SECI Model

SECI model is used for creating knowledge using four different modes known as Socialization, Internalization, Combination, and Externalization, as represented in figure 3.

The creation of new knowledge is a specific activity where each user in an organization acts as a knowledge worker, and it begins with each individual.

Externalization is used for transforming tacit knowledge into explicit knowledge. A combination process is used for combing various available explicit knowledge sources for creating new awareness.

Activity-based Knowledge Management Model

The activity-based model is proposed, especially for activities of construction projects. The information and knowledge from all sources are classified and stored as an activity unit, hence named activity-based modeling. The primary aim of this model is reusing expertise and easy knowledge acquisition. Activity-based knowledge divides the process into a top-level and sub-level phase. High-level phases are such as knowledge acquisition, knowledge extraction, knowledge storage, knowledge sharing, and knowledge update.

Knowledge Map

Using an activity-based knowledge management model as the base model. This model is used for acquiring and representing the knowledge known as a knowledge map. A knowledge map is the schematic graphical representation that tells what knowledge resource is available and missing in knowledge management. It’s an easy way for the user to find the required knowledge. This model uses a previous knowledge map of a similar activity to form a new one. Authors have proposed knowledge management architecture for describing components of knowledge management. This architecture consists of four different layers as an Interface layer, Access layer, Application layer, and database layer

Tacit-Explicit Knowledge Continuum

A model has been proposed for transforming tacit knowledge into explicit knowledge in the organization; there should be a clear understanding of the dynamic nature of education [15]. The experience can also be harmful to organizations if it is invalid, misleading, discouraging, and unsatisfactory for the organization. Learning is dynamic as it changes with time in a place to extract knowledge from users; it should be more productive, like creating a knowledge culture for sharing knowledge through face to face communication.

However, various other knowledge management models such as IMPaKT, e-COGNOS are proposed by authors depending on different organizations. Reviewing the literature and analysis helps in identifying the characteristics, their relationships, and components for knowledge management modeling related to government-based organizations.

4. Business intelligence

Business Intelligence can be defined as the combination of data analytical tools for gathering and effective use of organization information to improve business management. Some authors have argued business intelligence as an online decision-making process. Authors have suggested that Business Intelligence as a set of components such as data warehouse, data mining, OLAP, and decision support system depicts the input and processing of the Business Intelligence process. The basic description of Business Intelligence components is described in the next subsection.

Data Warehouse

The data warehouse is a system used for data repository and data analysis. Data warehouse stores the data into a repository, where it is processed and organized for strategic decisions. Information in the warehouse is stored in the form of Metadata. Metadata helps the user to understand what and where data is available, and how to access it and when to use data. Data warehouse system is categorized such as data mart, OLAP (Online analytical processing), and OLTP (Online transaction processing).

Data Mart

Data marts are the simple form of a data warehouse which specially focused on a single task such as for any individual departments. Datamart uses the data either from internal operations or from the external data source.

OLAP (Online Analytical Processing)

OLAP is a multidimensional model that supports roll-up and drilling operations. OLAP is a low volume transaction but consists of complex queries. Data mining techniques widely accept OLAP applications.

Data Mining

Data mining is the process of mining the available data to discover the hidden patterns, trends, and correlation among the data. A massive amount of data is stored in a data warehouse and processed using data mining tools and techniques.

ETL (Extraction, Transfer, and Load)

The ETL process is the group of three different methods for extracting and loading into the database. The extraction process refers to data extraction from various sources, including internal and external sources. The transfer process refers to data cleaning for correlating the inconsistent, missing, and invalid data sets. Finally, load refers to load the cleaned data into the data warehouse.

5. Integration of business intelligence and knowledge management

Business Intelligence and Knowledge Management both have shown significant improvement for organizational performance. However, both Business Intelligence and Knowledge Management are different but used for knowledge discovery and decision making. There are various arguments by the researcher for discussing whether Business Intelligence is part of Knowledge Management or Knowledge Management is part of Business Intelligence. Simply Knowledge management deals with both implicit and explicit knowledge, whereas Business Intelligence deals with only explicit knowledge. Integration of Knowledge management and Business Intelligence will broaden the research area of expertise while improving intelligence. The business Intelligence process converts data into information then into knowledge, which finally used for meeting user requirements. However, the primary emphasis on Knowledge management is knowledge and improves the utilization process.

The significant benefits of the integrated framework are

• It ensures to provide the highest quality of services to individual users in the global market.
• Tacit knowledge can be useful for business intelligence.
• It gives both understandings of business context, context interpretation for user benefits.

6. Basic framework for KM & BI integration in government organizations

Management of knowledge is of much importance for the government for dealing with the challenges of the knowledge economy. Government organizations are facing many problems, such as administrative, executive, and fierce competitiveness for achieving organizational goals. Today government organizations need knowledge work and knowledge workers for creating & sharing the knowledge to enhance interpersonal and organizational skills. Knowledge management and business intelligence have the potential to strengthen the effectiveness and competitiveness of government sectors.

Thus there is a need for having a combined integrated framework of Business Intelligence and Knowledge management for achieving this goal. The initial scope represents the possible outcomes and features which are expected from the BI, KM integrated framework. Based on the expected results of an integrated framework, it can consist of several layers.

After processing the unstructured and structured data, knowledge can be extracted as KDD or BI processes. Finally, obtained knowledge can be visualized and integrated with a decision support system. On analyzing the expected outcomes from the framework, it can be argued that there can be possible interaction between Knowledge Management processes and Business Intelligence Processes. The primary aspect of the integrated framework is the inclusion of both explicit and implicit knowledge, which benefits organizational decision goals as well as the work skills of an employee using tacit knowledge.

Extractions of tacit knowledge and its utilization is a challenging task for any organization and have many positive influences.

Conclusion & future work

Potentially this research would assist in the development of an integrated model for Business Intelligence and Knowledge Management, which helps government-based organizations for strategic growth. It will help evaluate the existing knowledge management system. This expanded integration will improve the effectiveness of knowledge at an individual and organizational level.

Implementation of integrated KM and BI framework for government organizations can improve the quality and efficiency of public services. In this paper, a base framework with its possible expected outcomes and detailed literature survey has been proposed. Further research aims to develop a new knowledge management framework integration with business intelligence that enables strategic development, decision making, and resource utilization within a government organization.

