When data become strategy

How access to connectivity can drive product evolution and open new business opportunities

Sara Strizzolo

16th May 2025

From connection to transformation

Once the first step - connectivity - is completed, the device begins to generate real usage data. But without a clear strategy, that potential remains untapped.

This is where a data strategy comes into play: a framework that gives strategic meaning to data and turns it into tangible value-creating new business opportunities, process optimization, and product innovation.

For many manufacturers, the IoT journey stops at data collection: the product is connected, sends data, and that data is stored in the cloud. But without a clear data strategy, much of that value risks going unrealized.


That’s when real transformation begins.

From fragmentation to strategic sharing

A key step in IoT implementation radically changes how companies approach both products and services: democratized access to data and its integration into day-to-day business processes.


The true strategic shift lies in distributing data effectively throughout the organization:



  • service teams gain access to machine data before arriving at the customer site
  • technicians consult real-time and historical parameters without intermediaries
  • R&D understands how products are actually used in the field
  • marketing identifies which features deliver real value.


This kind of access reshapes how information is used. It means organically integrating data into daily decision-making at all levels.

Data as a 360° strategic lever

Access to data enables a shift from:


  • assumptions and gut feelings
  • subjective and anecdotal experiences
  • reactive problem-solving


to:


  • decisions based on objective, measurable evidence
  • early identification of trends and issues
  • proactive optimization of products and services.


Here are a few business areas where a data strategy delivers immediate value:


🔧 Product design


  • Analysis of features actually used
  • Identification of usage pain points
  • Technical improvements based on real insights


🛠️ Service & After-Sales


  • Predictive diagnostics
  • More targeted, timely interventions
  • Lower support and maintenance costs


📊 Marketing & Go-to-Market


  • Anonymous analysis of usage patterns by geography or customer type
  • Detection of emerging market needs
  • Strengthened commercial offerings through value-added services


💬 Sales


  • Sales team training based on real data
  • Data-driven value propositions
  • Upselling opportunities linked to actual usage

IoT as a value enabler: from technology to services

This mindset marks a fundamental paradigm shift: IoT should not be seen as a cost to be passed on or written off, but as an enabler of entirely new services—services that simply couldn’t exist before.


  • We no longer design just products—we design products that enable services.


  • These services may be internal (support, maintenance, marketing) or external (offered to end users), and represent new revenue streams.


In this light, connectivity becomes a strategic resource, not an added cost. It drives data-informed product innovation and paves the way for the natural integration of Artificial Intelligence.

Building an effective data strategy

An effective data strategy is never one-dimensional. Relying on a single use case to justify an IoT investment is often risky.

Instead, companies need a comprehensive, cross-functional vision, where teams across R&D, service, marketing, sales, and management can access the right tools, interpret and act on data, contribute to a shared strategic vision.


This requires:


  • simple tools for visualizing insights (dashboards, apps, Power BI, etc.)
  • a strong data culture, to move from intuition to evidence
  • ongoing training for internal teams, commercial partners, and service centers.

Training as a catalyst for change

To unlock this potential, companies must strategically invest in training as a key enabler.

Training must include the entire ecosystem. At the management level, innovation starts with the diffusion of a data-driven mindset that builds awareness of its value and impact.


It must also extend to operational roles - salespeople, product designers, resellers, service centers, and field technicians -through:


  • role-specific training programs
  • hands-on workshops using real tools and dashboards
  • awareness sessions on data value
  • identifying project leaders who can drive the change.


Why training matters:


  • it reframes perception: from "one more tool to learn" to "a system that makes my job easier"
  • it builds awareness of the real value in the data collected
  • it lowers resistance by showing tangible benefits
  • it aligns technology, processes, and business goals. 


Only through data can connectivity become a true competitive advantage. Without data, none of this is possible.

👉 Want to discover how ready your company is to integrate AI into products?


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