Introduction

We partnered with a leading Engineering and Environmental Group in New Zealand for a prolonged digital transformation initiative. The core objective was to replace fragmented, paper-based processes and legacy systems with a single, Cloud-native (AWS) application Platform.

The platform was designed to seamlessly connect the Group’s three main operational pillars: Field Data Collection (Geological & Environmental), Centralized Data Storage and Laboratory Sample Management.

Team size

7 members

Industry

Environmental

Technology

React Native, ReactJS, Python, .NET, AWS (Lambda, DynamoDB, PostgreSQL/Aurora), GIS

Highlights

 Value Delivered

  • Speed and Accuracy: Achieved 30–40% time savings in data processing and eliminated almost all errors caused by manual workflows.
  • Data Integrity: Ensured consistent, accurate data from the field to the lab through a unified architecture and integrated QA/QC.
  • Unified Ecosystem: Replaced fragmented systems with a modern, scalable Cloud-native platform, connecting every step of the Group’s value chain.

Challenges

  • Low Efficiency and High Error Rates: Paper-based data capture and manual re-entry wasted 10–40% of project time and were primary sources of error.
  • Inconsistency and Fragmentation: Disjointed tools and inconsistent processes across different teams (Geology, Ecology, Contaminated Land) led to data redundancy and poor integration.
  • Lab Bottlenecks: Paper-based management of geotechnical soil testing caused significant delays in results, impacting project timelines.

Solutions

Phase 1: Field Data Collection

Core Function
  • Geological Digitization: Replace bulky paper logs and legacy tools.
  • Environmental Expansion: Support Ecology, Contaminated Land teams.
Solution Detail
  • React Native Mobile App (tablet) with full offline capability; integrated specialized Rock Mass Logging features.
  • Expanded the mobile app to include all survey forms for various environmental sub-fields.
Value Outcome
  • 30–40% faster data processing; reduced equipment needed, increased consistency of geological data.
  • Resolved process inconsistency, creating a unified data collection tool.

Phase 2: Centralized Data Storage

Core Function
  • Data Centralization: Consolidate scattered data from field teams.
  • Quality Control (QA/QC): Ensure reliable field data.
Solution Detail
  • Built a Central Data Hub using PostgreSQL on AWS Aurora for unified storage of all field data.
  • Integrated QA/QC processes directly into the mobile application logic, preventing errors at the source.
Value Outcome
  • Enabled easy, centralized data access and faster decision-making across teams.
  • Minimized data errors and manual checking, ensuring reliable data for analysis.

Phase 3: Laboratory Sample Management

Core Function
  • Modernize Sample Management: Eliminate paper forms and manual lab data entry.
  • Accelerate Results: Reduce client waiting time for critical data.
Solution Detail
  • Developed an online Sample Management Web Portal, digitizing the full process from sample receipt to results.
  • Optimized and automated the sample processing workflow.
Value Outcome
  • Improved reliability of laboratory data and faster sample processing, enhancing client satisfaction.
  • Eliminated bottlenecks, allowing the lab to deliver important results much quicker.