CTDI
CTDI Europe implemented Microsoft Fabric as its central analytics platform, automating price forecasting and unifying reporting across 26 locations in 12 countries.
A global leader in services for the telecoms sector
CTDI (Communications Test Design, Inc.) is a global provider of engineering, logistics and repair services for the telecommunications industry, founded in 1975. It serves the largest telecom operators and OEM manufacturers worldwide. It employs more than 20,000 people at more than 100 locations around the world, including 4,200 people in 26 branches in 12 European countries.
Project Description
After a decade of using a single BI platform, CTDI Europe decided to test the whole market. In an RFP process, the company compared its existing tool with the main alternatives, Tableau and Power BI. During that process, Microsoft released Microsoft Fabric, still in public preview. The integrated architecture combining data, analytics and AI in a single environment, together with unified security management, convinced CTDI to choose Fabric. ANEGIS was selected from five candidate implementation partners.
The project lasted six months, from February to August 2024. It focused on two key areas: unifying reporting across CTDI’s European structures and automating sales and price planning using machine learning. The scope included reviewing analytical methodologies, creating new visualisations and reports in cooperation with CTDI’s D&A team, and implementing advanced predictive analytics directly in Microsoft Fabric.
The price prediction project was deliberately chosen as the flagship: first, to showcase Fabric’s capabilities, and second, to teach the organisation the entire prediction process. Since its completion, CTDI has been running further ML projects, including one on optimising warehouse space utilisation
Challenge
- An outdated BI platform after a decade of use, requiring a review of analytical tools
- Scattered data sources and information silos between teams and locations
- Manual, time-consuming price forecasting and sales planning processes
- Weekly reports requiring manual work instead of automation
- Minimal use of machine learning and predictive analytics
- The need to unify security standards and data audits across the whole organisation
- No shared data culture between the European teams
Solution
- Implementation of Microsoft Fabric as a central analytics platform integrating data from various sources across CTDI’s European operations.
- Consolidation of reporting: new visualisations and dashboards created in close cooperation with CTDI’s Development & Analytics team.
- Automation of the full price forecasting cycle, from ETL through forecast generation to reporting, with weekly automated reports replacing manual processes.
- Implementation of three predictive models (statistical and ML-based) tailored to diverse sales data series.
- Launch of exploratory data analysis (EDA) directly in Microsoft Fabric, enabling more precise refinement of the predictive algorithms.
- Unification of security measures and simplification of data exchange processes with partners and customers, to the benefit of the Information Security department.
- A training programme for every new team joining Fabric, building a shared data culture based on uniform standards.
Benefit
- A unified analytics platform eliminates information silos and improves collaboration between teams across Europe.
- Automated price optimisation significantly reduced manual workload and improved forecasting accuracy.
- Decision-making and operational processes sped up thanks to access to integrated data in real time.
- Higher data security, with simpler audits and information sharing with partners and customers.
- Continuous improvement of forecasting models through automatic evaluation of results.
- A foundation for further ML projects, from price prediction to warehouse space optimisation.
- A change in data culture: standardised analytical processes eliminate duplication of work between departments.
project turnaround time
statistical and ML-based, integrated within a single Fabric environment
The solution addressed our key business intelligence and data analysis challenges by providing a unified platform that integrates diverse data sources across our global operations. The implementation of machine learning-based analytics has been particularly impactful. Automating price optimization has significantly reduced manual workload and improved forecasting accuracy.
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