Where do analysts stand in the data revolution?
In many organisations, business data is now more accessible and abundant than ever before.
It’s an era of data democratisation and anyone who wants to get nose-deep in the numbers is free to go ahead and do just that.
Data democratisation: Good or bad for analytics professionals?
Many analysts will be feeling threatened by this data ‘revolution’. And rightly so. Eager and able to get their hands on business critical stats, their stakeholders and decision-makers may choose to bypass them completely. This is almost certainly what will be happening in any case where the analyst and decision-maker have a poor working relationship (or none whatsoever).
But does a wider availability of data mean that it’s any easier to understand?
There’s a reason why job roles and entire departments are devoted to data science. The analysts are the people who have the technical skills to extract real meaning from the data and make commercially viable recommendations off the back of it.
So, in reality, the demand for skilled analytical staff will remain constant, even in an age of artificial intelligence and deep learning.
If anything, the trend of data democratisation presents analytics professionals with an opportunity to step forward, demonstrate their expertise and command more respect across their organisations.
How to go about this, though?
The analyst’s key to surviving the data revolution
Although analytics teams deal with figures and statistics day in, day out, their effectiveness cannot be measured in numbers. Not fairly.
If all analysts had the authority to implement their own recommendations, it would be another story. But they don’t. They just have to hope decision-makers take their advice.
So what is the most accurate way to measure an analyst’s effectiveness?
Largely this comes down to stakeholder perceptions. Ultimately, do the stakeholders feel that the analyst is helping them in their decision making process?
There are steps that any analyst can – and every analyst should – take to increase their influence among decision-makers and ensure they are adding value wherever possible, and this starts with developing (or honing) soft skills.
Not all decision-makers are the same. Many are more right-brained (creative) than left-brained (scientific), but many are balanced in the middle. The same goes for analysts but in reverse: they all have left-brain traits by definition, but they can have right-brain characteristics too. It would be far too simplistic to say that all analysts are left-brainers and all decision-makers are right-brainers. But no decision-maker is likely to be won over by technical expertise alone. For them, as for most people, they want to understand what the experts are telling them, not feel overwhelmed or (much worse) patronised.
Being able to engage and persuade all stakeholders is therefore paramount in this age of data democratisation. Analysts have to make the expert deductions but then explain their findings simply and clearly, in the language of the stakeholder.
5 key skills/attributes for any successful data analyst today
1. Personality profiling and emotional intelligence
As individual stakeholders can vary so greatly in their thought processes and motivations, the most successful analysts are those who can identify the different personality types and know exactly how to collaborate with each of them.
In order to get there, analysts have to develop their own emotional intelligence, which involves self-evaluation. We all have our own internal perceptions of what we’re like to work with, and these don’t always match up to reality. We’re naturally biased towards ourselves. The more emotionally intelligent an analyst becomes, the more sensitive they are to others’ emotions and behaviours, and the more aware they are of their own actions. And that objective perspective is priceless.
“It’s not what you know – it’s who you know.”
Well, in the case of analytics professionals, that’s only half true. It’s what you know and who you know. Or, more accurately, it’s what you know and who trusts you.
Getting off on the wrong foot is an age-old problem in analyst-stakeholder relations. Unfortunately, this harms the analyst more than it does the stakeholder – at least in terms of perceptions. That’s why it’s vital for analysts to establish and maintain strong working relationships with all potential stakeholders – securing trust and gaining credibility in the process.
The best way to go about this?
3. Commercial awareness
No analyst wants to be viewed as a ‘number cruncher’, but many non-analysts do hold that preconception. Commonly, it’s because they don’t understand (or they lose sight of the fact) that the main function of any analytics team is to inform better commercial decisions.
The way individual analysts can combat this is by demonstrating commercial awareness whenever liaising with stakeholders, making it clear that they know exactly what the organisation’s long-term and short-term goals are. Stakeholders will notice and be delighted.
Some analysts are naturally more commercially aware than others (perhaps those who lean towards the right side of the brain). Regardless, it is an attribute that can be developed over time – and the sooner, the better.
4. Data visualisation and storytelling with data
Analysts understand exactly what their data is telling them. They don’t need a translation. Stakeholders and decision-makers do.
Some analysts suffer from a tendency to overcomplicate their charts and their reports in general. It probably stems from some sort of instinctive defence mechanism: “If I make this look complicated and unfathomable to the average joe, my job is safe – because no-one understands it but me!” Something along those lines. Perplex to impress.
But this is a misguided (and somewhat cynical) way to approach the work. More to the point, decision-makers just want to know what they should do, in plain English, backed up by easily understandable tables, graphs and other diagrams. They’re frustrated, not impressed, by overly complicated charts. If they have to ask for clarification on any aspect of the report, the analyst hasn’t done their job properly.
To get there, analysts have to develop their data visualisation and data storytelling.
The secret to getting and staying on the right side of stakeholders isn’t saying yes to every request. It’s managing expectations.
Most stakeholders don’t realise when they’re asking too much, usually because they’ve only ever worked with passive analysts who don’t speak up. It is true that stakeholders often request work on short notice because they’re working to tight deadlines themselves, but they would all rather wait a few more days for high-quality work than receive rushed outputs that miss the mark entirely.
It’s a vicious cycle, and one that too many analytical teams find themselves in, but one that all analysts have to break out of if they want to be trusted, respected and, above all, valued.
data visualisationNegotiating and trying to be (politely!) assertive may be awkward for some analysts at first, but it pays off.
Equip your analysts for ongoing success
Our guide, How to train and retain your data analysts, covers everything we’ve talked about and more – including tactics for soft-skills development and professional growth that will help your analysts thrive in the current data landscape.
Download your copy here, and please get in touch if you’d like to talk to us about tailored soft-skills training for your analytics team.