Data & Machine Learning

We work with businesses who have data sitting in multiple disconnected systems with no single version of the truth. Leadership makes decisions based on gut feel or the previous month's spreadsheet, and the insights that could drive revenue or reduce costs are unreachable.

Acting as your fractional CTO, we bring all your data into one reliable structure, build clear management information on top, and then apply machine learning to surface the signals that matter. This solution moves data from a historic record of what happened into a forward-looking engine that highlights risks, see and forecast opportunities, and drives measurable bottom-line impact.

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This Service is a Fit if

 

You have data scattered across multiple systems (marketing, CRM, finance, operations, spreadsheets) and no single, trusted version of the truth.

 

Leadership is making decisions on gut feel or last month’s spreadsheet, and it takes days to answer basic questions about revenue, pipeline, or performance.

 

Different teams report different numbers for the same metric, and nobody is confident which one is correct.

 

You suspect there are hidden opportunities or risks in your existing clients and operations, but you can’t see them clearly enough to act.

Who we typically work with

Mid to large service businesses in Financial Services, Professional Services, and similar sectors where the business is drowning in data but starving for answers

Data Unification

We consolidate data from your marketing, sales, finance, operations, and supply chain into one reliable structure.

Management Information Framework

We help you not only define the KPIs that matter, but also what the source of truth is for that KPI and then build reporting your leadership team can trust.

Executive Dashboards

We deliver one version of the truth so leaders get clarity without chasing reports.

ML and Predictive Models

We apply machine learning to forecast demand, predict churn, and surface hidden opportunities.

Data Governance

We put the rules, ownership, and processes in place so data quality holds over time.

Ongoing Insight and Optimisation

We refine models and reporting as your business evolves and new data sources emerge.

 

What's Included

 

Shared Understanding

  • We run discovery sessions with your leadership team to understand what decisions you need data to support and where current reporting falls short.
  • We map every data source in your business and document what each system holds, how it connects, and where the gaps are.
  • We align your leadership and operations teams on the KPIs that will form the foundation of your management information framework.

 

Data and Tools Aligned

  • We consolidate data from your CRM, finance platform, operations systems, and external sources into one unified structure.
  • We clean, standardise, and validate your data so the reporting layer is built on a foundation your team can trust.
  • We build the integrations and pipelines that keep your data current without manual intervention from your team.
  • We document the data model so your team understands what they have and how to build on it going forward.
 

Insights and ML Models

  • We build the management information layer your leadership team needs: revenue by client, service line, channel, and period.
  • We develop ML models tailored to your business: churn prediction, demand forecasting, inventory optimisation, or next-best-action recommendations.
  • We translate model outputs into clear dashboards and alerts so the insight reaches the people who can act on it.
  • We validate every model against your historical data before deployment so the outputs are defensible, not experimental.
 

Instant Business Insights

  • We build executive dashboards that give leadership a live view of the numbers that matter, without anyone compiling a report.
  • We set up automated alerts that flag anomalies, risks, or opportunities as they emerge rather than after month-end.
  • We connect reporting to your existing tools so leaders see the information in the platforms they already use.
 

Check ins

  • We run weekly review sessions throughout the build to validate that the data structure and reporting genuinely support leadership decisions.
  • We refine what we report on and how we surface it so it meets the needs of your leadership team in practice, not just on paper.
  • After delivery, we stay engaged to refine models, add new data sources, and ensure the insight layer keeps pace with your business.

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How the Process Works

1

Discover

We map every data source in your business, assess quality and completeness, and align on the decisions your leadership team needs data to support.

2

Design

We design the unified data structure, management information framework, and ML model roadmap, then validate the approach with your team before any build begins.

3

Deliver

We build the data pipelines, dashboards, and models, validate outputs against your historical data, and hand over a reporting layer your leadership team can use from day one.

Frequently Asked Questions

Common questions we are asked.

How much data do we need before machine learning makes sense?

Most firms we work with already have more than enough data – it’s just scattered and under‑used. What matters is consistent history across a few key systems (CRM, finance, marketing, operations), not “big data” in the buzzword sense.

Do we have to move everything into a data warehouse?

No. We start by connecting the systems that actually drive decisions, then design a lean warehouse layer around those, not a giant IT project. The goal is a single version of the truth for leadership, not to replicate every field and report you already have.

What if our data is messy or incomplete?

That’s normal – if your data was perfect, you probably wouldn’t need us. Part of the engagement is cleaning and restructuring data, fixing KPIs, and agreeing the minimum rules so reporting and models are reliable going forward.

How do you measure ROI on data and ML work?

We anchor ROI to a small set of tangible levers: recovered or reallocated spend, improved conversion, higher retention, and time saved on reporting. For example, if a firm is spending six figures on marketing, redirecting even 15–20% of that budget from low‑value to high‑value channels can more than cover the cost of the project.

Is this just another dashboard project?

No. Dashboards are an output, not the offer. We fix the underlying data model and KPIs, connect the right systems, and embed the reporting into your operating rhythm so leaders can actually make and track better decisions.

Turn your data into revenue.

We will unify your data, build the reporting your leadership needs, and deploy machine learning where it moves the needle, typically within ten to sixteen weeks.

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