Requires the development of your Project for Learning (PfL) and, the examination of concepts/theories that will be used to analyse your PfL in A2. It has five steps.
The Computerization of PAYE is an advanced system of collecting taxes from civil servants. The system is complex yet the conventional method for tax collection from all taxpayers immediately they earn their salaries. With the growing number of people in government jobs and posts, the system pinpoints the tax process which directly affects the taxpayers. About 24 million taxpayers have active records, and therefore the PAYE system accurately helps the taxpayers to access their data conveniently. With the appropriate technology, the system allows for easy data entry through the use of terminals over the desks of revenue staff. It also allows them to have decentralized operations where the PAYE system revenue to follows suit (Prencipe, 2014).
The main issues of this case study; the Computerization of PAYE are broadly connected to the resources, the risks, technology, the taxpayers and the institutions. The institutions refer mainly to the vast computer system scale which was built for the proper functioning of bureaucratic structures. It combines the government functions that revolve around the departmental boundaries. With time, electronic data exchange was involved between the customers and suppliers. Again, the other issue which touches on the resources for the PAYE system, tax administration used in filing returns of staff. There are selected administrative remedies which rope in gathering a vast share of personal income tax (Baroon, 2013).
Under this assignment, the Computerization of PAYE critically analyses the main concerns which are allotment of knowledge in research, the certain context in undisclosed systems and how the PAYE system present an outlined procedure to solve problems and inconveniences in the present times (Kotlarsky, 2014). The allotment of knowledge, which can also be referred to as knowledge distribution, is essential mostly to industrial predicaments. This will provide an avenue to assess and detect the problems that bring back the developments in the industries.
The concepts underlying PAYE system are subjugated by the view that the Computerization of PAYE needs to be treated as an entity of analysis (Lousberg, 2016). This anchors the relative study on how internal processes influence the present and prospective strategies. The outcomes or results propose that researchers about managing projects require expanding the sequential scope, to analyze and develop how plans would evolve during these changing times and furthermore on the organizational structure (Lousberg, 2016). The main sections and the areas that this project will be built on is raising issues on the case of computerization of PAYE, give a critical analysis of the model and their explanation on the computerized system of PAYE (Blumenfeld 2015, p. 380). The project will also discuss in details the problems encountered during development of the project and explain the applications of the selected theories in the first assignment.
Application and explanation of the Cynefin Framework.
The Cynefin Model deliberates a broad framework that touches on the main areas in the implementation and management of knowledge. It articulates discussion on the topic of sense-making and analyzing decisions. This model when used in the computerization of PAYE, it enables us to get a clear picture of how organizations and edifying systems dissipate their procedures to avoid inconveniences (Snowden, 2014). Therefore, in the PAYE system case, the model can be explicitly applied to make a sound decision that relates to the implementation of computerization of tax process (Burston 2015, p. 10). Delays and inconveniences in the tax process are eradicated, and a faster and easier way to collect taxes becomes inevitable.
The four types of cognitive operational quadrants of the model are essential in active information processing. Thus one ordered domain, applied to detect the causes and effects of computerization of the tax process, the relationship in the linearity of the process. If there are flaws in the process, can be detected earlier and rectified. Second, the unordered domain; applied to the complex relationship. It is significant to note that the process touches a critical part of humanity regarding their salary (Blumenfeld 2015, p. 370). Hence, the complexity should be analyzed so that it does not infringe anybody. Because of its complexity, again there should be provided a period so that any challenges encountered can be understood before implementation.
To couple up the details of these quadrants, they all seek to achieve a process whose causes and impacts are known, their relationship and complexity. It is mandatory that they are understood to avoid chaos, discover patterns that are manageable so that the process of tax computerization becomes adaptable. The Cynefin model is mainly applied in the automation of the tax process because it does analyze the cognitive model (Snowden, 2014). It critically examines and explains knowledge-based components which are essential in the implementation of the PAYE systems.
Application and explanation of the Diamond Model.
