Elevating outcomes through data accuracy

Elevating business outcomes through data accuracy

Industry-leading companies treat data as a strategic asset, with data accuracy—how closely data reflects reality—at the core of this advantage. Poor data quality has become a silent liability; Deloitte estimates that majority costs are hidden, impacting 80% of companies, risking credibility, efficiency, and market positioning.

Deloitte’s findings indicate that costs of inaccurate data are not entirely quantifiable or visible

Hidden costs make up a majority share — weakening foundations and leading to severe instability at the core of the business

‍

‍

Complexities of emissions calculation

Accurate GHG disclosures are essential for effective climate action. Misreporting can distort Impact, Risk, and Opportunity (IRO), weakening decisions, accountability, and trust. Achieving accuracy in emissions data is inherently challenging due to:

1. Availability of relevant emission factors: Emission factors (EFs) — essential for converting operational data into CO₂ equivalents — are often incomplete or unavailable in the MENAP region. Sourcing EFs from international databases often makes the process both time-consuming and financially burdensome. BCG (2021) estimates that 55% of respondents reported that relevant emission factors are “hard” or “very hard” to find.
2. Value chain emissions: The GHG Protocol highlights upstream and downstream supply chain-specific challenges that limit enterprise control over data accuracy. These include limited access to data sources, reliance on partners, heavy use of assumptions and models, and greater dependence on secondary data such as national or industry averages.
3. Lack of automation: Manual data collection for GHG emissions often leads to errors and inconsistencies, reducing data accuracy due to human error, inconsistent methodologies, and lack of real-time validation. BCG (2021) presents that 49% of enterprises use manual methods for collection of granular data.

‍

Closing the emissions accuracy gap with AhyaOS

Artificial intelligence presents a powerful solution to the longstanding challenges in emissions calculation through seamless collection, easy detection of inconsistencies, and streamlined storage.

A 2024 BCG survey (N=1864) found that using AI in sustainability boosts efficiency and financial performance

Average amount of efficiency impact from using AI in sustainability processes (hours/week)

‍

Share of companies that experienced significant financial benefits (%)

AhyaOS, Ahya’s carbon management and accounting platform (CMAP), assists enterprises in achieving data accuracy to the highest degree possible, with features supporting extensive and comprehensive measurement and analysis capabilities:

1. Automation of EF selection: Access 160k+ emission factors from 34+ global databases, standardized for consistency and accuracy. Powered by AhyaAI EF Search, an LLM-based semantic engine with 90%+ mapping accuracy, the system links the right factor to the right activity, cutting manual work and making emissions reporting reliable across industries and geographies.
2. Collect: With AhyaOS Collect, enterprises can seamlessly engage supply chain stakeholders and portfolio companies to gather verified Scope 3 emissions data. Requests can be sent, tracked, and fulfilled directly within the platform, ensuring accurate reporting aligned with GHG Protocol and IPCC guidelines.
3. Integration hub: With AhyaOS Integration Hub, enterprises can automate emissions data collection by connecting directly to existing software and cloud services like AWS. This eliminates manual data entry, improves accuracy, and ensures all data flows seamlessly into the CO2e activity ledger for streamlined emissions management.
4. AhyaAI data capture: With Ahya AI – Data Capture, enterprises can automate data extraction from utility bills, invoices, PDFs, images, and even handwritten notes with 95%+ accuracy. This enables faster, scalable onboarding of emissions data by eliminating manual transcription and streamlining data collection at the source.
5. Activity ledger: With AhyaOS – CO2e Activity Ledger, enterprises get a structured, auditable record of emissions at the activity level, fully aligned with GHG Protocol. It links each CO2e value to its source activity, enables faster external verification, and reduces manual workload by 95%, ensuring compliance and seamless third-party audit readiness.
6. Data anomaly detection: With AhyaOS Anomaly Detection, AI continuously learns from past patterns to flag data errors and emissions deviations in real time. This reduces false positives and ensures cleaner, more reliable emissions reporting.