The quick analysis tool is one of the many built-in functions of Excel. The original purpose of the quick analysis was to try to guess what the users want from a particular data set. The benefit is huge because it made the painstaking process of making sense of different data sets simpler by applying easy-to-read visualizations. Nevertheless, when there is a benefit, there are also drawbacks. The main drawback is that it does not always get it right when it comes to guessing what the user wants. Another limitation is that this tool is also heavily reliant on accurate data. Hence, the user must also clean and validate the data sets beforehand for accuracy in order for it to provide the most accurate interpretation. Otherwise, although the quick analysis may still run, the results may vastly differ from their desired and intended outcome. That said, from a personal preference perspective, I would most definitely try to limit my reliance on quick analysis tools to eliminate every possibility of wrong interpretations. I will still use them if I desperately need to produce quick and non-decision-impacting reports in a limited and time-constrained environment. However, I would treat it with extreme caution because, just as with any data analytical work, detail orientation comes a long way. The best way to maintain a high level of attention to detail is to ensure you have total control of your data. It is very similar to that of an aircraft’s autopilot program. Although most modern-day aircraft can lift off or land themselves safely on their built-in autopilot program, any seasoned pilot will tell you that one cannot just mindlessly rely on autopilot. The pilot themselves must know the full scope of the various aircraft’s technical functionalities and engineering mechanisms. Take the recent Boeing 737 Max crashes; the pilots of both of these tragic air disasters were unaware of the addition of the MCAS system that Boeing put forth in their new models. Boeing did not notify the airlines that they had added such a system, so when the disaster happened, the pilots were fiercely trying to lift up the aircraft to prevent a nosedive, whereas the MCAS system actively pushed the nose down. So if we relate it back, the autopilot and MCAS were only there to make their lives easier and not to replace the pilots’ expertise entirely. So, in short, the quick analysis tool is a simple shortcut if we know what we are doing.

Responses to the professor or other students:

Response One:

I like your input and explanation on the quick analysis tool. However, there is a point that I do want to make very quickly, and that is the idea of it providing the best option. From my personal experiences with Excel, I don’t particularly see the quick analysis tool as the best reporting option; it is more of an acceptance and, at times, presentable alternative provided that I don’t have time to take a deeper dive into the data sets. If I can take some time to dig deeper into the specific data sets and perform a deep “house cleaning,” I find that the results are likely a lot more accurate and often more compelling.

Response Two:

Yes, I cannot agree more with your conclusion that there are a lot of ways of getting things done; it really is just up to us to find the best, most accurate, and efficient way forward. In my own discussion post, I have linked the use of quick analysis tools to the concept of aircraft autopilot. At the end of the day, it is there to make our lives simpler, but we should still know the ins and outs of cleaning, building, and making our own charts and tables. After all, excel can try to guess what we want, and it may occasionally get it right, but it certainly won’t get it right all the time. Quite frankly, in the business world, that one simple miscalculation and misinterpretation made by Excel can cause a business to lose hundreds of thousands or even millions of dollars.