IoT, AI, and the Future of Asset Management
These days, data is everywhere. In fact, we're obsessed with it. With the continuing evolution of the Internet of Things (IoT), data has become increasingly integrated into our daily routines – at home, online, in the car, and in the office.
Yet, while the challenge used to be finding data, today it’s more about using it effectively to create meaningful improvements.
U.S. astronomer Clifford Stoll famously noted, “Data is not information. Information is not knowledge. Knowledge is not understanding. Understanding is not wisdom.” This idea is more relevant today than ever. The true value of data lies not in its collection but in our ability to interpret it, recognize trends, and turn insights into actionable strategies, especially in asset management.
The Potential of IoT
IoT offers nearly limitless potential across manufacturing sectors, with experts projecting it to be a major force driving innovation over the next decade. For asset managers, IoT enables operators to monitor thousands of assets without constant manual intervention.
IoT can provide the insights manufacturers need to operate more efficiently by reducing unexpected downtime and improving maintenance tracking.
However, while the potential for IoT to be a game-changer for manufacturers, alone it may not be enough. Extracting clear and actionable insights from massive data volumes can be overwhelming, especially without automation. That’s where AI comes in.
Turning IoT Data into Actionable Insights
According to Gartner, the top technology trend for IoT is an increase in artificial intelligence (AI). This is because as the number and complexity of IoT systems grows, the ability to analyze the data collected will exceed human capability.
People used to worry that AI and automation might result in jobs lost. Instead, AI intends to enhance, not replace, human review and quality assurance.
AI uses powerful algorithms to filter through large amounts of data and identify patterns. For a manufacturer, AI can be used to collect and analyze data on assets or reduce the amount of time and resources required to make optimal decisions about downtime or repairs.
The power of strategic asset management
Optimizing your strategic asset management practices is key to making informed decisions and allocating expenditures that balance cost and risk. But where should you start?
- Identify the data you need: To set meaningful strategic goals, asset managers must first determine the data necessary to achieve them. Data should include both static information, such as asset material and installation date, and dynamic information like maintenance history, corrosion levels, or signs of fatigue. Collecting the right data is essential to answer critical questions and drive smarter decisions.
- Create a centralized data hub: A cloud-based central platform can serve as a single source of truth for asset data, helping to consolidate information scattered across different systems, devices, and even team members. Centralizing data provides the context needed to gain insights, monitor activity through dashboards, and present evidence-backed findings to stakeholders.
- Predict the future with scenario modeling: Machine learning enables asset managers to forecast asset behavior by analyzing historical and live sensor data. Scenario modeling provides an efficient way to visualize outcomes, weighing the cost benefits and intervention impacts over time. Managers can simulate various scenarios over 50-year spans, allowing for more informed planning and resource allocation.
Conclusion
The future of asset management relies on connecting the dots between your data, AI, and IoT. As these technologies evolve, asset managers will have new opportunities to make smarter, more sustainable decisions that benefit their organizations and communities.
To learn more about Brightly IoT and Smart Automation visit our Smart Automation Solution page. Or check out these additional resources to learn more about Strategic Asset Management in manufacturing or how predictive maintenance can help manufacturers achieve data excellence.
