The other week I was in Peru, visiting with our clients there and then presenting at the 15th Congreso Anual de Marketing Peru, otherwise known as CAMP 2016. The CAMP program offered us a varied feast of topics largely focused on the future of business and marketing. However, in spite of the focus on emerging technologies the comment that resonated with me most was ‘old goals, new tools.’
Much of the focus of CAMP was on making sure your business and marketing was well-positioned to face the future. We had the usual diet of Uber, Kickstarter, Internet of Things, Artificial Intelligence and 3D printing. And, of course, there was data, data, everywhere. There were even a few examples of data being made useful, for instance with Spotify’s Discover Weekly, which recommends new music that you might enjoy but based on your listening have likely never heard before.
In the course of his presentation Neil Perkin of Only Dead Fish added an interesting rider to the well-known phrase ‘data is the new oil’ to suggest that data, like oil, is toxic without being refined. We see this all the time with our analysis of social media and search data. Unless you can easily separate the signal from the noise and then break that signal down into long-term and short-term trends it is difficult to make any sense out of the data.
Neil Perkin’s presentation was about how organizations can learn to be more agile, but what struck me was that much of what he said was directly applicable to brands and the research business. For instance, he stated, “Speed without focus is foolish.” And that is so true. Everybody assumes fast is better, and sometimes it is, if you can sensibly interpret that data and take immediate action on it. However, all too often the situation – particularly for strategic decisions – is far less clear and which case careful contemplation of multiple data sets is probably going to give you a far better result.
Neil identified three different types of problem:
Simple: like a recipe, a combination of ingredients or variables has a defined outcome.
Complicated: like sending a rocket to the moon, lots of different factors need to be considered and calculated.
Complex: like raising a child, everything is in flux as the child responds to different things in different ways at different times.
To my mind, testing whether an ad is likely to be effective is a relatively simple problem; there are a proven set of variables that anticipate success. Creating an effective cross-media campaign is more complicated. But building a brand is complex, not least because consumers bring their own needs, values and desires to play in determining whether your brand will be successful or not. Complex problems require far more thought than simple ones, and demand us to take more time to arrive at the right decision for the circumstances.
I see a lot of people applying the same demand for speed to a wide range of different problems and arguing that some data is better than none if it helps make a decision, but is that really true?
Written by Nigel Hollis,Executive Vice President and Chief Global Analyst at Millward Brown