Introduction

Knowledge management is power, since it acquires answer for each issue the general public. The power of any knowledge management is relied upon the time allotment work the knowledge management find a good pace. Thurs is knowledge management that is gotten after the time period the answer for a specific issue has lapsed probably won’t allude to a decent knowledge management. Thusly, the requirement for curators and data researcher to deal with knowledge management appropriately is very catalyst for the improvement of any country of the world. Guinea is nation in western Africa, situated on the Atlantic coast. Three of western Africa’s significant streams the Gambia, the Niger, and the Sénégal ascend in Guinea. Characteristic assets are ample: notwithstanding its hydroelectric potential, Guinea has a huge bit of the world’s bauxite saves and critical measures of iron, gold, and jewels. In any case, the economy is to a great extent dependent on subsistence horticulture. Cognizant tackling of knowledge management and sharing is a key method for opening our possibilities and our network moored in exercises learnt for creating towns across Guinea republic. By what means would guineans be able to deal with their insight appropriately, what are the zone knowledge management the board will have effect in the improvement of Guinea republic. Accordingly, the author will in general look at the effect of knowledge management the board in three areas of Guinea republic, which are the Agricultural part, Health segment and the Rural Development.

What is Knowledge Management?

Knowledge management (KM) is the way toward making, sharing, utilizing and dealing with the knowledge management and data of an association. It alludes to a multidisciplinary way to deal with accomplishing authoritative destinations by utilizing knowledge management. Endeavors to characterize KM forms are various. Nonaka and Takeuchi (1995) portrayed four knowledge management change forms: socialization, externalization, mix, and disguise. Each procedure includes changing over one type of knowledge management (unsaid or unequivocal) to another type of knowledge management (implicit or express). Hlupic et. al. (2002) allude to Ruggles who recognized three principle sorts of exercises: knowledge management age including the formation of new thoughts and new examples; knowledge management codification, and knowledge management move, guaranteeing trade of knowledge management among people and divisions. Neither of these procedure models are expansive enough to take into consideration a total examination of authoritative knowledge management stream, precluding a few significant strides in the knowledge management chain, for example, getting and putting away knowledge management. Oluic-Vukovic (2001) traces 5 stages in the knowledge management preparing chain: gathering; sorting out; refining; speaking to; and scattering.

A set up discipline since 1991, KM incorporates courses instructed in the fields of business organization, data frameworks, the executives, library, and data sciences. Different fields may add to KM inquire about, including data and media, software engineering, general wellbeing and open arrangement. A few colleges offer committed graduate degrees in knowledge management the executives. Knowledge management the executives endeavors commonly center around hierarchical goals, for example, improved execution, upper hand, advancement, the sharing of exercises educated, joining and constant improvement of the association. These endeavors cover with hierarchical taking in and might be recognized from that by a more noteworthy spotlight on the administration of knowledge management as a vital resource and on empowering the sharing of knowledge management. KM is an empowering agent of hierarchical learning. Given the significance of knowledge management to proficiency and profitability, it’s important that associations deal with their insight successfully. Knowledge management the board is any framework that enables individuals in an association to share, access, and update business knowledge management and data.

The History of the Republic Of Guinea

Guinea which is formally the Republic of Guinea, is a west-beach front nation in West Africa. Some time ago known as French Guinea. The advanced nation is in some cases alluded to as Guinea-Conakry to recognize it from different nations with ‘Guinea’ in the name and the eponymous district, for example, Guinea-Bissau and Equatorial Guinea. Guinea has a populace of 12.4 million and a zone of 245,857 square kilometers (94,926 sq mi). The sovereign territory of Guinea is a republic with a president who is straightforwardly chosen by the individuals; this position is both head of state and head of government. The unicameral Guinean National Assembly is the authoritative body of the nation, and its individuals are additionally legitimately chosen by the individuals. The legal branch is driven by the Guinea Supreme Court, the most noteworthy and last court of request in the nation.

The nation is named after the Guinea district. Guinea is a customary name for the area of Africa that lies along the Gulf of Guinea. It extends north through the forested tropical districts and finishes at the Sahel. The English expression Guinea comes legitimately from the Portuguese word Guiné, which rose in the mid-fifteenth century to allude to the grounds occupied by the Guineus, a nonexclusive term for the dark African people groups south of the Senegal River, rather than the ‘brownish’ Zenaga Berbers above it, whom they called Azenegues or Moors. Guinea is an overwhelmingly Islamic nation, with Muslims speaking to 85 percent of the populace. Guinea’s kin have a place with twenty-four ethnic gatherings. French, the official language of Guinea, is the principle language of correspondence in schools, in government organizations, and the media, yet more than twenty-four indigenous dialects are likewise spoken. Guinea’s economy is to a great extent reliant on horticulture and mineral creation. It is the world’s second biggest maker of bauxite, and has rich stores of jewels and gold. The nation was at the center of the 2014 Ebola flare-up. Human rights in Guinea stay a questionable issue. In 2011 the United States government asserted that torment by security powers, and maltreatment of ladies and youngsters (for example female genital mutilation) were progressing maltreatment of human rights.

Guinea’s Agricultural Sector

Guinea in western Africa, agribusiness represents 19.7% of the complete GDP and utilizes 84% of the financially dynamic populace. In 1999, the fundamental subsistence crops were manioc, 812,000 tons; rice, 750,000 tons; sweet potatoes, 135,000 tons; yams, 89,000 tons; and corn, 89,000 tons. The economy of Guinea likewise relies upon money harvests, for example, sugarcane, citrus natural products, bananas, pineapples, peanuts, palm portions, espresso, and coconuts. In 1999, an expected 429,000 tons of plantains, 220,000 tons of sugarcane, 215,000 tons of citrus natural products, 150,000 tons of bananas, 174,000 tons of peanuts, 52,000 tons of palm parts, and 18,000 tons of coconuts were created. Espresso creation in Guinea has vacillated after some time because of illicit espresso sneaking that influenced the business before the nation’s changes in the mid 1980s. In 1999 creation of espresso beans was assessed at 21,000 tons, contrasted with 14,000 tons by and large every year from 1979 to 1981. Endeavors at value obsession influenced agribusiness in Guinea during the 1970s and 1980s since the freedom. The French has decreased their impact in estates and the evacuation of the French tax had influenced generation during the 1970s when dry spell was pervasive. During the 1970s and mid 1980s, nourishment creation declined and agrarian fares fell especially. In 1984, a year when dry season truly influenced Guinea, 186,000 tons of grain must be imported to forestall starvation.

Since 1985, free market approaches have upheld the decentralization of state-possessed estates and government-claimed rural produce towards confined private smallholders. There are upwards of 500,000 working in Guinea by the late 1990s which allegedly yielded twice as much as the rural yield than state-possessed horticulture did during the 1970s, even without monetary help.

