data analytics
What have your experiences been so far with data and could you give examples of where you see data analytics being applied?
In response to your peers, are the examples being cited by your classmates valid data analytics examples and how can stronger cases be made for those examples?
classmate 1
Throughout my academic and professional journey, I have gained substantial experience in data use and analysis. During my bachelor’s degree in economics, I engaged with data sets in seminars and utilized them extensively in my thesis. I also studied econometrics, learning about tools such as regression analysis, which explore relationships between variables (Albright & Winston, 2020), and I was introduced to the basics of machine learning. In my professional career, I first worked in a Sales Analytics role, analyzing sales data to aid stakeholders in making informed decisions regarding marketing and pricing. Subsequently, I moved into a controlling role, where I analyzed cost data from various departments to understand cost origins and forecast future expenditures to plan investment strategies. Currently, I work in financial reporting, analyzing financial performance data to report and clarify the company’s financial health to stakeholders and regulators. With extensive exposure to data analysis in both educational and professional settings I recognize the importance of data analysis for business success.
The first example I want to present is Meta, which owns the social networks Instagram and Facebook. Arguably, their entire business model is centered around data. Every time a user interacts with these social media apps, data is collected. This data is then analyzed using machine learning and AI to recommend content that users are likely to enjoy, serving as a prime example of predictive business analytics (Marr, n.d.), the act of predicting an outcome in the future (Olavsrud, 2022). In this example the approach is to predict future user preferences based on past behavior. By doing so, Meta optimizes the customer experience by ensuring that users are shown content they will most likely find appealing. Furthermore, this strategy is integral to how the company generates revenue. The primary income for Meta comes from ads displayed within the apps. With extensive data on each user, which is analyzed by machine learning algorithms, Meta can serve highly targeted ads. This capability is extremely attractive to companies wanting to place ads, making the advanced analytics of vast amounts of data the core of how Facebook and Instagram monetize their platforms.
The second example I want to highlight is the use of data analysis in Merger & Acquisition (M&A) deals. When evaluating a company’s worth, potential buyers analyze the historical financial performance data to gain insights into the company’s potential value (Hayes, 2024). By comparing the financial performance with other companies or historical deals, analysts can determine the appropriate market value of the company (Hayes, 2024). This is a form of descriptive data analysis that assesses the current state of the business (Olavsrud, 2022) and, consequently, its current worth. The valuation process is a critical aspect of M&A because its purpose is to ensure that both the buyer and the seller agree on a fair price for the company (Hayes, 2024). Thus, data analysis is an integral part of the M&A process.
References:
Albright, S. C. & Winston, W. (2020). Business Analytics: Data Analysis & Decision Making (7th Edition). Cengage Learning. https://ambassadored.vitalsource.com/reader/books/9798214338712/epubcfi/6/22[%3Bvnd.vst.idref%3Dbd-JRCEFQDJHAYFHPD45999]!/4/2[JRCEFQDJHAYFHPD45999]/24[LUVX1ZQ58S4TPPB1U437]/7:132[.%20%2C%20%20%20]
Hayes, A. (2024, Feb 20). What Are Mergers and Acquisitions (M&A)?. Investopedia. Date Retrieved: 2024, April 29. https://www.investopedia.com/terms/m/mergersandacquisitions.asp
Marr, B. (n.d.). The Amazing Ways Instagram Uses Big Data And Artificial Intelligence. Bernard Marr & Co. Date Retrieved: 2024, April 29. https://bernardmarr.com/the-amazing-ways-instagram-uses-big-data-and-artificial-intelligence/
Olavsrud, T. (2022). What is business analytics? Using data to improve business outcomes. Cio
classmate 2
Throughout my military career there have always been measures of data analyitics whether it be historical or future trends. However, it has been since my time in recruiting have I truly understood the value of these types of metrics. We have been using Marketshare data to measure historical trends to predict future or possible outcomes for enlistment data by zip code. Marketshre data has been the baseline for understanding where we could apply more personnel, advertising and where we could be missing out on potential enlistments.
Albright, S. C. & Winston, W. (2020). Business Analytics: Data Analysis & Decision Making (7th Edition). Cengage Learning.
classmate 3
My experience with data has been used in my current role as a Benefits Manager in human resouces. I often create reports with employee data within our HRIS system for a variety of reasons. One of the reasons that I need to run reporting and analyze data sets is during our annual open enrollment period. Giving concrete data trends to our healthcare broker and vendors during open enrollment help us mitigate some of the cost increase that comes every year when insuring our staff. Understanding the demographic of our pool of staff, how likely they are to enroll, incur large claims and insure dependents are various factors that can contribute to a annual increase.
Another example of running data within my professional career, involves workman’s compensation claims. Manipulating the data to understand where the highest claims are being generated from is a crucial part of my role. Identifying factors that need to be eliminated or identified for additional safety measures is a important area of ensuring compliance with our programming as well as a cost savings measurement. This data can then be helpful in identifying risks within our workforce and evaluating if it is worthwhile to continue with the current course or adjust it if needed. I also use financial reporting for our retirement program and work with our finance department to forecast employees being eligible for our employer match. The data helps provide a picture of our staff as a whole and how much we are liable for as well as who we expected to be liable for in the future.
In addition, my colleague uses data analytics for posting jobs online and reaching a audience of candidates for the role we are trying to fill. We have found certain platforms that help fill roles more quickly based on their advertisment visability and internet traction. Having this data available to see how many people view our posting and the applications generated per viewer is helpful to identify what systems are beneficial to our staffing resources.
On a personal level, I see data being applied all around me, espiecally in online commerce and social media ads. The data that the internet or apps collect help drive what you are exposed via advertising and visability for product placement. As reported by Forbes, businesses are often among the first to leverage the power of new technology, 77% of small businesses use social media to connect with their customers. In addition to building brand awareness (44%), a significant number of small businesses—41%—also depend on social media as a revenue driver. (Wong, 2023).
References:
Wong, J. D. (2024, April 12). Top social media statistics and trends of 2024. Forbes. Retrieved April 29, 2024 from https://www.forbes.com/advisor.business/social-med…
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