A straightforward process
Working with a data consultant shouldn't feel open-ended or overly technical. I keep the process simple: understand the problem, agree the scope, deliver something useful, and make sure you can use it.
Intro conversation
We start with a short conversation — by email, phone, or video call — to understand:
- What you're trying to achieve
- What data you currently have and how and where is it stored
- What is (or is not) working for you with the existing process
- Any deadlines or constraints
There's no obligation at this stage. The aim is simply to establish whether I can help and what kind of project would make sense.
Scoped proposal
If we're a good fit, I'll send a clear proposal covering:
- Deliverables — exactly what you'll receive
- Timeline — realistic start and completion dates
- Cost — a fixed price for the agreed scope
- What I need from you — data access, context, and any key contacts
You'll have a chance to ask questions and adjust the scope before anything is confirmed. Work only begins once you're happy to proceed and you have been provided with, and agreed to, the Data Services Agreement contract.
Delivery
During the project, I:
- Work through the agreed deliverables
- Keep you updated on progress
- Flag any issues early — for example, data quality problems that affect timeline or scope
- Stay focused on practical outcomes, not unnecessary complexity
Projects are generally short to medium term, with check-ins as needed rather than constant meetings.
Handover
At the end of the project, you receive:
- The agreed outputs as per the scope
- A practical handover so you understand how to use and maintain what's been delivered
- Optional guidance on next steps if you want to build on the work later
The goal is for you to be self-sufficient — not dependent on me for every small change.
Tools I work with
Depending on your needs and existing setup, I may use:
- Microsoft Excel
- Google Sheets
- SQL
- Power BI
- AI Tools (Claude, ChatGPT, Copilot)
The right tool is the one that fits your business — not the most impressive one on paper.
Your data, handled responsibly
Client work often involves sensitive commercial information. As standard, I:
- Store client data securely
- Use password-protected systems and two-factor authentication where possible
- Apply data minimisation – reducing the dataset to only what is needed for the project
- Anonymise, aggregate or modify data used with AI-assisted analytical tools to prevent identification of individuals
- Retain data only for as long as necessary to provide the services
- Work under confidentiality agreements where appropriate
- Comply with UK GDPR and applicable data protection legislation
If you have specific security or confidentiality requirements, we can discuss these during the intro conversation.
Let's talk through your situation
Whether you have a clear project in mind or just know something isn't working with your data.
Get in touch