Susan Walsh - The Classification Guru

Fixer of dirty data ★ Spend data classification, supplier normalisation, and taxonomies ★ DataIQ100 x 2 ★DataIQ Data Champion 2022★ Author "Between the Spreadsheets" ★ Creator of COAT ★ TEDx - say NO to NO ★ DataVenger

I’m Susan Walsh, also known as The Classification Guru, a globally recognised expert in spend data classification, cleaning, and transformation. For over a decade, I’ve helped organisations fix dirty, unreliable data and turn it into insight they can actually trust.

In 2017, I founded The Classification Guru Ltd, rebuilding my career from the ground up after coming back from bankruptcy after my first business failed. What started as a solo consultancy has grown into a specialist business supporting 100+ organisations globally, particularly in procurement, sales, and marketing, where clean data underpins reporting, automation, and AI.

I work with mid-sized and enterprise organisations, consultancies, and technology providers that rely on complex, high-volume data but struggle with inconsistency, duplication, and poor structure. My clients include procurement, finance, sales, and marketing teams who need data they can stand behind, whether that’s for spend analysis, supplier management, CRM reporting, forecasting, compliance, or AI initiatives.

Keeping a business alive and growing for almost nine years hasn’t been about shortcuts or hype. It’s been built through real-world delivery, practical problem-solving, and a refusal to accept “good enough” data as acceptable. Along the way, I’ve developed frameworks and tools to help organisations embed sustainable data quality, including the COAT framework (Consistent, Organised, Accurate, Trustworthy) and Samification, a self-service supplier normalisation platform launched in 2024 to make clean, structured data accessible at scale.

I’m also an active contributor to the wider data and business community. I’m a TEDx speaker, international conference speaker, and recognised thought leader in data quality and classification. I’ve authored three books, including Between the Spreadsheets 1st and 2nd editions, and the upcoming Optimizing Sales and Marketing. I teach globally via platforms such as Pluralsight, O’Reilly, and the Analytics Institute. Through consistent, practical thought leadership, I’ve grown an engaged LinkedIn audience of 43,000+ professionals.

Alongside my commercial work, I founded the Women Who Speak LinkedIn group, a free initiative connecting women speakers with event organisers to improve visibility and representation. I hope my journey shows that you don’t have to fit a mould to build a credible business, lead in your field, or create meaningful impact.

My mission is simple: help organisations move from spreadsheet chaos to clean, organised, trustworthy data that actually works.

Founder/MD (Mistress of Data)

I love improving the quality of procurement spend data, giving teams clarity so they can make better business decisions and cost savings.

Why not let me take the pain out of laborious data issues and make your life easier?

Whether it's a small or large data set, the accuracy can be improved by identifying classification errors, conflicts or gaps. I can provide a data verification service to efficiently find and correct these in a fraction of the time it would take you or a team member.

And a crucial part of having accurate data is also working with a comprehensive taxonomy, something that can be easily overlooked. I can provide a taxonomy development service to ensure you have all the vital areas covered for the greatest visibility - job done!

If you struggle with the time, resources or willingness to tackle your data, why not get in touch to see how I can make your life easier.

Who does quiet, easing back into work in January? Not me!

Just had a wonderful evening up in London meeting Adita Karkera, Ph.D. and lots of fabulous ladies from Women In Data™️

Gonna need a lie in tomorrow now 🤣🤣

Thanks Shubhangi Goyal for organising and Samir Sharma for being an honorary woman in data! 

The Classification Guru Ltd Samification

Susan Walsh

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Ok 2026, I may not be ready, but let’s do this!

When you work for yourself there’s very few h&s measures in place, like a warm workplace.

I woke up to -4 outside and not much different inside, even with the heating on, so whoever gets on call with me today will find me like this. #sorrynotsorry

The Classification Guru Ltd Samification

It's baaaack!  That's right, lipsyncsunday is back in 2026, and this is the energy I'm bringing into 2026 - bad vibes we tell them bye bye!

And not just that, after years of resisting, I've now set up a TikTok account @classificationguru so give it a follow if you want even more crazy, and of course some great data tips, eventually...

What energy are you bringing into 2026?  

Oh and good luck in your first week back, take it easy!

The Classification Guru Ltd Samification

I asked ChatGPT one question: "Based on our interactions, how could I be leveraging you more?"

Because I want to work smarter, not harder this year.

And the answer wasn't, “write more posts faster," it was slightly unexpected - AI works best before things are polished, not after.

