There is a debate that is coming to a head in the UK at the moment about the future of cigarette packaging. The government has been running a consultation exercise to examine the potential effect of making all tobacco products available in generic packaging, removing any individual branding. The debate, hugely simplified, goes a little bit like this:
Supporters of the proposal: Cigarette packaging encourages people to smoke. It’s the only remaining vestige of marketing in the industry, and if we were to remove it then we’d see a continued fall in the numbers of people smoking, and therefore ultimately the number of smoking-related deaths.
The tobacco lobby: Nah. Marketing doesn’t make any difference.
Supporters of the proposal: So why are you opposed to the proposal then?
The tobacco lobby: Oh.
Putting aside the whys and wherefores of the public health implications of the specifics, the case does for me exemplify what I have always seen as the classic dilemma of social science: that, without the ability to do double-blind style experiments, it’s next to impossible to remove subjectivity from any “evidence” in the field of social research. Traditional marketing (or “Applied Social Science” as I sometimes like to think of it) is very difficult to objectively measure because there is always going to be the challenge of a lack of control group (ie would the thing that has claimed to be attributed to the marketing activity have happened anyway?). It’s interesting to see the supporters of the tobacco lobby turning this around at the moment in support of continued branding on packaging.
This of course is also the reason behind much of the appeal of digital forms of marketing, and particularly the ability to do things like A/B testing – which has had the effect of turning marketing activity from firing money at scale into a void into endless refinement based on minute data analyses.
The rise of quantitative analysis at scale, though, scares me somewhat. The logic of the numbers can stand so strong against gut instinct, intuition and creative revelation. Analysis of numbers alone tends to force thinking around refinement of the now, rather than challenging and disrupting. Although A/B and it’s like have been disruptive in their introduction, have significant step changes come later as a result?
Current book of the moment for me is The Master Switch – in which Tim Wu traces the rise and fall of various Information Empires over history. One of the challenges for dominant information empires is that they tend to focus exclusively on refining their current product, making them blind to new technologies that emerge that will usurp them. For example, Western Union ruled the telegraph industry in the 1800s, but thought the telephone a novelty distraction when it emerged at the end of the century. Western Union spent its energy in making telegraphy better, and became irrelevant over time as a result.
So here’s a contentious thought: with big data, analytics and the like all the rage at the moment, do they run the risk of encouraging organisations to become even more wedded to tiny incremental change and introspection, and thus to ultimate extinction as a result of being unable to truly innovate and take note of disruptive competition?