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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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

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

Entrust

To compile, report and deliver key information and trends from large and varied sets of data. The role will report to the Policy and Regulations Manager, becoming an essential resource for decision making, providing an evidence base for all proposals, reports and developments.

Data Officer

Capita

The role sits within the Performance Management and Forecast Team which is part of a wider multi-disciplinary Support Services team that covers Performance Management, Capacity and Forecasting, MI and Analysis, Scheduling & Contractor Management.

•	Creating a Database for Departments to view Employee Data and Linking it to SharePoint for easily viewing by the Management. Adding Pro-active Queries to identify Employee Attrition, Churn, and Turnover.

•	Created Macros that from one Sheet sends 200 Emails on a loop to Staff with up to 50 Task Reference Codes. Then depending on length of time outstanding Auto copies in the Manager or the Regional Manager to escalate tasks.

•	A Macro to validate Quarterly and Monthly Bonus payments to Staff for the Finance Team. To ensure accurate and timely payments.

•	Producing Power BI Report for a Rolling 7 Days and uploading them onto Microsoft Teams for the management to view performance. To see if they have achieved daily targets and view trends.

•	Data Mining from CRM Dynamics 365. Looking at the end-to-end process. Producing Innovative reports based on key audience objectives.

•	Training colleagues on complex reports. By documenting the process and recording on Video then uploaded onto MS Teams. Shadowing, providing assistance and support where necessary.

Business Data Analyst

Utility Team

Reporting directly to Director Level. Looking at current Processes for Consumption Data. Developing VBA Macros to highlight Spike, Overlaps in Consumption Data for our Clients.
Looking for Sale Opportunities in Company Data. 
Created VBA Macro to forecast & view Contract Performance Revenue for Accounts Dept & Directors. Important for Covid-19 impact on Supplier Claw Backs
Read and analyse HH data and has worked extensively with data aggregators. 
The role will be to overcome dataflow queries and issues particularly related to change of supply. 
The Data Analyst will be responsible for all operational dataflow processes and will be working closely with Data Collector/Aggregators and MOP providers.   

•	All dataflow management
•	Created VBA Macro to Monitor Contract Performance in Covid 19 times. 
•	Change of supplier issues and resolution
•	Working with HH data, MOP’s DC/DA’s
•	Auditing and review of operational processes
•	Quality management of processes
•	Generating adhoc reports for clients
•	Working with clients to help them understand their usage to look for reduction measures

Data Analyst

Providor

General Duties/Key Responsibilities: 

•	Produce Daily SAIF file to Process Dataflows for Smart Meter Exchanges for BMSL  Providor MOP 
•	Develop VBA Model to Process Dataflows from Jobwatch Application to AMOP
•	Process D0135 Dataflows Informing the DNO of Meter Faults to protect Customer Safety
•	Process Daily MOP Workflows D0001, D0005, D0134, D0142, D0194 
•	Report back to Providor Operation of Resolved DNO Call Outs on D0126 Flows
•	Investigating and Resolving data exceptions falling out of the interface between work 
•       management   systems and data flow management capabilities
•       Production of MAM/MOA billing files
•	Bill Validation were required
•	Ad hoc report production, manipulating data in Excel formats
•	Investigate And Resolve ECOES Rejections of D312 Flows
•	Produce MI Reports for my area of the Business
•	Analyse industry data and interpret unusual patterns and possible causes
•       GDPR Certified
•       Build and Maintain the Portfolio Database
•       Data Visualisation Skils with Power BI and Tableau

Industry Data Analyst

E.ON

•	Create Customers New Accounts from Developer Information in Eon’s  ICE Application.
•	Investigate and Problem solve any Migration issues such as Industry Dataflows both Power and Gas. 
•	Solve ICE Application issues in a timely manner.
•	Support Team Training for Department Migration from Leicester to Coventry Office 2017 to 2018
•	Manage MI Reports from the Team to Management at Leicester. Breakdown Reports for each Category so continuous improves to service can be made. 
•	Monitor Team Performance by Key Performance Indicators.
•	Improve MI Reporting with VBA to reduce reporting time
•	Manage Team Move within Coventry with internal stakeholders

