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This part follows on from the previous Intelligent Information Inc Assignment 1 Case Study. Now that the project sponsor has approved your Initial Project Plan (delivered in Assignment 1) and associated documents, you may proceed to the planning phase of the project by providing a formal project report for the project sponsor based on the following project planning documents. You may make any appropriate assumptions needed to enable the successful completion of the project. Again, make these assumptions explicit in your report. Use screen shots from your MS Project file. It is a mandatory requirement that you use MS Project. It should be available in the lab. Here are the required sections:

1. Gantt chart
2. Network Diagram (Critical path diagram)
3. Identify at least six milestones for this project using SMART criteria.
4. Resources table
5. Project budget, as calculated by MS Project
6. RACI Table
7. Identify 6 potential risks for this project and write the risk register for all of them. Ensure one of your risks is a positive risk.
8. Construct the Probability/ Impact Matrix for those 6 potential risks.

The project plan is based on aspects related to implementation of big data into existing infrastructure of the Intelligent Information Inc. The main purpose of this project is to hire of consultants to support selection of analytic packages of big data. The report analyzes the schedule of the project, milestones, resource plan, and budget plan and identifies possible risks into the implementation of big data. Implementation of big data enhances internal as well as external operations to ensure about the performance of organization.

Milestone activities

Specific

(S)

Measurable (M)

Achievable

(A)

Relevant

(R)

Time bound (T)

Planning phase

The goal of this phase is to define the business case and technical specifications of big data implementation.

Hire of consultants to support selection of analytic packages of big data

There is 100% increase into the implementation work of big data into the organization.  

It increases productivity of the company by 9% by implementing of big data.

It takes of 76 days to complete the planning phase.

Project specifications phase

It is required to have big data implementation and installation process.

There is enhancement of the loyal customers to implement of Big Data analytics within the IT infrastructure of the company.

Due to installation of big data, the profitability of Intelligent Information Inc. is raised by 10% within 2 months.  

There is providing of analytic package which is suitable for needs as well as requirements of organization.

It takes of 38 days to complete the project specifications phase.

Implementation phase

There are modifications into the implementation phase and verification of the equipments.

There are establishment of network and IT infrastructure.

There is achievement of 20% of the organizational goals accomplished by the organization.

There is providing of analytic package which is suitable for needs as well as requirements of organization.

It takes of 52 days to complete the implementation phase.

Testing phase

There is testing of the plan and review of the project plan.

The proposed big data analytic system is properly tested ad per the business requirements.

There are 99% successes into implementation of the big data into the organization.

It allows for enhancement of internal as well as external operational activities to enhance the organization’s performance.

It takes of 52 days to complete the testing phase.

Risk management phase

Identification and mitigation of project risks

Each of the business objectives are delivered to higher quality along with better standard.

There is 100% prevention of the risks while implementation of system is done.

The risks are mitigated properly by assessment of risk management plan.

It takes of 39 days to complete risk management phase.

Closure phase

There is evaluation of project success and final review.

All the project phases are properly completed on time.

There is 100% completion of each of the tasks after starting to work on other tasks.

There is suitable implementation of the big data analytic package as per requirements of the organization.

It takes of 29 days to complete closure phase.

Resource Name

Type

Initials

Max. Units

Std. Rate

VP of operation

Work

V

100%

$500.00/hr

VP of Marketing

Work

V

100%

$550.00/hr

Risk Manager

Work

R

100%

$390.00/hr

Project Sponsors

Work

P

100%

$400.00/hr

IS Project Manager

Work

I

100%

$450.00/hr

Customers

Work

C

100%

$450.00/hr

Big Data Vendor

Work

B

100%

$400.00/hr

IT Department

Work

I

100%

$400.00/hr

Employees

Work

E

100%

$400.00/hr

Task Name

Duration

Resource Names

Cost

Implement the Big Data within the Intelligent Information Inc.

