We live in a world of data. Data is collected all around us every minute of the day. Everywhere we go, in our cars, on the bus, through our carrier networks, at work, at school, the shopping mall, and church, etc. Information about who we are, what we do, and how we do it is constantly being stored. Data can be overwhelming, so is it necessary for an organization to collect so much? And if so, when does collecting data become ‘too much’?
Data are specific facts or pieces of information gathered intentionally for a precise purpose. The circumstances in which data are collected may vary, but it is typically collected to address or answer questions. Often, data collected is analyzed and reported to provide insight and understanding. There are many focuses for data collection serving different needs, such as financial data, scientific data, statistical data, and meteorological data.
But the question remains, is all the data being collected necessary? There may be moments for an organization when it certainly feels like there is too much data. If you or your organization have felt overwhelmed with data, perhaps this is the reason why:
Data collected with no real purpose in mind.
Someone may have thought it was a brilliant idea to collect certain information because it would be nice to know. So, now you have data collected with no plan for how it would be used or helpful to have. Collecting data for the sake of just ‘good to know’ serves no credible meaning to the data and is not a good use of time or resources. Data should be collected intentionally, with a predetermined purpose or use in mind.
Lack of knowledge on how to analyze data.
Even when the scope for data utilization is clear, if the data collected is not well-analyzed, then the conclusions drawn from the data are meaningless. Data analysis is necessary for understanding results, answering key research/evaluation questions, identifying gaps, drawing unbiased conclusions, and can be used to predict outcomes down the road. Many businesses use intelligence software to help organize their data and present their data using graphical representations.
Trained data analysts are not involved.
After it is all said and done, although the purpose for collecting the data may be clear and the data may be analyzed appropriately, someone who is knowledgeable and skilled at interpreting data should assist. In fact, a trained professional should be around the table from the beginning to assist in determining the goal as well as the best data to collect and analyze in relation to the goal. Then interpretation becomes a no-brainer for the expert. Having the most sophisticated graphics available with exciting colors and 3D images are useless if you cannot determine what it means. That is one caveat to having a trained data analyst on your team.
Do not let the abundance of data overwhelm you. Involve a data analyst on your team to help you determine the purpose for your data collection, decide on appropriate analysis, and provide accurate interpretation.