Companies are investing in the Internet of Things (IoT), but few feel that they’re completely prepared for it. There are concerns about IoT security, integration with other technologies, and the ability to scale out IoT for broader applications. Some companies also question if they have the onboard talent to run IoT or a well-defined IT strategy that can govern IoT deployment.
As IoT best practices develop, this trepidation is likely to continue. But there are several steps organizations can take now to make the IoT transformation easier.
SEE: Special report: The rise of Industrial IoT (free PDF) (TechRepublic)
1. IT and user collaboration on IoT
Many IoT solutions are coming in the door through manufacturing, engineering, facility management, fleet management, and more, but they aren’t necessarily being funded or reviewed by IT. This is a plus because the company’s end users have the best understanding of the business use cases for IoT for; but it’s a negative if IT consultations on security, scalability, and support get skipped.
It’s best if end users and IT can work together collaboratively in IoT solution reviews, planning, and implementation to ensure no steps are missed.
2. Plan for IoT projects to scale
If you’re successful in a pilot IoT project, the next step is to scale out the technology to other locations and applications. This maximum scale-out should be identified in your IoT strategy before conducting the first pilot so you can plan for and fund the networks, software, hardware, security, data management, and support that will be needed for the IoT when it is expanded.
3. Jitter-proof and segregate IoT-intensive networks
When networks get congested with too much data throughput, data transfer delays occur, and this IoT jitter degrades network performance. Jitter is small intermittent delays during data transfers, and it can become an issue when organizations begin to scale out IoT without first right-sizing their network capacities and bandwidths. Architecturally, companies can plan multiple network paths for IoT transmissions so that no one path gets overloaded. IoT-intensive networks should also be segregated from networks that carry very large data files or voice- and video-based communications.
SEE: Harnessing IoT in the Enterprise (ZDNet special feature)
4. Use a decentralized network infrastructure strategy
By using decentralized, smaller networks in manufacturing, logistics, facilities, and other areas of the company that may be using IoT, you can tamp down jitter and pre-process IoT data locally before sending it to a central data repository. Local network processing can weed out extraneous IoT data, such as machine-to-machine communications “handshakes” so the data that finally gets sent to central data repositories is clean and streamlined.
5. Implement a network quality of service strategy
A network quality of service (QoS) strategy is unique for each company and addresses the degree of security at each network node and device to ensure the data being processed and transmitted is secure. IoT security is a central concern of companies since IoT doesn’t have as many robust or uniform security standards as it has vulnerabilities. This makes taking charge of your own IoT network a must. Companies can do this by defining the levels of security needed for data at each router, device, sensor, and endpoint of an IoT network. Organizations often approach this task by adopting the vendor security presets of each router, sensor, device, etc. purchased, but the vendor presets don’t necessarily match up with your own network’s security needs. This is where quality of service comes in; you set your own security levels device by device. The job can be demanding and time-consuming, so companies often hire a QoS consultant.
6. Develop your own IoT talent
IoT talent is in demand and will continue to be. While it might not be the fastest route to achieve IoT excellence, training your employees in the end business and in IT so you gain mission-critical IoT skillsets is a good idea. Among the IoT skills that should be developed are: IoT device mastery and programming, network QoS, IoT integration, and IoT data analytics.