Sample MBA633 Real World Business Analytics and Management Case Study

MBA633 Real-world Business Analytics and Management Case Study Sample

Your Task

Develop a real-world business analytics project plan/proposal based on the learnings from the course.

Assessment Description

This assessment seeks to simulate a real-world task that you may have to undertake. Therefore, the assignment is non-prescriptive and requires you to pose a relevant, creative and significant problem to solve that could result in benefits to the organisation of choice.

In this assessment, you need to consider an organisation in an industry of your choice and articulate the steps needed to enable data driven decision making. The organisation and industry need to be familiar (e.g., where you have worked or are working, a future start-up company), NOT an organisation such as Amazon/Boeing/Qantas etc.

Assessment Instructions

• Week 11

Identify a company and industry you are familiar with that would benefit from Data Analytics.

• Week 12

Draft a preliminary report - You are encouraged to consider the current mode of operation, highlight the possible inefficiencies, and look for available data and how this data may be used to provide efficiencies based on the concepts and techniques covered in the subject.

Your lecturer will advise on the appropriateness of your choice and proposed methodology with regard to the requirements for the assessment.

In addition to the components discussed in your draft, your final report should include the project life cycle, management of the project, ethical considerations and stakeholder management as discussed in course workshops.

Solution

Introduction

Background

The Australian company Telstra offers communication services through its telecommunication system and technology (Telstra 2021). For Assignment Help, The company provides data services to build a future where people feel connected. The report will portray the benefits of data analytics to solve Telstra's possible issues in business. The operational strategy evaluation provides effective techniques to implement modern data analytics in the company's communication system network.

Purpose

The report aims to evaluate the benefit of data analytics to the company Telstra. It will evaluate the technique to solve the issues or possible issues in Telstra's business management. The key metrics identification will help to understand how the data analytics can be used. However, the insufficiencies of the company will be demonstrated for identifying proper techniques for applying data analytics.

Problem-Identified

Telstra operates a communication network using modern technology, which can create various issues for the company's operation management. The company's effective network system is the trust of 18.8 million retail mobile services (Telstra 2021). The modern era of digitalization has led to security issues in IT services. Telstra can be a victim of cyber hacking and data breaching as the company advances itself with information technology networks. Analytical capabilities of data often lack in system infrastructure, which leads to data breaching. However, cyber risk is a vital issue for many organizations that have acquired information technology as their basis of growth (Kopp, Kaffenberger& Wilson 2017).

The company is taken into account as it holds the necessary information in accessible manner, which helps to evaluate in a convenient way. Therefore, I also found the high risk of data theft in the communication network, which the company needs to prevent through proper analytics implementation.

Ethical Consideration

Data privacy and security come under ethical consideration within every organizational structure. Ethics create appropriate policies and standards to protect the data. The company can implement the Data Protection Act for managing vital information within the communication network.

Methodology

The methodology will undertake a specific approach. The identified approach for the research is CRISP methodology. The approach provides a standard framework for the project life cycle where it increases the flexibility and usefulness of the data analytics system, which solves the business issues (Sv-Europe 2021). The analytics techniques provide effective security to software systems. The company Telstra needs to implement a data analytics process in its communication network for promoting proper security.

Figure 1: CRISP Framework
Source : (Licdn 2021)

Business Understanding: The process specifies the business need (Wyzoo 2021). The Telstra company's objective is to provide the largest mobile network and other communication services through digital networking systems (Telstra 2021). In that case, the security of the network is needed for safeguarding the data from unauthorized access.

Data Understanding: Telstra operates mobile communication networks which involve the data of the public. It may be personal information, residential address, finance-related information, or any other vital information. Also, the company provides communication networks to the retail industry through voice services which can involve the information related to organizations and clients.

Data Preparation: The process strengthens the understanding regarding data by creating a data dictionary that ensures that each piece of information should be understandable (Wyzoo 2021). Another process of data preparation is data analytics which helps to create new data points by calculating the existing entries of data. This helps in developing a predictive model for the solution.

Modelling: Proper model development for solutions is necessary to solve the cyber risk issue in Telstra company. The company can implement a machine learning process for managing the system performance, and it will also help gain an insight into the risk management strategy.

Evaluation: After the identification of a specific model, it is important to evaluate the test results. It will help the company to understand whether the data analytics tool is appropriate for the problem or not. Evaluation of results determines the success criteria (Albert, Balve& Spang2017). This process can be undertaken through specific stakeholders of the company who will evaluate the potentiality of the data analytics technique to solve the cyber risk issue.

Deployment: Through monitoring and observation of the process, a proper deployment method can be developed. It will help to understand the proper result evaluation process.

Challenges and Limitations

Facilitate a project regarding risk management through data analytics can create practical challenges. The project needs a proper budget. As the data analytical tools require a high budget for implementation, the project team can face significant challenges. However, time can be a limitation as a pre-determined framework of time for projects often limits the potential result of the project. In the approach CRISP method, there are several problems like mindless rework, lack of clarity, failure to integrate, and blind hand-offs to IT (Taylor 2017). In the case of the decision-making process for proper modelling of analytics tools or techniques to solve problems, the CRISP method can create challenges for the team.

