Logistic Business Using Business Intelligence: Project Description, Scope, Objectives, And Constraints

Introduction to Internship Organization (Evergreen Cargo)

The report describes the objective and constraints of the project. During development period all the professional phases such as initiation, planning, execution, control and closure will be maintained by the project team members. The scope of the project will also elaborate in this report. For developing the project for Evergreen Cargo professional tools will be used such as Gantt chart, work breakdown structure to prepare the schedule roles and responsibilities of the team members. It will also divide the work burden systematically among the team members. The project depicts the importance of using business intelligence technologies in a logistic business of Nepal. In order to prepare this project, the chosen organization is Evergreen Cargo, Logistic Supply Chain Company.

The Evergreen Cargo organization is founded in the year of 1984, headquartered in Katmandu, Nepal. It serves a broad range portfolio to the users by serving air freight services, railways roadways and also sea cargo services. In order to meet the relocation of the residential clients a comprehensive as well as tailor made solution in terms of data warehouse is provided by this business organization. The organization is credited for delivering different logistics medium to the users. With extensive logistics and customized channels the organization maintains protection over the import and export process. Currently the organization is not specializes in framing complex supply chain design, integrated IT system, distributed business operations and IT functionalities but is has a warehouse management system. In order to reduce the data warehouse oriented problems, Business Intelligences tools are needed to be used by the management authority of the business organization to improve their logistic operations and to resolve the existing issues.

The proposed project for Evergreen Cargo, will improve the existing supply chain operations effectively and for that they must invest a large amount of capital to adapt business intelligence tools. The global operation of Evergreen Cargo’s supply chain management system is not enough effective and it is also complex at the same time. Though Evergreen Cargo maintains strict safety and standard quality control measures but still certain issues are identified. The proposed project will help Evergreen Cargoto reduce the global operational complexity carefully.Due to lack of visibility in their existing supply chain implementation of Business intelligence tools are required to be adapted.Due to this reason the level of risk exposure is getting enhanced with fluctuating cost and restriction in import and export. These challenges are reducing the profit margin of Evergreen Cargo. Business Intelligence will help Evergreen Cargo to convert their gathered data into effective knowledge so that the knowledge can be used further to serve different business purposes.

In order to support the gathered data, its analysis process, presentation and distribution of the business information, different business strategies, processes, applications, data, technologies and technical architecture have been adapted by Evergreen Cargo to implement BI with their existing Logistics process.

Factors Save Time On Research and Writing Hire a Pro to Write You a 100% Plagiarism-Free Paper. Get My Paper	Implementation  steps
Business strategies	Ø Choosing C-level sponsor (C-level executives are sponsors those are related to through security matters ) Ø Planning for data storage Ø Understanding client’s requirements Ø Designing analytical data model
Processes	Ø Data gathering Ø Data analysis Ø Requirement break down Ø Selecting priority phase Ø Continuous data validation Ø Final implementation for Evergreen Cargo
Applications	Ø Sales and marketing Ø Manufacturing and supply chain management Ø Consumer services
Technologies	Ø Data warehousing Ø Dashboard Ø Ad Hoc reporting Ø Discovery of data
Technical architecture	Transferring Data with Intelligence (TDWI) business intelligence architecture and SAP BI tool is used in this project for introducing BI with the existing logistic business process of Evergreen Cargo.

• Business strategies and vision of Transferring Data with Intelligence (TDWI) architecture.
• Planning and implementation of business intelligence
• Development of high level architecture

After successful completion of the project it will be able to cover the requirements of the owners and users also.

• The project will deliver the successful implementation of SAP BI toolsto convert data into knowledge.
• BI will help to manage all the confidential data efficiently
• The project will provide effective logistic functionalities and operations to Evergreen Cargo’s supply chain management system
• Project schedule will distribute the roles and responsibility among the team members so that they could complete the task within the deadline

• To introduce SAP Business intelligencetool with the existing logistic operation serve by Evergreen Cargo Supply Chain Company
• To gain insights in the behavior of the consumers of Evergreen Cargo
• To improve the visibility style of the management authority of Evergreen Cargo
• To boost up the analysis ability of the company by understanding the buying trend of the customers
• To convert data into knowledge or actionable information
• To develop the business efficiency
• To gain competitive advantages

Triple constraints are considered while developing the project for Evergreen Cargo. As in this project the developers need to include one of the advanced technologies-Business Intelligence in their logistic operations thus the estimated budget for this project is around $180,000. In order to complete the project 3 months are required including initiation, planning, execution, control and closure. After successful completion of the project it will be able to deliver all the pre-determined objectives effectively and will also meet the requirement of the consumers.

