{"id":191,"date":"2026-10-06T18:46:54","date_gmt":"2026-10-06T18:46:54","guid":{"rendered":"https:\/\/quantumtiger.in\/insights\/?p=191"},"modified":"2026-10-08T08:36:01","modified_gmt":"2026-10-08T08:36:01","slug":"quantum-tiger-board-advisor-co-authors-insight-on-data-visibility-trust-and-governance","status":"publish","type":"post","link":"https:\/\/quantumtiger.in\/insights\/quantum-tiger-board-advisor-co-authors-insight-on-data-visibility-trust-and-governance\/","title":{"rendered":"Quantum Tiger Board Advisor Co-Authors Insight on Data Visibility, Trust and Governance"},"content":{"rendered":"\n
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\n \"Suchit\n
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SUCHIT AHUJA<\/h3>\n

Suchit Ahuja is a higher-education academic, researcher, and innovation leader based in Montreal, Quebec. He serves as Co-Director of the Applied AI Institute at Concordia University<\/strong> and Associate Professor of Digital Innovation & Transformation<\/strong> at Queen\u2019s University. He is also the Co-Founder of Frugalis Nova<\/strong>, and is involved in advancing the adoption of AI, digital innovation, and emerging technologies in higher education.<\/p>\n <\/div>\n<\/div>\n\n\n\n

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\n \"Reihaneh\n
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REIHANEH P.<\/h3>\n

Reihaneh P. is a Product Manager specializing in digital platforms and telecom & media products<\/strong>. Based in Tehran, Iran, her expertise includes product strategy, requirements engineering, and digital product development<\/strong>, with a focus on translating business and user needs into effective technology-driven products.<\/p>\n <\/div>\n<\/div>\n\n\n\n

October 6, 2026 \u2014 Suchit Ahuja, Board Advisor at Quantum Tiger, has collaborated with Reihaneh P., a student researcher, on a new article titled \u201cShared Dashboards, Disputed Numbers: Why Visibility Is Not the Same as Trust.\u201d<\/p>\n\n\n\n


The collaborative article examines an increasingly important challenge facing organizations that rely on shared data for operational and strategic decision-making: having access to the same data does not always mean having the same level of trust in that data.<\/p>\n\n\n\n


Drawing on a telecom reporting scenario, the article explores how differences in measurement methodologies and data interpretation can lead to disputes between organizations, even when stakeholders have access to common dashboards and reporting systems.<\/p>\n\n\n\n


While improving technical measurement can help reduce discrepancies, the authors highlight that technical accuracy alone is not enough to establish trust. Organizations also need clearly defined governance frameworks that determine how data is measured, reconciled, investigated, and ultimately used for decision-making.<\/p>\n\n\n\n


A significant focus of the article is the importance of data governance and accountability. Establishing clear definitions, acceptable variance thresholds, reconciliation mechanisms, escalation procedures, and decision-making authority can help organizations move beyond simply sharing data toward creating confidence in the information they use.<\/p>\n\n\n\n


The authors also examine the growing role of Artificial Intelligence in data investigation and governance. AI-powered systems can assist organizations in identifying anomalies, connecting evidence across multiple data sources, and accelerating the investigation of discrepancies. At the same time, the article emphasizes the importance of maintaining clear human accountability for decisions involving financial, operational, and strategic consequences.<\/p>\n\n\n\n


The article reinforces a key principle:
Data visibility is a technical achievement; data trust is a governance challenge.<\/p>\n\n\n\n

Through this collaboration, Suchit Ahuja, Board Advisor at Quantum Tiger, and Reihaneh P. contribute to the broader conversation around data governance, trustworthy analytics, AI-assisted decision-making, and organizational accountability.<\/p>\n\n\n\n


The article highlights that the future of data-driven organizations will depend not only on making information increasingly accessible, but also on establishing the frameworks and accountability needed to determine what the data means, how disagreements should be resolved, and who has the authority to decide.

Read their original post at : https:\/\/lnkd.in\/p\/d5tQgqj2<\/a><\/p>\n\n\n\n


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