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- Creators: College of Integrative Sciences and Arts
- Creators: Dawson, Gregory
- Resource Type: Text
- Status: Published
The next question: What do these changes in the roles and responsibilities look like for the auditors of the future? Cognitive technology will assuredly present new issues for which humans will have to find solutions.
• How will humans be able to test the accuracy and completeness of the decisions derived by cognitive systems?
• If cognitive computing systems rely on supervised learning, what is the most effective way to train systems?
• How will cognitive computing fair in an industry that experiences ever-changing industry regulations?
• Will cognitive technology enhance the quality of audits?
In order to answer these questions and many more, I plan on examining how cognitive technologies evolved into their use today. Based on this historic trajectory, stakeholder interviews, and industry research, I will forecast what auditing jobs may look like in the near future taking into account rapid advances in cognitive computing.
The conclusions forecast a future in auditing that is much more accurate, timely, and pleasant. Cognitive technologies allow auditors to test entire populations of transactions, to tackle audit issues on a more continuous basis, to alleviate the overload of work that occurs after fiscal year-end, and to focus on client interaction.
Corporate buzzword terms like “big data” and “data analytics” are vague in meaning, and are thrown around by media sources often enough to obfuscate their actual meanings. These concepts are then associated with company-wide initiatives beyond the reach of the individual, in a nebulous world where people know that analytics happens, but don’t understand what it is.
The power of data analytics is not reserved for company-wide initiatives, or only employed by Silicon Valley tech start-ups. Its impacts are visible down at the team or department level, and can be conducted by the individual employees. The field of data analytics is evolving, and within it exists a rapid transition in which the individual employee is becoming a source for insight and value creation through the adoption of analytics based approaches.
The purpose of this thesis is to showcase an example of this claim, and demonstrate how an analytics based approach was applied to an existing accounting process to create new insights and information. To do this, I will discuss my development of an Excel based Dashboard Analytics tool, which I completed during my internship with Bechtel Corporation throughout the summer of 2018, and I will use this analytics tool to demonstrate the improvements that small-scale analytics had on a pre-existing process. During this discussion, I will address conceptual aspects of database design that related to my project, and will show how I applied this classroom learning to a working environment. The paper will begin with an overview of the desired goals of the group in which I was based, and will then analyze how the needs of the group led to the creation and implementation of this new analytics-based reporting tool. I will conclude with a discussion of the potential future use of this tool, and how the inclusion of these analytical approaches will continue to shape the working environment.
The influx of readily available sports data has transformed the landscape of recruitment analysis conducted in European soccer leagues. Clubs now have access to a repository of information that helps to monitor the status of current players and filter those they wish to recruit. Supplemented by extensive financial backing, the teams in the English Premier League have shifted from a local, more traditional approach to a focus on the acquisition of players in international markets. This paper analyzes the rapid effects of implementing a data-driven approach to recruitment and argues that the dominance of Liverpool in the EPL from 2017 to 2022 has stemmed from a superior focus in this data-driven recruitment compared to other clubs in the league, specifically Manchester United. Other teams have recently shifted their structures to model the modern, fast flow of data that the two European super clubs manage each season yet consistently fail to match either. Furthermore, this project establishes the feasible prospect of clubs prioritizing their staffing for data over other departments, including players.
The influx of readily available sports data has transformed the landscape of recruitment analysis conducted in European soccer leagues. Clubs now have access to a repository of information that helps to monitor the status of current players and filter those they wish to recruit. Supplemented by extensive financial backing, the teams in the English Premier League have shifted from a local, more traditional approach to a focus on the acquisition of players in international markets. This paper analyzes the rapid effects of implementing a data-driven approach to recruitment and argues that the dominance of Liverpool in the EPL from 2017 to 2022 has stemmed from a superior focus in this data-driven recruitment compared to other clubs in the league, specifically Manchester United. Other teams have recently shifted their structures to model the modern, fast flow of data that the two European super clubs manage each season yet consistently fail to match either. Furthermore, this project establishes the feasible prospect of clubs prioritizing their staffing for data over other departments, including players.