Influence through Data

“Yeah, Says Who?” – Influence Through Data

You know you’ve achieved results – the data tells you so – but how do you influence sceptics to believe it?

It can be a rude awakening to take the findings of a study outside your own team or organisation, where trust and mutual support are more or less a given. In front of a wider audience of funding providers or other stakeholders, you will inevitably in my experience find yourself being challenged hard.

This is as it should be – scrutiny is a key part of a healthy system – but, at the same time, it’s always a shame to see an impactful project or programme struggle purely because its operators fail to sell it effectively.

Fortunately, while there are no black-and-white rules, there are some things you can do to improve your chances.

Confidence = Influence

When I present findings I do so with a confidence that comes with experience and from really understanding the underlying mechanics. But if you’re not a specialist and don’t have that experience there are things you can do to make yourself feel more confident and thus inspire greater confidence in your audience.

First, make sure you have thought through and recorded a data management policy. Are you clear how often data should be entered? If information is missing, what will you do to fill the gaps? What are your processes for cleaning and regularising data? Is there information you don’t need to record? A professional, formalised approach to keeping timely and accurate data sends all the right signals about your competence and the underlying foundations of your work.

Secondly, use the data as often as possible, and share the analysis with those who enter your data so that they can understand its purpose, and own it. Demonstrating that your data is valued and has dedicated, accountable managers hugely increases its (and your) credibility.

Thirdly, take the initiative in checking the reliability and validity of your own tools. If you use well-being questionnaires, for example, take the time to check whether they are really measuring what you want to measure in most instances. In other words, try to find fault with your own approach before your stakeholders so that when they find a weak point you have an answer ready that not only reassures them but also underlines the objectivity with which you approach your work.

Own Your Data’s Imperfections

Finally, and this might feel counterintuitive, you should identify the weaknesses in your own data and analysis and be honest about them. All data and analysis has limitations and being clear about those, and the compromises made to work around them demonstrates objectivity which, again, reinforces credibility.

In conclusion, the better you understand your own data and analysis, flaws and all, the more comfortable and confident you will feel when it, in turn, comes under scrutiny.