Data Blueprint
Build a reliable data foundation that accelerates decisions, technology adoption, and measurable growth.
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Why it matters
Most organizations are flooded with data, but without structure and business alignment, it leads to confusion, not clarity.
Data Blueprint turns your disconnected data into a strategic asset that drives efficiency, compliance, and innovation.
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What you’ll gain
- Clarity on which data drives decisions and which creates noise
- Identification of your most valuable data assets
- Immediate cost-saving opportunities through better use of existing data
- Strong foundation for AI, BI, ERP or automation
- Clear roadmap with prioritized initiatives, quick wins, and long-term impact
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How it works
We map your data flows, assess quality and compliance, and identify what truly matters for your growth.
You receive a step-by-step, business-aligned roadmap – from fast wins to strategic investments.
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When to start
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When data exists but is not trusted or not actionable
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When you plan to implement AI, BI, automation or a new ERP/CRM system
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When you aim to reduce costs and increase efficiency through better data use
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When compliance with regulatory frameworks is a priority
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When you seek to strengthen your data culture and cross-functional collaboration
From Vision to Results
Scenarios we transformed into successful change
Clarity is the starting point.
Let your data work for you.
Schedule a consultation to discover how your data can become a driver of smart decisions and sustainable growth.
Improving Service Quality through Data
Sector: Professional Services (telecommunications)
Challenge:
The company aimed to improve customer experience and reduce complaints, but lacked a unified and reliable view of service quality. Customer feedback arrived through multiple channels (phone, email, online surveys), yet the data was fragmented, inconsistent, and rarely used in decision-making. There were no accurate indicators of response or resolution times, and complaints were not classified by service type.
Our approach:
🔹 We began by mapping all customer support data sources, both formal and informal. This revealed serious data gaps and duplication across channels.
🔹 We assessed the accuracy, completeness, and business relevance of the data and identified systemic issues contributing to inefficiencies and dissatisfaction.
🔹 In collaboration with internal teams, we defined new standardized KPIs to measure service quality,including response time, complaint frequency and type, and satisfaction levels by service segment.
🔹 Based on the client’s strategic goals, we provided recommendations to consolidate multi-channel data and proposed tools for automated classification and real-time visualization.
Outcome:
For the first time, the company had a consolidated view of service quality metrics, enabling faster problem identification and more informed decisions. Response times were significantly improved, and recurring causes of complaints were systematically addressed. Quarterly management reports were introduced, and the entire customer support function began operating with clearly defined performance standards. The project laid a solid foundation for the next phase - predictive analytics and personalized service recommendations.
Optimizing Procurement and Inventory Processes
Sector: Manufacturing (metal processing, automotive parts)
Challenge:
The company faced frequent production delays due to late raw material deliveries and misalignment between procurement and production planning. Although historical consumption data existed, it was neither systematically analyzed nor used for forecasting. Additionally, certain processing phases, such as heat and surface treatment, were not digitally tracked, making it difficult to monitor the end-to-end production flow.
Our approach:
🔹 We started by mapping all data flows related to procurement, inventory, and production, including internal databases, documentation, and supplier communications.
🔹 We analyzed historical consumption patterns, delivery timelines, downtime reports, and the frequency of urgent procurement. Several untapped data sources were identified, data that already existed in the system but was not integrated or analyzed.
🔹 A clear connection was established between inventory levels, production capacity, and delivery schedules, enabling modeling of optimal procurement timing by material type and demand seasonality.
🔹 Special attention was given to non-digitized parts of the process, resulting in a proposal for digital tracking of heat treatment status and its integration with the ERP system.
Outcome:
For the first time, the company gained a consolidated view of raw material consumption, delivery performance, and production plans. Procurement decisions are now data-driven, and urgent orders have been reduced significantly. Real-time tracking of key production stages has improved predictability and enabled more accurate resource planning. The project laid the groundwork for implementing AI models for demand forecasting and early risk detection in the supply chain.
Optimising Patient Experience and Regulatory Compliance
Sector: Healthcare (private hospital)
Challenge:
The hospital sought to shorten wait times, raise patient satisfaction, and strengthen compliance with medical protocols and GDPR. Data on appointments, lab results, diagnostics, and patient feedback was scattered across multiple systems—EHR, lab LIMS, scheduling software, even paper forms—with no single source of truth or clear performance indicators. The absence of standardised metrics made rapid decision-making and early risk detection difficult, exposing the organisation to operational and regulatory issues.
Our approach:
🔹 Mapped clinical and administrative data flows, covering each step of the patient journey, from booking to discharge, including lab results, imaging, and satisfaction surveys.
🔹 Assessed data quality and completeness, revealing critical gaps (e.g., inconsistent timestamps, duplicate EHR entries, manual data with no validation).
🔹 Standardised key KPIs: time-to-consult, lab turnaround, protocol deviations, readmission rate, patient NPS.
🔹 Linked data to hospital objectives, correlating data flows with strategic goals such as reduced length of stay, higher scanner utilisation, and fewer compliance incidents.
🔹 Consolidation & visualisation roadmap, produced a plan for an integrated real-time dashboard and privacy-by-design recommendations that meet GDPR and national medical-records regulations.
Outcome:
The hospital now has a consolidated view of the patient journey and core performance metrics, enabling swift action on scheduling and lab bottlenecks. Diagnostic wait times have fallen, while patients receive proactive updates on appointment status via digital channels. Clinical staff have clear tools to monitor protocol adherence and escalate deviations promptly, reducing regulatory risk and boosting patient trust. The project laid the groundwork for the next phase: predictive triage modelling and dynamic resource planning.