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Project Management Systems Approach To Planning

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Question:

Disucss about the Project Management Systems Approach To Planning.

 

Answer:

Introduction

This project is based on the purchase and implementation of a Big Data Analytics package for Intelligent Information Inc that will enhance the existing business operations and marketing policies of the company (Marz and Warren 2015). The implementation of the Big Data Analytics Package has been suggested by the CIO due to a number of reasons. Firstly, the Big Data Analytics Package will be able to provide an integrated platform on which all the various required operations from different stakeholder groups can be performed all at once. This will replace the need for separate platforms for each department that are not only hard to manage but also have too much maintenance and management costs (Wamba et al. 2015). Secondly, with the new analytics platform almost of the operations will become automated and not further require too much human interference. This will also reduce the operational errors caused by the manual management systems.

Project Charter

Project Background

The CIO of Intelligent Information Inc wants to deploy a suitable big data platform that will help various stakeholder groups of the company. Some of the important requirements include identification of potential customers, improvement of service, management and maintenance of IoT sensors, fraud detection and prevention and others (Dhamodaran, Sachin and Kumar 2015). The main challenge of the development is that all of the requirements should be met such that all of these should be integrated within one common platform. In other words, there should not be separate systems for the different requirements; there will be one common platform through all of the required operations can be performed.

Project Scope Statement

Based on the background and requirements of the project, the project scope can be determined as follows.

Scope 1 – Purchase and implementation of a Big Data Analytics Package is within the scope of the project.

Scope 2 – Integration of all stakeholder groups is within the scope of the project.

Project Objectives

The objectives of the project are as follows.

  • To hire a suitable consultant for helping to identify best analytics package
  • To recruit project team consisting of technical experts
  • To procure sufficient budget for the project
  • To deploy the new Big Data Analytics Platform
  • To train the existing employees to use the system
 

Implementation Plan

Project Schedule

The estimated project schedule is shown in the following table.

Task Name

Duration

Start

Finish

Implementation of Big Data Analytics

142 days

Mon 02-04-18

Tue 16-10-18

   Project Initiation

10 days

Mon 02-04-18

Fri 13-04-18

      Appointment of Project Manager

2 days

Mon 02-04-18

Tue 03-04-18

      Listing of Project Requirements

2 days

Wed 04-04-18

Thu 05-04-18

      Meeting between Primary Stakeholders

1 day

Fri 06-04-18

Fri 06-04-18

      Preparation of List of Deliverables

1 day

Mon 09-04-18

Mon 09-04-18

      Consultation with Big Data Expert

2 days

Tue 10-04-18

Wed 11-04-18

      Finalization of Plan

2 days

Thu 12-04-18

Fri 13-04-18

   Project Preparations

32 days

Mon 16-04-18

Tue 29-05-18

      Preparation of Project Charter

5 days

Mon 16-04-18

Fri 20-04-18

      Determination of Project Scope

2 days

Mon 23-04-18

Tue 24-04-18

      Determination of Project Objectives

1 day

Wed 25-04-18

Wed 25-04-18

      Preparation of Project Schedule

2 days

Thu 26-04-18

Fri 27-04-18

      Estimation of Project Budget

3 days

Mon 30-04-18

Wed 02-05-18

      Assign Roles to Stakeholders

4 days

Thu 03-05-18

Tue 08-05-18

      Preparation of Stakeholder management Plan

2 days

Wed 09-05-18

Thu 10-05-18

      Analysis of Potential Risks

4 days

Fri 11-05-18

Wed 16-05-18

      Preparation of Risk management Strategy

3 days

Thu 17-05-18

Mon 21-05-18

      Procurement of Project Budget

2 days

Tue 22-05-18

Wed 23-05-18

      Allocation of Duties and Roles

2 days

Thu 24-05-18

Fri 25-05-18

      Deployment of Project Teams

2 days

Mon 28-05-18

Tue 29-05-18

   Project Execution

88 days

Wed 30-05-18

Fri 28-09-18

      Purchase of Necessary Hardware

15 days

Wed 30-05-18

Tue 19-06-18

      Purchase of Necessary Software

10 days

Wed 20-06-18

Tue 03-07-18

      Installation of Hardware and Software

15 days

Wed 04-07-18

Tue 24-07-18

      Installation of Big Data Platform

5 days

Wed 25-07-18

Tue 31-07-18

      Purchase of Big Data Analytics Package

4 days

Wed 01-08-18

Mon 06-08-18

      Phase 1: Marketing

15 days

Tue 07-08-18

Mon 27-08-18

         Installation of Sales Forecast Feature

5 days

Tue 07-08-18

Mon 13-08-18

         Installation of Potential Customer Identification Feature

5 days

Tue 14-08-18

Mon 20-08-18

         Testing of the System

5 days

Tue 21-08-18

Mon 27-08-18

      Phase 2: Operations

9 days

Tue 28-08-18

Fri 07-09-18

         Link the Platform to Existing IoT Sensors

2 days

Tue 28-08-18

Wed 29-08-18

         Control the Sensors using the Big Data

2 days

Thu 30-08-18

Fri 31-08-18

         Testing of the System

5 days

Mon 03-09-18

Fri 07-09-18

      Phase 3: Risks

15 days

Mon 10-09-18

Fri 28-09-18

         Install Fraud Detection Feature

5 days

Mon 10-09-18

Fri 14-09-18

         Install Fraud Prevention Feature

5 days

Mon 17-09-18

Fri 21-09-18

         Testing of the System

5 days

Mon 24-09-18

Fri 28-09-18

   Project Closing

12 days

Mon 01-10-18

Tue 16-10-18

      Project Handover

5 days

Mon 01-10-18

Fri 05-10-18

      Project Documentation

5 days

Mon 08-10-18

Fri 12-10-18

      Stakeholder Sign Off

1 day

Mon 15-10-18

Mon 15-10-18

      Final Closing

1 day

Tue 16-10-18

Tue 16-10-18

Project Budget

The overall budget of the project is estimated as follows.

