As management guru Peter Drucker once said, “What gets measured, gets managed.” Unfortunately, many companies have struggled to apply that principle to their Internet of Things (IoT)-enabled digital transformation programs. In theory, IoT should allow companies to collect and track data across all of their critical business processes, operations, and even products in use by customers in the field.
In reality, most companies are still using IoT to track individual assets and devices, often through a case-by-case, isolated approach that yields marginal benefits at best. They may have embedded sensors in a manufacturing facility, or on a company’s fleet of vehicles, and they’re able to generate data—sometimes significant amounts—but they’re not able to synthesize that information into genuine insights or make near-real-time decisions. They’re not measuring enough, and they’re not integrating that information with other data.
Instead, organizations should link IoT-enabled devices, assets, and processes as part of a holistic digital transformation—not just intelligent sensors and devices and siloed applications but information from all internal operations, business models, and customer-facing aspects. That stream of data gets aggregated on a central, enterprise-wide platform, powered by a back-end analytical engine empowered with artificial intelligence and machine learning.
In that way, managers and the C-suite can have real transparency into what’s actually happening across the organization, at a highly granular level. As a result, they are better equipped to execute against strategic objectives like increasing operational efficiency, improving customer service, Improving product design and reliability, or rethinking the business model. They can take corrective actions much faster. Moreover, predictive analytics can use this data to give mangers and leaders a sense of what’s coming, allowing them to take proactive steps to capitalize. And in many cases, those corrective actions can happen autonomously.
In other words, companies need to imbue IoT with intelligence.
To consider the potential gains from this approach, consider a large Industrial pump manufacturer. The company incorporated IoT across several of its production facilities into an integrated analytics platform. Through this platform, the company was able to implement real-time predictive maintenance, increasing both asset and network utilization. It reduced maintenance costs by 25% and improved overall production capacity by 5%, even as it generated significant environmental gains (avoiding 665,000 tons of CO2 emissions per year). Productivity and profitability both improved, and the company was able to grow its service offerings to boost sales.
Four priorities to get there
To create this kind of intelligent enterprise capitalizing on the strengths of IoT, companies should focus on four priorities.
- Integrate IoT as part of a broader digital transformation
Companies should evolve beyond the isolated, pilot approach of the past. They should seek to build an IoT platform with the right balance of centralization (linked to the ERP system and analytics suite) and autonomy (capable of on-boarding business partners and enabling new IoT applications as they become available).
- Implement the right data structure
All employees and business partners should be able to tag, capture, share, and publish information about their assets and processes—all in a secure manner. We refer to this as the company’s “data fabric,” but it requires a foundational architecture to ensure that it is stable, resilient, and accessible to the right people at the right time.
- Governance should be in place to address emerging issues
Companies must instill practices for issues such as privacy and unintentional biases in algorithms, and—on the positive side—to objectively quantify the value from data and analytics initiatives.
- Create the right culture and mindset
Digital transformations involving IoT are challenging, and failure along the way is inevitable. People need to be willing to embrace risk, to learn through trial and error, and to embrace failures as an inherent part of growth. To support this culture, leaders need to accept and embrace change, fostering a mindset of data-driven and objective decision-making and relentless innovation. Front-line employees need to adopt new ways of working – for example, side-by-side with intelligent systems.
Many organizations are, understandably, dissatisfied with their IoT initiatives thus far. But rather than being written-off as failures, those efforts should be treated as the foundation on which companies can now build and grow. Truly capturing the benefits of IoT calls for a broader and more comprehensive approach, one that helps companies achieve their goal of becoming an intelligent enterprise.