The Impact of Knowledge Management of the Agricultural Sector of the Guinea Republic

Knowledge management is sees as a monetary asset. In the knowledge management based society, the assignments of knowledge management the board is high. The effective circulation of knowledge management is expecting a more prominent job. Farming and its augmentation isn’t a special case of it. Agribusiness associations understood the significance of dealing with the both unequivocal and verifiable knowledge management for dispersal of knowledge management just as to satisfy the Ranganthan’s idea right data to the correct client at the opportune time. In the evolving situation, the National Agricultural Research (ICAR) wishes to be the knowledge management entryways for Agriculture. Knowledge management the board procedure is the procedure of bit by bit procedure of from empowered individuals and innovation dependent on knowledge management, trust and validity. It included procedure of making, sorting out and sharing of knowledge management. Web journals, twiter, book checking, labeling, online life, twitter are the change of knowledge management association from one to many. Compelling knowledge management the board is arrived at when the correct knowledge management and data is conveyed to perfect individual at the opportune time. The result of successful knowledge management the executives improved the profitability and execution in Agriculture division. The achievement of productive knowledge management the board in horticulture incorporates the ranchers, rancher associations, strategy creators, augmentation operator, and researcher. Successful knowledge management the board is arrived at when the correct knowledge management and data is conveyed to ideal individual at the opportune time. The result of powerful knowledge management the executives improved the efficiency and execution in Agriculture division. The fulfillment of effective knowledge management the executives in agribusiness incorporates the ranchers, rancher associations, approach producers, expansion specialist, and researcher.

The impact of knowledge management of the Agricultural sector of the Guineans are as follows:

1. Knowledge management has help farmers to know the right seeds to plant.
2. It has help them to knowledge how to test the soil they are planting their seeds on
3. Knowledge management has also help farmers to know how to apply fertilizer to their soil. Due to the fact a lot of research has been carry out in the agricultural sector, knowledge management has help policymakers to see the need to supply fertilizers to farmers, educating them on how, when they are to apply it.
4. Knowledge management has help farmers to know how to get their harvest to the market. Before now in Guinea, most of their Agricultural production is not done to be exported to other part of the world, but as a results of knowledge management, fertilizer was introduced, agricultural production step up and the economics of Guinea is been sustained.
5. Knowledge management has also help people to know that fish production is lacking, thereby making people go into fish production, which is a plus to the economic development of the country.
6. Knowledge management has help farmers to know, how and where to sought for loan to boast their agricultural production.

Abstract

Purpose: The purpose of this paper is to synthesize Industry 4.0’s on knowledge management process and practices, and to explore the improvements that will arise from it. It also provides an idea of how to use approaches for enhancing the knowledge management process in Industry 4.0. The main objective is to highlight the role of the technologies that support Industry 4.0 in facilitating the knowledge management process.

Design/methodology/approach: The aforementioned dynamic suggests that a thorough analysis of the existing literature on the topics related to the subject is needed to better understand what Industry 4.0 is for and how it can support the knowledge management system. Despite the analysis of the literature on Industry 4.0, this study develops an approach that presents the importance of this new industrial system, especially its technologies in the knowledge management process. It outlines the way in which Industry 4.0’s components are useful to overcome several stages of the process and improve the performance of the organization.

Findings: Findings reveal that Industry 4.0 is an important factor in the growth of various organizational management processes. Industry 4.0’ components such as the Internet of Things (IoT), big data, cyber-physical systems (CPS), and Cloud computing play an important role in supporting the knowledge management process that contributes to the organization’s performance.

Research limitations/implications: How to manage the knowledge process is one of the important questions that pursue organizations to investigate possible ways. In this context, this paper deals with the relationship between Industry 4.0’s technologies and knowledge management. It provides an approach that covers the key technologies of this industry that can support managing knowledge in the organization. It contributes to the literature of Industry 4.0 and knowledge management by examining the role of its technologies in acquiring, creating, storing, sharing and protecting knowledge. Despite opening a new perspective for academics, this study also has limitations. As the main contribution is conceptual, further empirical studies are needed to analyze the impact of Industry 4.0 on knowledge management.

Originality/value: Business models are evolving along with the growing globalization and technological advancement, thus increasing the need for creative knowledge management. This paper highlights the current trend in knowledge management related to industry 4.0 and its technology. It focuses on the effect of this Industry and, subsequently connected technologies in the knowledge management process. This paper is one of the pioneering studies which examined the role of industry 4.0 in the process of knowledge management. It discusses the connection between industry 4.0’ technologies, mainly IoT, big data, cloud, and CPS and the knowledge management process. Therefore, this study contributed to the literature by providing valuable insights into knowledge management through Industry 4.0.

KEYWORDS: Industry 4.0, Knowledge management, IoT, big data, Technology.

Introduction

Nowadays, organizational management is widely linked to the innovative application of management techniques in knowledge processes and the organizational capacity to adapt to changing environments based on the rapid development of new technologies. Companies are facing complex structural changes and are increasingly based on knowledge which is a key driver of innovation. It is, therefore, necessary to implement strategies to support the knowledge management strategies. In addition, it is shown that the implementation of knowledge management strategies has a direct positive impact on the performance of the organization.

Therefore, the ability to manage information in today’s business landscape is becoming increasingly important. Knowledge management strategies can often be focused on new technologies and companies can adopt methods and use technologies to support knowledge management strategy and ensure dynamic and timely use of knowledge. Companies have to face challenges and embrace the opportunities offered by the new emerging technologies in order to remain competitive.

In the possible use of knowledge management, there is an apparent need for suitable and practical solutions to support innovation (Roblek et al, 2016). This is particularly evident in the fourth industrial revolution, known as Industry 4.0, which reflects the new manufacturing paradigm based on technology and which is heavily dependent on knowledge. In Industry 4.0, knowledge management that is strategically focused could prove to be a critical component in securing relevant knowledge to help foster innovation.

Industry 4.0 and the related digital transformation refer to the advent of new digital technologies, such as the Internet of Things (IoT), artificial intelligence, cloud computing, and Big Data, and involve a profound transformation of processes and activities, skills and business models. The emergence of these technologies generates a multiplicity of challenges for companies and particularly upsets the organizational ecosystem by the development of robotics and the arrival of smart and virtual factories.

In this context, we have seen an exponential increase in research developing methods and tools to address this challenge in the recent decade but still, the exchange of knowledge is crucial for practical technological application and implementation in the knowledge management field. To examine this issue, the present paper focuses on what kinds of creativity characteristics and related future innovation trajectories are important in forming knowledge management formal strategies and tools. Therefore, this paper aims to identify the technology flows and key elements of a successful technology roadmap that matches knowledge management formal strategies. Its contribution is, therefore, mainly conceptual.

This paper has been achieved as follows. Before discussing how Industry 4.0 can support the Knowledge management system, a brief overview of Industry 4.0 and the pillar of technological advancement that support it are presented in section 2. This section covers also a scientific contribution analysis related to Industry 4.0 with the focus on the technologies that support this new industrial system. Section 3 describes the process of managing knowledge and highlights its different stages. Section 4 outlines the adopted research approach and details the role of the components of Industry 4.0 in supporting the different stages of the knowledge management process. Section 5 discusses presents a brief discussion about the relationship between the different technologies of Industry 4.0 and how they fit together to improve the process of knowledge management in the organization. Section 6 summarizes the conclusions of the study and proposals for future research.

