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How to select the right IIoT solution

There is a growing need for IIoT technology that can streamline business operations and costs. A study from Juniper Research found that the global number of industrial IoT connections will increase from 17.7 billion in 2020 to 36.8 billion in 2025, representing an overall growth rate of 107 percent. At the same time, however, implementing successful IIoT projects is typically an arduous and expensive undertaking. A 2020 Beecham Research study found that 50 percent of companies across industries failed to take IoT initiatives past proof of concept (POC) because of the sheer complexity of implementing IoT solution components. And in Microsoft’s 2020 IoT Signals report, 28 percent of organizations polled cited budget as a barrier to further IoT adoption. 

IIoT is complex by nature – but that doesn’t mean it has to be too complex and costly to implement. Choosing a platform that makes things more simple is critical. This is the first step on the path towards bringing projects to fruition and empowering end users so they can effortlessly interact with IIoT technology and utilize the data generated in a way that improves day-to-day operational efficiencies and delivers ROI. 

How can enterprises ensure they are choosing the right IIoT solution to bring their projects from POC to production faster and with a higher success rate? With a dizzying array of options on the table, organizations need to ensure they are selecting a fully featured yet uncomplicated solution that is customizable to best fit their unique needs. Here are some of the selection criteria buyers should consider when looking for the right IIoT solution.

Reduce implementation friction and complexity 

An ideal IIoT project starts with a platform that is easy to deploy, scalable and flexible. It’s important to choose one that can integrate successfully with existing infrastructure. It should be seamless to connect heterogeneous sensors, devices, machines and data streams to eliminate possible sources of friction.

Future-proofing must be a key consideration so that users can always access the full potential of the data they already own. Moreover, some companies have already embarked on large investments in production management systems but they aren’t able to act on the data that’s being collected and need a way to gain actionable insights across disparate systems. The chosen solution should be able to normalize data across diverse data sets, accommodate heterogeneous technology and future innovation to prevent data fragmentation and siloes that result in added complexity.

Avoid hidden costs  

Implementing and scaling IIoT solutions shouldn’t require exorbitant investment. Some solutions seem very low cost to start with, but then they hide costs in the long term. Many platform vendors charge hidden fees that can stack up, so be extra sure to read the fine print about what is included and which fees are incremental. Additional costs can be hidden when scaling to larger volumes of data, increasing the quantity of data points, or adding more sophisticated functionality such as alerting or reporting.

IIoT solutions also commonly require advanced technical skills which means outside hiring is needed to get projects off the ground. This can inflate the total cost of ownership even more. Choose a platform that will dramatically simplify IoT implementation and utilization costs as well as time. The ideal platform ensures easy adoption of comprehensive IoT and AI solutions through a no-code toolset that can be deployed without technical expertise. Solutions that natively integrate with and call third-party APIs and work with various cloud infrastructures are able to automate onboarding of sensors, eliminating the costs and complexities of solutions that need manual configuration.

It is important to consider platforms that are compatible with communications protocols that are robust enough to connect in places with scarce connectivity or require long range connectivity, without adding infrastructure costs. Organizations that need long range connectivity, for example, should consider selecting a platform that works with LoRa (long range, low power) sensors. These battery-powered sensors send data through the cloud public or private networks, can connect over distances of up to 15 km and last up to 10 years. LoRaWAN networking provides greater range than cellular networks and is compatible with existing infrastructure, making it a reliable and low cost alternative for organizations that traditionally had to rely on spotty WiFi networks.

Choose customizability and ease of use by anyone 

In evaluating IIoT platforms, businesses should look for customizability and flexibility in how users visualize and access insights and information through dashboards and alerts. You should also be able to create custom applications to meet your specific needs for monitoring operations. This shouldn’t require coding or technical expertise; rather, users with little to no prior experience should be able to take full control of and program their IoT system and dashboards in a simple visual programming interface. It should be straightforward and easy to set up alerts and monitoring of operations via the information collected from sensors. An ideal solution has intuitive tooling that allows users to concentrate on the configuration of their information systems – not backend programming – and make changes and updates on the fly. This streamlines the continuous improvement process and helps drive adoption of the IoT platform among users.

A robust platform will be able to aggregate and normalize real-time data from multiple sources and provide end-to-end visibility while consistently updating with the most accurate and up-to-date information in real time.

Prioritize search-driven AI and natural language querying capability 

Gaining actionable insights from IoT-generated data has historically been challenging. A solution that offers AI-driven analytics puts you one step closer to driving more value from IoT deployments. Seek out platforms that offer innovative technologies that work in concert with AI analytics to make the diagnostics process more specific and actionable. For example, NLP-powered search functions make it possible to easily ask for insights about or to identify problems with business operations being monitored, in natural language. Responses should pull from all relevant data, dynamically surfacing insights tailored to the user asking the question.  

Choose a partner not just a vendor 

A final consideration as you evaluate IIoT vendors: pick one that is collaborative, flexible and transparent. The implementation process will only work if both parties acknowledge the value of partnership. Don’t make IIoT projects more complex than they already are – select a vendor who understands that strong communication is crucial. All communication should be seamless with the common goal of customer satisfaction. This makes the process of deploying and managing IoT in your environment a less painful process at every stage. 

Lucas Funes, founder, Webee

Lucas Funes founded Webee to give enterprises the tools to easily combine data and insights in a new way providing a real-time, 360-degree view of their operations.