Leveraging the Power of Product Data Signals

In a world with billions of connected devices, products generate a constant stream of data. Most products we build, deploy, and support are more intelligent and, in some cases, capable of measuring and sharing their own performance. We are in a great position to assess their impact on business outcomes.

For many organizations, however, this is little more than background noise—telemetry data used by backend support teams to react to failures. But what if it’s not noise? What if it’s a conversation, rich with insights about performance, customer behavior, and untapped opportunities?

Leading enterprise players like Cisco, HPE, and Pure Storage have already started listening. They are transforming device-based telemetry from a reactive service function into a front-line strategic weapon. This shift allows them to differentiate their brand, deepen customer loyalty, and unlock powerful new revenue streams.

The key is moving beyond simple AI readiness, having the tools and data, to genuine business outcome readiness. It’s about creating living, learning ecosystems that continuously sense, interpret, and act, turning raw data into measurable impact on your customer's business. This transformation is a new frontier of enterprise value, and it unfolds across three critical dimensions.

At Tech Mahindra, we work with organizations to help reimagine their product ecosystems as living, learning systems that continuously sense, interpret, and act. This is not merely about data collection but about data orchestration and enrichment across the entire product life cycle with three dimensions of value delivery – (a) silos to systems, (b) metrics to meaning, and (c) insight to impact.

From Silos to Systems

True value emerges only when you can hear the whole story. Right now, crucial data is likely locked in silos across your engineering, support, sales, and operations teams. A support ticket doesn't talk to the sales database, and an engineering log is disconnected from real-world operational performance.

To break down these walls, you need to build an Enterprise Intelligence foundation—a Unified Telemetry Fabric that connects every data point. This system creates a single source of truth that can:

• Ingest signals from diverse sources, including hardware sensors, software logs, and user interactions.
• Contextualize and analyze the information to gain a complete understanding in real-time.
• Trigger the right actions, from automated alerts and proactive service interventions to strategic recommendations tailored to your customers.

By connecting these disparate voices, you move from a collection of isolated data points to a cohesive, intelligent system.

From Metrics to Meaning: Understanding the "Why"

A dashboard full of metrics—CPU usage, latency, error rates—is good at telling you what has happened. But it rarely tells you why. The journey from Metrics to Meaning is about moving from observation to exploration.

Consider these scenarios:

• A compute node in a specific geography constantly overheats. Is it simply a faulty piece of hardware, or is it an environmental adaptation issue unique to that climate, indicating a need for a more robust product variant for that market?
• A router frequently resets under specific traffic conditions. Is it a bug, or is the customer missing a critical firmware update that could resolve the issue and enhance their network stability?

Seeking this deeper meaning and acting on it promptly unlocks significant opportunities. It enables you to move beyond reactive fixes to proactively enhance product reliability, reduce customer churn, and dramatically improve customer satisfaction. This is how you transition from being a vendor to becoming an indispensable partner. 

From Insight to Impact

There was a time when insights went solely to service support needs. Things have moved on into very different impact zones now. It initially transformed engagements from a transaction focus to an outcome orientation, such as uptime guarantees, energy optimization, and user experience enhancements – all powered by product data signals. It then evolved into creating recurring new revenue streams, leveraging the same data signals, such as ‘Performance as a Service’ offering by Storage OEMs and ‘Resilience as a Service’ offering by network providers.

At Tech Mahindra, we’re designing innovation-ecosystem playgrounds where these signals can be captured, contextualized, and commercialized. These ecosystems encompass OEMs, hyperscalers, and AI partners, creating collaborative value chains that amplify enterprise impact. The goal is not just to help build smarter products, but to enable the creation of smarter systems — systems that learn from every interaction, adapt to changing conditions, and evolve in response to customer needs.

Reflection for Innovation Ecosystem Players

As we move deeper into this frontier, here are some critical questions to reflect on:

• Are you extracting higher value from product data signals?
• What kind of value are you extracting, and how are those linked to your customers’ business outcomes?
• How will you exceed your customers’ expectations?

Answering these questions can help us evolve from AI readiness to business readiness. Pursuing this path can help us identify gaps in current telemetry strategies – gaps that, if addressed, can unlock tremendous enterprise value and enable them to expand their canvas to differentiate, transform, and monetize.

Final Thought

AI readiness becomes business readiness when we know how to listen when smart products start speaking – as that is a conversation waiting to be understood. And, when we start doing that, it opens a frontier to unlock enterprise value.