Data: More than Just Numbers
It seems like everywhere you turn, you can find someone talking about data. Data science, big data, databases, etc.
Likely, when you think about “data”, you probably think about numbers. The word “data” conjures ideas of science, math, finance, computer science, and so on.
And lot of data are quantitative – they come in the form of something that can be measured numerically. Sales data from the previous quarter, stock prices, number of visits to your webpage, average length of phone calls at a call center – these are all examples of quantitative data. These kinds of values are easy to analyze and report.
But a lot of very important data are qualitative as well. For example, in the Census, they collect quantitative data (like age, income levels) and qualitative data (like education level, various demographic indicators). We rely on qualitative data every day in the form of things like weather forecasts – will it be sunny or partly cloudy?
Moreover, data can be thought of in a different way – not whether it is quantitative or qualitative – but rather whether it is objective or subjective. Again, we usually think of data as something objective. Things that can be independently verified and confirmed like the number of orders for a product, length of wait times at a theme park, etc., can be objectively measured.
However, subjective data can be equally important for decision making. A subjective evaluation might involve rating risks as High, Medium, Low, or evaluating whether a project is aligned with the company’s portfolio. When making a new hire, the decision is largely subjective – does the candidate seem like a good fit with the company?
When you ask someone what they think is the probability of something happening in the future, this is also a subjective data-point. These types of probabilities are known as subjective probabilities, and are individually-held judgements about the likelihood of a future event. While they look like objective values (probabilities are expressed as numbers, after all), they are essentially just opinions.
It is easy to disregard data that are qualitative and/or subjective, but these forms of data are vitally important to decision making. How much earlier should you leave for the airport based on how much traffic will be on the interstate? A quantitative/subjective estimate might be that there is a 50% probability of heavy traffic. A qualitative/subjective estimate might be something along the lines of “very likely that there will be heavy traffic”.
There is a whole world of data out there that relies on people’s judgements, opinions, preferences, and imagination, and isn’t easy to summarize with a number. However, ignoring these data-points, instead focusing only on what can be easily quantified, means missing out on valuable information which can make the difference between a successful decision and an unsuccessful one.
At Collier Research Systems (www.collierresearchsystems.com), we can help you sift through and make sense of the messy data you have and derive insights that can help you make better decisions.