Industry 4.0: Theoretical framework

Industry 4.0 in literature

In recent years, the term of Industry 4.0 has attracted very high-level attention. Google trends (see Figure 1) reveal that up to 2013 there was little searching interest even the concept introduced in 2011. There has been an increase in search interest in the period between 2016 and 2019, which has continued to increase.

By analyzing the number of the scientific publications indexed in Scopus database from 2013 to 2019, and containing the following keywords: Industry 4.0, 4th industrial revolution, Smart factory, Smart Industry, and Manufacturing 4.0; we can notice that more than 6000 publications were made as shown in the following Figure.

Figure 2 reflects the interest of the Industry 4.0 among the scientific community and shows that the number of scientific contributions of Industry 4.0 has been increasing since 2013. In addition, the results of this analysis show also that the publications were maximal in the field of Engineering (54.20%), Computer Sciences (37.85%), Business, Management and Accounting (13.25%), and Decision Sciences (11.73%). It is worth noting that Industry 4.0 has attracted less attention in other research areas such as Social Sciences, Mathematics, and Materials Science with 3.61%, 9.06%, and 8.13% respectively.

Despite its popularity, especially during these last years, a clear and commonly accepted definition of the term Industry 4.0 still seems difficult to pin down (Muller, et al, 2018). Many studies have tried to develop different definitions of what constitutes Industry 4.0 (Lu et al, 2016; Muhuri et al, 2019). Industry 4.0, which presents the next level of manufacturing, does not concern only industrial. It concerns also all the change using digital integration and intelligent engineering, where machines redefine themselves to more communicate and perform different operations.

Based on digital transformation, Industry 4.0 and the smart factory have served as the basis for many countries’ programs. The appendix illustrates the different visions of some countries that have embraced the Industry 4.0 in very ambitious programs. The Appendix indicates that most of the European countries’ program is closer to the German’s Industry 4.0 strategy. Similarly, other countries have also put forward the corresponding Industry 4.0 program.

Globally, Industry 4.0 can be viewed as the utilization of cyber-physical systems in the systems of industrial production (Flynn, 2017). It affects manufacturing because of its emphasis on making a smart environment. In this context, this new industrial system needs advanced manufacturing technologies including the Internet of things (IoT), cloud, big data, cyber-physical systems (CPS), etc. We have paid specific attention to these components, and we selected some relevant technology in the following section.

Industry 4.0’s technology

Industry 4.0 is related to (i) the technical perspective of CPS coordinated into manufacturing activities, and (ii) the IoT tools into the industrial process. Therefore, humans, machines, and resources are vertically connected, while organizations are connected horizontally over the value chain (Waibel et al. 2017). It aims to provide employees with more accurate and relevant information, empower them with smart technology, and give them greater responsibility and flexibility with a higher perspective on workplace autonomy while delegating repetitive and low-level decision-making to machines and systems.

In this context, different advent technologies that are related to the main features of Industry 4.0 (Cheng et al, 2016) mainly: (i) Interconnectivity, (ii) data, (iii) integration, and (iv) innovation, are used to perform Industry 4.0 elements.

It should be noticed that it is not an exhaustive list, but it serves as a guide to select technologies that are of particular importance to Industry 4.0. These technology groups bring together a variety of technologies, approaches, methods, and techniques, as shown in Table 1. Their judicious combination enables the implementation of the company’s digital strategy.

Table 1 – Industry 4.0’s technology groups and support resources

Technology

For Industry 4.0

Resources involved

IoT and connected object (Molano et al, 2018)

Connecting a huge variety of digital and physical resources.

Decentralizing real-time decision-making

RFID, Wireless Sensor Networks, etc.

Cloud computing (Kagermann et al, 2013)

Facilitate data-sharing systems.

Deploy the functionality related to production, process, monitoring, and control

Infrastructure as a service (IaaS), Software as a Service (SaaS), Platform as a Service (PaaS).

Cyber-physical systems (Kagermann et al, 2013)

Integrating sensors, software and communications components to monitor and act in real-time on the physical world.

Smart and connected communities, physical components, etc.

Big data and analytics (Sedkaoui, 2018)

Driving and supporting real-time the decision process based on the analysis of the available data generated from different sources.

High-performance computing, High-Performance Computing Cluster, Hadoop-YARN, etc.

Industrial integration and enterprise architecture (Pereira and Romero, 2017)

Digital information integration and interoperability of engineering across the value chain service-oriented architecture, Business process management, etc.

Artificial intelligence

Support the management of the production process machinery.

Neural networks, machine learning, Bayesian networks, etc.

Simulation

Simulate all production operations machines, products, and humans

Cybersecurity

Reliable and proven communication protocols can be used to control access to the machine control systems.

VPN, P2P, RFID, etc.

The implementation of elements from the range of alternatives illustrated in Table 1 may depend on the case, redefine the way of monitoring, controlling, optimizing or even making Industry 4.0 products, processes or services autonomous.

Today’s business environment is moving towards Industry 4.0, marked by the use of cyber-physical systems, smart factories and developments in services. The term Industry 4.0 suggests that the effort is focused on improving manufacturing processes. However, the increase in the presence of sensors and real-time exchanges also opens up new opportunities in the definition of communicating products. Indeed, the contributions of digital technology can be broken down along the two following axes:

• The process, Industry 4.0 promises a transformation of production methods, going from mass production to individualized production. Processes are more agile and reconfigurable to adjust to customer needs and thus maximize value creation. Production decisions are adapted in real-time with the appearance of autonomous machines and communication between machines and cyber-physical systems.
• Connected objects allow real-time data collection. This data can be analyzed in real-time and allow the system to adapt to its environment autonomously, or be used later for the development of new products or services. The availability of data and the possibilities of analysis bring opportunities for the development of new services (Sedkaoui, 2018).

Knowledge management: process and practices

The success of an organization depends widely on the quality of knowledge applied to its business processes. Therefore, the knowledge management process, as a part of the business processes, is essential for effective knowledge management. This process requires that personal knowledge be transformed into corporate knowledge that can be widely shared and applied appropriately across an organization.

The literature identifies a multitude of knowledge management processes and divides it into several stages:

• Creation, Storage/Retrieval, Transfer, Application (Alavi and Leidner, 2001)
• Discovery, Capture, Sharing, Application (Beccara-Fernandez et al, 2004)
• Acquisition, Conversion, Application, Protection (Mills et al, 2011)
• Acquisition, Sharing, Application, Storage (Lee et al, 2013)

It should be mentioned that there is no consensus to illustrate the classification and implementation of these processes. However, all these knowledge management processes contribute to the performance of knowledge management practices in the organization.

