In a recent episode of the Analytics Insight Podcast, host Priya Diyalani sat down with Vishal Ranjan, Founder and CEO of Claight, to explore why so many organizations remain data-rich yet insight-poor despite massive investments in AI, analytics, and digital transformation. The conversation cut through the hype to reveal the critical differences between raw data, information, intelligence, and actionable insights—and why dashboards alone rarely drive business success.
The Data Paradox
“Organizations today generate more data than ever before,” Ranjan noted. “Dashboards, reports, KPIs, AI tools, and analytics platforms have become standard. Yet many business leaders still struggle to answer simple questions: Why did sales decline? Where are we losing revenue? What action should we take next?”
This paradox—being data-rich but insight-poor—is at the heart of Claight’s mission. Ranjan, whose background is in sales at a large FMCG company, experienced the problem firsthand. “I had access to huge volumes of market research, customer surveys, demand forecasts, and sales reports. The problem wasn’t lack of data. The challenge was understanding what to actually do with that information,” he explained.
Bridging the Gap Between Data and Action
Claight was founded to bridge the gap between data, intelligence, and decision-making. “Everyone could see that a market was expected to grow by 30 or 40 percent, but very few people could translate that into clear business actions,” Ranjan said. “We wanted to help businesses move beyond reports and actually use data to drive growth.”
He outlined a clear hierarchy: Data tells you what happened. Intelligence explains why it happened. Insights tell you what action to take next. “Unfortunately, many organizations stop at the dashboard. They invest heavily in analytics but never transform that information into practical business decisions. That’s why executives often rely on instinct instead of data when making important decisions.”
Real-World Example: From Raw Data to Actionable Insight
Ranjan illustrated the concept with a client case. “One of our clients had years of procurement and import-export data. That was raw data. Once we cleaned and organized it into trends, it became information. Next, we analyzed why certain countries had become major suppliers while others had become expensive due to policy changes. That became intelligence. Finally, we recommended alternative sourcing countries that could reduce procurement costs. That recommendation became an actionable insight because it directly influenced business decisions.”
The biggest value, he emphasized, isn’t in owning data—it’s in knowing what action that data should drive.
Why Data Silos Persist Despite Digital Transformation
When asked why data silos still exist after years of digital transformation, Ranjan pointed to organizational behavior rather than technology. “Sales teams have their own dashboards. Finance has its own systems. Procurement works independently. Operations manage completely different datasets. Each department is optimizing for its own goals, so while every team has accurate information, nobody has a complete business picture.”
He argued that digital transformation successfully digitized departments, but the next challenge is connecting those departments to create one unified source of truth. “That’s more of a cultural transformation than a technical one.”
Three Barriers to Turning Data into Business Value
Ranjan summarized the biggest barriers with three words: Trust, Context, and Speed.
- Trust: If leaders don’t trust the numbers, they won’t use them. One conflicting report is often enough to make executives rely on intuition.
- Context: A dashboard may show sales dropped by 10%, but it rarely explains why or what should happen next. Without context, numbers create more questions than answers.
- Speed: Markets move fast. If analysis takes six weeks, the business environment may have already changed. Data must be timely enough to support decisions before opportunities disappear.
Measuring Data Investments the Right Way
Many organizations measure the wrong metrics, Ranjan cautioned. “They count dashboard logins, platform usage, reports generated, data stored. None of those prove business success.” Instead, companies should ask: Are we making decisions faster? Are our forecasts becoming more accurate? Are we responding to market changes quicker than before? Are we improving revenue, profitability, or customer satisfaction?
“When data directly improves business outcomes, it stops being an IT expense. It becomes a strategic business asset,” he concluded.
For the full discussion, including more insights on how to build a data-driven culture, listeners can access the complete episode of the Analytics Insight Podcast.