Data analysis has evolved so much that it has led to the apparition of new tools and professional careers entirely dedicated to the collection, organization, monitoring of data in order to make informed decisions. In fact, what was once the role of a business owner has now become a job in the marketing, technical and business management departments. Nevertheless, only large companies have the luxury of multiple data analysts within their teams. More often than not, small businesses need to make do with one data expert or with one tool. Ultimately, data analysis is a difficult task that often hits obstacles. Here are the four most common causes of data analysis failures in small and large companies.
Your collection process is faulty
If your company supplies software tools, it’s likely that you’ve embedded a service that automatically collects data. The data can then be used to improve the performance of your tools and understand how your clients interact with the various functions. However, if your data collection tool slows down the device, it’s likely that your clients will have it switched off. This is what happens to the Microsoft Development team. By the way, if you’re experiencing issues the MS data collection tool, you could check here how to turn it off. Keep a smooth collection process to let clients use your tool.
You have to give up data collection
Every business needs to collect data on a daily basis. As a result, you might find yourself struggling with vast quantities of information and no time to go through them. For instance, a marketing team needs to keep track of ad click-through rates, social media interactions, sales and conversion figures, and overall web traffic. But in a single-person team, you’ll have to make a deliberate choice to stop collecting some of your data. Consequently, you could be missing out on crucial information and take the wrong decision.
You don’t know which data matters
There are fortunate situations where time isn’t the problem, which means that you can collect as much data as you need. But according to Forrester Research, up to 73% of the data collected is never used for any strategic purpose. It’s a case of not seeing the connections through complex streams of continuous data. Data is an overwhelming topic, and it can become confusing when you simply have too much to identify the valuable from the insignificant piece of information.
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