XYZ Global Pvt. Ltd decided to implement the CRM project using their high end product of project management methodology. However, due to complexity and budget of the project requires in-depth analysis of critical factors for CRM implementation and support of tip management. Through my research and compliance with industry constraints, the project management, change management and sponsorship is crucial in getting green signal for the implementation of CRM project (Reinartz, Kraft & Hoyer, 2004).
User adoption is generally highlighted as key challenge in success of CRM project. Market analysis shows that 47% of the company finds that inadaptability of the end-user with CRM applications put ...view middle of the document...
Statistics and Probability Tutorial(n.d.) states that Bayes’ theorem looks appropriate in the context as it provides logical inference to calculate the degree of confidence based on already gathered evidence. This evidence is best stated in terms of quantitative as well as qualitative probability, where the probability is based on evaluating opinions and information, then estimating this data and finally assigning probability to the outcomes. Therefore, Bayes’ theorem is best used for the purposes of predicting confidence levels for implementing CRM project, predicting the success of an implementation, and or predicting a project’s failure if there is said lapses in project management methodology.
There are other methods also to analyze the market data which can be useful. Hypothesis testing also provides reasonable statistical criteria to evaluate the result of the observation. But it is more suitable for comparison of different products. But Bayes’ theorem provides better insight as it measures the result based on the subjective evidence of the CRM product. If one result is already established, it measures the evaluation of other results. In our CRM project scenario, for example, hypothesis testing could be used if one professional body said the probability of a project management methodology being success is .5, while another body stated that the probability of a project management methodology being success is .35. Since our variables are not defined, it is more effective to use Bayes’ theorem.
With the appropriate theorem chosen, I continued to gather my data.
After contacting the CRM user, consultant and others, I found out that 47 % of CRM projects fail due to poor project management.
I then set up the variables to examine the probability of.
Cruise 1 = C1 = failed due to project management methodology
Cruise 2 = C2 = not failed due to project management methodology
In turn, this helped me decide whether I should suggest the implementation of CRM.
This is what I knew:
• the dates of the project implementation within next 2 years
• the probability of project being failed by a project management methodology is 47%; (P (C1) = being failed by a project management methodology = .47).
So, prior probability of a project not being affected is P(C2) = .53
The CRM LANDMARK historical evidence cross-referenced showed that if there is established project management methodology in the firm there was a 16% chance the project would fail. In other words, B = established project management methodology is present (as indicated by the market research). This is written as P (B|C1) = .16.
The CRM research analyst additionally stated that even though a...