Which basically means that even with AI, I'm still a control freak, not delegating until the last minute, so that's something I'll be working on this year.

Here’s the recommendations I'll be taking forward:

 • Using it as a thinking partner, not just a writing tool
 • Pressure-testing ideas before they’re fully formed
 • Acting as an editor with opinions, not just a spellchecker
 • Repurposing one solid idea into multiple formats
 • Being a built-in “so what?” detector
 • Exploring bolder positioning without committing to it publicly
 • Preparing for talks, panels, and conversations earlier, not at the last minute

The biggest shift for me? Bringing AI in when things are messy, not when they’re “ready”. Drafts, fragments, half-formed opinions… that’s where the real leverage is.

So tell me, where in your workflow could AI take more of the heavy lifting, so you stay in your zone of genius? 

Why not try this prompt or a variation and let me know!

The Classification Guru Ltd Samification

Have you met the Dirty Data Villains?

Every dataset has them.
Some are obvious. Some hide in plain sight.
Together, they’re responsible for broken reports, failed joins, messy dashboards, and far too many “why doesn’t this match?” moments.

Here’s the current Dirty Data Villains lineup 👇

🟡 Rogue Punctuation
Commas, apostrophes, periods, and symbols turning up where they don’t belong. Breaking imports, splitting values, and causing errors that are frustratingly hard to spot.

⬜ Sneaky Spaces
Invisible troublemakers lurking at the beginning or end of values. The reason your “exact matches” aren’t exact and your duplicates refuse to reveal themselves.

👯 Duplicate Dan
The master of cloning. Same customer, same supplier, same invoice… entered twice (or more), often with just enough variation to avoid detection.

🔤 Typo Tracey
One wrong letter is all she needs. Misspellings, swapped characters, missing letters — causing failed lookups, bounced emails, and embarrassing mistakes.

📅 Format Fred
The chaos king of inconsistency. Dates, phone numbers, and text fields all formatted differently across systems, making automation and reporting painful.

💥 Why they matter
These villains don’t just make data messy; they undermine trust. And without trust, data can’t be relied on for decisions, insights, or AI.

The good news?
Once you can name them, you can spot them.
And once you can spot them, you can clean them.

More villains may be lurking… but for now, this is your most wanted list.  And if you need some help identifying them, ask me about our new data diagnostic service, more details coming soon!

Which Dirty Data Villain causes you the most pain?  And who would you add?

📘 Two books
📉 Big discounts
📊 Cleaner, calmer, more trustworthy data

Get more Susan for less!

🟣 Between the Spreadsheets from Facet Publishing – 20% off using NEW20
🔴 Optimizing Sales & Marketing Data from Kogan Page Publishing – 40% off with SALE40

What you’ll actually learn:

💡How to spot dirty data before it wrecks reporting
💡Practical ways to fix duplicates, inconsistencies, and naming chaos
💡Why “the tech will fix it” usually doesn’t
💡How to build data you can trust for decisions, automation, and AI
💡Real-world lessons from projects, not fluffy theory

If you’re wrestling with messy data, unreliable dashboards, or a CRM that feels held together with hope and pivot tables, these will save you time, frustration, and a few awkward meetings.

Built on real client work. Powered by the COAT framework. Zero nonsense.

Grab them while the discounts are live!

Shoutout to some fellow authors Jordan Morrow Tiankai Feng Nicola Askham Caroline Carruthers Kristen Kehrer Roberto Maranca Albert Bellamy Keith McCabe (MCIPS) Samir Sharma Dr. Joe Perez

The Classification Guru Ltd Samification

Data Storytelling & stakeholder communication training | MindSpeaking | The Human Side of Data

Many Data professionals are brilliant.

Their analysis? Razor-sharp.
Their models? Sophisticated.
Their attention to detail? Exceptional.

But translating insights into a story that non-technical stakeholders understand…
 
That’s a different ball game.

In 2015, I presented insights to a group of Marketeers. 

I expected: 
Applause.
Approval.
Action.

But I was wrong. 
Nothing got implemented. 

That’s when I learned the hard truth: technical skills don't drive impact—communication does.

🔹 Stakeholders don’t care about dashboards. They care about decisions.
🔹 Insights mean nothing — until people see why they matter.
🔹 Numbers get forgotten. Stories get remembered.

That’s why I founded MindSpeaking in 2020.
Since then, we’ve helped 15,000+ Data professionals transform from data providers to trusted business partners.

