What if your story doesn't match your data?
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What if your story doesn't match your data?

I'm asked variations on this question all the time. And there is no satisfying answer.

I was speaking at a conference yesterday, giving my most-requested speech, "From Numbers to Narrative: A Story in 5 Parts", wherein I give an overview of the required way of thinking to get from a pile of numbers to a visual story with impact.

One of the key ideas is that you need to focus in on what the data is saying, what your audience needs, and what you really want to say. And that's where the trouble starts.

"What if the data isn't saying what you really want to say?", an attendee asked in front of the audience of 700 or so people. The question refers to when the data results don't align with what you want to be the case. And the implied question, really, is "can I spin the story to say what I want to say, regardless?"

This is a very easy question in some ways. The answer is no. I consider myself a "data fiduciary". My first responsibility is to the truth in the data. So...no...you can't "spin" the story to say what you want.

It's a hard question because I understand the other underlying implication. Your boss wants and expects an answer that may not be there...so now what do you do? You can't spin it. You can't lie and manipulate. But yes, there is a way to tell that story. But first you have to accept that the story isn't what you hoped.

For instance, if you're doing a drug safety trial, and the drug doesn't work. You can't spin that. You can't put lives at risk. The story is "this drug doesn't work". End of story. Simple.

But if you're looking at employee retention and the data shows that retention is down across the entire company, but especially for people reporting to your boss...who asked for the report...oof. Tough one!

Guess what, though? Same answer. The story is "retention is down across the board, and it looks like a comparison of managers shows that some are faring better than others...um..."

But here's where you don't necessarily spin things, but you can be "diplomatic". If there is no need for a manager by manager comparison, you can leave that out. (But is that serving the business?) You can leave it in the visualization, but not verbalize it in the meeting. (But is that serving the business?) You can aggregate the results up or down to obfuscate...but IS THAT SERVING THE BUSINESS?

Let's be honest. Data analysis and stories that are "diplomatic" or obfuscate or spin or otherwise hide hard truths aren't helping anyone. They may help you avoid a difficult conversation, but long term (or even short term), they can be harmful.

So...excuse the harsh expression here, but it's time to put on your "big boy pants" and tell the story the data is telling, even when it's uncomfortable.

Be a data fiduciary, even if it means occasionally upsetting people.

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Jack Speranza

I emphasize excellence in operations to build great products, great services & great companies.

7mo

You’re absolutely right here, but the sad reality of most people in larger companies is they lack the culture to support handling the truth. Anecdotally, absent a strong culture that values candor, I’d estimate less than 15% of enterprise employees are equipped to navigate through these challenges effectively. I’ve yet to find a magic bullet for navigating through this major constraint.

Irina Roxana Sucoverschi

Legal project management; Legal Operations; Data analysis: Python, PySpark, SQL, Azure Synapse; Power BI; Financial and operational data analytics; Manual software testing and automation; Agile: Kanban; Paralegal degree

7mo

Thank you for bringing up this ethical issue. Such dilemmas used to be reserved for researchers and scientists, so while not new, it is increasingly relevant in our data-driven world. Being a data fiduciary means telling the story honestly, otherwise what insight are we really getting? You can't conduct an experiment exclusively to confirm a hypothesis and to that end, corrupt the process. If the experiment disproves the hypothesis, you go back to analyzing the data to find out why. Maybe you just need to reformulate the hypothesis.

Oz du Soleil

Microsoft Excel MVP | Excel Instructor on LinkedIn | YouTube: Excel on Fire | Professional Raconteur | Video Editor

7mo

Bill How do you deal with something that's more nuanced? Like: - The data says that we should do more of X, but X is unsustainable. - These are our Top 5 performers but I suspect #2 is gaming the system. - These types of articles get the most engagement but it's trolls and bickering. I've told the story a million times about my time in Customer Service. My metrics were terrible and I never won any of the contests for a paid day off. But we finally got a Director who saw my value in the types of problems I was solving--at the expense of good metrics. It taught me to be very very suspicious of data.

Ibrahim Nurudeen Musa

Business Intelligence| Data Analytics| SQL| Power BI| Tableau|

7mo

Interesting. By default, I am leaning to believe that every professional data analyst should be a data fiduciary as well...

Interesting read! It emphasizes the importance of ensuring our narratives align with our data. Discrepancies can lead to mistrust and misinformation.  Thank you for sharing

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