Recommendations

An Expanding World Requires an Expanding Mindset

Speed up your own path to IoT wisdom

Here are some final insights to help you move toward greater IoT success:

Ask (and answer) the right questions. We’ve reiterated this point throughout our report. The value and success of your IoT use cases depends largely on the types of questions you ask and how you answer them. Don’t know all the questions? Don’t know all the answers? Ask trusted partners to help you define them.

Base IoT decisions on the best practices of business-driven analytics. IoT devices will exist at the edge of a (hopefully) valuable pipeline of data and emerging insights. Look to disciplines and experts in data intelligence and the field of analytics, ML, and AI to help you define what that pipeline should look like and where IoT can have the most impact. This report offers a glimpse into how best to approach these answers, including one framework from which to develop your own pipelines of IoT data.

Do away with “Shadow IoT.” We’ve all heard of Shadow IT and the runaway cloud governance/management/security troubles it started at the outset of the Great Hyperscale Cloud Migration. Unfortunately, today’s IoT use cases often start in the same shadowy fashion. Whether you are the head of an LOB or an industrial operational technology (OT) group, let your central IT team, your platform team, and other business stakeholders in on your latest IoT dreams. You, and your use cases, will be stronger for it.

Bring the right people together to support edge and IoT

Create an IoT/Edge Center of Excellence (COE). Take a page from many of the IoT consortiums, vendors, and solution providers involved in delivering technology answers to edge business questions. Build out a Center of Innovation or Center of Excellence to help incubate your own emerging IoT use cases. This team should be chartered to successfully define and map business objectives of an IoT or edge project with the related enterprise architecture and technical requirements needed to support the project. This includes defining what’s needed for initial PoC and production deployments at scale.

Build an IoT platform team. IoT use cases based on areas like ML and AI often require continuous improvement and refinement of the underlying models and systems used to extract meaning from IoT data. Here, a modern and iterative approach from your own platform team can apply ongoing improvements, based on their own continuous integration and delivery (CI/CD) pipeline. Representatives of this team should also have a place at your IoT/Edge COE table.

Expand your definition of an IoT ecosystem. Large IoT applications involve many moving parts. To make IoT use cases truly successful, you need to expand your idea of an IoT ecosystem well past even the hardware, software, networks, and applications required to move and process your data. Include trusted providers, trusted vendors, and industry leaders you can rely on to help answer your questions, build new connections, and build out a technology roadmap for the future of IoT.