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Finding the right tech experts to build an Avengers-like dream team for an IoT initiative can seem as daunting as saving the world when starting from scratch.
With emerging IoT technology, organizations must stay current on the latest trends, adapt constantly and be prepared for any incoming threats. No matter how effective an organization's IoT strategy is, it will only run smoothly if the right people and skills are involved. Organizations need IoT experts, external partners and overlapping skills, even if they do not specialize in IoT.
Select experts and skills specific to IoT
Organizations that need to provide specialized products and services for their customers at a lower cost and better performance must build their own IoT deployment. However, building will cost more upfront and require more expertise, as executives must assemble IoT developers, systems integrators, data scientists, engineers and tech leaders with change management skills. The ideal team -- whether hired internally or externally -- must cover all aspects of an IoT initiative, including hardware, software, networking, data management, analytics, control systems and team management to succeed.
If organizations are building their IoT deployment in-house, they will need well-versed IoT developers who are capable of designing and testing the hardware, communications protocols, user interfaces and the application. IoT data aggregation and analysis is shifting from the cloud to the edge, making expertise in cloud and edge-based infrastructure essential. With the number of skills needed for IoT developers to build IoT initiatives, organizations will likely need more than one expert to fulfill the role. If IoT developers choose to use platforms to build out their IoT project, developers also must know how to use the chosen platform, such as IoT and cloud offerings from AWS, Azure or Google.
The value of IoT technology comes from the data that sensors and devices generate. IoT data scientists play the key role in ensuring the quality of data analysis and predictive systems in IoT deployments. They can also address the widespread device distribution and complicated networking infrastructure. The data IoT devices create at the edge must meet different data management and analytics requirements than the cloud, including preprocessing data, integrating multiple sensor inputs, establishing machine learning and AI models at the edge and functioning in real time. Organizations must also determine what data needs to stay at the edge and what data should be sent to the cloud or data center. The IoT edge architecture requires data scientists who understand signal processing, gateway layers, edge analytics and blockchain. Although edge computing has much in common with cloud computing, and both call for machine learning, IoT technology typically demands real-time response and expert skills not necessary for cloud computing.
General tech, soft skills make teams more successful
Whether or not tech experts have a background in IoT, many current employees will likely interact with IoT technology or data and need specific skills to ensure systems work and to get the most out of IoT.
Cybersecurity is a major concern for any technology, but for IoT devices it is particularly problematic due to the increased attack surface and lack of built-in security. IoT leaders must ensure their cybersecurity team is up to the task or hire additional support.
For many organizations, incorporating IoT creates challenges -- such as security -- that require IT and operational technology (OT) convergence. IoT requires software, hardware, control systems and networks that both IT and OT teams manage, but both groups approach each differently. IT pros must protect the organization's data and systems -- including the deluge of data from IoT devices -- and OT pros must ensure everything runs smoothly in production when combining old and new technology. With greater security risks and increased complexity, IT and OT must work together. One way organizations can address this is by cross-training IT and OT teams to promote collaboration and understanding of often conflicting priorities.
Soft skills needed for IoT include collaboration and communication. All tech experts working on IoT must understand the organization's needs and objectives and have project management skills. At the pace new IoT technology evolves, experts must be willing to learn and adapt to create a more effective team.
When to turn to outside resources
Even if an organization has IoT experts in-house, most organizations will need to partner with outside experts, such as IoT platform vendors, manufacturers or systems integrators. If an organization already has a product but wants to add IoT connectivity to it, then it might make more sense to find a product or platform instead of starting its own in-house team. There are many options regardless of whether the organization builds its own IoT deployment from the beginning and needs assistance or buys equipment, vendor platforms or as-a-service offerings where the provider team handles more of the work. The complexity of IoT might push organizations to seek assistance with connectivity, data analytics, data management and security from an IoT vendor that has a tested platform to scale and provide additional functionality.
The choice depends on the organization's objective in acquiring the IoT data and how quickly they want to get their product or service to market. The fast pace of the IoT industry makes it essential to get products to market before competitors. Buying IoT products and services costs less upfront but can't be customized as much as those made in-house and may not include security. Organizations purchasing IoT products and platforms must understand their own needs and the limitations of offerings.