Data analysis can be traced back to as early as the days of the Ancient Egyptians started keeping statistical records while building the pyramids. Since then, data analysis have developed by leaps and bounds, and today is considered to be an integral part of our daily lives.
For businesses, data analysis has shifted the professional landscape to become more human-centric, resulting in effective ways to boost revenue while simultaneously improving customer service.
Today, you’d be hard pressed to find a company that didn’t dedicate significant resources to data analysis. Yet, just because data analysis is commonplace, doesn’t mean that there isn’t always room for improvement. There are still companies that often fail due to the following reasons:
1) You have unrealistic expectations
A lot of companies understand that data is important, which it is, but there shouldn’t be a sense of over importance placed on data. A company’s eventual success is based on a variety of factors, and data analysis should be treated as simply one of those vital factors, rather than a magic solution. A common mistake that some businesses make is assuming that data analysis will immediately improve their business model, thus putting cultivating unrealistic expectations.
Some of the main things that you should not expect data to do for you include:
- You should never expect data to solve any issues you are facing, but rather show you what you need to do to improve as a company
- Data analysis won’t identify the ideal target market but can help you identify potential consumers
- Data analysis is still susceptible to error, thus it’s important to carefully manage and monitor your results to ensure there aren’t any major faults
Expecting that data will replace all things human is a common mistake that companies make when first investing in data infrastructure. First, understand what data can do for you and your business and focus on realistic expectations.
2) You are lacking expert knowledge
Since pretty much every company today deals with data analysis in some form or another, those who are new to data analytics may think it’s simpler than it actually is, thus underestimating the power of an expert opinion. Companies that decide against taking on a data expert often miscalculate the dedication it takes in order to manage data, often asking too much of current employees who are potentially out of their depth.