The Diamond model, which is geared to international competitiveness, is known to flaw adversely in micro-economic businesses (Rugman 2014, p. 20). Accordingly, the Diamond model can be applied as an emphasis in discussion to improve the sectors; performance, growth, and competitiveness (Pancratius, 2015). Considering the impacts of each of the divisions, growth can be termed as the development and progressing of a firm. The model presents strategies that when applied the firm will experience growth both in the capital generation and amassing of profits (Rugman 2014, p. 28). Also, it helps in rendering good performances where the flaws are eradicated, and a smooth flow of industrial activities be seen. Significantly enough is the issue of competitiveness. It is well known that for any business firm to survive, it should be able to meet all the ethical concerns and be able to compete with other businesses linearly.
The Diamond model, therefore, presents new strategies that help to outnumber other businesses in productivity. Now to be precise, this model forms the fundamental variable which touches comprehensively on the way and how growth and competitiveness can be improved in the PAYE system in computerization of the tax process (Wu 2017, p. 831). The Diamond model is applied in industries including multi-domestic and international industries. The model to bridges the various tax reforms thus its application in the PAYE system is inevitable.
How the models affected the development of the computerization of PAYE.
Project development is not a simple task to pursue. It required a lot of commitment and dedicated time to do thorough research on the topic. In the development of this project; the computerization of PAYE using the Cynefin and Diamond models, the encountered drawbacks, the complexity of the domains ‘known unknown’ and ‘unknown unknowns’ of the Cynefin model presented a difficulty in the development of the computerized PAYE system (Snowden, 2014). There was a need to explain these domains which posed a challenge in understanding the dynamics of the process.
A vast majority regards to project development and writing a simple endeavor until one gets involved in it. As far as the models provide a knowledge-based framework for sense-making and competitive fields of research and improvement in the computerized PAYE system, one would underrate them, which affects the computerization of the tax process several (Snowden, 2014). At later stages, if the early strategies are perused, they may disconcert the public who are the taxpayers. The output of the models created a tremendously valuable contribution in the decision-making process. Bringing on board new information on the PAYE system, which directly affects the taxpayers, requires reasonable procedures where those who get involved would find it easy to make the follow-up.
Using the lone Diamond model was not good enough since inadequate to integrate multi-national accomplishments. Therefore, a great need to concentrate on the double Diamond model, which has significant extensions. Furthermore, the two models presented a strengthened taxation process with receptiveness, culpability and led to enhancements in the industrialized dimension. In the development of this complex project, action impacts expressed as uncertain and ambiguous in relations to data sufficiency. The well-known rudimentary project approaches; knowledge, instructional and selections. These terms have the notion of situated learning with profound effects upon how project management concerns. It is worth noting that knowledge is acquired through formalized procedures accepted by all and so the development of complex projects should follow the laid down systems so that it is not out of context.
Knowledge management in complex projects
KM Strategies
The KM strategy has become essential in the distribution of goods and services during this age hastened by servitization, globalization, and digitalization. For maximum growth and prosperity, the key resources that the organization owns should be used wisely. Definite dogmas and support services are required in the vast category of organization, which include knowledge-intensive service oriented, resource-based and product-based organizations to improve the management of knowledge (Wu 2017, p. 833). KM strategies provide a framework for organizations to come up with new ideas, share prevailing expertise and also in the dissemination of these ideas among its workers and stakeholders, the most important being the organizations’ employees. Knowledge is a significant constituent of any business plan. Due to limitless quantities of information knowledge application is a “must have” and no longer “nice to have” for the progress of any business (Sung 20116, p. 260). To get the best of the application necessitates semantic technology which encompasses the shades of human language and communication (White 2014, p. 7).
There are four primary applications of knowledge management which transform the ability to make the most of information when they are motorized by cognitive technology (Wu 2017 p. 833). These applications include one strong semantic search engine which reaches all the enterprise content and re-claims the precise pieces of information that one will be expecting, and this search engine is used with the required speed that is as well planned from the usual search from the internet (White 2014, p. 9). It is through this search engine (intranet) that business firms and companies make information available to all its clients. There will be easy access and retrieval of data. The next knowledge management strategy application is a proper cataloging and customized taxonomy. This implies that, due to the diverse company vocabulary, documents, tools and product names an active enterprise search is essential. This would create a proper understanding of the meaning and help differentiate information in its contextual settings and uses.