In this study, the authors explored the following knowledge management process: (i) acquisition, (ii) creation, (iii) storage, (iv) sharing, and (v) protection, in order to examine the impact of Industry 4.0 or more specifically its components. Where all these stages (see Table 2) contribute to the performance of knowledge management practices.

An organization needs to continually generate new knowledge, promote its sharing, and use knowledge in order to achieve a competitive advantage.

Table 2 – Knowledge management process

Stage

Definition

Acquisition

Defining applicable external knowledge, turning it into a form suitable for assimilation or internalization in the sense of an organization that can be applied to the creation of knowledge

Creation

Generating new knowledge by applying the knowledge acquired from outside and within the organization appropriately.

Storage

Collecting and recording of organizational knowledge available and knowledge acquired for future reference

Sharing

Mechanisms that allow safe transfer of knowledge within the organization.

Protection

Mechanisms of protecting an organization’s knowledge from illegal or inappropriate use.

The process of knowledge management allows an organization to acquire, store, use and protect knowledge to facilitate problem-solving, creating creative insights, and supporting the decision-making process.

The analysis of literature indicates generally accepted distinction in knowledge management between the two following strategic focus areas (Choi et al, 2008):

• Explicit oriented strategy: or the use of information and communication technologies (ICT) to manage knowledge across the organization.
• Tacit oriented strategy: Knowledge management is allowed using people-focused tools and techniques

A clear link can be seen in the literature between the strategic orientation and the form of shared knowledge. The first strategy is related to explicit knowledge that is data-driven, codifiable, and not connected to individuals. While the second strategy is linked to tacit knowledge, which refers to the person’s knowledge and cannot be codifiable. In practice, two main types of knowledge branch off entire strategic focuses.

The use of ICTs increases the organization’s effectiveness and improves collaboration. In this context, the emphasis in the knowledge management process is on codification, storage, structured knowledge sharing, and internal organizational links (Sedkaoui, 2018). The improvement of collaboration can support innovation. Its main purpose is to share knowledge through informal connections that can be created, for example, through social networks or directly at meetings.

If we examine more deeply into modern business practices, we can notice that new organization’ trends show that the internet of things and connected objects, big data analytics, smart systems, etc. are increasingly being integrated into knowledge management processes.

The knowledge management process becomes more flexible and smart, thanks to the development of new technology (North et al, 2018). With the advent of IoT and the development of several devices, organizations can now gain an insight that has never been possible before. This technology facilitates the way in which knowledge is acquiring, creating, sharing, storing and protecting. It stimulated the development of integrated software platforms to optimize knowledge management strategies.

Abstract—

One of the issues of the academic institution is knowledge management. How the academe disseminates information over the academic community on real-time and the availability of knowledge anytime and anywhere is a challenging task in every institution. The objective of this study is to bridge the gap between present and prior contexts of knowledge creation, sharing, or application by developing Knowledge Management System for Camarines Norte State College. The proposed system is designed specifically to cater the requirements of the academic institutions especially Camarines Norte State College in terms of knowledge management. Moreover, KMS in Higher Education Institution (HEI) could help in the growth of learner-centered knowledge and action learning, growth in work-related learning, movement from closed to open knowledge systems and extensive development in computer-based communication technologies.

Index Terms – knowledge management, knowledge management system, system development

I. Introduction

The new frontier towards the industrial economy is the knowledge or information-based system where this wealth of knowledge is an intellectual asset that if given proper management would offer greater benefits and competitive advantage to an institution. Knowledge management can be defined as: the systematic process of creating, exploiting and sharing individual, corporate and team knowledge (tacit and explicit) utilizing technology, culture, strategy and people in enhancing innovation, efficiency, completion times and organizational performance[1].

Knowledge management systems is not easy to develop and deploy, there are several challenges on the manner. It includes IT infrastructure to form new knowledge, store it, share and diffuse it, and to apply it for effective actions[2]. Moreover, knowledge management once applied to Higher Education Institutions (HEI’s) poses a lot of challenges, particularly from the stakeholders. Given the growing needs of HEI’s as they are now more aware of the clear advantage of having KMS. However, there is limited research in this field while there is no evidence of an effective framework that will answer HEI’s needs for better KMS[3].

Being one of the members of SUC’s that aims for quality education and services as it enhances management efficiency, fiscal autonomy, and institutional competitiveness. Therefore, the Knowledge Management System (KMS) in CNSC is expected to benefit the organization through the utilization of its intellectual assets and foster a competitive edge and a capacity for learning. However, at present, there are no HEI’s in the Bicol Region that is equipped with a KMS deployed in their school. As a primer educational institution that will implement a fully working KMS in a Higher Educational Institution (HEI) this will establish a common benchmark that other institutions in Camarines Norte and possibly the Bicol region could adopt. Hence, this is the challenge and motivation that the researcher is trying to address in this study.

II. Related review

A. Knowledge Management System and its Features

Knowledge Management (KM) is an approach to achieving strategic objectives by visualizing, sharing, and using intangible resources of an organization and its stakeholders [4], [5]. In this regard, one of its core processes and techniques is data mining and knowledge production which is one of the important steps in knowledge discovery and a subfield of knowledge management [6],[7].

The concept of a knowledge management system (KMS) is not new but an important emerging technology that would enable better management towards better decisions for an organization. Although it found worldwide recognition as an important strategic tool, its integration into academic organization becomes lagged and it have much lesser collaboration with its counterpart which is the industry [8],[9],[10]. Even if there are disagreements in several studies regarding knowledge and knowledge management [11],[12],[13] but still most authors agree on the bases of KMS and its use as key to competitiveness.

As such, knowledge sharing is vital to the success of knowledge management practices in all organizations including universities. An effective KMS sharing is essential for the organization to benefit from the knowledge its employees have generated [14],[15]. However, even the higher administration and various stakeholders in universities might have heard KM but they do not have a clear idea how to initiate and implement it even the richness of literature for the past three decades have given various points in its development and implementation [16]. Knowledge sharing is vital to the success of KM practices and even though there are some factors affecting the willingness to share knowledge which can be classified as organizational, individual, and technology factors; this can be countered through driving academics to engage in knowledge sharing activity,[14].

In fact, KM can also support higher education in learning circle and social interaction which can be used by teachers and students to improve the teaching-learning process[17].

There is a need for KMS technology and systems to bridge the gap between present and prior contexts of knowledge creation, sharing, or application. KMS in Higher Education Institution (HEI) could help in the growth of learner-centered knowledge and action learning, growth in work-related learning, movement from closed to open knowledge systems and extensive development in computer-based communication technologies [18].

