Data Me This
Data, data, data.
Like most overused corporate jargon, the word is often devoid of meaning or worse, purposely deceptive. To be fair, it's not data's fault. 'Data' has become a required selling proposition for every product in the media value chain. Who cares what data actually is or why it's useful. Let's cram the fact we use it into a couple of slides at the front of our deck.
The irony of our industry's obsession with simply having data for the sake of data is two fold.
1. Data is a ubiquitous term that could mean literally anything.
2. Data by itself, IS NOT USEFUL.
In an effort to treat data better, let's take a look at its definition.
The takeaway here is that 'data' is simply a collection of information, but is too often treated as knowledge. To be of any use it must be a representative set of what you're trying to measure and it must be processed.
Say I'm a leading pet food producer that wants to know the US large breed dog food market. In response, my ad agency collects the following data set.
In addition to putting my agency into review and asking Wanda some serious questions about her life choices - this set of data does not help me answer my question - yet it is still data. The hyperbolic example should encourage all of us to ask some simple questions. What do we want to measure? How are we collecting the data? What is our end goal? Without these guiding questions, we run the risk of wasting energy collecting or analyzing data that does not represent the universe we are trying to understand.
Second, data remains useless before it's processed. From the data set above, we can tell that most of our copywriters own pets. Based on this information, perhaps we should create an office pet club? Maybe a bring your pet to work day would boost moral?
In order for data to solve a problem or answer a question, we must extract meaning from it. What are we trying to learn? Insights gleaned from data are the nuggets in the river bed. Data is the stream. People adept at sifting through data to find insight gold will continue to be prized professionals. Collection is necessary but understanding is paramount.
We should go deeper as an industry. We need to be better at understanding our goals. It's not enough to say we got the data. Insights drawn from valid samples should become the framework we build on, not data itself. So next time we hear the word, let's treat our data with respect and ask two questions:
"What are we measuring? And why should we care?"