‘…global is a good thing and warming is a good thing. If [the scientists] had called it ‘Atmosphere Cancer’, they probably would have started on a better footing because atmosphere is scientific and cancer is a bad thing. There are no cancer deniers. Everyone knows that cancer is a chronic and degenerative disease, and you need to stop it soon.’
Seth Godin
Marketing problems are everywhere. Marketing is about change. Getting people to take action and perhaps a slightly different action than they did last time.
There is no doubt ‘atmospheric cancer’ carries a much more powerful punch than global warming or climate change. Especially if you or someone close to you have experienced cancer.
Perhaps we have a similar problem.
When we talk of ‘responsible data management’ we seek a positive framing. We seek to inspire people and organisations to aspire to improving how they manage data. Sometimes we talk of ‘Do No Digital Harm’ to link it to a historic, and well received, movement. And responsible is a good thing, organisations tend to believe they are being responsible already and they don’t tend to have goals or values that include being irresponsible. Data or data management tend to be viewed as positive or benign.
If we talk of data tumours we frame it as something to be cut out. Or if we talk of data disease, data disorder, cancerous data, or data plagues we frame data as the problem.
If we talk of data justice we highlight power. We highlight or hint at that there is some form of injustice present which needs correcting. It is a slightly more positive framing than data injustice.
If we talk of data malpractice we frame as ignorance, negligence or intent. It may invoke thoughts of doctors. And malpractice certainly gets the attention of lawyers and risk departments. It activates our imagination immediately. It will likely make people immediately defensive, uncomfortable and scrambling for justifications. This may or may not be helpful.
Thinking about it as a marketing problem helps frame things differently. We don’t need to be data scientists to see gender discrimination in data and technology. To see discrimination against BAME people in our response to COVID. Or even to understand how the bias gets into our datasets. There is no doubt there is significant injustice and malpractice happening with data and technology.
Therefore, perhaps we need to call it out more even if it causes us to squirm a little in our seats.
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