A Match Made in Data: 5 Mistakes to Avoid When Building Your Analytics Dream Team

Companies have fallen head over heels for analytics, convinced that data is what they’ve been looking for all these years, and that its insights are the key to thriving successfully ever after.

And to be honest, they’re not wrong.

Data analytics have become an important part of business success; allowing companies to achieve a clearer understanding than ever before of how and what their customers engage with, where to focus their spend and how to get customers to say ‘I do’ to their products or services again and again.

Yet, despite the rose-coloured enthusiasm, budgets and resources now being dedicated to the cause, many businesses are walking away from this union disillusioned with the results and wondering where it all went wrong.

Let’s take a look at the 5 most common mistakes that companies are making when deciding to take the plunge into a data-driven future.

  • Unrealistic team structure

The hiring of an analytics team often comes hand-in-hand with some seriously unrealistic expectations. This is made worse by a lack of understanding of the necessary skill sets involved in delivering on your data.

Sure, investing in a few data analysts with BI skills and a data scientist to perform those complex machine learning techniques is a great start.

But in reality without an engineer in the mix to give access to and tidy up your data, analysts and data scientists will spend 90% of their time wading through your messy information baggage – just to get usable data. And with precious little of their time left, you’re likely to generate less insight and more resentment from those in upper management.

But having an in-house engineering team isn’t always cost effective. Which is why a hybrid model outsourcing this component to a provider like Conjura is becoming increasingly popular as economies of scale help make it a cheaper and more efficient solution.

However you decide to delegate your set-up, remember that Engineers, Analysts and Data Scientists all have a role to play in a healthy analytics team.

So to sum up – If you like it, put 3 teams on it.

  • Suboptimal tooling

Mysteriously, companies will sometimes choose a particular tool or set of BI tools before an analytics team has even been put into place.

This is a pitfall we refer to as: All the gear, no idea.

For example a BI tool may be chosen due to its snazzy data ingestion engine. The marketing was great, the packaging looked good, but when you get down to business you realise that the volume of your data is too robust for that particular BI tool; making it an unscalable solution after all. But by this point, you’ve already spent far too much time and effort setting up data feeds and transformations in this tool, making a switch in strategy sound less attractive than just sitting back and settling for less.

Remember, there’s no “BI” in team.

  • Absence of focus

Your data can help you to form a true understanding of how your business is operating and reveal areas of improvement with huge potential impact. A bedrock of any successful relationship is listening – so be sure to listen to the story your business is telling and choose an issue to tackle with your analytics accordingly.

A subscription business might very well consider building a churn model, simply because it seems like a smart thing to do. However, had they listened to what their data was telling them they might have realised a much larger opportunity existed in lowering the cost of customer acquisition instead.

Similarly, data science resources can be consumed in building complex algorithmic attribution models, which end up confusing or misleading the marketing team rather than enlightening them.

A little focus goes a long way and picking the correct problem to solve before embarking on an analytics journey is the single most important factor in your success.

Take a deeper look on this topic here.

  • Bad hires

The days of companies wondering whether they should jump on the data analytics bandwagon, or having a single data analyst on staff, are gone. A new focus is beginning to shift towards the building of the right team to harness all that data has to offer. But what does this look like?

Enthusiasm aside, a bad hire can be a lot like a bad date, better on paper than in practise.

And with analytics being a relatively new area of focus, many management teams don’t know what good looks like before they make a commitment.

Often a new head of analytics is appointed to a business without truly understanding what type of candidate is required. Which is why it’s vital to first nail down the structure for your dream team and then evaluate which skill sets you need to get from disarray to data-driven.

The likelihood is that you will require a combination of high technical expertise and good project management skills. Make sure you know who will lead the pack in each of these areas to create forward the motion you are striving for.

  • Lack of patience

Have you heard that good things come to those that wait?

Perhaps surprisingly, this could not be more poignant than in the world of data analytics. With most businesses entering the playing field completely oblivious to the quality of their existing data, or the absence of key data fields needed to inform their queries – they know not of the journey ahead.

Only by embarking on the discovery mission will they uncover data issues and be able to begin addressing them by altering data capture processes or tool configurations. Once the necessary changes have been made, historical data will then need to accumulate to enable insight generation.

But to a management team that lacks understanding, this may appear to be a bunch of excuses to justify the lack of value generated. The key here is patience and persistence. Without fixing data issues a business can never become a data-driven organisation. So the best way to overcome these challenges is to educate management teams from the outset.

Afterall, we can all agree that patience is a virtue.

Read more about this here.

With all of this in mind, thoughtfully creating the right analytics team for your business is an invaluable opportunity to truly know your business and its customers inside and out.

With the proper support and understanding of what your analytics journey will entail, this team can help you to understand how the information that you collect relates to the rest of the world, giving you the ability to take real action, in real time.