Automation is everywhere. It can be seen through long completion times and human error being almost completely eliminated by artificial intelligence (AI) and mechanical vendors. On the other hand, it can be seen through people losing their jobs to these improved technologies. Show
Some industries have felt it more than others. According to U.S. News and World Report, the industries that have felt the biggest brunt of automation so far are in:
Now, it’s easy to think that other industries, such as accounting, are safe from being automated. However, that’s not true; there are jobs within the accounting and finance sectors that are also in danger of being lost as AI continues to improve. That’s why the accounting industry is stressing the understanding and practice of data analytics. It’s no longer about being able to just add, subtract, multiply, and divide; now accountants need to be able to think outside the box and guide businesses through decisions based on data, past examples, and future predictions. In a recent Wiley Webinar, Kimberly Church, Director at the School of Accountancy at Missouri State University, discussed the role data analytics plays in accounting, why it's so important to come to the table with a data analytical mindset, and how you can sharpen these skills in your accounting/finance career. Which accounting jobs are susceptible to automation?According to the report The Future of Employment: How Susceptible Are Jobs to Computerisation? by Carl Benedikt Frey and Michael A. Osborne, bookkeeping, clerical accounting jobs, and tax preparation are among the fields most susceptible to automation (with a probability of 98–99 percent to be automated). They also identified accountants, auditors, and tax examiners as being in the 47 percent probability range. What’s data analytics?According to Investopedia, data analytics is the science of analyzing raw data to make conclusions about that information. Data analytics techniques can reveal trends and metrics that would otherwise be lost in the mass of information. This information can then be used to optimize processes to increase the overall efficiency of a business or system. In the accounting and finance fields, you deal with data all the time. You gather a company’s financials and report them to boards, presidents, and stockholders. For many old-school accountants, that’s all their jobs required. However, in today’s world, accountants need to show that they can do more with data than just record it. How can we stress the importance of data analytics?The change needs to start in our education system. Previously, there was a perception that the accounting and finance fields have mind-numbing, black-and-white, monotonous work that would always be in-demand. So, many people chose those fields based on those beliefs and only retained the skillsets needed for them. Unfortunately, their jobs will be the first to be automated. However, true accounting is the art of analyzing the financial position and operating results of an organization from a study of its business processes. By arming your students with a data analytics mindset, they can understand all that goes into the gathering and interpretation of data. With this, they’ll be ready to spread their skillset and become vital to companies in many areas, not just in the counting aspects. Educational institutions have taken note of this and started to change their curriculums and teaching methods to have various data analytics requirements. They’ve come to realize that right now, they must create accounting unicorns that can record, analyze, and use this data for actionable intelligence. What are the data analytics best practices to know?There are many best practices that today’s accountants need to familiarize themselves with to become those accounting unicorns that businesses will need for a long time: Logical & Critical ThinkingThe ability to think critically and interpret the information that’s in front of you. Data SourcingUnderstanding the sources of your data and being able to find reliable information. Data ModelingCreating flow charts that show processes from beginning to end and finding potential gaps. Data MiningPlotting your data on graphs to find correlations, patterns, and anomalies. Data AnalysisThis can be used in different analytic formulas such as Structured Query Language (SQL) analytics, path/time series analytics, text analytics, rich media analytics, and graph analytics. Data Visualization and StorytellingCreating graphs and visuals so that the data is easily digestible for the intended audience(s). Data EthicsThe study of how data is gathered within the laws of the territory that you’re working. Learn more.No matter how far you’ve gone in your accounting/finance career, understanding and using data analytics can give you the tools to avoid seeing your job become one of the thousands that are automated every year. To learn more, watch the webinar featuring Kim Swanson Church here. Picture Title Dr. Kimberly Swanson ChurchDesignation Description Dr. Kimberly Swanson Church is the BKD Professor of Leadership & Director for the School of Accountancy at Missouri State University. Dr. Church teaches in the area of managerial and accounting information systems with an emphasis in data analytics and emerging technologies and has two decades of entrepreneurial and higher education experiences. She works actively with a variety of professional organizations and serves frequently as an invited speaker on topics related to professional development and technology disruptions to the accounting profession. Dr. Church is a national award-winning educator for her many classroom innovations using experiential learning techniques that best reflect real-world applications of accounting concepts. She has published many academic and practitioner articles, won several best paper awards and her articles have appeared in Accounting Horizons, Journal of Information Systems, Journal of Emerging Technologies in Accounting, Journal of Accounting Education, BizEd, and Strategic Finance. What parts of the analytics mindset can automation help with?Through automating analytics, you create systems that can automate a portion or even the whole data flow that brings a data-related product to life, from automating dashboards for business intelligence to self-governing machine-learning models based on data models.
What are the four general steps to analytics mindset?Guide: Adopt an analytics mindset. Introduction.. Ask the right questions.. Understand the analytics value chain.. Choose your data and metrics.. Make inferences using statistics.. Tell a story with your data.. Take action on your findings.. What is automation in analytics?Automated analytics is the analytical capability to automatically detect relevant anomalies, patterns and trends and deliver insights to business users in real-time, with no manual user-analysis or IT intervention required.
What is the correct order of the steps in the analytics mindset?The analytics mindset consists of a four-step process of (1) asking the right questions; (2) extracting, transforming, and loading the necessary data; (3) applying appropriate data analytics techniques; and (4) interpreting and presenting the results.
What are the four general steps to analytics mindset quizlet?Asking the right questions is the first step of an analytics mindset.. Understand the data and the desired outcome.. Standardize, structure, and clean the data.. Validate data quality and verify data meets data requirements.. Document the transformation process.. What is the analytics mindset according to EY?An analytics mindset is the ability to: Ask the right questions. Extract, transform and load (ETL) relevant data. Apply appropriate data analytics techniques.
|
Select all that apply what parts of the analytics mindset can automation help perform
zusammenhängende Posts
Urheberrechte © © 2024 WIKIFI Inc.
