Analytics through the looking glass

The dummy’s guide to analytics

Friday 04 May 2018


Key takeaways

  • Analytics teams deliver most value when you strike the right balance between commercial guidance and analytical freedom
  • Treating analytics teams in the same way as IT or reporting teams is a great way to achieve high churn and a low return on investment

One of the biggest problems with analytics is the different expectations about what it is. Analytics lives (and tends to get lost) at the intersection between IT, digital, reporting and commercial analysis. So expectations often depend on where in the organisation your analytics team sits. Analytics works best when it is connected to all of these but remains distinct.

In this post we aim to break down a few myths. Our purpose? To help you maximise the power of your data and avoid analytics becoming an expensive waste of energy and time.

What is analytics?

Analytics is simply a buzzword for analysis of datasets that are too large or complex to manage in a spreadsheet. These analyses are initially done by a human being, but become more valuable when they are automated and integrated into business decision-making, for example with dynamic pricing of tickets.

It's part of digital, so this is about online?

No! Wherever there’s data in the business, it may be useful to analyse it. Just because e-commerce produces a lot of data, that doesn’t mean it’s the only area in which you can apply analytics.

So how does it relate to IT?

Analytics works closely with IT to get the right data, and to convert one-off analysis into automated reporting, but they are different teams with different roles, motivations and needs.

Okay, so it’s reporting then?

Analytics is more about answering a new question every week than giving answers to the same questions every week. The results of analytics work may become embedded in a regular report (e.g. the effectiveness of promotions), but that’s not the same thing!

So what is an analytics team?

Analytics are your elite problem-solving team. They use data to help your commercial teams make decisions, and to make your commercial processes data-responsive.

How should I manage the people in an analytics team?

We’re going to make some sweeping generalisations here – apologies in advance...

Analytics practitioners are explorers in the data universe, hunting for the answer to a problem. They often fit the role of a specialist, are best motivated by being given problems and the freedom to solve them, but are likely to lose interest once the problem is solved. This means that managing them with the same performance criteria as IT or a finance team is unlikely to get the best from them. Another common trait is getting lost in the beauty of a problem rather than seeking a pragmatic 'good enough' solution. This makes it extremely important to find someone to lead the team who can talk both commercial and analytics to keep them focussed on business impact.

How can I get the most impact from my analytics team?

You need a data-driven culture and a commercial direction. Analytics must stay close to commercial teams so that it stays focused on problems that are important to your business today. The analytics team should have the freedom to analyse data from across the organisation to provide support (and challenge) to the business.

The team should be connected enough to IT to able to turn one-off moments of truth into ongoing insights, and should be championing bringing new data into the business.

Your team needs critical mass so that it’s big enough for mutual support and to avoid people feeling isolated amongst others with a different skillset and motivation.

Where should an analytics team be located in my organisation?

There’s no clean-cut answer to this; it will depend on factors such as:

  • How mature your business is in using data to make decisions
  • What’s driving value in your organisation
  • How innovative your IT people are
  • How large your analytics team is

You can choose a centralised team, a hub-and-spoke model, or functional teams integrated into your commercial teams – or a mixture of all of these.

In summary:

You will get most out of your analytics team by balancing commercial pull with analytical freedom. You should think of analytics as a distinct group, with different motivations from the IT/reporting/digital fraternities. Their key role is to be the providers of new insights so that you can make better decisions.

In the coming weeks we will begin a mini-series on how consulting is changing due to analytics.

For more information on what analytics can mean to your business, see ‘The mechanics of business’.

Graham Alexander, Manager

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