FAQs

You’re not buying a generic “data strategy deck”; you’re buying a practitioner who’s led data & analytics in demanding, regulated environments and still enjoys doing the technical work. I’m as comfortable in a boardroom discussing ROI and risk as I am in a notebook or SQL editor. I don’t bring a bench of juniors or a cookie-cutter framework; just pragmatic, Data & AI leadership focused on turning your data into better decisions that drive measurable impact.

A fractional data leader is a senior data & AI lead you “share” with other clients. Instead of hiring a full-time CDO or Head of Data, you get that level of experience a set number of days per month - to shape strategy, oversee delivery and coach your team - without the permanent headcount cost.

An interim leader steps in full-time or near full-time for a defined period. That might be to cover a gap between hires, stabilise a struggling function, or lead a specific transformation. The focus is on quickly understanding your context, delivering change, and leaving you in a better place than I found you.

Hiring a senior data leader is a big commitment: six-figure total cost once you include on-costs, a long notice period, and a lot of risk if you’re not yet clear on your data strategy or what “good” looks like.

Fractional or interim leadership lets you bring in that experience quickly, shape the strategy, prove the value of data & AI, and understand the kind of permanent role you actually need. If, after that, a full-time hire is the right move, I can help you define the role and support recruitment from a much stronger starting point.

Consultancies are great for large, multi-national programmes. They’re less suited to focused, pragmatic work where you need a senior practitioner embedded with your team. With Datavyse you get me: the person you meet is the person doing the work with minimal overheads, no junior “learning on the job”, and solutions tailored to your context, not a generic playbook.

I typically work with scale-ups and mid-market organisations: big enough to feel the pain of messy data, lean enough that every project needs a clear ROI. That includes fintech, SaaS, professional services and purpose-driven organisations, plus established firms that want to modernise how they use data.

Both. Generative AI and machine learning are powerful tools, but in many organisations the biggest wins still come from getting the fundamentals right: clear KPIs, trusted data models, and usable dashboards. I’ll recommend AI where it genuinely helps, not because it’s fashionable.

No. A common engagement is helping a business move from “spreadsheets everywhere” to a simple, robust data foundation and a first wave of high-value use cases. I can also help you decide what your first permanent data hire should look like and support recruitment.

Most clients start with a short discovery to identify their top 3–5 opportunities or solve a specific problem. From there, we either deliver a focused data/AI solution or agree a fractional/interim leadership arrangement for a defined period. I'm flexible with travel and enjoy collaborating in-person with clients, I am equally comfortable working remotely if that's how you prefer to operate.

Discovery and “solve a specific problem” pieces are usually fixed fee. Delivery and leadership work is priced based on scope, outcomes and the level of involvement you need: either as a project, a day-rate, or a simple monthly retainer. Whatever the model, I’m upfront about costs and we anchor the work on measurable value.

Yes. I work within your security and compliance requirements, and I’m happy to sign NDAs and DPAs. Where we use AI tools, we prioritise secure, enterprise-grade options (for example within your Microsoft 365 / Azure environment) and strictly avoid sending sensitive data to external services.