qualitative versus quantitative data
August 19, 2007
There are times when qualitative data are more powerful, valid, and useful for guiding action than quantitative data
Shawn points us in the direction of a terrific post by Bob Sutton blogger and author of Hard Facts: Dangerous Half-truths & Total Nonsense, (I haven’t read the book but it’s now on my list).
Sutton is writing about the difference between quantitative and qualitative data generation and the assumption in business that the former is always better than the latter. I come across this assumption regularly and it’s particularly prevalent when you work in an area that’s about emotion and unconscious processes in the workplace
Sutton gives three examples of when qualitative is better than quantitative:
1. When you don’t know what to count. Unstructured observation of people at work, open-ended conversation, and other so-called ethnographic methods are especially useful when you don’t know, for example, what matters most to customers, employees, or a company. Just hanging around and watching can have a huge effect.
2. When you can count it, but it doesn’t stick. ..people are swayed by stories , not statistics.
3. When What You Can Count Doesn’t Count. Researchers are always looking for things that are easy to count, so they can get numbers that are amenable to statistical analysis. There are times when these numbers do matter. Sales, numbers of defects, and so on can be valuable. But in the hunt for and obsession with what can be counted, the most important evidence is sometimes overlooked. As Einstein said, “Not everything that counts can be counted, and not everything that can be counted counts.”
Quantitative data collection will give you the “what”– what has worked, what needs to work and what actions should be taken next. What it won’t give you is the “why” and very often the “how”. Why it happened, why it hasn’t and how action is sometimes stifled by other processes. Knowing what needs to happen and making the leap to making it happen requires a different kind of data generation and management which is why so many change processes aren’t as successful as they might be. How many organisations do you know that spend a fortune making sure the IT system communicates properly but leaves the human communication to the bottom of the “to do” list?