B. Knowledge Management System Development

Knowledge management system development involves different approaches and techniques. One of such, is that the KMS architecture based on four layers which includes the application layer, technology layer, infrastructure layer and repository layer. Its functions also required internet, extranet, and intranet infrastructure using client and server computing [19],[20]. Another is taking considerations of an organization framework through proper observation and survey to provide effective periphery participation within the system. Taken in consideration the design of KMS to facilitate movement of information and decisions from the center towards the periphery. It is highly encouraged to have a two-way interaction between center and periphery for effective utilization of KMS where character of periphery participation is generally directed at knowledge discovery and application, instead of than creation and sharing [21].

In terms of framework, there’s a very important factor to be considered such as setting up a schema as [22] have done which was utilized as a starting point of an iterative process until reaching the expected and desired final and common KM framework. Several schematic categories were identified such as knowledge and knowledge management artifacts, knowledge management frameworks and models, knowledge management systems, knowledge management ecosystem, influencing factors, and knowledge management reference disciplines and research method. It is necessary to have a proper infrastructure to fundamentally reengineer knowledge creation and delivery based on principles of knowledge management and organizational learning [23].

A different but relevant framework was presented in the study of [24] that might be used as a guide in developing and implementing KMS but this is often supported a Socio-Technical Systems based on Pan and Scarborough view. It consists of Infrastructure (technology), Info structure (organizational structure) and Info culture (organizational culture) which is believed to give clear understanding on KMS. Knowledge management systems can improve firms’ agility. Their framework supports the positive impact of knowledge management systems in the absorptive capacity through better collaboration and a decision-oriented management system promoting dynamic capabilities. [2]

Moreover, in developing a university knowledge management system essential points are to consider such as cooperation, tacit knowledge, knowledge continuity, power relationships, and social knowledge management. Cooperation is important to enhance KM performance while a multi-dimensional view of knowledge encompassing the tacit is better for capturing complex phenomena of knowledge in an organization [25]. There is a distinct difference between tacit and explicit knowledge types and determining the use of separate knowledge modules using their own knowledge management strategy depending on the knowledge type of the stored information was necessary to support KM initiative successfully [26].

Also, holding essential operational knowledge should be incorporated into KMS framework while considering that power and its consequences have both negative and positive impacts on the system where KM is expected to be seriously influenced by the potential of social/media software through interactivity, social processes to promote organizational knowledge. Tacit knowledge is never easy and its collection through interviews and videos has not succeeded hence, a story-telling approach might be useful on the process [27]. Therefore, it is important to be able to understand the whole concept and process before the actual development and such can be done using roadmap or even knowledge models [28] .

One of the challenges within the development of an effective KMS is the financial issue that may arise from building it towards its completion since there are many things to consider such as its value, internal business process, growth and learning, as well as the infrastructure that is involved. Moreover, KM is not widely adopted in industries due to a lack of an effective approach [29]. On the case of its development so far, there is not just one KMS “silver bullet” that is critical for the successful implementation of KMSs in organizations [30].

C. Knowledge Management System Implementation

The implementation of KMS have brought up different views and ideas based on its needs and purpose. Several implementation means have been covered by different literatures and one of the major concern in its deployment is to have an effective resolution of cultural and organizational issues which is consistent to information system management literature, advocating organizational and behavioral change management as critical success factors in the implementation of information systems [11]. Even its increased usage forms virtual communities, expert localization and establishment of knowledge taxonomies, knowledge transfer and sharing processes, incubation and Mentorship, collaborative software development and their role in creating entrepreneurship initiatives and knowledge economies [31].

However, in its implementation there are several challenges that could be used as motivations and even best practices that could be made to make key success in small and medium sized organizations [32],[33]. Some of the challenges in its implementation were financial and information security, technology and management, senior management support and strategy, acceptance, user’s motivation and culture and project management, change management and training. However, only four of these determined the success of its implementation such as financial and information security, senior management support strategy, technology and management, and acceptance [34]. Another research finds sustainability as one of the major challenged in KMS implementation because stakeholders have various expectations and firms need to decide how they intend to address these which becomes a great pressure in its effective implementation [35].

III. Methodology

A. Method of Research

The descriptive survey method of research was used in the study. The questionnaire-checklist supplemented by informal interview and evaluative observation was utilized in gathering the needed data.

B. Software Development Methodology

The researcher used the Rational Unified Process (RUP) methodology since the present study requires documentation and information processing that RUP can handle and because it is supported by tools, visual modelling processes as well as documentation guides and testing hence, it became an important component in the development and deployment of the proposed system entitled “Knowledge Management in the Academe: An Interaction of Technology and People”. The RUP Methodology is shown in Figure 1 which has nine (9) disciplines that use iterative approach for organizing projects in terms of workflow and phases, each consisting of one or more iterations. Each project iteration cycle begins with a plan outlining what were accomplished and concluded with an evaluation of whether objectives have been met.

Aside from that, the researcher believes RUP can help manage fast changing user requirements and the difficulty in gathering the data since KM in CNSC is a primer and so this particular methodology suits to the needs of the proposed system.

The RUP phase is shown below in figure 1.

Fig 1. The RUP Methodology

Phase 1: Inception. This is the phase to establish the business case for the system and delimit the project scope. This requires identification of all external entities with which the system interacts and define the nature of this interaction at a high-level. This involves identifying all use cases and describing a few significant ones.

In this phase, the researcher will conduct requirements analysis through series of interviews with the end-users to gather pertinent information such as document storage, retrieval and sharing process in the academic community. The researcher will provide proposed document storage, retrieval and sharing through initial use-case model for this part.

Phase 2: Elaboration. This phase is responsible for developing a visual tool to represent the system, a detailed plan for the construction phase, a proper scheduling for project and on determining the actual cost of the proposed system. Likewise, in this phase processes, tools, and automation support are put into place and development of system architecture are put into action.

In the phase, the researcher will design a logical as well as physical design using Unified Modeling Language such as use-case diagrams and a sequence diagram of the proposed KM System, a Gantt chart, and a proposed software and network connectivity design, hardware infrastructure setup and user interface design to handle the information system will also be developed.

Phase 3: Construction. This phase is anchored on the resource management, control and process optimization, complete component development and testing against the defined evaluation criteria, and assessment of evaluation of product releases against acceptance criteria for the vision.

In this phase, the researcher will conduct usability tests for the system usefulness, satisfaction, and ease of use. A user-manual and a description of the current release will also be develop and a package diagram will also be provided.

Phase 4: Transition. This phase involves deployment-specific engineering packaging, beta testing to validate the new system against user expectations, parallel operation, conversion of operational database, training of users and maintainers, rolling-out to the marketing, distribution and sales force, tuning activities, achieving user self-supportability and achieving stakeholder concurrence that deployment baselines are complete.

In this phase, deployment diagram will be provided along with beta testing with the employee of the Camarines Norte State College to validate user-expectations. Likewise, a comprehensive implementation plan will be developed.

IV. Results and discussions

The system design and development led to the creation of the full-packaged Knowledge Management System for academe especially the Camarines Norte State College.

