I’ve been working on a data project today. Thought it might be nice to share some of my notes…

 

Insights are things you don’t know, should know, but have the ability to change“. Eric Swayne

 

Companies are vacuuming up data to make better decisions about everything from product development and advertising to hiring. In their 2012 feature on big data, Andrew McAfee and Erik Brynjolfsson described the opportunity and reported that “companies in the top third of their industry in the use of data-driven decision making were, on average, 5% more productive and 6% more profitable than their competitors”. Picking the right numbers is hard though.

 

Three big stats I read in reports recently (and you can obviously read whatever you want into numbers you read in reports, but I have no reason to doubt these ones):

  • Of all the data that has ever been collected, only 22% of it ‘useful’ and less than 5% of it has ever been analysed (no idea how anyone actually knows this, but it opens up a debate worth having).
  • Less than 20% of enterprise organisations use more than 50% of their customer data.
  • 88% of enterprise business don’t even share their own customer data internally between sales and marketing departments.

 

I have even seen companies build algorithms that can figure out the most effective metric for measuring the success of each digital channel, only to shut them down because they got too complicated and the computers lacked consistency when trying to understand consumer behaviour. In one case, the company built a swat team of analysts and employed a consulting firm (to the tune of almost $1m), only to can the entire project when key executives disagreed about the accuracy of the figures. They wanted to find a “Moneyball Metric” (their words), that would help to give them a competitive edge, as they were losing market share. Sadly, it didn’t work out as well for them as it did for the Oakland A’s.

 

Which leads me to one of my all time favourite quotes, this time from W. Edwards Deming, a quality control consultant from Ford (based in Japan in the 1960’s), and is the most quotable data scientist’s I’ve ever come across ~

Deming-in-Tuxedo-DEM-1078-Dr.-Deming2-1940x1130

Just because you can measure everything doesn’t mean that you should”. W. Edwards Deming.

 

So if teams of professors, engineers writing algorithms, management consultants or analysts struggle to figure out which metrics should be measured, how are marketing professionals supposed to do any better? Marketers are especially guilty of making  decisions upon “gut feeling” or emotion. In the brilliant strategy book “Good Strategy, Bad Strategy” by Richard Rumelt, he warns us of this ~ saying (and I’m paraphrasing), good strategy should be devoid of emotion, bias or personal agenda. It should be based upon evidence, data and hard facts. Marketers are emotional beasts though, and we are all too quick to jump on a figure (often the wrong figure) that “feels right“, or paints a picture or a story in the way that we want to tell it. We’ve all done it ~ I know I have.

 

If we have data, let’s look at data. If all we have are opinions, let’s go with mine.” Jim Barksdale (Ex-President & CEO Netscape).

 

 

So, one of the most important steps in attempting to make decisions with “big data” (hate that phrase but what else are we supposed to use?) is to pick the right metrics, and have the right filters in place to make sense of the data that we are examining. Good metrics are consistent, cheap, and quick to collect, but most importantly, they must capture something your business cares about.

 

Again, one of the biggest mistakes business make is trying to capture more data, instead of making sense of the customer data that they already have. From what I’ve seen, many brands seem to be sat on goldmines of data and they don’t even realise it.

dilbert dashboard

In a great article by Walter Frick from the Harvard Business Review, Walter suggested that executives should refer to “Six Questions” when asking questions of data. Regardless of what results your analysts, agencies or consultants give you, these questions were formulated to help executives feel more confident about making big decisions, based upon what their your data is telling them. I thought it might be useful to share them. Seems like a smart list of questions to me:

 

6 Questions Successful Executives (and Marketers) Should Ask of Their Data;

  1. What was the source of your data?
  2. How well do the sample data represent the population?
  3. Does your data distribution include outliers? If so, how did they affect the results?
  4. What assumptions are behind your analysis? (Would certain conditions render your assumptions and your model invalid?)
  5. Why did you decide on that particular analytical approach? (What alternatives did you consider?)
  6. How likely is it that the independent variables are actually causing the changes in the dependent variable? (Might other analyses establish causality more clearly?)

 

Finally, I read an incredible statistic in the British Airways in-flight magazine recently, from consulting firm Price Waterhouse Coopers. They estimated that 75% of executives still made major strategic business decisions based upon their gut feeling, even when they have all the necessary data at their finger tips to help them make an informed decision, based upon their business data.

big-data-funny-meme

We clearly need people (not just algorithms) to make smart decisions, otherwise computers would be able to do everything, but neglecting data because you don’t feel confident enough to use it is not an acceptable excuse. Successful executives, marketers and business professionals don’t need to have maths Phd’s, a deep understanding of economics or know the basics of data science, but they should have confidence in their numbers.

  • Good executives communicate the data that they are given.
  • Great executives ask questions of their data before they share it across the business.

 

There is a difference between numbers and numbers that matter”. Jeff Bladt and Bob Filbin

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Worth reading (and following):

 

 

Evangelist @IBM • IBM Watson • Travel Around Talking about AI, Big Data and the Future of Marketing • Lover of Old Business Books and Good Bourbon • Based in London, UK.

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