Description of the Proposed Project forEvergreen Cargo

In the field of project management statement of work is referred to as a routine document that covers all project specification very much carefully and minutely. The project specification activities are developed in the project schedule and RACI matrix considering the roles and responsibilities of all individual project team members. The main aim of the project is to add BI tools such as SAP, Hadoop with the existing logistic operation of Evergreen Cargo’s Supply Chain. Based on the consumer’s requirement the vendors of BI software will be selected and the development team has planned to complete the project within three months without any error.

Project activities or project deliverables	Leaders of the project	Team members of the project	Supportive team for the project
	Executive sponsors	Project sponsor	Legal Advisors	Project manager	IS manager	Project Developers	Project analysts
Project initiation phase
Request for the Project	R/C	R/A	NA	R/A	A/C	NA	NA
Feasibility study phase	I	R/A	A	R	R	NA	I
Business case development	I	A/C	I	R	R	I	I
Project planning phase
Preparation of project charter	R/A	A/C	A/C	R/C	R/A	I	I
Project Scheduling	R/C	R/C	R/C	R/A	R/A	A/C	I
Additional project plans	I	I	I	I	I	I	I
Execution
Configuring project deliverables	NA	NA	NA	R/C	R/C	R/C	R/C
Status reporting	NA	C	I	I	R/C	A	I
Project Control
Project change management	C	C/I	C/I	R/I	A/I	A/I	A/I
Project Closure	I	I	I	R/A	I	I	I

Project stakeholders	communication methods	Frequency	Responsible person or authority
Project key stakeholders	Kickoff meeting	Project startup	PM office
Extranet	Daily	PM office
Executive client	Execute guide committee	monthly	Account manager
Project development team	Meeting	Weekly	Project manager
Project sponsor	Email and meeting	Monthly	Project manager

                         

                                                       Figure 1: Work Breakdown Structure for Evergreen Cargo

                                                                                    (Source: created by author)

Task Name	Duration	Start	Finish	Predecessors
Business Intelligence implementation	48 days	Mon 3/13/17	Wed 5/17/17
1.0 Project initiation phase	17 days	Mon 3/13/17	Tue 4/4/17
1.1 project request submission	5 days	Mon 3/13/17	Fri 3/17/17
1.2 Project feasibility study	6 days	Mon 3/20/17	Mon 3/27/17	3
1.3 business case development	6 days	Tue 3/28/17	Tue 4/4/17	4,3
2. Project planning phase	14 days	Tue 3/28/17	Fri 4/14/17
2.1 Analyzing additional requirements	3 days	Tue 3/28/17	Thu 3/30/17	4
2.2 Introduction of Business intelligence	2 days	Fri 3/31/17	Mon 4/3/17	7,4
2.3 Data management	6 days	Tue 4/4/17	Tue 4/11/17	8,7
2.4 Defining aim of the project	1 day	Wed 4/5/17	Wed 4/5/17	5,7,8
2.5 Defining mission and vision of the project	3 days	Wed 4/12/17	Fri 4/14/17	9,10
3. Project execution phase	17 days	Thu 4/6/17	Fri 4/28/17
3.1 critical initiatives	5 days	Thu 4/6/17	Wed 4/12/17	10
3.2 project plan and budget integration	5 days	Mon 4/17/17	Fri 4/21/17	11,13
3.3 Risk assessment	5 days	Mon 4/24/17	Fri 4/28/17	14,13
4.0 Project control and monitoring phase	12 days	Mon 5/1/17	Tue 5/16/17
4.1 Identification of risks	6 days	Mon 5/1/17	Mon 5/8/17	13,15
4.2 monitoring business progress	6 days	Tue 5/9/17	Tue 5/16/17	17
5. Project closure phase	1 day	Wed 5/17/17	Wed 5/17/17
5.1 Building secured link between logistic service provider and customers	1 day	Wed 5/17/17	Wed 5/17/17	18