Fig 2. Main Interface of CNSC KMS

The researchers developed the system with three main features:

A. Members Log-in Page

The system was design for academic community use only all users must register to use the system, different user has its own access level for security purposes.

B. KMS digital databank.

The system has database for storing digital knowledge/information that are useful for academic use, such as research, data gathering for accreditation, documentations and other academic uses.

Figure 3 shows the interface of the documents that are stored on the CNSC Knowledge management system. All documents that stored by different stakeholders has its own directory for convenience and easy access of the users of the system.Fig 5. The document upload interface of CNSC KMS

Fig 3. The databank structure of CNSC KMS

B. KMS knowledge creation and sharing.

The system allows the users to create and share documents. This features let the users to store and retrieve documents/information from the CNSC KMS. All documents that store by the users shall be available to the academic community for the purpose of academic use.

Fig 4. The document download interface of CNSC KMS

C. KMS knowledge collaboration

The system has its collaboration features, the users can be allowed to modify, edit and update the document. Only documents subject for revisions can be modify or edited.

Fig 6. The document modification interface of CNSC KMS

v. Conclusion

The researchers were able to determine one of the major problems in academic operations especially in Camarines Norte State College. This problem is focused knowledge management. The need to have knowledge management system with Digital Databank, Knowledge Creation and Sharing, and Knowledge Collaboration features will cater to the ever growing cases of knowledge management issues in the academic community.

The new system is designed specifically to cater the needs of the academic institutions especially Camarines Norte State College in terms of knowledge management. With the CNSC KMS helps in managing information and making sure that knowledge is available anytime, anywhere and 24/7 operational.

As a future work area, in order to increase the flexibility of the software, the researchers would like to include comprehensive data warehouse data analytics built with intelligent decision-support system for Camarines Norte State College administrations and personnel.

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Abstract

The purpose of the paper is to introduce the concept of knowledge management. It helps to find a link between business consulting and knowledge management. It also focuses on need of knowledge management for consultants and how they can implement it. Further the paper elaborates the advantages of using knowledge management. It also includes the views of some of the top business consultancies on knowledge management and how they use it. Then the paper showcases some of latest developments in this field.

Introduction to Consulting

Consulting can be defined as the process to transferring knowledge, expertise from one to another in order to provide a solution or a help. There are two side, a client and a consultant and the client pays the consultant. At times, there is a third place which is the ‘problem’ to be solved. The overall process of consulting has various stages taking place in timely manner. First there is analysis of the problem faced to analyse the current business situation of the company. This analysis is provided to the client in a form of a proposal. The proposal included internal and external issues, strengths and weaknesses. If the proposal is accepted by the client, the consultant provided alternatives and recommendations to the client followed by an implementation plan. There are three major reasons behind the need of consultants; one is changes in sectors that encourage businesses to look for more expertise, second is the political aspect where consultants become a further legitimate aid, third is being cost-effective and overcoming budget issues. The consulting approach varies with different sectors and different organizations. Every consulting approach and strategy is based on different values, ethics, goals, outcomes and ideologies. It may focus on either a product or a process. The interactive model of consulting involves clients and consultants working is more collaborative manner to achieve the organizational goals (Jacobson, Butterill, & Goering, 2005).

Introduction to Knowledge Management

Started as an academic theory to becoming an essential part of organizations now, the concept of Knowledge management is being studied for over 30 years now. Defined by O’Dell and Grayson in 1998 as a strategy to provide right information to right people in right time and to help people put their actions into work. The process of knowledge starts with a piece of information. Whenever some information is processed, it has the potential to become knowledge. Information is processed if people are able to relate, link, or find patterns in it. Moreover there are two types of knowledge, tactic and explicit. Tactic knowledge is present in the brain where as explicit is knowledge present on documents. The process of producing knowledge is mainly based on a double spiral movement between tacit and explicit knowledge. There are four modes of conversion of knowledge: socialization (conversion of individual tacit knowledge to group tacit knowledge), externalization (conversion of tacit knowledge to explicit knowledge), combination (conversion of separate explicit knowledge to systemic explicit knowledge), and internalization (conversion of explicit knowledge to tacit knowledge) (Uriarte, 2008).

The need of knowledge management arises because some information is more important to the organization as compared to other information, and it is important to manage this information in order to achieve the organizational goals. When the organization is large, it is more difficult to know who has what knowledge and to make it accessible to all the people. This is the main purpose of knowledge management (Uriarte, 2008).

There are various definitions of knowledge management. One is result-oriented definition, to have the right knowledge at the right time in right place. Another is process-oriented definition, the systematic management of a process where knowledge is gathered, shared, created and applied. Another definition, is business-oriented where knowledge management is a collaboration of business intelligence and search engines (Uriarte, 2008).

Some organizations create a specific role like “knowledge managers”. These knowledge managers help create new initiatives aiming at sharing and developing knowledge. They also take the role of consultants relating the daily tasks to long term goals. They are tech-savvy and updated with latest information in technology. They also promote an environment suitable for knowledge sharing (Kubr, 2002)

Link between consulting and knowledge management

Knowledge is one of the core assets of any business or organization. A business generates its value through knowledge. Current economic models in business focus on the fact that value only comes from physical assets or outputs that can be physically measured. Recent developments show that organizations have been shifting their focus onto intellectual capital such as employee capabilities, company relationship with customers and stakeholders in order to create value. Consulting should be seen an interactive tool for transfer of knowledge between people (Kubr, 2002).

There are three major factors that encourage the use of knowledge in consulting. First is urgency of the issue. Whenever clients are in an urgent need to solve the issue, to overcome the challenges they are facing, they often tend to accept and utilise the knowledge the consultant has to provide. On the other hand when the urgency to reach to the solution is low, or even when the client is unaware of the problem, there is very little knowledge that is being transferred or used. Second factor is the way clients and consultants perceive each other. If the clients perceives the consultant as an expert, organized and credible there are chances that knowledge is more likely to be shared. On the other hand if the client perceives the consultant as more communicative, open-minded and interactive, again there are more chances of knowledge transfer. Third sharing of knowledge is usually facilitated at various stages of consulting to promote client collaboration and participation (Jacobson, Butterill, & Goering, 2005).

Advantages of using Knowledge Management in an organization includes effective operations. The organization is able to utilize time effectively, extra work is avoided with improvement in quality. With the help of knowledge management the responsiveness. As the access to knowledge sources gets easier, processes like providing high quality services, solving queries in timely manner and roll out services improve. Knowledge management also plays an important role in developing core competencies and creating an environment to enhance them through values, incentives and human resource policies. Moreover it encourages to use new ideas and develop new strategies through innovation (Kubr, 2002).