The third application is about entity extraction. Entity extraction is a remarkable application that structures unstructured information making it readable to machines. Through the identified contented entities, it’s possible to reveal where what and from who specific data sets are originating from. Finally, knowledge management strategy can be applied in analyzing feedback from customers. Customers form a vital link between a business and other businesses in the surroundings. They are the primary determinants of the success of any business since a company cannot consume its goods and services. Knowledge management strategies are therefore applied to assess customers’ point of view about the business firm, competitors, the brands and the products and services that the business offers.
Learning in complex projects.
Learning is a process of knowledge acquisition and practice that is achieved through repeated activities to gain experience. Elias and Merriam in their book; Understanding e-learning skills in practice over philosophies in practice state that ‘theory without practice leads to an empty idealism, and action without philosophical reflection leads to mindless activism’ (Syejyig 2015, p. 280). This statement implies that any developed theory of knowledge needs to be applied directly both to the local and international communities to solve problems and make precise corrections without which such knowledge becomes useless. Upcoming knowledge should be in both theory and practice. They should bring about new ways and strategies to deal with everyday problems and better ways of doing things.
The theory on learning in complex projects tends to explain learning processes, which should take place for complex project business to grow the competencies in adopting new technology. A project can be defined as a deliberate endeavor that contains several tasks and activities geared toward coming up with a specific result. To achieve the desired outcome in a project the project tasks and activities are integrated into methods and processes, which work in coordination within the set period. Due to the diversity in information technology and computing systems, there is a growing demand for projects, which has resulted in complex projects. Learning in complex projects applications are found in all areas of life. Some of the recent studies learning in complex projects, which is a subsection of organizational education, are one of the best ways in which firms advance the capacities to increase their performance. According to (Davies, 2015), the central problematic of maintaining project competence is that unless knowledge and experience gained on a plan may be dissipated and the similar faults are repeated.
The classroom context, learning uncertainties are countered through the knowledge acquired on learning in complex projects, factors such as difficulties in learning, motivation, barriers to active education and the like through appropriate technology are examined so that knowledge is sustained. Again in prominent organizations and business firms management tasks become complex. Four main uncertainties include market, organizational, technical and resource (Rice 2015, p. 58). The market uncertainty refers to the extent to which the product and services satisfy the customers, the changes in customer’s tastes and fashion, product branding and interaction forms between products and customers. Organizational uncertainties can be termed as persistence and the organizations’ resilience, the organizations’ internal and external changes in partnership and unpredictability prospects and metrics (Rice 2015, p. 60). The third uncertainty, technical communicate the comprehensiveness and precision of logical data to the extent that product stipulations can be instigated (Schwalbe, 2015). Finally is the resource-based uncertainties that stance hitches when the project teams strive endlessly to acquire the desired resources. When all these uncertainties are discussed and analyzed a proactive learning plan can be designed that will enable the team managers to deal with the difficulties and emulate the characteristics of an innovative breakthrough project.
The complexity of complex projects has debatably increased, and it is surprising that there is no single book written to explain them. Several studies have affirmed that business firms and organization benefit profoundly over projects. According to (Prencipe 2014, p. 1378), numerous firms generate organizational learning mechanisms as considered attempts to capture the experience gained through projects. Some of the corporate learning mechanisms are the established, necessary preparations that enable organizations to collect methodically, analyze, store, disseminate and use information (Dutta 2015, p. 298).
The different aspects of this theory are that projects bring people together in an organic, adaptive and flatter structure than the hierarchical and mechanistic management structures used in functional organizations (English, 2013). The comparison drawn from evidence from scientific equipment and medical industries show that complex projects for learning are more effective in producing CoPS than traditional and matrix organizations (Pancratius, 2015). Through complex projects for learning, its tools can be used in identifying the strength and weaknesses of the project enterprise. Projects for learning organizations are capable of coping with the unpredictable changes in consumer needs and emerging design properties.
