The role of Data & Analytics in IoT

By: Antony ByfordVP IoT and Collaboration

The Internet of Things (IoT) generates an enormous amount of data. Whether it’s sensors monitoring a factory floor or smart devices collecting customer behaviour, all this data has immense potential—if you know how to utilise it. That’s where data and analytics come in, helping businesses not just make sense of these data streams but turn them into actionable insights.

For technology resellers and enterprises, understanding how to leverage advanced analytics in IoT is key to creating significant value. From minimising downtime to optimising performance, here's how actionable insights from IoT data can drive better business outcomes—and how partners like Westcon-Comstor can support you in succeeding with IoT.

Turning IoT data into insights

IoT data stands out because of its sheer volume, variety (both structured and unstructured), and velocity (real-time updates). A single IoT sensor might collect thousands of data points daily—spread out across an entire IoT network, this becomes millions or even billions. According to?IDC, 55.7 billion IoT devices globally are anticipated to generate almost 80 zettabytes (80,000,000,000 terabytes) of data annually by 2025.

However, data alone is not inherently valuable. It’s the ability to analyse and interpret this data that turns it into actionable insights. Here’s how advanced techniques are helping to make that happen:

Advanced data mining

Data mining algorithms identify hidden patterns, trends, and correlations within IoT datasets. For example, manufacturers use these techniques to uncover inefficiencies in production processes. By analysing sensor data, bottlenecks are pinpointed or resource needs predicted, boosting operational efficiency. Advanced clustering and classification methods also provide deeper insights into usage patterns, customer behaviour, and equipment performance.

Predictive analytics

Predictive analytics builds on data mining, enabling businesses to forecast future outcomes by analysing past patterns and real-time data.?Gartner?predicts that by 2026, over 80% of IoT projects will incorporate predictive analytics to enhance results. For instance, retailers use predictive models to better align supply chain deliveries with customer demand, reducing excess inventory costs while maintaining stock availability.

Proactive monitoring

For industries like healthcare and manufacturing, downtime doesn't just cause inconvenience—it can be disastrous. Proactive monitoring mitigates this risk by continuously tracking the health of IoT-connected equipment. Predictive maintenance, a prominent example, uses sensors to monitor parameters like temperature, pressure and vibration. Proactive monitoring in sectors such as energy has already saved millions of pounds by pre-empting failures in critical assets such as wind turbines.

Real-world applications and gains

IoT data and analytics are already helping organisations worldwide create smarter workplaces and solutions. Some use cases across industries include:

Smart manufacturing

McKinsey?estimates that predictive maintenance driven by IoT analytics can reduce factory downtime by 30-50%, leading to significant cost savings. For example, sensors in assembly lines detect anomalies in vibration or temperature, prompting preventive maintenance and reducing unplanned downtime.

Aerospace

Industries like aerospace and automotive rely on predictive models to prevent failures.?Rolls-Royce, for example, uses IoT analytics to forecast engine maintenance needs, ensuring greater operational reliability for their customers.

Logistics

Companies like DHL use IoT-enabled predictive analytics to fine-tune delivery routes and vehicle maintenance. This not only reduces delays but also enhances service quality, cutting logistics costs by up to 15%, according to?McKinsey.

Retail

IoT sensors paired with analytics provide real-time inventory management.?McKinsey?reports a forecast accuracy improvement of up to 85% among retailers utilising IoT-enabled inventory systems. For example, a beverage company can monitor vending machines across their network, ensuring refilling schedules are based on usage trends. This reduces operational costs while keeping products in stock for consumers.

?We can potentially replace or include the vendor case in this section

?No case study at the moment in this area, so I think its best to keep this section in the current form.

The opportunity in IoT data

Transforming IoT data into a growth-driving strategy requires not just technology but the right expertise and direction—and Westcon-Comstor is here to help make it happen. We help technology resellers and enterprises unlock new growth opportunities for your customers via:

• Simplified rollouts: Pre-configured solutions that reduce setup time and enable seamless IT/OT integration.
• Ongoing technical expertise: From real-time troubleshooting to strategic advice, our experts are on hand to support your IoT ecosystem.
• Scalable portfolios: Build the right IoT package to match the demands of businesses of any size, from SMB clients to large enterprises.

Ready to turn IoT data into results? Westcon-Comstor is here to help.

Explore solutions