Creating analytical pixie dust

Written by Sam Gardner

Great analytics is invaluable. An organisation’s ability to use its data better than the competition is often the most powerful competitive advantage – just take Amazon as a case in point! However, too often, analytics teams fail to live up to this potential. Why?

I have had the pleasure of leading analytics teams for two decades and believe the secret to success stems from having a clear understanding of what makes a great analyst and ensuring that the analytics team sits at the heart of the organisation.

Seeking out the wizards of the analytics world…



Great statisticians do not necessarily make great analysts. We often confuse the two and this can lead to issues. Over the years, I have been lucky to work with some of the best analysts in the business and they have all demonstrated three key traits:

1. CAPABILITY

A breadth and depth of analytics skill and experience is essential – this is the toolkit!

2. CREATIVITY

Analytics requires more than the right toolkit, it is about how to apply that toolkit in the right way, bespoke to the challenge at hand. As Einstein once said, “Imagination is more important than knowledge”

3. COMMUNICATION

This is not just about the ability to communicate results back in a clear and easy to understand manner – although this is undoubtedly vital! It is also about the ability to listen to others, interpret and translate a given problem into an analytical framework and solution.

THE PROBLEM WITH SETTLING FOR LESS...

It’s rare to find someone who embodies all three traits and finding great analysts is a challenge I’ve wrestled with for most of my career. I can understand why many agencies treat their analytics teams as operational departments, kept safely at arms-length from the client themselves. I’ve witnessed what can happen when a great “statistician” is let loose in the boardroom to wreak havoc on a trusted relationship that has taken months, if not years, to cultivate. I have also seen the blank expressions on the faces of marketeers as an analyst gleefully presents regression coefficients into stunned silence.

However, this tendency that agencies have to treat the analytics team as an operational function, mostly hidden from the client’s view, has serious drawbacks:

ONE: STIFLED AND UNCREATIVE APPLICATIONS OF ANALYTICS

Analysts are often excluded from conversations with clients about how their toolkits can help to solve business issues. Often non-technical team members will instruct analysts on what they require. For example: “I need a drivers analysis” or “I need a TURF analysis”. If analysts are included directly in the analysis planning process and working directly with clients, they are empowered to suggest alternative, more creative and powerful approaches and the end result will be a more inspiring and valuable piece of analysis.

TWO: POOR COMMUNICATION OF RESULTS

A lack of client contact can exacerbate the problem that many analysts face, in terms of being poor communicators of their work. In fact, many analysts don’t feel it is their responsibility to turn their results into a story. If analysts come into contact with clients and have to explain their work on a daily basis, they learn how to do this better. Practice makes perfect!

THREE: A CULTURE OF 'US AND THEM'

When an analysts perceives their sole role to be running the statistical analysis, they can develop a tendency to horde their techniques. As a result, boundaries can go up between quantitative researchers and analysts and this can be counter-productive to collaborative working.

RISING TO THE CHALLENGE...

We need to challenge the role played by analytics teams. We should aspire to involve analysts at all stages of the projects we deliver, from design through to delivery. We should encourage analysts to tell their own analytical stories and share their statistical secrets with colleagues. In my experience, many colleagues have some grounding in statistics and get a real kick out of running their own statistical analysis.

We need to blur the boundaries between the disciplines of quantitative analysis and advanced analytics and work as one team. This is the environment that creates the analytical pixie dust!