133 days

$1,500,000.00

   Planning phase

76 days

$431,120.00

      Define the business case

5 days

IS Project Manager, IT Department, Project Sponsors

$50,000.00

      Define the business objectives

6 days

IS Project Manager, Project Sponsors

$19,200.00

      Identify the project stakeholders

8 days

IS Project Manager, Risk Manager

$26,880.00

      Define the technical requirements

27 days

$270,000.00

         Hardware requirements

15 days

Big Data Vendor,  IS Project Manager, IT Department

$150,000.00

         Software requirements

12 days

Big Data Vendor, IS Project Manager, IT Department

$120,000.00

      Create of business value assessment

8 days

Customers, IS Project Manager

$65,040.00

      Milestone 1: Completion of planning phase

0 days

$0.00

   Project specifications phase

38 days

$140,400.00

      Improvement of big data system

15 days

Big Data Vendor, IS Project Manager, IT Department, VP of operation

$52,000.00

      Improvement in installation process

12 days

IS Project Manager, IT Department

$40,000.00

      Understand the business requirements

11 days

IS Project Manager, IT Department

$48,400.00

      Milestone 2: Completion of project specifications phase

0 days

$0.00

   Implementation phase

52 days

$168,400.00

      Start to implement as per business goals

14 days

IS Project Manager, IT Department

$46,000.00

      Modify the implementation stage

17 days

IS Project Manager, IT Department

$69,600.00

      Verify the equipments required to implement big data

12 days

Big Data Vendor, IS Project Manager

$52,800.00

      Milestone 3: Completion of implementation phase

0 days

$0.00

   Testing phase

52 days

$330,400.00

      Start testing

14 days

IS Project Manager, IT Department, VP of Marketing, VP of operation

$186,800.00

      Report on testing of plan

8 days

IS Project Manager, IT Department

$47,200.00

      Review the test plan

12 days

IS Project Manager, IT Department

$38,400.00

      Analyze test results

14 days

Employees, IS Project Manager, IT Department

$58,000.00

      Milestone 4: Completion of testing phase

0 days

$0.00

   Risk management phase

39 days

$146,400.00

      Identify the risks

7 days

IS Project Manager, IT Department, Risk Manager

$49,440.00

      Address risks to manager

12 days

IT Department, Risk Manager

$37,920.00

      Mitigate the project risks

9 days

IS Project Manager, Risk Manager

$38,880.00

      Risk register

5 days

IS Project Manager, Risk Manager

$20,160.00

      Milestone 5: Completion of risk management plan

0 days

$0.00

   Closure phase

29 days

$283,280.00

      Evaluate project success

9 days

IS Project Manager, VP of Marketing, VP of operation

$108,000.00

      Final review

11 days

IS Project Manager, Project Sponsors, VP of Marketing, VP of operation

$106,400.00

      Sign off the project documents

6 days

Customers, IS Project Manager, Project Sponsors, Risk Manager, VP of Marketing, VP of operation

$68,880.00

      Milestone 6: Completion of closure phase

0 days

$0.00

Roles

VP of Operation

VP of Marketing

Risk Manager

Project Sponsor

IS Project Manager

Customers

Big Data Vendor

IT Department

Employees

Monitor and guide company's operations

R

-

C

I

R

-

-

-

-

Implementation of big data

R

A

I

R

R

-

-

-

-

Analyze the market

C

R

C

I

-

-

-

I

I

Identify the risks and threats

-

C

R

-

R

R

-

-

-

Analyzing the risks

-

-

R

C

I

R

I

C

I

Collect funds for project

-

-

I

R

I

R

-

-

-

Execution of the project

C

-

-

-

R

R

-

I

I

Deliver the constraints of project

I

I

I

R

R

-

C

I

I

Consume the products and services

-

-

-

R

C

R

R

C

I

Provide analytic package

R

I

R

-

-

-

R

-

-

Establishment of network and IT infrastructure

R

-

R

-

-

-

-

R

-

Accomplish of operational activities

R

A

C

-

I

R

I

C

R

Provide high quality services and policy complies

R

-

R

I

C

-

R

I

R

Provide quality services

R

-

-

C

I

-

R

A

-

R- Responsible

A- Accountable

C- Consulted

I- Informed

Impact

Trivial

(1)

Minor

(2)

Moderate (3)

Major

(4)

Extreme

(5)

 

 

 

 

 

Probability

Rare

(1)

Unlikely

(2)

Moderate

(3)

Likely

(4)

Very likely

(5)

Green- Low risk level

Orange- Medium risk level

Red- High risk level

Conclusion

It is concluded that the project is based on implementation of the big data analytics into the IT infrastructure of the Intelligent Information Inc. so that the project is used to hire of consultant will support selection of the analytic packages of Big Data. The project work is being delivered with expected schedule as well as budget. The purpose of this study is to enhance the loyal customers for reduction of any errors. The system allowed enhancement into internal as well as external operational activities to ensure that performance of organization is enhanced. There are requirement of internal needs for the founding of both network as well as IT infrastructure.

References

Boholm ÅM Prutzer, 'Experts’ Understandings Of Drinking Water Risk Management In A Climate Change Scenario' (2017) 16 Climate Risk Management

Hornstein H, 'The Integration Of Project Management And Organizational Change Management Is Now A Necessity' (2015) 33 International Journal of Project Management

Joslin R Müller, 'Relationships Between A Project Management Methodology And Project Success In Different Project Governance Contexts' (2015) 33 International Journal of Project Management

Kousky CH Kunreuther, 'Risk Management Roles Of The Public And Private Sector' (2018) 21 Risk Management and Insurance Review

Samset KG Volden, 'Front-End Definition Of Projects: Ten Paradoxes And Some Reflections Regarding Project Management And Project Governance' (2016) 34 International Journal of Project Management

Whitney S, 'A Fern In Amber: Risk Management In Research With Humans' (2015) 17 Risk Management

Zwikael O, 'International Journal Of Project Management Special Issue On “Project Benefit Management”' (2016) 34 International Journal of Project Management

Andersen EK Grude, 'Our Tribute To Rodney – And The Importance Of Goal Directed Project Management' (2018) 36 International Journal of Project Management

Botchkarev AP Finnigan, 'Complexity In The Context Of Information Systems Project Management' (2015) 2 Organisational Project Management

Davidson Frame J, 'Reconstructing Project Management' (2014) 45 Project Management Journal

Focacci A, 'Managing Project Investments Irreversibility By Accounting Relations' (2017) 35 International Journal of Project Management

Wearne S, 'Evidence-Based Scope For Reducing “Fire-Fighting” In Project Management' (2014) 45 Project Management Journal

Yun S and others, 'Measuring Project Management Inputs Throughout Capital Project Delivery' (2016) 34 International Journal of Project Management

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[Accessed 29 February 2024].

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