                               

                                          Figure 2: Gantt chart for Evergreen Cargo Supply Chain Company

                                                                            (Source: created by author)

From the overall discussion, it can be concluded that, after implementing business Intelligence with the existing logistic operation of Evergreen Cargo, it will be able to renovate the gathered data into effective useable business information. The logistic sector of Nepal holds a wide range of organizations that operates in air, surface and even in sea transport. The latest tracking facility of Evergreen Cargo is capable to handle critical situation. However, after combination of BI with their warehouse they will be able to serve a more secured service to their consumers without any kind of privacy error. None of the external users can hijack professional as well as personnel data from the data server. The company can adopt the 24X7 work culture for its consumers regardless of the location of the customers after implementation of the planned project. The project schedule, roles and responsibility for each of the project team members are clearly stated in this report. Apart from this, the project aim, scope and constraints are also demonstrated in this report. Moreover, a project communication plan for Evergreen Cargo is also developed in this report.

Dmitriyev, V., Mahmoud, T. and Marín-Ortega, P.M., 2015. SOA enabled ELTA: approach in designing business intelligence solutions in Era of Big Data. International Journal of Information Systems and Project Management, 3(3), pp.49-63.

Francia, M., Gallinucci, E., Golfarelli, M. and Rizzi, S., 2016, June. Social Business Intelligence in Action. In International Conference on Advanced Information Systems Engineering (pp. 33-48). Springer International Publishing.

Hu, Y., Zhang, X., Ngai, E.W.T., Cai, R. and Liu, M., 2013. Software project risk analysis using Bayesian networks with causality constraints. Decision Support Systems, 56, pp.439-449.

Kerzner, H., 2013. Project management: a systems approach to planning, scheduling, and controlling. John Wiley & Sons

Kisielnicki, J.A. and Misiak, A.M., 2016. Effectiveness of Agile Implementation Methods in Business Intelligence Projects from an End-user Perspective. Informing Science: the International Journal of an Emerging Transdiscipline, 19.

Monica, L.I.A., 2015. Customer Data Analysis Model using Business Intelligence Tools in Telecommunication Companies. Database Systems Journal BOARD, p.39.

Moscoso-Zea, O., Luján-Mora, S., Caceres, C.E. and Schweimanns, N., 2016, April. Knowledge Management Framework using Enterprise Architecture and Business Intelligence. In 18th International Conference on Enterprise Information Systems (ICEIS) (pp. 244-249).

Ramasesh, R.V. and Browning, T.R., 2014. A conceptual framework for tackling knowable unknown unknowns in project management. Journal of Operations Management, 32(4), pp.190-204.

Richter, A., Stocker, A., Müller, S. and Avram, G., 2013. Knowledge management goals revisited: A cross-sectional analysis of social software adoption in corporate environments. Vine, 43(2), pp.132-148.

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

Sharda, R., Delen, D., Turban, E., Aronson, J. and Liang, T.P., 2014. Businesss Intelligence and Analytics: Systems for Decision Support-(Required). Prentice Hall.

Sharma, R., Mithas, S. and Kankanhalli, A., 2014. Transforming decision-making processes: a research agenda for understanding the impact of business analytics on organisations. European Journal of Information Systems, 23(4), pp.433-441.

Simon, A., 2014. Modern Enterprise Business Intelligence and Data Management: A Roadmap for IT Directors, Managers, and Architects. Morgan Kaufmann.

Stone, M.D. and Woodcock, N.D., 2014. Interactive, direct and digital marketing: A future that depends on better use of business intelligence. Journal of Research in Interactive Marketing, 8(1), pp.4-17.

vom Brocke, J., Debortoli, S., Müller, O. and Reuter, N., 2014. How in-memory technology can create business value: insights from the Hilti case. Communications of the Association for Information Systems, 34(1), pp.151-167.

Wu, D.D., Chen, S.H. and Olson, D.L., 2014. Business intelligence in risk management: Some recent progresses. Information Sciences, 256, pp.1-7.