🚀 𝗧𝗥𝗔𝗜𝗡𝗜𝗡𝗚 𝗙𝗢𝗥 𝗬𝗢𝗨𝗥 𝗧𝗘𝗔𝗠
Want your team to move from presenting numbers to influencing decisions?
Let's talk: 
MindSpeaking.com/companytraining



Free Resources: 

📙  𝗕𝗢𝗢𝗞
People Skills for Analytical Thinkers 
#1 bestseller — read a free preview:
▪️ MindSpeaking.com/book

🧠  𝗙𝗥𝗘𝗘 𝗘𝗠𝗔𝗜𝗟 𝗖𝗢𝗨𝗥𝗦𝗘
Want to turn Data into compelling stories? 
Join 4,100 Data pros and take my free email course (only 2 min/day): 
▪️ www.mindspeaking.com/datastorytelling 

📊  𝗙𝗥𝗘𝗘 𝗦𝗘𝗟𝗙-𝗧𝗘𝗦𝗧
How skilled are you at Data Storytelling?
Take the free self-assessment (5 min) and grow to the next level:
▪️ MindSpeaking.com/maturity-model

Gilbert Eijkelenboom

Data teams talk in ingredients.
Stakeholders want a meal.
Here’s how to bridge it 👇

1. Start with the plate (end result). Not the grocery cart (your method).
↳ Stakeholders don’t care what you used yet.
They care what’s for dinner.

↳ Practical:
Open with the outcome.
“So the takeaway is: fewer false fraud alerts for high-value customers.”

2. Translate metrics into decisions.
↳ Numbers don’t create action.
Decisions do.

↳ Practical:
After any metric, add one sentence:
“This means we should…”
If you can’t finish it, don’t show the metric yet.

3. Use one example to anchor the whole story.
↳ Abstract explanations stay abstract.
Examples stick.

↳ Practical:
Pick one concrete case and return to it.
“For example, this means customer X would no longer be flagged for fraud.”

Simple shift.
Massive clarity.

How do you prepare your data meals?

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Data Storytelling training | Bestselling author: People Skills for Analytical Thinkers | Founder of MindSpeaking | Building the Human Side of Data

Technical skills got you here.
Communication will take you further.

Look at the shift.
2018 rewarded technical skills.
SQL.
Python.
Statistics.

2022 rewarded speed.
Automation.
BI tools.
Faster delivery.

But 2026?
A different game.

AI is taking over the technical parts.
Tools are getting faster than us.

People can generate dashboards in seconds.
So what’s left for you to do?

Understand the business.
Influence stakeholders.
Guide decisions.
Tell a story people remember.

That’s the skill set the market rewards now.
Not more dashboards.
Not more models.

Communication is the new leverage.
And the analysts who grow will be the ones who lead the conversation.

What’s your take?
Is communication a crucial skill for data professionals?

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In 2018, being “good with data” was enough.
Build dashboards.
Answer questions.
Explain the analysis.

Today?
That’s the baseline.

In 2026, the Data Analyst who thrives isn’t the one who builds dashboards…

It’s the one who drives decisions.

Not “Here’s the dashboard you asked for.”
But “What decision should this support?”

That shift changes everything.

Here are practical steps to move into the 2026 version of your role:

1. Stop answering too quickly
↳ The first question is rarely the real question.
↳ Say: “What decisions are you trying to make?”

2. Frame insights instead of explaining charts
↳ Stakeholders want clarity, not detail.
↳ Use: “This means…” → “So we should…”

3. Challenge gently, but consistently
↳ Influence comes from curiosity, not conflict.
↳ Ask: “Before deciding if we should use AI, let’s talk about the business problem we’re trying to solve?”

4. Lead the conversation
↳ Don’t be a report generator. AI will do that.
↳ Become a trusted business partner.
Do you think the “decision-driven analyst” will become the new standard?

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Stop building dashboards. 

Start creating impact. 

Want to shift from order-taker to decision-shaper in 2026? 

Here’s are 5 tips:

1. Focus on the “Why” behind the data
↳ Dashboards are just tools. The real value is the insight.
↳ Ask, “What business question does this answer?” It’ll guide you to what matters most.

2. Translate data into stories
↳ Numbers alone don’t change minds. Stories do.
↳ Connect the dots. “Here’s what this data means for our strategy.” It makes the data stick.

3. Know your audience’s pain points
↳ Not everyone needs all the details. Tailor your insights.
↳ Ask, “What keeps them up at night?” Then answer with data.

