Fi (00:10)
Welcome to Undubbed, the podcast that's unscripted, uncensored, and undeniably data. I'm Fi Crocker.
Sarah (00:18)
And I'm Sarah Burnett and we're recording this one fresh off the back of Tableau Conference 2026 in San Diego. And honestly, we're still buzzing.
Fi (00:29)
We had the absolute privilege of presenting at TC26 this year and we want to bring that session straight to you because if you weren't in the room, you deserve to hear it.
Sarah (00:42)
Our session was called building a data culture with Datafluencers And the whole premise of this was the best data at work in most organisations will never be seen. Not because it isn't good enough, but because nobody told the story.
Fi (00:59)
Today we're gonna walk you through exactly what we covered, why brilliant work goes invisible, how to fix it, and the tools you can use this week to start changing that.
Sarah (01:10)
Before we dive in, if this resonates with you, please share this episode with someone on your data team. This is exactly the conversation they need to hear.
Fi (01:21)
Right, let's get into it.
Sarah (01:24)
We've spent decades inside some of the world's largest organisations and the single biggest problem we see isn't bad data. It isn't even bad analysis. It's not even incompetent leaders. It's brilliant work that disappears. And today we're going to fix that.
Fi (01:44)
I'm Fi and Sarah's here with me. We're co-founders of DubDubData and both Tableau ambassadors. Between us, we've spent decades doing exactly what you do, building pipelines and dashboards, running analyses, building predictive models, and leading large digital transformations inside some of the world's biggest organisations. The projects we've worked on have delivered more than 65 million in ROI.
We know what makes data work and we're sharing it with you today.
Sarah (02:17)
We're covering three things. One, why your work is invisible. The work is great, but the story is missing. Two, how to fix it and why it's on you, not your manager. Three, the tools to do it this week. A framework, a format, a channel. The only thing standing in your way now is you. And as a special bonus, stick around till the end where we share access to our free
training course on everything we covered today in more detail.
Fi (02:53)
Let's crack on and explore why your work is invisible.
Sarah (02:57)
Hands up if this sounds familiar. You built the dashboard, the training was delivered, and the stakeholder loved it. Yet six months later, no adoption and nothing's shifted.
That's not bad luck. That's the gap between delivery and adoption. And most data people were never taught how to close it.
Fi (03:20)
So why does great work go unseen? Well, it comes down to these three things. No channel to see it, no story for people to hear it, and no leaders to promote it. Take a moment, consider those.
Which ones are missing for you? Fix the ones you're missing and everything changes.
Sarah (03:44)
so now you know why let's talk about how.
Fi (03:49)
So who fixes this? It's you, the data fluencer, not your manager or your senior leader. Your manager is across a hundred things. They're managing up and they're managing down, trying to get across everything and make sure those plates are still turning. Meanwhile, your senior leader is in the boardroom, justifying data investment. They all want to celebrate your work. They want to promote it.
but only if you make it easy. And the datafluencer, they make it easy. They share the win, they tell the story, they make the work visible. And not because it's their job title, but because it's their behavior. Then they help the leaders to amplify.
Sarah (04:33)
So what does a datafluencer actually need? These five things. First, a piece of work with a result worth sharing. Now I'm sure you've already got that. Second, manage a sign-off, both on the initial channel setup and every story that goes out. Bring them along, get their buy-in, don't blindside them. Third, a channel to share it, public, discoverable, and set up properly.
This is the foundation of how you become seen, heard, and promoted. Fourth, a story framework with a variety of ways to share. Keep your audience engaged. And fifth, people to amplify. Leaders and stakeholders promote the success. You do the work, they carry the story further. Get these five things in place and nothing is standing in your way.
Fi (05:33)
So now you know how to make it visible, here are the tools to do it this week.
Sarah (05:39)
Datafluences follow an easy framework to share and engage with people. They measure impact, tell stories, post-collateral, build engaged channels, and support leaders to amplify work so they are seen, heard, and promoted. Today, we'll take you through the seven-part data story arc in detail with an example on how to build and grow a winning channel
and how to get support from leaders to amplify.
Fi (06:14)
Before we get into the framework, meet Freshmart a fictional wholesale food chain with a very real problem. Kirk owns operations at Freshmart where waste is consistently over target and he doesn't know why. The dashboard exists, the data is there, team are capable and yet nothing is shifting. He comes to me, Fi, the supply chain analyst and shares that he's getting some pressure from above.
He needs a way to reduce the waste closer to targets so he can meet their KPIs. To kick off the job, I reviewed our order model and the data quality and everything was okay. They had the data, so why wasn't anything changing? shifted to observation. How were the store managers using the data?
And that's when I discovered the problem. You'll learn more soon.
