helping you master customer insight leadership

10 all too common VoC program mistakes and how to avoid them

VoC program

Our focus this month is how to achieve success, including with VoC programs.

Previously, Alan Murray shared his advice on keeping analytics team roles fuzzy, especially for smaller teams. In this post, guest blogger Annette Franz returns to talk about Voice of the Customer (VoC) programs.

Like Annette, I have all too often seen such programs lose their way or just be badly designed from the beginning. Whether using NPS, CES or CSat scores, the focus can become on the metric not action from insights.


Setting up an Analytics team for success = Get Fuzzy!


Building on our month focussed on controversial topics, let’s turn to what will set your team up for success.

Different contexts can require different types of analytics team. A lot of the advice that I offer within the Opinion section of this blog is based on a lifetime leading teams in large corporates. So, I’m pleased to partner with guest bloggers from other settings.

On that basis, I am delighted to welcome a new guest blogger. Alan Murray. After a career in the worlds of consultancy & large corporate, Alan has spent plenty of years in both medium-sized firms & lately startups.


Unicorn Farming: Building Capabilities Against the Odds (Part 2 of 2)

Unicorn Farming 2

Guest blogger Ryan Den Rooijen returns to complete his two-part series on Unicorn Farming.

It’s been great to see the conversations that part 1 has sparked on social media. It’s always encouraging to hear other experienced analytics leaders, like Martin Squires, agree with many of the key points & share their insights.

Hopefully you find part 2 as interesting and useful. I’m tempted to make a “neigh” joke, but I’ll resist. Here is part two, with a focus on how to assess candidates background & experience.


Unicorn Farming: Building Capabilities Against the Odds (Part I)

unicorn farming

Continuing our focus on controversial issues, let’s talk about unicorn farming.

I’ve previously used the term recruitment & retention, but Ryan den Rooijen has the more poetic term of Unicorn Farming. How to successfully recruit for your Data Science team.

Ryan is Global Director of Data Services at Dyson and has previously blogged for us on data artists. We also interviewed Ryan on his role, so you can find out why he know what he’s talking about (including his background at Google).


Why Data is everyone’s job, other leaders don’t leave it to your CDO

data is everyones job

We’ve shared some conflicting views on the need for business partners, but is data everyone’s job really?

Should transforming a business into a data-led culture be the challenge for Data Science leader or CDO? Or should this cultural transformation be shared by everyone in the C Suite?

To make the contention that data is everyone’s job (or at least every leader’s job), I’m pleased to welcome a new guest blogger. David Gonz├ílez is Group Head of Big Data Analytics & AI for Vodafone Business.


The need for analysts to have improved commercial awareness

Commercial Awareness

I have mentioned before that analysts benefit from stronger commercial awareness. But what do I mean by this term?

The easiest way to explain is to set it in context. A lack of commercial awareness is normally shown when an analyst presents their findings. The impression they leave with internal customers is that they are commercial naive & irrelevant.

I’ve written before that this too often happens to otherwise very technically capable analysts. Their work may be based on high quality, well prepared data. Their analysts may be statistically robust & perhaps even presenting using engaging data visualisation.


Factfulness – a suitable legacy from the great communicator Hans Rosling


Readers may remember our obituary on the passing of Hans Rosling, whose book Factfulness was published posthumously.

In this post, I will review this engaging book. It is a fitting legacy for a man who dedicated so much of his life to education and relief. A  number of lessons can be taken from this work, on Data Visualisation, Biases and Communication.

It is a handy sized little hardback, measuring only 19 cm by 13 cm. Small enought to carry around while experiencing the world around you, which would be a fitting way to read this book.