Full Breakdown
Case studies,
Case studies,
in full detail
Tap any project below to see the full challenge, our approach, the tools we used, and the result we delivered.
Client names have been anonymised in accordance with our confidentiality agreements.
All case studies
- Challenge
- Inaccurate weekly sales forecasts causing widespread overstock and significant wastage.
- Solution
- Built an ML forecasting model using 3 years of historical sales data and external signals.
- Result
- 40% reduction in forecast error, £180K annual cost savings achieved.
Our approach
- Audited three years of POS and inventory data to find the real demand drivers.
- Built and validated an ML forecasting model incorporating seasonality, promotions and weather signals.
- Deployed automated weekly forecast refreshes integrated into the client's existing ordering workflow.
Tools & technologies
Python
scikit-learn
Pandas
Power BI
Azure SQL
- Challenge
- C-suite had no unified view of production KPIs across six European manufacturing plants.
- Solution
- Designed a live Power BI dashboard pulling from four ERP systems across all six sites.
- Result
- Board reporting time reduced from 3 days to under 2 hours per week.
Our approach
- Mapped KPI definitions across four disconnected ERP systems to find a common standard.
- Built standardised data pipelines feeding a single reporting warehouse.
- Designed a live Power BI dashboard with drill-down by plant, production line and shift.
Tools & technologies
Power BI
SQL Server
Azure Data Factory
DAX
- Challenge
- Dense statistical annual report was inaccessible and unengaging for lay stakeholders and donors.
- Solution
- Redesigned as an interactive web-based data story with custom D3.js charts and infographics.
- Result
- 3× increase in stakeholder engagement with annual impact data within 6 weeks of launch.
Our approach
- Reworked the report's narrative around outcomes donors actually care about.
- Designed custom D3.js visualisations for each key impact metric.
- Built a lightweight, accessible web experience that loads instantly on mobile.
Tools & technologies
D3.js
JavaScript
HTML/CSS
Figma
- Challenge
- No early warning system for at-risk subscription customers — churn was only detected after the fact.
- Solution
- Trained a logistic regression and gradient boosting churn prediction model in production.
- Result
- 25% reduction in monthly churn rate within 3 months of model deployment.
Our approach
- Engineered behavioural features from transaction and product usage history.
- Trained and compared logistic regression and gradient boosting models.
- Shipped the winning model into production with a weekly risk-scoring pipeline.
Tools & technologies
Python
XGBoost
scikit-learn
SHAP
SQL
- Challenge
- Legacy on-premise SQL Server could no longer handle growing data volumes and query times.
- Solution
- Migrated to Azure Synapse with automated dbt transformation pipelines and a data quality layer.
- Result
- Query times dropped from 45 minutes to under 90 seconds after migration.
Our approach
- Audited the legacy schema and identified the biggest transformation bottlenecks.
- Migrated the warehouse to Azure Synapse with automated dbt pipelines.
- Added a data quality layer to catch issues before they reached client reports.
Tools & technologies
Azure Synapse
dbt
SQL
Python
Apache Airflow
- Challenge
- HR team lacked data-driven insight into staff retention patterns and absence trends.
- Solution
- Built a GDPR-compliant workforce analytics dashboard in Power BI with role-level access.
- Result
- Identified £220K in preventable agency spend, directly informing a new HR retention policy.
Our approach
- Designed a role-based access model to keep sensitive HR data compliant.
- Built a Power BI dashboard tracking retention, absence and agency spend.
- Worked with HR leadership to translate the findings into a new retention policy.
Tools & technologies
Power BI
SQL
Microsoft Purview
Excel