Analytics and Decisions

This past week in class we have discussed about the difference between analytics and analysis and what each tell us or do. One of the main differences that I can remember about them is that analytics are ongoing and an analysis is more of a one time thing. Since analytics is the discovery and communication of meaningful patterns in data, I wonder if data can get hacked just as easily as self-driving cars. In class we also talked about the risk of self driving cars and drones being hacked, and data can be effected in the same way.

Within business, many companies rely on analytics to determine what products they market or customers to aim for or drop. Fast Company, the newspaper says that although analytics are important that they do not know if they can trust them, “Yet, according to a recentĀ survey of over 2,000 data and analytics (D&A) decision makers in 10 countries by KPMG and Forrester Consulting, only 38% of respondents have a high level of confidence in their customer insights, and only one third trust the analytics they generate from their business operations”(Fast Company). As helpful as analytics can be, they can also be untrustworthy. When you are higher up in a company and look at the different data presented to you, you do not really know where the information may be coming from. So instead they choose to ignore the information presented to them because they are unsure if it is trustworthy or not. Many companies do however take a different path when it comes to data and do not really try to obsess over it. According to Towards Data Science, one of their major cases is that sometimes the average value does not represent your customer. This means that although maybe only half of the population like your product, that statistic does not matter to you unless the whole entire world is your target market. Data can sometimes not represent your target market which can make it invaluable to your company. One major thing to remember when talking about data as well, is to remember that data many times can just be a prediction. Although many people hate to admit it, including myself, but technology and data can be wrong or incorrect sometimes. Government Technology, wrote a article about how big data can be wrong and predict incorrect information for a company.

It is always important to think about the analytics that are being received and pushed out to the world for everyone to see. The predictions, statistics, and data can be wrong or altered by other people and you have to be able to be aware that some information can be wrong.

Resources:

https://www.fastcompany.com/3065294/why-executives-dont-trust-their-own-data-and-analytics-insights

https://towardsdatascience.com/why-focusing-on-data-points-can-hurt-your-business-and-what-you-should-do-instead-1583d008b7b9

https://www.govtech.com/data/When-Big-Data-Gets-It-Wrong.html

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