Predictive Data Analytics for Tracking and Optimising Performance

Anirudh Varshney, Founder & CEO, Trailytics talks about how to track and optimise performance of large and small enterprises

- DR ARCHANA VERMA

In today's data-driven world, why do you think transparency in analytics has become such a critical demand across industries; and how are businesses adapting to meet this expectation?

Transparency in analytics has become a cornerstone for businesses striving to build trust and foster informed decision-making. As organisations increasingly rely on data to drive strategies, the demand for clarity around how insights are derived has never been higher. Simply presenting results is no longer enough - stakeholders now want to understand the methodologies, data sources and algorithms behind the numbers.

This growing demand stems from several factors. First, transparency builds trust. Whether it's customers, employees, or investors, people are more likely to engage with businesses that are open about their data practices. Second, it ensures accountability. Transparent analytics allows businesses to identify and address biases or inaccuracies, leading to more ethical and reliable outcomes. Finally, regulatory compliance, particularly with data protection laws like DPDPA, has made transparency non-negotiable.

With increasing regulatory scrutiny, ensuring that analytics and RCA (Root Cause Analysis) processes are transparent and auditable has become essential. Key trends include Explainable AI (XAI) which provides clear explanations of how insights or RCAs are derived. Along with, Data Privacy Compliance that builds trust by aligning with GDPR, CCPA, or other local regulations.