Why data analysts must simplify their outputs for stakeholders
As crucial as the detail is, many analysts fall into a trap when it comes to communicating the fruits of their labour back to their stakeholders and decision-makers. Very often, the analyst overcomplicates the message – sometimes without meaning to – and this can lead to the real value in their work not being realised. In any such case, the end result is that the audience simply doesn’t get the message.
Technical ability and attention to detail have always been crucial to robust analytical work, and always will be. They are what enables the analyst to make the right connections, and therefore draw accurate conclusions that drive commercial value.
However, the analyst’s job doesn’t start and end with the execution of those technical tasks. For their hard work to actually make a difference, they have to feed their findings back to the business decision-makers in a way that makes clear sense. The analyst therefore has to translate technical work into simple messages.
And this is where many analysts struggle.
What causes this overcomplication?
There are many potential reasons why analytical work fails to drill down to those core messages.
First of all, heavy workloads. Many analysts struggle to negotiate with their stakeholders, which means they take on more work than they can realistically deliver. When deadlines are looming and stakeholders are waiting, the analyst may not spend enough time on the translation of the technical jargon into digestible insights.
Perhaps most commonly, the analyst has a poor gauge of their audience’s level of understanding – both technically and in the subject at hand. Stakeholders and decision-makers need things spelled out for them, because they’re non-technical and they don’t have their heads in the detail day in and day out. If the analyst is unaware of that, and therefore produces work that assumes far too much understanding, they’ll fall at the first hurdle.
Another common scenario is that the analyst feels as though they have to convey the complexity of their day-to-day work, perhaps in order to justify their role within the business. This is understandable, but stakeholders ultimately just want to know what they should do as a result of the analyst’s findings – they care less about the science that led to those findings. It’s the end that they’re after, not the means. If you have developed sufficient trust and credibility with your stakeholders, they will have faith your technical work is robust and accurate.
3 steps towards clearer, more digestible outputs
Spell out a top-line message, and present the information in layers. If you had to summarise your findings in one short sentence for a non-technical person to understand, how would you word it? That’s the approach to take for your introduction. Only share the top-level information to begin with – including recommendations and conclusions.
Exorcise jargon! – And speak the decision-maker’s language. Analytical jargon only makes sense to analysts. Everyone else in the business will respond better to simple English and everyday commercial language, so, as an analyst who’s trying to influence decision-makers, you must become fluent in those as well.
Don’t be afraid of stating [what you think is] the obvious. As an analyst, immersion in the data makes you incredibly familiar with their subject matter, and of course you are able to make connections and inferences that non-analysts can’t. When summarising reports and making recommendations, you must remember that. What seems obvious to you now, at the end of the project, will probably not seem obvious at all to the stakeholders you’re trying to educate.
Taking these steps is especially important if your stakeholders are in senior management positions. They will be spinning many different plates, and will have very little (if any) time or inclination to absorb the technical detail. Make your outputs as simple as possible for them. Talk straight and keep it short.