pjm400 mod2 peer response discussion post 200 words each

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Please reply to both POST1: and POST2: in at least 200 words each

Original discussion post:

Module 2: Discussion Forum

15 15 unread replies. 22 22 replies.

Explain the process of using data analysis during the Plan Project Management process (please note that data gathering and data analysis are two of the tools and techniques that the PMBOK® Guide identifies for Plan Procurement Management. See Part 1, Section 12.1.2 to find out more).

  • What are some of the positive and negative outcomes if data analysis is not conducted properly during the Plan Project Management process?

POST1:

The significance of data analysis for a project manager should never be underestimated for the collection and analyzing of industry data serves many purposes, such as supporting informed decision making, certifying compliance with business policies, confirmation of proper function of existing controls, reconciliation of statistics across contrasting systems, and quick utilization of system solutions (Kim, & Ki-Seok Choi, 2018). There are two data analysis techniques used when creating the project procurement management plan. The make-or-buy analysis that involves comparing the internal costs of providing a product with the cost of outsourcing; and source selection which is a set of features desired by the buyer which a seller is required to meet or exceed to be selected for a qualifying vendor contract (Baily, Farmer, Crocker, Jessop, & Jones, 2015).

The impact from this data is critical to any project’s planning functions therefore analysis must be well directed. The initial approach to analyzing data in project management is collecting information from various sources and converting it into a presentable format for demonstrating and making estimates. This involves collecting and recording data from business processes, including quantitative data such as time sequences, occurrence rates, and extent of deviations of processes from the standard mean; and qualitative data such as customer complaints, incidence reports, daily status reports, and more. Then next step includes examining the collected data to correct errors, remove discrepancies, and eliminate unnecessary and unrelated data. The actual data analysis is either an exploratory approach that discovers something new, such as trends or probabilities; or a confirmatory approach that validates assumptions and establishes controls (Kim, & Ki-Seok Choi, 2018).

The performances of the analysis are decided by the finishing results. If the results achieve the reduction of expenditures or costs, improve product and service quality then the analysis was conducted well and successfully. If data analysis results damage the project due to missing scheduled deadlines and overage on budget, or poor quality performance or overall failure then the analysis was conducted poorly (PMI, 2017).

Reference

Project Management Institute. (2017). A guide to the project management body of knowledge (PMBOK® Guide) (6th ed.). Newton Square, PA: PMI Publications

Baily, P., Farmer, D., Crocker, B., Jessop, D., & Jones, D. (2015). Procurement, Principles & Management (11th ed). United Kingdom: Pearson (Intl) Inc

Kim, Jong Won, Young Jun Yoon, Minwoo Park, and Ki-Seok Choi. 2018. “Analysis of Privacy Protection for Joint Use of National R&D Project Evaluation History Data.” Indian Journal of Public Health Research & Development 9 (8): 1005–9. http://search.ebscohost.com/login.aspx?direct=true&db=edsijc&AN=diva.ijphrd.9.8.168&site=eds-live.

POST2:

Good Morning Class,

Data Analysis during the Plan Project Management Process

During the planning phase of project management, data analysis must be done to fully understand the next steps. This process is often called make-or-buy analysis which is exactly what it sounds like. PMI states, A make-or-buy analysis is used to determine whether work or deliverables can best be accomplished by the project team or should be purchased from outside sources (2017). In a previous company, I worked with we manufactured and sold many different types of food. As the company grew we acquired a few different plants where we could manufacture our products, as well as giving other companies the option to co-pack or pay us to pack products. In one facility we manufactured all of our sandwiches and what we called Anytimers, which are just Lunchables that meet USDA nutritional guidelines for K-12 Schools. During the operation of this plant, we were approached by Walmart and we co-packed their Lunchable style options for them. This all being said both our company along with Walmart needed to employ the analysis of make-or-buy to see what would be more profitable for each perspective company.

Some positives would be: Reduction of cost, creating efficiencies, enhanced and quicker decisions. All of these would create a perceived increase in customer satisfaction (Alexander, 2017). Alternatively, some negative outcomes could be added cost, struggling to meet deadlines, both could result in not meeting project requirements that would damage the reputation of the company (Six,2019)

References:

Alexander, M. (2017, March 20). How to use data analytics to improve project outcomes. Retrieved February 17, 2020, from https://www.cio.com/article/3182352/how-to-use-dat…

Project Management Institute. (2017). A guide to the project management body of knowledge (PMBOK® Guide) (6th ed.). Newton Square, PA: PMI Publications

Six, T. (2019, February 13). 7 Impacts of Poor Risk Management (And What You Can Do About Them). Retrieved February 17, 2020, from https://tensix.com/2017/03/7-impacts-of-poor-risk-…

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