Benefits and Consequences

Proper implementation of data analytics techniques in the communication network system of Telstra will help to analyze network traffic to detect threats. Data analytics tools or techniques will benefit the company in cybersecurity development by monitoring user behaviour and finding suspicious behaviour. Data analytics security can detect the insider threat and investigate the cloud traffic for managing the potential attack (Forcepoint 2021). Not only that, the implementation of a data analytics tool will help the company to identify the accounts which may have been compromised. This will benefit the company to increase flexibility in the communication network and create a secure and trustworthy network. Improvement in User experience will increase a company's reputation. The CRISP method will also benefit the company to implement a long-term security management strategy which will lead the project team to focus upon a specific goal for risk management.

Management of the Project

The Agile methodology will help the project to be accomplished within a limited timeframe. It will increase the speed of the project by breaking the entire task of the project into several small goals. The Agile method divides the entire task of project management into short iterations (Rasnacis&Berzisa 2017). Scrum is the agile project management method that includes small teams, which are led by the scrum master who helps to remove obstacles for getting the work done. Another method of project management is Prince 2, which controls the entire project by managing the possible risks inherent in the process (Slate 2019).
On the other hand, the PMBOK method of project management ensures the standard guidelines and best practices for managing the project. The outcomes are derived through specific stages in the PMBOK method. It is the traditional process of project management. Hence it lacks the feasibility like the modern Project management methods. For Telstra, the Agile (Scrum) project management method will be effective as it will help minimize the project workload by dividing the entire project into several small iterations.

Key Stakeholders

The owner of the company will create a specific strategy for managing the risk in the network through engaging in project planning. The investors and shareholders of the company will help the project team by providing project expenditure. However, the project team will actively engage in developing a proper data analytics technique for solving the cyber risk issue. The employees are other stakeholders who will be given enough knowledge and training to manage the new system for risk identification and management.

Budget

The project will cost approximately $120,000, and the data analytics tool implementation can approximately cost $80,000.

Schedule

The project will be completed within 45days, where the task will be divided into several sprints.

Data

The specific data will be driven from secondary resources like scholarly articles and journals. The company website will also be used to gather the data. Specific information regarding the data implementation technique will be collected from the system testing method.

Quality of Data

The data will be sourced from reliable websites like company websites and other authentic sources. The data gathered from scholarly sources will justify the quality of the data. Moreover, reliable sources like scholarly articles, journals, and books will make the data more authentic.

Data Preparation

For the process of data preparation, two methods will be selected, such as data dictionary and data analytics. The data dictionary process will help to divide the information into specific segments. It may include mailing data, purchasing data, and communication data. The second process, data analytics, will help to specify the information like mailing addresses and gender information. In this process, the data points will be created.
Data Analysis

The process of data analysis will include several perspectives of security measures. For risk management, the key risk metrics will help to measure the potentiality of risk. 47% ransomware infection gripped the system network where the loss of data was 60% (Appendix 2). The security metrics help to measure the risk for promoting proper work flexibility in the system network so that business can be improved and business objectives can be achieved (Lakshmi 2019). The security cost in leased facilities is needed to be reduced by 10%, while the guard force overtime is required to reduce 20% (Appendix 1). However, the safety hazards have decreased up to 20% from the past cycle. The rate of unsecured data needs to be minimized as it has exceeded the past cycle, and the system is prone to high risk in this case.

Visualization

Figure 2: Notable Risk Exposures Mitigated by Inspection Activities & Operational Readiness Reviews
Source : (Securityexecutivecouncil 2021a)

The rate of AMS operation ineffectiveness and the safety hazards have decreased significantly. But the export control is more insecure than in the past cycle.

Figure 3: Security Metrics for Success
Source : (Securityinfowatch 2021)

The evaluation of success metrics demonstrates that the security risk appetite performance has exceeded the determined objective. On the contrary, business ownership of security risks and controls is significantly lower than its objective.

Key Metrics

Table 1: Key Risk metrics
Source : (Developed by the author)

Design for the system

Risk management systems will be developed within the communication network of the company. A specific user interface design will be developed for system management. The users will input proper credentials into the system while taking service from the company, and they have to register within the system to become authorized users. The system will identify the credentials and data of authentic users while entering into the device. The data analytics tool will be implemented within the system, which will restrict access to unauthorized users. The tool will detect potential threats through the system.

Conclusion

The report demonstrated the risk management process in the communication network of Telstra company through implementing data analytics techniques. The methodology highlighted the CRISP approach for the project life cycle, where the project management will be done through the agile scrum method. The challenges and benefits of the project and the specified approach have been discussed for understanding the need of the stakeholders for project management. However, the data analysis and visualization have portrayed the necessity of risk management through identifying several key risk metrics. The design of the system will help the company to manage the cyber risks in the network.

Recommendations

• The company needs to implement a data analytics tool to manage the possible risks in a communication network.
• Artificial intelligence and blockchain technology are effective security providers to data.
• The company needs to analyze the cost of data analytics tool implementation.
• The stakeholders need to evaluate the key risk metrics for measuring the potentiality of risks.
• Proper system design is needed to restrict the third party's interference. 

References