Interviews, insight & analysis on digital media & marketing

Data scientists take centre stage – but don’t ignore your supporting cast

By Josh Nicholson, Managing Director, Head of MarTech, Credera EMEA

Trawl through search engine results while trying to pin down the value of data to business and you can spend hours comparing estimates. What isn’t in question is that enterprises the world over have cottoned on to the importance of using data to drive commercial success.

This understanding has prompted the rise of the data scientist. According to one analysis it’s becoming a more common role at all but the smallest of firms. The expertise of data scientists is much-vaunted – and rightly so. It’s a specialism that underpins change and growth at many companies; not least, the likes of Amazon, Google and Facebook.

But I believe many businesses are missing a trick with their data. Rather than place giant pressure on the shoulders of data scientists alone, if data’s use is democratised organisations can flourish further.

It’s fair to say many businesses are now proficient in collecting large volumes of data. There’s also a healthy trend of data software investment and implementation across departments – from operations and HR, to product development and marketing – procured from the likes of Amazon, Microsoft, Google, Salesforce, Adobe etc.

However, firms are less proficient when it comes to making best use of their data and driving actionable insights from all of the information at their employees’ fingertips.

There are several main reasons for this:

Organisational silos

Employees organised into departmental silos, working from different databases making it hard to collaborate to deliver an excellent experience for your customers.

Poor implementation of technology

The idea that you can buy a silver bullet solution that will fix all other problems when more often it’s the fundamental strategy, organisational design or processes that are broken.

Poor data literacy & cultural alignment

Decisions should be empowered by data but too many employees feel uncomfortable with this, they don’t trust the data, they don’t trust it’s been collected or analyses correctly or they don’t even know it exists.

On this last point, our Savvy CMO Survey, due to be released later this month, polled over 200 CMOs in the UK & US and found that 83% say they already struggle to integrate and analyse data to inform decision-making.

The common outcomes of these problems are a “gut-feel” approach to decision-making; lost opportunities for commercial gains; and the expense of constantly using data experts when wider team members could competently and confidently pick up the slack.

As always people, processes and tools must combine seamlessly to get the job done.

Small steps

There’s no harm in taking small steps at the start of a new data strategy. In fact, a narrow focus on one area of your business that needs attention is a great way to get started for minimal cost and maximum reward.

I’d advise finding a thin slice of your organisation where you can can quickly add value. This could be a particular area of product development, or analysis of communications-to-conversion in a chosen marketing channel, for example.

Next, assess the tech you’ll require – or which is already available in your business – that is up to the task. There are tools available that allow for drag-and-drop data-set creation which won’t cost the Earth or require users to learn a new coding language.

Then, determine who in your team is best-placed – with relevant training and support – to carry out the data management, analysis or implementation necessary to meet your defined goals.

Again, this could be as simple as identifying “data stewards” to structure and de-dupe your data and ensure it’s ship-shape for use. Remember, too, that awareness of current and existing data privacy legislation – think the growth of GDPR fines and tighter control of cookies – is essential to avoid potentially damaging difficulties.

Occasionally, when attempting the above, you’ll need to consider investing in external help for optimal outcomes. This is often a good starting point in itself – understanding what you currently don’t have the talent or time to do a best practice job of with your internal talent. For example; outside experts can conduct a data maturity assessment over several weeks. This gives you an independent, quick view of your current data set-up – but also a roadmap for quick wins, and a longer-term data strategy to strive towards.

Following these small initial steps can be a catalyst for business benefits but also wider cultural change. When one department realises good results are produced by switching from gut-feel decisions to smart data application that’s driven by better use of tools, people and processes, they’ll want a slice of that success by getting involved, too.