Dr Archana Verma
Ashish Singh, Co-Founder and CBO, ScatterPie talks about changing spectrum of data analytics
Indian companies’ data maturity – What C-suites still get wrong about decision science
Many organisations still see data as a technology purchase rather than a business capability. The common misstep is assuming that analytics platforms alone will improve decision-making. In reality, data maturity depends on three fundamentals – clear ownership, quality of inputs and a culture that values evidence over hierarchy.
Failures occur when leadership treats data projects as one-off initiatives, disconnected from frontline processes. Fixing this requires embedding decision science into business rhythms where every strategic and operational review is backed by data, and leaders are measured on how effectively insights translate into outcomes.
Why AI is only as good as your data strategy – lessons from ScatterPie’s frontlines
AI programmes struggle when enterprises underestimate the importance of robust data foundations. We have seen that algorithms can scale only when data pipelines, governance and feedback loops are in place. Without this, AI quickly becomes an experimental showcase with no measurable ROI.
What works is linking AI initiatives to specific business priorities, supported by strong semantic data models and clear accountability. The lesson is simple – AI is not about deploying the newest technology, it is about building trust in data so that predictions, recommendations and automation drive measurable business impact.
Beyond dashboards – the rise of geospatial intelligence in enterprise decision-making
Dashboards are only the first step in analytics maturity. Increasingly, enterprises are turning to geospatial intelligence to uncover context that traditional reporting cannot provide. For example, mapping sales, operations, or supply chain data against external layers such as demographics, weather, or infrastructure surfaces insights that are otherwise invisible. Our work in this space, supported by our partnership with ESRI, has shown how spatial patterns directly influence strategy and execution. The next wave of enterprise intelligence will integrate geospatial analytics as a standard layer in decision-making, moving from “what happened” to “where and why it happened.”
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