Strategy and Advisory
In our experience, data and AI programmes rarely fail because the technology was wrong. They fail because the strategy was drawn up separately from the team doing the delivery, because maturity was assumed rather than tested, and because nobody wanted to take a hard, honest look at the platform before spending more on it. That honest look — uncomfortable as it can be — is exactly where a strategy and advisory engagement earns its keep.
Before the next investment decision, it's worth asking harder questions. Do your teams trust the data they're working with? Is your architecture making AI possible, or quietly preventing it? Does the business understand what it's actually spending and what it's getting back?
We help organisations slow down long enough to answer those questions honestly, then move faster with purpose.
Data & AI Strategy and Roadmap
Strategy without execution is aspiration. Execution without strategy is expensive noise. A data and AI strategy needs to do more than articulate vision. It must connect to how work actually gets done, where budgets flow, and which capabilities need to exist before others can. We work with leadership and technical teams together, because the most common failure point sits in the gap between the room where the strategy was written and the teams expected to deliver it.
Most organisations have data initiatives. Fewer have a strategy that connects them.
Data & AI Maturity Map
Knowing you have gaps is not the same as knowing which gaps matter. A maturity assessment that produces a report without a prioritisation model is just a mirror, showing you what you have, not what to do next. Our Maturity Map benchmarks your current data and AI capabilities against where your business needs to be, not against an abstract industry average. The output is a structured view of where to invest, what to defer, and what's holding everything else back.
You can't close a gap you haven't measured.
Data & AI Platform Review
Technology investments have a way of accumulating quietly. A platform that made sense three years ago may now be carrying technical debt, redundant tools, or architectural decisions that made the migration harder than the original problem.A Platform Review gives you an independent, structured assessment of your current data and AI environment (people, process, technology), covering what's working, what's creating drag, and what is constraining what the business wants to do next. It's not an audit for its own sake. It's the clarity needed to make confident decisions about what to keep, what to consolidate, and what to replace.
The most expensive platform decision is the one made without reviewing what you already have.
Data & AI Commercial and ROI Advisory
Most data and AI business cases are built on aspiration. The costs are real and immediate; the benefits are projected and deferred. That asymmetry makes it hard to get investment approved, and harder still to demonstrate value once a programme is underway.
Commercial & ROI Advisory brings rigour to both ends of that equation. We help organisations model the true cost of their data investments, including the hidden operational overhead that rarely appears in initial proposals, and construct a value framework that connects data capability to business outcomes that leadership actually cares about. When the numbers are honest, the conversation with the business becomes significantly easier.
If you can't explain the return, the investment won't survive the next budget cycle.
Capabilities
Everything included in a Strategy & Advisory engagement
From an honest read on where you stand today through to the roadmap, governance and readiness work that gets a programme funded and moving.
Delivery Roadmap
Capability Gaps
Technology Selection
Operating & Cost Model
Adoption & Transformation
Data Governance Assessment
AI Readiness Assessment
Implementation Recommendations
The Benefits of a Strategy and Advisory Engagement
Direction before investment: A data and AI strategy that's grounded in your actual business objectives, not a vendor's reference architecture, prevents the most common and costly form of rework: building the wrong thing well. Organisations that establish strategic clarity first consistently spend less correcting course later.
An honest picture of where you stand: A maturity assessment works as a prioritisation tool, not a report card you file away. Understanding precisely where your data capabilities are strong, where they're creating risk, and where gaps are quietly blocking your AI ambitions gives leadership a defensible basis for deciding what to fund, what to defer, and what to stop.
Confidence in what you've already built: Platforms accumulate complexity. A structured platform review surfaces what's working, what's creating drag, and where architectural decisions made under different constraints are now limiting what's possible. That clarity is what makes modernisation decisions rational rather than reactive.
A business case that holds up to scrutiny: Data and AI investments are increasingly expected to demonstrate return, not eventually, but as a condition of continued funding. Commercial and ROI advisory builds the cost and value framework that connects data capability to outcomes the business actually measures, making it significantly easier to maintain investment through leadership changes, budget cycles, and competing priorities.
Shared language across the organisation: One of the most underrated outcomes of a strategy engagement is a leadership team that agrees on what good looks like, and can articulate it consistently. When engineering, data, and business teams are working from the same strategic framework, programmes move faster and with less friction.
A sequenced plan, not a wish list: Roadmaps that account for real constraints, team capacity, platform dependencies, funding cycles, regulatory requirements, get executed. Those built purely around ambition tend to get revised every quarter until momentum is lost entirely.
Why choose us for Strategy and Advisory
Partnering with Barfoot & Thompson to Enable a Data Strategy
Read about how we helped Barfoot & Thompson with their Data Strategy and Data Roadmap.
Implementing Generate's Greenfield Data and AI Platform
Discover how we helped Generate to strategise and implement a greenfield data and AI platform, deliver instant insights, and accelerate decisions with AI agents.
Working with One NZ to Enable Customer Insights
Explore how we unified data for a single view of Enterprise customer for One NZ, enabling customer insights and conversations.
Other Services
Data Foundation
Before we advise anyone on strategy, we look at what's actually holding their AI ambitions up: the state of the data, how reliable the pipelines are, whether the architecture can take the weight, and how much engineering rigour went into the decisions made so far. Strategy built on an honest read of these fundamentals holds up. Strategy built on assumptions about them doesn't.
Applied Intelligence
Applied Intelligence is where data infrastructure becomes organisational capability. It spans analytics and decision science, AI solution deployment, agentic workflow orchestration, and the AI architecture and governance frameworks that enable organisations to fundamentally transform how decisions get made.
Your questions answered
How do you assess AI readiness?
We look at four things together: data quality and accessibility, platform maturity, governance and security posture, and organisational capability. Most AI initiatives stall not because the model is wrong, but because one of these four was assumed rather than actually measured. That's typically where we start.
What does a data strategy roadmap actually include?
A clear view of where you are today, where the business needs to get to, and the sequenced set of platform, capability, and governance investments that get you there, each tied to a business outcome, not just a technology upgrade. It's built to survive contact with budget cycles and leadership changes, not sit in a slide deck.
Do you work with our existing team, or replace them?
We work alongside your team. Most engagements include upskilling and knowledge transfer so your people can own and extend what we build together, rather than being dependent on us indefinitely.
How long does a strategy engagement take?
It varies by scope, but a typical strategy and roadmap engagement runs 6 to 10 weeks. Larger, multi-stakeholder organisations sometimes take longer simply because alignment takes longer, the analysis itself moves quickly.
General Enquiries
If you are keen to have a chat with an expert or discuss a project, please fill out the form and we'll get in touch.