4. Influence, don’t just inform.
↳ It’s not enough to report. Push for action.
↳ Say, “This trend suggests we need to pivot.” Be the guide, not the messenger.

5. Build trust through transparency.
↳ Stakeholders hate surprises. Share early, even rough drafts.
↳ Try, “Here’s a preview. Any thoughts?” Early feedback builds buy-in.

Shift your role. 

Instead of reporting data 

Drive decisions.

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A good manager improves your life. 

8 things good managers do differently:

(Picture credit: Daksh Sethi)

1) 🎯 They connect your work to something bigger.
It’s not just about tasks. You see the impact of what you do.

2) 🔥 They’ve got your back when it matters.
In tough meetings. During messy projects. When things go wrong—they’re there.

3) 🎓 They push you outside your comfort zone.
Only because they see what you’re capable of.

4) 💬 They give real feedback.
Not just “great job” or vague comments. Specific feedback that actually helps you grow.

5) 🌟 They recognize your strengths.
Sometimes, they see what you’re good at before you even realize it yourself.

6) 🌀 They stay calm under pressure.
Even when things are falling apart, they’re steady. And you learn to be steady too.

7) 💡 They make work a better place to be.
A joke here. A kind word there. Suddenly, Mondays aren’t so bad.

If you’ve had a manager like this, you know how rare they are.

Who is a good manager? 
Tag them below👇 

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Stakeholders keep asking for dashboards... but do they actually use them?
Don’t just serve more dashboards. Take these 3 steps instead.

For all new requests, use the 3 C’s:

1️⃣ Connection
Build trust first. Show you care about their needs.
↳ Acknowledge their request: "I see these insights are important to you."
↳ Set the tone: "Let’s dive deeper to discover how I can best help you."

2️⃣ Curiosity
Ask the right questions to uncover the real need.
↳ "What business problem are we solving?"
↳ "What does success look like?"
↳ "What decision are you trying to make?"

3️⃣ Clarity
Set clear expectations and push back when needed.
↳ Reframe their request to avoid endless rework:
↳ "Instead of tracking every KPI, let’s create a simple dashboard showing which channels drive the most revenue, so you can optimize your budget."

💡 Next time a stakeholder asks for a new dashboard...
Don’t just serve it right away. 
Start with the 3 C’s and deliver insights they’ll actually consume.

Can you relate? 
Have you ever seen dashboards go unused?

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#Data professionals, can you relate? 
You built the perfect dashboard. And no one cared. (3 tips below)

Your dashboard.

Covered in dust.
Buried under reports, spreadsheets, and unread emails.
Long forgotten.

It was once urgent.
A must-have dashboard.
Needed ASAP.

You built it.
Polished it.
Delivered it.

And then?

Nothing.
Just silence.

No logins.
No views.
No impact.

Sound familiar?

Too many dashboards meet this fate.
Not because the data was wrong.
Not because the insights weren’t valuable.
But because it was overwhelming. 

Too many numbers.
Too many filters.
Too much effort to find the actual insight.

Here’s the truth:

Stakeholders don’t want dashboards.
They want clarity.
They want faster, easier decisions.

So before you build:

🔹 Ask: “What decision will this help you make?”
🔹 Challenge: “What will you do differently with this data?”
🔹 Align: “How will this fit into your workflow?”

Because a dashboard that no one uses?

Might as well not exist. 💀

Ever built a dashboard that no one used? 

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You have a lot to share. But business isn't academia. 

What's relevant to the other person? How do you keep the attention? What influences their decision-making? 

Yes, the analysis is important.

We'll gain new knowledge through research and writing 7 pages.

But if we can't communicate with brevity and in a way that's relevant to our audience, people won't understand our insights.

I believe schools should spend more time on soft skills. 

Because without good communication 

Technical potential goes to waste. 

#data
#analytics 
#datascience

Most data presentations stop too early.
Don’t forget this step 👇

Business people don’t struggle with data.
They struggle with:
1️⃣ What does this mean?
2️⃣ What should we do next?

Think of it like an X-ray 🩻

If a doctor only says:
“Here you go.”
Nothing happens.

Even if they say:
“Here’s the issue.”
You’ll still ask: OK… what now?

The value isn’t the scan.
It’s what decision it leads to.

Same with data.
Insights without:
• meaning (so what?)
• risk (what if we ignore this?)
• next step (what do you recommend?)
→ don’t change decisions.

