Nancy Porte knows what she is talking about
I have been reading a PR release on the latest Verint-Vovici voice of the customer survey. The key finding is “organizations hailing from a wide range of industries and company sizes are catching on to the value of the Voice of the Customer”. And the conclusion is “research shows that as long as companies aim to enhance the customer experience, improve customer loyalty and increase profitability, the VoC will always fill a mission-critical role”. It is good to see that an ex-employer, The Peppers & Rogers Group, has been involved in this study. Let’s move on to the part of the press release that did catch my attention:
“People are amazing at collecting data, but they’re often less skilled at creating insights out of it and spreading them throughout the whole organization,” adds Vovici’s Porte. “Data is great, but it rarely means anything unless you’ve figured out exactly what that data is saying and what you’re going to do about it.”
What happens when you give a budding Alexander the Great a fleet of stealth bombers?
Imagine that you turn up at the residence of a budding third world ‘Alexander the Great’ – a dictator with dreams of empire. You offer him a fleet of stealth bombers with all the associated armaments. You are excited, the dictator is excited – you see yourself as rich and the dictators sees the world at his knees. What you have both forgotten is that it takes highly skilled pilots to fly these stealth bombers. And you need to put in place a whole ‘infrastructure’ (hangars, airstrips, fuel, missiles, technicians) to enable highly skilled pilots to make use of these stealth bombers. You might be wondering what this has to do with VoC and Customer Analytics. Everything.
There are plenty of vendors offering analytics stealth bombers (advanced data mining and analytics platforms, packages and ‘solutions’). Before you embrace your dreams of ‘world domination through analytics’ you might want to consider and prepare for the following:
- The fuel (data) that powers analytics is typically missing, insufficient and/or ‘dirty';
- The pilots (statisticians) that need to fly the stealth bombers (the analytics packages) are in short supply – there simply are not enough of them to go around to fulfill the dream that is being aggressively communicated;
- The infrastructure (leadership, mindset, culture, practices, processes….) that is required to ‘make use of the skills of the pilots’ and ‘exploit the potential of the stealth bombers’ is simply not present in the vast majority of organisation and putting it in place is a BIG ask, which requires patience (think long term) and commitment (to face and overcome the hurdles – big and small).
What is so in the real world?
What is the state of affairs in the real world? I cannot answer that question as I have not sampled the whole world of business. Yet, I can share my lived experience with you when it comes to the analytics front. Allow me to illustrate with two examples.
As a customer based strategist I need and generate insights in order to construct viable strategies. In one consulting engagement I asked a question: how many customers did you sign-up last year over channel X? Sometime later I was handed a report. I got a different answer depending on which page I looked at. There was only a small difference between the numbers and the point is that there should have been no difference! Either the definition of ‘customer’ was not consistent over the enterprise. Or the definition of the ‘channel X’ was not consistent. Or the enterprise systems and/or people were not able to add up properly. Sound bad enough? What if I told you that the managers in this enterprise prided themselves on the quality of their management information?
In another consulting assignment (involving the formulation of a customer strategy) I was in the process of getting to grips with the customer base – specifically, customer profiling and segmentation. I needed to understand who was buying a particular product. So I asked a helpful member of the client organisation to come back with the answer. I was handed a small document and it clearly stated that the buyers were male, in their thirties and living in the larger cities. Having been burned more than once, I asked to see the actual figures. Upon reviewing the figures I found that the buyers (customers) were indeed in their thirties and living in larger cities. However, there was no statistical difference in gender: the buyers was just as likely to be female as male. You might be wondering how someone who is trusted (and whose job it is) to interpret data get it wrong so badly? I can tell you that this is no exception – misinterpretation of data is the norm rather than the exception. Why? Because we are not statistically minded. Thinking statistically is arduous and is a skill that has to be learned and continually practiced.