Developer New Connections Analyst

•	Maintain industry SLA of 99% with Actual Meter reads
•	Investigate and raise D1 Data flows to the MOP (Meter Operator) to resolve meter communication line failures; keeping  supplier and customer informed, as required, to ensure timely fault resolution
•	Investigate validation failures to identity and resolve root cause. This includes errors Alarms, Overlap, Gap etc.
•	Export valid Meter Reads from Mv90 to MDR and Trigger Dataflows to the Supplier, HHDA and Distributor in a timely fashion. 
•	Use EON Applications including HHDC Query to check if Meter Read is within the Date Window.
•	Combine files in Mv90 to remove invalid status on meter reads
•	Re-Pole Meters by the Remote interrogation Tool to see if we can obtain meter reads without the Spike Errors
•	If there has been a Meter Exchange and we do not support the new meter type like ‘IP’ to email the supplier to De- appoint ourselves as the Data Collector.
•	Respond to D170 Dataflow requests to provide 14 Months (426 Days) of Data to the New DC by sending a D0036 flows.
•	Investigate the DC errors on all Gateways  PGEN, EMEB, OXPO and CNRG. These include P272 errors.

HHDC (Half Hourly Data Collector) Analyst 

First Utility

•	I work closely with internal departments to assist with any system errors and look for permeant fixes
•	Working through a variety of problem accounts to identify and then apply a fix which provides a satisfactory resolution for the customer
•	Identify and analysis trends that occur to aid in fixing the issue within a fixed SLA
•	Manage my own caseload of work through to resolution, ensuring they are completed within agreed timescales 
•	Make recommendations on improving processes and procedures to increase the productivity
•	Resolution of technical data errors to ensure customers are billed accurately and timely
•	Management and resolution of customer queries and complaints generated throughout the joining process

Technical Team Advisor

npower

•	Pricing Customers with New Acquisition and Renewal Products  
•	Producing Both Small Medium Enterprise (SME) Power and Gas Costs on a Daily Basis
•	Updating Price Models each day with Latest Costs.
•	Maintaining and Supporting with Visual Basic (VBA) code the Price Models for our Internal Sales Channels
•	Providing SPM data to the Internal Sales Channels
•	Billing Power Configuration at Admin Level, Entering Monthly and Quarterly Cycle Dates, Peel Off Dates for Group Billing, Updating Both VAT and Climate Change Levy (CCL).
•	Market Domain Data (MDD) Support, Updating Top-lines each Month with Meters which are valid and supported in our SME systems.
•	CMA Collation and Reporting

SME Price Analyst

•	Working in the Beryl Project Team to help Build and Test the New Billing System
•	Adding New Data for Setting up of the New SME Billing system.
•	Liaise with the rest of Business to support their Billing requirements.
•	Add Price Products and Billing Cycles

Beryl Billing Configurator

•	Bill Checking for Errors and then intercepted before been sent to the customer.
•	Making Sure the Correct Independent Energy Tariff had been applied to the customer’s Account.
•	Making sure the correct consumption had been applied. Fixing any Deductive Metering errors. Also Checking the Customers Max Demand, Reactive Power and Capacity Charges were correct.

Tariff and Bill Check Analyst

Data Analyst at Capita

I am a Data Analyst with Software experience, I have Worked for three Energy Suppliers, An HH Data Collector and a SME/Domestic Smart MOP.  Working in Customer Service, SME Billing, SME Pricing,  Data Flows for MOP for Smart Meters and now Energy Consultants.  I am always looking at ways of improving internal systems, for advanced efficiency and remove human error by Automating processes by VBA Macros & Python code. I have programming experience using Python 3 ( Including Jupiter Notebook, Numpy, Pandas, Matplotlib, Pyautogui. ) and MySQL and MSSQL. I have Data Visualisation Skills with Power BI and Tableau. I can create Company Databases and Automate them. MS Power BI experience in Visualising Data .  Salesforce Lighting Admin User in last current role.

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