IoT extends the operational benefits of telematics by using wireless technology and the Internet to connect a far broader spectrum of sensors enabling companies to drive process improvement, product innovation and most importantly gain insights from their data. The proliferation of affordable sensors and data processors dramatically accelerates the monitoring, control, analysis, and execution of tasks when paired with enterprise AI, leading to increased operational efficiencies and cost savings. Enterprises will have to cultivate data as a core competency, utilizing AI analytics to succeed and remain a step ahead of traditional competitors.
Steering ahead of competitors by exploiting the benefits of historic requires a combination of technology, people, and processes. Developing expertise in analyzing vast amounts of data, (not just by data scientists) leveraging and up-leveling the skills of data analysts will be crucial as well. The power of merging sensor data with other sources such as enterprise data ( such as sales and CRM), third-party data (behavioral, demographic), and open public data ( Such as Census and weather) will be critical to AI strategies.
The recent times have seen an increase in IoT devices that can detect, capture, and transmit (or store) information about their environment. This information that may be transmitted in (near) real-time or recuperated periodically only has meaning once it is processed. What makes IoT data unique is that there are billions of data points and data science, AI and ML focusing on an advanced interpretation of the aggregate data. This helps enterprises derive value from IoT data, making operations more systematic.
Moreover, with an abundance of data from IoT, data science teams, with the right people, processes, and tools working collaboratively are required to transform extreme data sets into actionable insights. Machine learning can reveal patterns or build models to forecast the future of behavior of people, things, or processes.
Traditional companies must exploit the benefits of the IoT wave to compete with each other and also with disruptive IoT startups. Businesses will need to grow their data science abilities and develop more efficient ways to do ETL, transformation, processing, and modeling.
Therefore, successful execution on IoT data requires adopting analytical techniques, and methodologies better-suited to IoT itself. By adopting IoT, companies will bring significant value to their stakeholders and remain relevant.