As data analysts, we often stop at the insight.
But impact starts when you stay responsible for the decision.

Show the X-ray.
Explain it.

And tell people what to do next.
That’s how data actually creates value.

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You spend weeks on a dashboard.
Interactive.
Beautiful.

You present it.
Silence.

Then the question:
“Can you export this to Excel?”
😐

That moment hurts.
But it’s also a signal.

Not that your dashboard is bad.
But that the need wasn’t clear.

Because stakeholders don’t want dashboards.
They want answers.

❌ How NOT to present a dashboard:

Here’s the data, the filters, and how to drill down.
✅ Use this 3-step process instead:

1. Start with the decision
↳ Ask: “What’s one decision you want to answer today?”

2. Turn it into a concrete question
↳ Example:
“Which customers should we focus on in the next campaign?”

3. Walk them through the answer
↳ Use the dashboard live.
Show how to get the answer.
Not what buttons and filters exist.

When people see the answer being formed,
they stop asking for Excel.

Because now the dashboard makes sense.

Will you try this next time?

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1 mistake analysts keep making
They present data the same way to everyone.

But not every stakeholder listens the same.
Not every stakeholder cares about the same things.

Some want speed.
Some want stories.
Some want proof.

If you don’t adapt?
They switch off.
Or push back.

That’s why I built a cheat sheet:
Data Storytelling for 4 Stakeholder Types
🔥 Red → fast, focused, results
🌞 Yellow → energy, stories, big picture
💚 Green → steady, people, support
🔵 Blue → facts, logic, detail

People are complex.
No one fits perfectly in one of these boxes.

But once you know someone’s main preference, you can speak their language.
And finally make your message stick.

Because I’ve learned:
Your insight is only as strong as your communication.
Do you adapt your message to your audience?

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My toughest stakeholder so far?
1.5 years old.

No clear requirements.
Changes scope constantly.
Emotional feedback only.

Sound familiar?

Last week I tried to get her dressed.
She didn’t want to.
I tried to force it.

The result?
Even more resistance.

Then, I gave her a hug.
Sat next to her.
Something changed.
She held her arm up.
Finally, I could put her coat on.

When your coworker is resisting your idea:
Don’t push harder.
Don’t give more details.
But stand next to them.

Ask: how do you look at the situation?
What’s important to you?

Do that, and the resistance might be gone.

Ps. Soon my daughter will be the one teaching me all the communication lessons (or actually, she already is)

Everyone’s obsessed with #data storytelling.
But that’s only the tip of the iceberg.

Yes, combining data + visuals + narrative matters.
But if you wait until the final slide to build trust…
Or to understand the request…
It’s already too late.

What really makes the difference is everything beneath the surface:
- Understanding stakeholder requests
- Alignment across stakeholders
- Influence and persuasion
- Business understanding
- Getting buy-in
- Building trust 
- Empathy

That’s where effective communication with data really begins.

Where do you see the biggest communication gap for data professionals?

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I'm an overthinker. And hey, in many situations it helps. I'm prepared. I think things through before I decide. But it also slows me down. Makes me doubt myself. Today, my friend Alex Østergaard published this book "Dissolving Overthinking". 

I had the pleasure of reading it while he wrote it. 

And I can say: Alex has written something genuinely rare. 

A clear, human, and surprisingly practical take on overthinking that goes far beyond theory. 

The stories stay with you. 

The exercises help you step out of your head and back into your life.

If you want a calmer mind and more inner freedom without losing your ambition, this book is outstanding.

Only today and tomorrow: 

The eBook is FREE on Amazon:
See link in comment.

I worry about the next generation.
This guy gave me hope.

Social media gave me a lot:
- Opportunities
- Connections
- Learning

But it also cost me a lot:
- Stress
- Distraction
- Always checking

So I got more intentional.

Deleting apps.
More time outside.

Less scrolling.
More real conversations.

Because let’s be honest.

📱 Apps are designed to keep us hooked.
🧠 Kids are burning out younger and younger.
💬 Many struggle with real conversation.
🌍 Disconnected from life around them.

This man does something simple:

⚽ He plays football in the park
⏰ For 3 hours
📅 365 days a year

Just to get kids outside.
Moving.
Talking.
Being human.

The solution might be simpler than we think.

Forecast: heavy rain.
Decision: sunglasses.

We’ve all seen this.
The analysis is clear.
And still…

The decision is made on gut feeling.
Then what happens?
❌ Projects drift
❌ Money leaks away
❌ Data teams stop speaking up

So how do you get leaders to actually trust the data?

