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

Having more than 35  years in Business Process Management, Change Management, Data Governance, Data Protection,  Software Development, Business Intelligence, Risk Management, Quality Assurance, and Internal Audit, but also Project and People Management.
Passionate for Cross-functional, inter-disciplinary projects, addressing systems, technology, processes, people, and data across all functions of an organization, to run efficiently supporting the organization’s goals.
In the last 7 years, performed consulting engagement and fractional DPO roles for various companies – SMEs and large corporations, NGOs, and Public Administration, across various industries/sectors. "
Due to my preference for cross-functional projects, aside from my specific domain, I got trained/ certified(*) and have practical experience in implementing various international methodologies and frameworks in different domains - COSO, COBIT, ITIL, ISO 27001, NIST, CMMi, PMP, Prince 2, TQM, Lean, Six Sigma, SoX, BPM, GRC, ISO 9001, ISO 19011, ERM, ISO 31000, TAM/eTOM/SID…and few others.
*Note: no certification is maintained anymore, so please don't ask for credentials

You can contact me for discussions on mobile, email, or through LinkedIn messaging
Mobile: 0723 250 333
email:   daniel.suciu@gmail.com

For specific work inquiries, you can find me (and my colleagues) in the Data Protection City here:
 https://dataprotection.city/

Daniel SUCIU

Exemplul perfect care arată cum societatea românească face cu boltă pe principiile protecției datelor (AKA minimizarea datelor)
 
Subsemnat(a/ul) ..............................., domiciliat(ă) la adresa ................................... , localitatea …………………………., județul ……………………….., țara ……………………..,
născut(ă) în localitatea ………………., județul …………….., în data de ……………., 
identificat cu act de identitate (CI/BI/ Pasaport) seria ….…, numărul……………..., eliberat de către……………….., la data de………..,  valabil până la ……………………, CNP …………………………
vă rog să….
 
Data ....................                                     Nume, prenume ...............................
                                                              Semnătura ..........................................
 
Sunt cel puțin 3 forme diferite de identificare (4 când se face o copie a actului de identitate), fiecare fiind absolut suficiente (conform unor legi specifice în diverse domenii, nu doar a bunului simț), pentru identificarea unei persoane, unele conținând ele însele informații redundante/ irelevante.
(la care se mai cere uneori și o copie a actului de identitate... la fiecare interacțiune, evident).

Nu mai zic că nu rareori se cere completarea manuală a informațiilor, chiar dacă datele există în sistemul IT intern al organizației.

În cazul unei bănci a fost chiar și mai tare: s-a cerut numărul de abonat al clientului (pe baza căruia poate fi identificat orice client), plus validarea unui card al băncii, dar cererea tot trebuia să conțină acele informații.

Mai mult decât asta, la puțin timp mi s-a comunicat că trebuie să-mi actualizez datele personale (îmi schimbasem cartea de identitate). Evident că cele completate de către mine în cerere nu au fost preluate în sistemul intern.... că nu am cerut, deși operatorul le-a introdus minuțios într-o aplicație, că doar nu puteau rîmâne doar pe hârtie... iar actualizarea necesita (evident) prezența mea fizică.
 
BTW, nu e aplicabil doar la stat, poate chiar dimpotrivă, unele instituții chiar limitându-se la a cere mai puține informații, ci și la societăți comerciale, inclusiv (sau mai ales) mari firme multinaționale.

No, trăiască GDPR-ul și ”experții” care-i consiliază pe aceștia (pe bani buni de obicei) 😁 
BTW, nu dați în DPO, că pe el(ea) nu îl(o) întrebă nimeni dacă e corect 😇

Data Protection/ Management / Governance & AI dude | Engineer by background, Entrepreneur/Intrapreneur by choice | Proud dad of 2 daughters | Human Being by design and by default

Minimizarea datelor cu caracter personal în societatea românească

My strengths as a consultant... and why these matter>

Leaving modesty aside, I should also highlight my (perceived) strengths, so here they are, in a random order. BTW, some of them were also presented as weaknesses, but I see no contradiction - a weakness for some could be a strength for others.

I’m not a lawyer … nor just an engineer. Background is not all, learning and experiences matter more. It matters because I invested 1000+ hours to read laws, authorities' recommendations, court cases, and articles on the topics I was interested in;

Worked 30+ years to implement real processes (and tools) in different domains, being in operation long after I left the projects. It matters only if you want to implement changes in your operational processes;

I don’t rely on „relevant” certifications… just on experiences and continuous learning. I don’t pretend to be an expert, just a curious and passionate professional. It matters because I can say “I don’t know” and finding the right answer/ people who know;

Strongly disliking bullshit, so I’ll never use it. No moral compromises. Mutual trust is a pre-requisite, but is has to be gained. I’m sure you don’t need a reason why it matters;

100% independence, but not objective. My open opinions come from experience/ learning, not interests. It matters because I will actually be looking at your interest only;

I’ll always tell you what I believe you need to hear, not what you want to hear. It can be unpleasant sometimes, but also useful;
I hate Compliance… except when it’s the result of good Governance. It will take longer, but also last longer;

I don’t consider experience as a matter of years, but a matter of projects – accomplishments and failures. Past experience can find a good use in your specific case;

I’m a very curious guy and motivated to learn continuously. At least I’ll try to understand your problems and we can learn together;

I was lucky to build a network of professionals from many domains, backgrounds and cultures. When I don’t know something, I can always read, discuss and ask.

As for my weaknesses (which can be found in the first comment), the list is open 😁. Any feedback will be highly appreciated, especially constructive feedback. 

Thank you,
Daniel Suciu / unCommon Sense Advisory

My strengths as a Consultant /consultancy business

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