Conclusion
The current world of science is characterized by significant advancements in technology that has resulted in the creation of new ideas and knowledge in all aspects of life. The list of the project developed is endless for example in aerospace, marine, firearms, education, agriculture and the like. One of the development includes projects for learning which also known as project-based learning. These cut across all industrial sectors, and they have helped gather extensive information through research. They are not a one-man development and therefore attract a group of individuals says from a given business firm who work and struggle collaboratively and bring new methods and ideas to improve the efficiency and performance of the business.
References
Barron, B. J., Schwartz, D. L., Vye, N. J., Moore, A., Petrosino, A., Zech, L., & Bransford, J. D. (2016). Doing with understanding: Lessons from research on problem-and project-based
Blumenfeld, P. C., Soloway, E., Marx, R. W., Krajcik, J. S., Guzdial, M., & Palincsar, A. (2015). Motivating project-based learning: Sustaining the doing, supporting the learning. Educational Psychologist, 26(3-4), 369-398.
Burston, J. (2015). Twenty years of MALL project implementation: A meta-analysis of learning outcomes. ReCALL, 27(1), 4-20.
Davies, A., and Hobday, M. (2015) The Business of Projects, Cambridge: Cambridge University Press (Ch 7: Learning in the project business).
Dutta, D., & Bose, I. (2015). Managing a big data project: the case of ramco cements limited. International Journal of Production Economics, 165, 293-306.
English, M. C., & Kitsantas, A. (2013). Supporting student self-regulated learning in problem-and project-based learning. Interdisciplinary Journal of problem-based learning, 7(2), 6.
Gold, A. H., Malhotra, A., & Segars, A. H. (2015). Knowledge management: An organizational capabilities perspective. Journal of management information systems, 18(1), 185-214.
Kotlarsky, J., & Oshri, I. (2014). Social ties, knowledge sharing and successful collaboration in globally distributed system development projects. European Journal of Information Systems, 14(1), 37-48.
Lousberg, L. H. (2016, April). Towards a theory of project management. In Proceedings SCRI Symposium (pp. 03-04)
Osborne, J., Simon, S., & Collins, S. (2015). Attitudes towards science: A review of the literature and its implications. International journal of science education, 25(9), 1049-1079.
Pancratius, J. (2015). A study on the lack of scale within the hedge fund industry in Canada (Doctoral dissertation, MANCHESTER BUSINESS SCHOOL).
Prencipe, A., & Tell, F. (2014). Inter-project learning: processes and outcomes of knowledge codification in project-based firms. Research Policy, 30(9), 1373-1394.
Rice, M., O’Connor, G.C., and Pierantozi, R. (2015) Implementing a learning plan to counter project uncertainty, MIT Sloan Management Review, 49(2): 54-62.
Rugman, A. M., & D’cruz, J. R. (2014). The” double diamond” model of international competitiveness: The Canadian experience. MIR: Management International Review, 17-39
Schwalbe, K. (2015). Information technology project management. Cengage Learning.
Snowden, D. (2014). Cynefin, a sense of time and place: an ecological approach to sensemaking and learning in formal and informal communities.
Sung, Y. T., Chang, K. E., & Liu, T. C. (2016). The effects of integrating mobile devices with teaching and learning on students’ learning performance: A meta-analysis and research synthesis. Computers & Education, 94, 252-275.
Svejvig, P., & Andersen, P. (2015). Rethinking project management: A structured literature review with a critical look at the brave new world. International Journal of Project Management, 33(2), 278-290.
White, D., & Fortune, J. (2014). Current practice in project management—an empirical study. International journal of project management, 20(1), 1-11.
Wu, W. W. (2017). Choosing knowledge management strategies by using a combined ANP and DEMATEL approach. Expert Systems with Applications, 35(3), 828-835
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