Sarah (07:05)
A key part of people understanding the value of data is hitting the mark with a story. Every data story arc has seven parts. Let's explore the framework, then we'll walk you through how we leverage this for fresh Mart
The hook, your biggest, most striking result. Its only job is to make someone stop and think. The problem, what was broken? What wasn't working? Set the tension because if there's no problem, there's no story. The insight, the turning point, the thing that reframed everything. This is your aha moment.
The solution, one change, one decision. Resist the urge to list everything. The simpler it sounds, the more impressive it is. The result, before and after. The proof, don't cushion the numbers, just let them land.
the learning, the transferable line, the thing that someone reads and sends to their own team.
The call to action, one clear door to walk through. Give people one thing to do next.
Fi (08:29)
Let me bring this to life with a fresh mart example. It's what we call a carousel, the image that you see on screen on the mobile. There are small images that we use to capture people's attention on your Slack channel and get them engaged. Our hook, 2.4 tonnes of fresh produce saved from waste, one quarter, one dashboard change, no new tooling, no model rebuild.
That's what stops the scroll and captures people's attention.
The problem? Well, the dashboard was accurate and waste was still climbing. All the data was there, sell-through rates, forecast variants, safety buffer levels, and yet we were still well above target at 6.3 % versus 5%. The insight? Everyone was right. Partially. The store managers were ordering responsibility.
My model was slightly over buffering, but nothing to be concerned about. What was discovered was that the store managers needed the same data, but in a different view. And they needed it upfront, not tucked away over multiple tabs. The gap was visibility and not performance.
So our solution, we reframed that first dashboard tab from how did we perform to what becomes waste if nothing changes. The first thing managers now see is projected surplus volume, dollar impact, and days to expiry of the food.
The result? Waste dropped from 6.3 % to 5.1 % in 6 weeks.
672,000 of annualised cost was avoided.
The learning for us was that the data was always there, but what changed was how we framed the decision and we made the store manager's actions easy. Finally, get your win. If your dashboards are accurate, but nothing is changing, reach out. This makes the reader feel like they could get results too.
They understand their part in the call to action. That's the seven part data story arc. And don't forget, this is all covered in detail in our free training course. Even this template that you can rebrand in your own company colors.
Sarah (11:13)
So you've got your story, now where does it live? This is it in practice, a public channel, a data wins carousel
built to the scroll. But the post is only part of it. The culture is what makes it compound.
Fi (11:31)
I know this because building strategy and data culture used to be my job. At JLL, I built a Teams channel that became the highest subscribed technology channel in the entire organisation second only to the All Hands channel and that one was compulsory. We had over 700 people in a team of 150 analysts that were subscribed. You do the maths.
We invited people in, but as we gained momentum, people joined through discovery. The best moments I found were when people stopped lurking and started talking. They got involved. They celebrated wins and elevated people. That doesn't happen by accident. It happens because you build a place that people actually want to be. You open the doors and you make it public.
You invite your team, the analysts, the leaders, and then the stakeholders. But it's not one and done. You have to keep nurturing the channel. Keep up with the invites as your stakeholder base grows. Say hi when people join and celebrate everyone's wins. The channel is your foundation, but the culture is what fills it.
Sarah (12:58)
Amplification. This is the part most people skip and it's where the real impact happens. You post but you don't stop there. You make it effortless for your manager to amplify. Caption written, message sent, one click. They comment, they tag and they take it higher. Then you prompt them to nudge the senior leader. A comment on a thread, a mention in all hands.
However they show up, it compounds. And don't forget the person who asked for the work in the first place. They had credibility with reinforcement because they lived the result.
Fi (13:43)
We started today with the truth. The best data work in this room will never be seen. Not because it isn't good enough, because nobody told the story. but now you will. You have a seven part data story arc that turns any result into something worth sharing, a channel that outlives the project, and an amplification stack that takes your story all the way to the top.
And from today, the right people will know your name. That's what seen, heard, promoted actually means.
Sarah (14:21)
We've touched on the key concepts today, but there's so much more to go deeper on. So we built a course, the Data Fluencer Toolkit, and it goes end to end on everything a Data Fluencer does. The seven part data story arc, the channel, the amplification stack, and everything in between. It's free with no catches, and it's easy to get through. So get your phones out and take a photo of this slide, or we'll also put the link in the comments down below.
Here you can register for the Data Fluencer Toolkit.
Fi (14:55)
Stop waiting to be noticed and start making it impossible to be ignored.
Sarah (15:02)
And that's a wrap on our TC26 session, Building a Data Culture with Data Fluences. Even if one thing landed for you today, go and do it. Pick a result, tell the story, and make it impossible to be ignored.
Fi (15:18)
without a doubt, make sure that you register for our training. All of the links are in our show notes, including the course, our LinkedIn and the podcast to subscribe to. And if you love this episode, please share it with someone on your data team. They need to hear this.
Sarah (15:37)
Until next time, thank you for joining us on Undubbed, where we're unscripted, uncensored, and undeniably data.
