PLEASE WATCH VIDEO https://www.youtube.com/watch?v=RIYN2F6fW2Y
Review the short video above.
This week you were introduced to managerial accounting and cost methods. Discuss the differences between fixed, mixed, and variable costs by providing two examples of each type of cost as they relate to a company you have worked for in the past, currently, work for, or plan to work for in the future. Why do you think it is important for managers of this organization to understand the differences in these costs (be sure to provide a specific related example)?
Example of a Substantive Post (Please review before you post your discussion)
Current Topic Discussion Guidelines:
Please review the video on Understanding Scholarly Journal Articles and 10 Type of Plagiarism, then review the Example of a Substantive Post to use as a guide for all of your posts.
Students must make a minimum of three substantive (several paragraphs per post) contributions on three separate days of the learning week to the discussion topic. Post your initial response to the discussion question early in the learning week (no later than Wednesday), and then respond to a minimum of two other posts. Initial posts must contain 3 scholarly sources (using the KU Library), one of which may be the textbook.
FYI: A general guide we use to explain what a substantive post is:
A post that comprises at least 3 detailed and related paragraphs
Ideas and opinions are backed up by scholarly sources found at the KU library
Sources and citations are in APA format
Big data refers to extremely large and complex data sets that can be described according to four characteristics known as the four Vs: volume, variety, velocity, and veracity (Gepp, Linnenluecke, O’Neill, & Smith, 2018). Some businesses use big data in order to identify common bottlenecks, understand customer behavior, and improve performance (Tang & Karim, 2017). Big data has also been adopted in accounting practice to adjust inventory and to measure intangibles (Tang & Karim, 2017). In addition, with the availability of different types of tools such as predictive models, data layering, and visualizations, big data can be used effectively in the audit field (Prem & Marthandan, 2018). In fact, these big data techniques help auditors to assess the company’s financial condition and to improve the audit evidence.
There are also big data techniques for forecasting financial distress that help auditors to improve the going concern evaluations. For instance, the incorporation of big data models should help auditors to avoid the cost of issuing an unmodified opinion prior to bankruptcy (Gepp, Linnenluecke, O’Neill, & Smith, 2018). On the other hand, internal auditors can also use big data models for forecasting financial distress that focus on longer periods. These models when combined with the opinion of the internal audit team could provide useful information for senior management and the Board of Directors (Gepp, Linnenluecke, O’Neill, & Smith, 2018).
Big data can also improve the quality of audit evidence. In fact, the use of big data can provide a population-based audit generating more relevant audit evidence. For instance, an auditor can conduct an extensive examination to a client’s complete records of accounts receivables in order to reduce the bias from sampling (Tang & Karim, 2017). The high volume of data allows auditors to stratify the accounts by transaction amount, date, and location. Auditors also can compare the stratified groups in order to find patterns and to obtain useful information (Tang & Karim, 2017). In addition, big data such as GPS data can provide auditors with more solid verification about shipping information.
References
Gepp, A., Linnenluecke, M. K., O’Neill, T.J. & Smith, T. (2018). Big data techniques in auditing research and practice: Current trends and future opportunities. Journal of Accounting Literature, 40, 102-115. doi:http://dx.doi.org/10.1016/j.acclit.2017.05.003
Prem, L. J., & Marthandan, G. (2018). The hype of big data analytics and auditors. Emerging Markets Journal, 8(2), 1-4. doi:http://dx.doi.org/10.5195/emaj.2018.153
Tang, J., & Karim, K. E. (2017). BIG DATA in business analytics: Implications for the audit profession: Certified public accountant. The CPA Journal, 87(6), 34-39. Retrieved from https://search.proquest.com/docview/2213054542?accountid=35796