1️⃣ Make the risk visible

Don’t start with:
“This is what the data says.”

Start with:
“What happens if we ignore this?”
Let them talk it through.

Then show the numbers that answer that question.
Now the data isn’t arguing.
It’s protecting the decision.

2️⃣ Translate numbers into consequences.

Stats don’t create urgency.
Outcomes do.

“90% chance of heavy rain” is abstract.
“This means the launch will get delayed again” is not.

Anchor the data to something real:
- Time
- Money
- Reputation
- Missed opportunities
- That’s when people lean in.

3️⃣ Make ignoring data feel unsafe

Remind them of patterns.
“Last time we ignored a signal like this, we lost X.”

Patterns are hard to dismiss. Especially when they’ve already hurt.

The best data storytellers don’t fight intuition. 
They guide it.
Curious.

Which number resonates most? 👇

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Most people fail because they don’t plan.
Data professionals fail because they don’t adapt.

They double-check every number.
Rehearse every line.
Plan every slide.

But then the meeting takes a turn.
And suddenly… the plan falls apart.

So next time, remember this:
If you fail to adapt, you’re planning to fail.

Because the best communicators?

They prepare… and then let go.
They read the room.
They connect.
They adjust.

💡 Try this:
Halfway through your next meeting, ask one of these:
“Do you recognize this number?”
“Does this answer your question?”
“Does this direction make sense to you?”
“Is this the level of detail you were hoping for?”

Small moments like these…
Turn data into dialogue.

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What’s the difference between a good Data Analyst…
and a great one?

They say the insight in one sentence.

One sentence. That hits right away.

But most insights aren’t like that.
They’re messy.
They’re buried.
They’re hiding behind 20 slides and 14 charts.

That’s the problem.

If you can’t summarize the insight in one sentence…
The analysis isn’t ready.
The audience isn’t ready.
And the decision definitely isn’t ready.

In 2026, this is the resolution Data Professionals need:

1. Write the insight in one sentence
↳ If it doesn’t fit, it’s not an insight yet.
↳ Try: “The key thing you need to know is…”

2. Remove everything that doesn’t support it
↳ Clarity grows when clutter disappears.
↳ Delete first. Add later if needed.

3. Make the decision obvious
↳ Insights matter only when they guide action.
↳ Use: “So the decision becomes…”

Because simple isn’t shallow.
Simple is powerful.

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In high school, you learn to solve math problems.
But you don’t learn how to solve conflicts with friends or coworkers.

You learn history.
But not how to collaborate.

You learn how to connect computers.
But not how to connect with people.

And then real life hits.
Messy projects.
Unclear expectations.
Stakeholders who don’t speak your language.
School teaches theory.
Work demands communication.

Here are practical tips to close that gap:

1. Translate complexity into simple language
↳ Real life rewards clarity, not jargon.
↳ Try: “Here’s what this means for you…”

2. Ask questions that uncover the real need
↳ The first question is rarely the real problem.
↳ Ask: “What decision will this help you make?”

3. Name the emotion in the room
↳ Most tension comes from unspoken worries.
↳ Use: “It sounds like timing is the concern, right?”

4. Frame your message for the audience
↳ School trains you to explain.
↳ Work expects you to influence.
↳ Start with their goal, not your data.

The future isn’t technical.
It’s human.

♻️ Liked it? Repost to your network.
👉 Follow Gilbert Eijkelenboom to join the top 1% of Data Professionals.

How do you bridge the gap between #Data and Business?

Many #Data professionals are eager problem solvers. Too eager, sometimes. They dive in without grasping the business problem.

The result? 

Little value. 

3 tips for impactful data work:

🔍 1) Ask good questions 
Try to understand the business goal. What are they trying to achieve?

🚫 2) Learn to push back and say no
Become a consultant, not just an executor. Saying no is hard. But in the long run, stakeholders appreciate that you only work on impactful projects.

🤑 3) Communicate value
Don't explain HOW you've built your dashboard or model. Instead, speak about WHY it's relevant to your audience. 


Thoughts?


#analytics
#datascience

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Gilbert Eijkelenboom

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taplio

The Battle

Susan Walsh - The Classification Guru

Gilbert Eijkelenboom

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Susan Walsh - The Classification Guru's LinkedIn Performance

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Performance ScoreSusan Walsh - The Classification Guru's LinkedIn Performance