Research shows that knowledge management projects fail if there is a lack of knowledge strategy or a weak anchor-link to the organization. On the other hand if there is explicit knowledge strategy overall supported by management, technology and well- defined structure, knowledge management proves to be more successful (Petersen & Poulfelt, 2010).

The task of a consultant should be developing a knowledge market. An organization has all kinds of people, knowledge buyers, knowledge sellers, knowledge brokers etc. the task of a consultant lies in enabling such an environment where all of these can interact and help the organization eventually. Enabling conditions for knowledge sharing environment not only includes technological advancements but also inculcation soft competencies like values, ethics, mission, vision. Such factors help to create an environment where people start valuing each other and share more knowledge (Kubr, 2002).

In order to understand knowledge management, it is important to understand how knowledge transferred, generates and shared within an organization.

• Yellow pages helps to identify people on basis of their competencies. People who have expertise in specific area are grouped together.
• Skill profiles and knowledge maps would group people according to what they know. The skill profiles help to define the roles in the company and the competencies required for the role .
• The collective memory would include databases for manual, and electronic books and used for high quality content.
• · Communities of practice include people of same expertise who come together. E.g. strategic marketing consultants who come together to develop a new approach.
• Centers of excellence are units in an organization with committed fill time staff who work together to solve queries, provide response and develop new strategies.

The process of developing Knowledge Management strategy involves knowledge management assessment and benchmarking. This is the first step to analyse the current situation in the organization. To understand what has been done, why it has been done and what are the strengths, weaknesses, gaps and hurdles. The second step would involve a knowledge scan, to be able to run through important procedures and data. After analysis a proper knowledge management strategy should be developed. In order to reduce risk, consultants should also focus on developing a knowledge retention strategy. For large organizations this is more helpful as they have more data to be managed. Moreover rather than depending on single technological tools, there can be a knowledge management framework. A knowledge management valuation also helps in knowing the value of the plan and how much to invest in it. Moreover a knowledge management policy would ease the governance of knowledge management policies and activities (Knoco, 2017).

The implementation paths of knowledge management is most important for consultants.

• The first path involves information management to knowledge management: IT systems , yellow pages, databases are used to develop a support structure for information.
• The second path involves knowledge managers to change agents: a knowledge manager is appointed to manage the entire network. The success mainly depends on the nature of the manager and his or her abilities to improve structure.
• Third is the problem oriented path: Here pilot initiatives are used and project leaders create solutions. The aim it to integrate management initiatives and apply a common IT structure.
• Fourth is the top-down approach: here knowledge management is handled directly by the corporate leaders. A corporate knowledge framework is developed (Kubr, 2002).

Top consulting firms on knowledge management

Bain & Company

Bain & Company define knowledge management as the process to create, access and transfer he correct information to make better decisions. It is also the process that helps transform data into actions. There are five stages of how information can be transformed into knowledge: Create, capture, organise, transfer and use. They believe that knowledge management helps to save revenue by providing the right information to the people at right time. When it come to restructuring due to an acquisition or a merger, knowledge management is highly effective. At the time of a merger, knowledge can be combined and pooled in (Horwitch & Armacost, 2002).

Some basic principles of knowledge management to be used by organizations

• Knowledge management should serve your strategy. In order to do this there has to be a well defined business strategy by the organization.
• Knowledge management should be driven from the top. E.g. in Siemens, the CEO Heinrich Von Pierer admitted that knowledge management became his biggest tool when he had to communicate with shareholders. The company’s strategic goal was that all people can access the pool of knowledge they built.
• Good knowledge management is all about brokering and not distributing knowledge. A common mistake organizations make is believing that business can be run without investing in people’s skills. Tim Savino, the head of organizational development at Harley-Davidson, mentioned that the company would check what is working and what’s not and always document their data for future use.
• Technology is a critical component for a well built knowledge management strategy. Also a clear focus on the process to achieve the strategic goal of the organization and focus on skills and people.
• There should be support from all levels in the company. In the Bain & Company’s Management tool survey, Knowledge management was positioned 19th among all the tools surveyed and about 14% of the senior employees did not utilize it. They believe Knowledge management can be beneficial to an organization only if the senior employees value it and understand its potential (Horwitch & Armacost, 2002).

Deloitte Consulting

According to Delloitte Consulting, knowledge sharing is very important as it helps to avoid knowledge barriers and helps to overcome them. Moreover different organizations have different barriers like poor knowledge sharing resources, short term plans, lack of resources in context to communication trend. The company believes that knowledge management aims at making a balance between people, process and exchange. The two major aspects of knowledge management include giving quality support and enhancing collaboration among people. This can be achieved through providing reward schemes, communicating properly and using KPI for knowledge sharing. Further, knowledge management helps to define a better road map and implement long term strategic plans (Noirhomme, 2019).

Accenture Consulting

According to Accenture, it is difficult to keep up with the voluminous amount of data flow today through knowledge management. This encourages organizations to provide employees with new information to lead them towards the strategic goals of the company. Therefore it is important to move forward leaving behind the traditional tools of knowledge management. Rather than connecting people to people organizations should focus on connecting people to knowledge. There are three steps through which companies can connect knowledge: first by creating a hub for knowledge, organizing more strategically and encouraging team and collaborative work (Accenture, 2012).

Latest Developments in different areas

• Knowledge management strategy in development sector: Just like the corporate sector, business strategies in development sect are equally valid. For any development project to achieve success, information of all stakeholders is necessary and to be able to utilize this knowledge in to define the project strategy. Knowledge management in development sector aims at sharing, gathering and using the knowledge for public goods. Development agencies do have a faster pace of acquiring knowledge. Exchange of knowledge should be promoted from successful projects and preventing similar mistakes from unsuccessful projects. Sustainable development is another growing aspect in development sector (Batra, 2017).
• Knowledge management strategy in project management: Knowledge management in context to project managements helps in achieving experiential knowledge. When there is no knowledge management system in a business, there is loss of knowledge moving from one project to another. Some of the widely used knowledge management applications for project management are know-how database, project profiles and project memory. Moreover, knowledge is divided into two major components, kernel and ephemeral. Kernel relates to the core competencies of an organization where as ephemeral relates to knowledge that is project specific (Batra, 2017).
• Knowledge management strategy in Artificial Intelligence: The aim is to identify and analyse the knowledge assets related processes and proper planning and use of the assets in order to achieve the organizational goals (Girad, 2015). AI and machine learning have started becoming an integral component of Knowledge management solution. This helps companies to identify data gaps, create new data, and improve data integrity (Fluss, 2018).

Conclusion

It is important to understand that a every business can only create a useful product when there is a respectful process followed by knowledge transfer in context of the consultant’s expertise and clients willingness. The scope of this transfer of knowledge should be determined mutually by clients and consultants (Jacobson, Butterill, & Goering, 2005). Technology plays a significant role in knowledge management, but the real hurdle lies in creating a balance between technology and people.

References

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