Week 6 : Case study Based on article

The case study applies a processual analysis to the implementation of Customer Relationship Management system from a knowledge management perspective to a contemporary situation within a City Council. The main focus of the article is sub-cultures, psychological contracts, how tacit knowledge is surfaced and shared, and with what effects on implementation. David Finnegan and Leslie Willcocks entitled “Knowledge Issues in the Introduction of CRM Systems: Subculture Interactions, Tacit Knowledge sharing and Psychological Contracts”. Their article specifically discusses the knowledge management issues in CRM implementation in Birmingham City Council (BCC).

Issues leading towards the failure of BCC

• Political issues
• Lack of end-user support
• Internal communication
• User involvement
• Data accuracy and consistency
• User training (Lack of training to new staff)
• Selection of Vendor
• Lack of management support
• Loosing of key staff

To conclude, knowledge-sharing culture is critical in implementing CRM system. Thus, organisations implementing CRM should have knowledge management initiatives in place in order to facilitate knowledge sharing between employees, improve staff retention, and prevent knowledge loss when experienced staffs leave the organisations.

Week 5: Data mining

Data mining is powerful tool in finding large set of data. The article discuss about techniques of data mining such as Decision tree, Neural network and CART methodology. Comparing all the three techniques it seems that adoption of decision tree is the most simple technique, but it is not as useful as neural network.In case of decision trees result can be derived according to the design of the tree, so if there is no adequate design of the tree than the result will be different. The back point of decision tree is, one decision tree can find out one patter. There are different splitting rules which could lead to different number of terminal tree nodes, that may also lead to different results from the same data.

A part from decision tree, neural network is one of the other data mining techniques which has been frequently used. Neural network could assist experts in credit card risk assessment, it is generated as a black box; users just feed the training data to construct it and testing data to exam it. The major difference between both the techniques is decision tree are simple and easy to understand, but on other side neural network is bit complicated. With Neural Network, a considerable amount of time and money need to be spent in training as it would require the analyst to have background understanding of Neural Network such as:

How to best design its algorithm ?
How to maintain to get the accurate outcome?

From the article it is seen that both the tools had been widely adopted by the organization but than also it is necessary to have a further research on both the techniques to get an accurate results.

Week 4: Data mining and Knowledge Discovery

‘Data mining is the process of exploration and analysis, by automatic or semiautomatic means, of large quantities of data in order to discover meaningful patterns and rules’. (Berry & Linoff 2000) In data mining, data sampling is very important. Data mining is not only automatic process but it is automatic as well as manual process which involves human interaction, because without human interaction and participation organization cannot build the software that is required for gathering the useful information for data mining. Algorithms pattern for proper interaction with organizations data mining, data warehousing is very important. In the presentation of Raman lyer, the author believes that data mining is discovered due to the major gap between disk capacity and the process ability to maintain the data. Data mining can be used for classification, estimation, segmentation, association, forecasting, text analysis and advanced data exploration. Lecturer in the lecture gives an idea about Data mining and Knowledge discovery which can be used in cross pointing the organization. It is said that data mining is the part knowledge discovery. To put in nutshell, Knowledge discovery are more than data mining. People can discover knowledge from various sources as it is and end product of a chain. It is believed that we cannot use the information unless it is not accurate or to the point, and if we cannot use the information that it is not a part of knowledge. Thus the information which is useful can only be said as knowledge. To increase the knowledge any one needs information and data. In short, data mining can also be seen as part of knowledge discovery. This is because knowledge can be gain through different methods, and data mining is one of the methods for gaining the knowledge. Thus in my opinion data mining plays an important role.

Week 3 seminar

In the last week lecture an interested seminar presented by Barry Schwartz, author of The Paradox of Choice discuss about the choice of the customer by giving the best examples. The main focus of the seminar is to convey the message to the industry that by producing a variety of goods will not fulfil the customer needs, along with the variety there should be quality and service which plays a major part for the customer satisfaction. As per the tendency of human nature it can be said that smaller the choice better will be the selection for the product. More option there are, the easier it is to regrate any thing at all the disappoint about the option that you choose. When there are lots of alternative it is easy to the amount of alternative you regret, that make it less satisfy than the one which you have chosen. Even though a person chooses the best from the available option, he/she will never get satisfy, because the expectation of the person will be different from the one they choose. For example buying jeans, in past jeans come in one flavour so there is no expectation, but now when there are many flavours there is more expectation. Human expectation is too high in today’s life; the secret of happiness is low expectation. When there is one style of jeans available you can blame the whole world because there is no other option, but when there are multiple options and person is not satisfied of the thing he/she had purchased than they are the only one who are blamed. Thus it can be said that higher the expectation, higher will be confusion for person.

Now a days as the expectations of the person increases the need for the CRM also increases because it helps in decreasing customer confusion. For example a customer want to buy a mobile phone there are many options and plan available, which makes customer confuse even though he/she is sure which mobile he wants to buy and for what plan, at this point of time CRM is helpful for taking the decision. If the product is not good or suitable for the customer, still CRM tries to convince the customer, it inturns result in to waste of time and money.

In conclusion, a good understanding of the role of CRM is critical in marketing the products to their customers, which is clearly depicted in the example of mobile phone. Thus, CRM is rubbish but it is helpful in increasing customer satisfaction.