Resources / Requirements

Estimated Cost

Hardware Requirements

$50,000

Necessary Software

$10,000

Big Data Analytics Platform

$40,000

Development Costs

$10,000

Developer Wages and Consultation Fees

$15,000

Stakeholder Wages and Payments

$25,000

TOTAL

$1,500,000

Risk Management Plan

The risk management plan for the project is developed using risk register matrix as follows.

Risk Description

Chance of Occurrence

Impact on Project

Mitigation Strategy

Scope Creep caused due to inappropriate definition of project scope

High

High

Define scope statement properly during development of the project charter

Budget overshoot due to additional costs and expenses

High

Very High

Develop accurate budget estimation and keep 10-20% of the budget as contingency money (Gandomi and Haider 2015)

Cyber attacks through various online media during setting up of the big data platform

Very High

Extreme

Install strong firewalls, anti-virus softwares and ad blockers to prevent any kind of malwares and broken files to enter into the system

Poor management and maintenance of the system due to lack of sufficient technical expertise in big data

Very High

Medium

Conduct training sessions for all the stakeholder groups after the project is over

Stakeholder Register

The stakeholder register for the project is developed as follows.

Stakeholder Name

Stakeholder Designation

Stakeholder Category

Stakeholder Role

PLEASE FILL NAME

IS Project Manager

External

Analysis of the requirements, execution, monitoring and control of project and related human resources

George Smith

VP of Operations

Internal

Management of the operational aspects of the project including development of IoT control using the integrated Big Data platform

Sam Johnson

VP of Marketing

Internal

Management of the marketing aspects of the project including development of business analytics in the platform

Vinh Tran

Risk Manager

Internal

Assessment and management of project risks as well as managing the risk management feature of the big data platform

Jack Smith

CFO, Sponsor

Internal

Providing sufficient funds for the project

Susan Wong

CIO, Steering Company Member

Internal

Manage and employ external stakeholders for the project

Robert Beric

Business Consultant

External

Provide business suggestions and recommendations including selection of Big Data Analytics Platform

Jason Johnson

Hardware Technician

External

Upgradation of the existing hardware at the company

Magnus Olsson

Big Data Expert

External

Development of the Proposed Platform

Gary Ebbert

Trainer

External

Train stakeholder groups for using the big data platform

Stakeholder Management Strategy

In order to develop an appropriate stakeholder management strategy, an RACI matrix is developed as follows.

 

Charter Development

Budget Allocation

Risk Management

Big Data Platform Development

System Testing

Staff Training

IS Project Manager

R

A

R

A

A

I

VP of Operations

C

I

C

R

C

I

VP of Marketing

C

I

C

R

C

I

Risk Manager

C

I

R

I

I

I

CFO, Sponsor

C

R

I

I

I

I

CIO

C

I

I

I

I

I

Business Consultant

R

I

I

I

C

I

Hardware Technician

C

I

C

R

C

I

Big Data Expert

C

I

C

R

R

I

Trainer

I

I

I

I

I

R


Furthermore, as per the stakeholder management strategy, each stakeholder must follow the following guidelines.

Communication – The stakeholders must communicate with each other via appropriate medium throughout the project.

Cooperation – The stakeholders must cooperate with each other throughout the project (Kerzner and Kerzner 2017).

Performance – The stakeholders must exhibit maximum enhanced performance throughout the project.

Adherence to Policy – The stakeholders must stick to company guidelines and policies at all situations.

Conclusion

In this report, an initial project plan has been developed for the proposed implementation plan of the Big Data Analytics Package for Intelligent Information Inc. As per the estimated plan, the overall project duration is around 6 months and the estimated budget for the project is $1,500,000. As per the proposed plan, ten different internal and external stakeholders have been appointed for the project who will manage various aspects of the same.

 

References

Dhamodaran, S., Sachin, K.R. and Kumar, R., 2015. Big data implementation of natural disaster monitoring and alerting system in real time social network using hadoop technology. Indian Journal of Science and Technology, 8(22), p.1.

Fleming, Q.W. and Koppelman, J.M., 2016, December. Earned value project management. Project Management Institute.

Gandomi, A. and Haider, M., 2015. Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), pp.137-144.

Harrison, F. and Lock, D., 2017. Advanced project management: a structured approach. Routledge.

Hashem, I.A.T., Yaqoob, I., Anuar, N.B., Mokhtar, S., Gani, A. and Khan, S.U., 2015. The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, pp.98-115.

Heagney, J., 2016. Fundamentals of project management. AMACOM Div American Mgmt Assn.

Kerzner, H. and Kerzner, H.R., 2017. Project management: a systems approach to planning, scheduling, and controlling. John Wiley & Sons.

Marz, N. and Warren, J., 2015. Big Data: Principles and best practices of scalable realtime data systems. Manning Publications Co..

Schwalbe, K., 2015. Information technology project management. Cengage Learning.

Walker, A., 2015. Project management in construction. John Wiley & Sons.

Wamba, S.F., Akter, S., Edwards, A., Chopin, G. and Gnanzou, D., 2015. How ‘big data’can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, pp.234-246.

Wang, Y., Kung, L. and Byrd, T.A., 2018. Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, pp.3-13.

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