Data Consultancy
Your data already has the answers. We help you find them.
Most organisations are sitting on more data than they realise but without the right approach to understanding it, it just sits there. We help you discover what your data contains, what it’s really telling you and how to use it to make better decisions.
What we deliver
From understanding what you have to predicting what comes next
Data Discovery and Audit
A clear picture of what you hold, where it lives and what it actually means
Data Interpretation
Understanding the patterns, stories and signals hidden in your existing data
Predictive Analytics
Models that help you anticipate what’s coming and act before problems arrive
Data Governance
The framework and processes that keep your data trustworthy and useful
The Challenge
Data is only valuable if you understand it
The organisations that make the best decisions aren’t the ones with the most data. They’re the ones who know what their data means and have built the right habits around using it.
We have data everywhere but no signal view of what we actually hold.
Siloed systems, inconsistent formats and years of organic growth mean most organisations genuinely don’t know what data they have. The first step is always discovery, not dashboards.
Our teams make decisions based on gut feel rather than evidence.
Not because they don’t want data because the data they have isn’t in the right shape, format or place to be useful at decision time. That’s an organisational and process problem as much as a technical one.
Our reports tell us what happened. We need to know what’s coming.
Descriptive reporting is useful but limited. Predictive analytics shifts the conversation from “what happened last quarter” and that’s where real value lives.
We don’t trust our data. Different teams have different numbers.
Data governance, the rules, processes and ownership structures that keep data consistent, is often the missing piece. Without it, dashboards and analytics tools just surface conflicting answers faster.
Our Approach
Understand first. Then analyse.
Data consultancy that skips the understanding phase, jumping straight to dashboards or analytics tools, usually creates expensive problems. You end up with sophisticated analysis of poorly understood data, which is often worse than no analysis at all.
We start by understanding your organisation: what decisions you actually need to make, what data you have that could inform those decisions and what’s currently getting in the way. That grounding shapes everything we do next.
From there we work through discovery, interpretation and, where its appropriate, predictive modelling. The goal at every stage is the same: give your people better information, so they make better decisions.
We combine out business analysis skills with data expertise, which means we understand the organisational context of your data, not just the technical structure. That makes the difference between analysis that sits in a report and analysis that actually changes what people do.
Data discovery and audit
Mapping what you hold, where it lives, how it flows, and what it means before anything else.
Interpretation and insight
Finding the patterns, anomalies and stories in your existing data that your teams haven’t yet seen.
Predictive analytics
Building models that help you anticipate demand, risk, or behaviour so you can act earlier and more confidently.
Evidence-based decision making
Embedding data into the way your organisation actually works, not just producing reports that sit unread.
Data governance
The frameworks, ownership, and processes that make your data trustworthy and keep it that way.
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The building blocks of a data-informed organisation
Each engagement is different, but these are the core capabilities we build and the outputs we deliver.
Discover
Data discovery and landscape mapping
Before you can use your data, you need to know what you have. We audit your data estate, systems, formats, ownership, quality, and produce a clear picture of your data landscape.
Data asset inventory and mapping
Data quality assessment
System and flow documentation
Gap and duplication analysis
Embed
Evidence-based decision frameworks
Analytics only adds value if it changes how decisions get made. We work with your teams to embed data into your planning and governance cycles making evidence the default, not the exception.
Decision framework design
KPI and metric definition
Dashboard and reporting design
Team training and adoption
Understand
Interpretation and insight generation
We analyse your existing data to surface pattern, trends, and anomalies that are currently invisible, translating raw data into plain-language insight your teams can act on.
Exploratory data analysis
Trend and pattern identification
Insight reporting and visualisation
Plain-language findings for non-technical stakeholders
Govern
Data governance framework
Without governance, even good data becomes unreliable. We build the ownership structures, data standards, and processes that keep your data consistent, trusted, and compliant.
Data ownership and stewardship
Data standards and definitions
Quality monitoring processes
Compliance and policy alignment
Predict
Predictive analytics and modelling
Where your data supports it, we build predictive models that help you anticipate what’s coming, demand, risk, churn, failure, so you can act before problems arrive rather than after.
Demand and capacity forecasting
Risk and anomaly detection
Behavioural pattern modelling
Model documentation and validation
New uses
Identifying new uses for existing data
Your data was probably collected for one purpose but it often contains value for several others. We help you identify adjacent use cases and opportunities you haven’t yet considered.
Use case identification workshops
Feasibility and value assessment
Cross-team data sharing opportunities
Data product concept development
How We Work
From confusion to clarity
01
Discover
Understand your organisation and the decisions you need to make
We start with your business needs, not your data. Who makes what decisions? What information do they currently use? Where does gut feel substitute for evidence and what would change if it didn’t?
Only once we understand the decision landscape do we turn to the data itself: what you hold, where it lives, how trustworthy it is, and what’s missing.
02
Interpret
Find what your data is already telling you
Before building anything new, we analyse what you already have. Exploratory analysis surfaces patterns, trends, and anomalies that have been sitting unseen in your systems, often revealing answers to questions your teams have been guessing at.
We present findings in plain language, not technical reports so the people who need to act on the insight can actually understand it.
03
Model
Build the predictive capability your decisions need
Where your data supports it, we develop predictive models tailored to your specific decisions, demand forecasting, risk scoring, behavioural modelling. We validate rigorously, document clearly and make sure you understand what the model is doing and why.
We don’t build black boxes. Every model we build comes with documentation your team can understand and governance your organisations can trust.
04
Embed
Make evidence- based decisions the default
Analytics that doesn’t change behaviour isn’t analytics, it’s reporting. We work with your teams to embed data into planning cycles, governance meetings and day-to-day decisions, so insight becomes habit rather than one-off exercise.
That includes training your people to interpret data confidently, governance to keep it reliable, and a clear owner for each data product we leave behind.
Example
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Illustrative example across the sectors we know best.
Central Government
A team making funding allocation decisions based on instinct, with no consistent evidence base.
Data discovery revealed three underused internal datasets. Combined and modelled they gave the team a demand forecasting tool that now informs every quarterly allocation, replacing subjective debate with shared evidence.
Predictive Analysis
Healthcare
Different departments reporting conflicting patient numbers from the same underlying system.
A data governance framework that defined ownership, standardised terminology and established a single source of truth ending the monthly argument about whose numbers were right.
Data Governance
Financial Services
Customer data collected for compliance that had never been used for anything else.
An analysis that identified three new use cases in the existing data including an early warning model for account risk that the compliance team hadn’t considered possible.
New Data Uses
Local Government
Service demand rising unpredictably, making workforce planning extremely difficult.
A demand forecasting model built on five years of service request data giving operational managers a 6-week forward view with enough accuracy to plan staffing with confidence.
Demand Forecasting
Ready to find out what your data is really telling you?
Tell us about your organisation and the decisions you’re trying to make better.
We’ll help you understand whether the data you need already exists and what to do with it