How to build a successful IoT strategy in 10 steps

1. Define clear business objectives

First, identify and understand the business goal that prompted adoption of the technology. IoT deployment is an attempt to align solutions to real business issues and objectives. Therefore, define each issue and objective clearly, with a focus on identifying specific business problems that IoT helps solve.

Among the key considerations in this step:

• Begin with business problems, not the technology fix.
• Identify specific organizational pain points in current operations.
• Ensure the IoT strategy aligns with overall business objectives

2. Identify use cases and prioritize

With business objectives defined, the next step is pinpointing high-impact IoT use cases and prioritizing them based on potential benefits and feasibility. Strategic use-case selection typically underpins any successful IoT initiative.

• Focus on proven, high-ROI applications first. Common examples include predictive maintenance, asset tracking and energy management systems.
• Evaluate use-case complexity and organizational readiness for data availability, infrastructure requirements and skills gaps.
• Develop a use-case prioritization matrix, with scores based on business impact, technical feasibility, required resources and deployment timeline.
• Map use cases to IoT technology maturity. Start with established technologies before adopting emerging solutions.
• Consider regulatory compliance benefits, including automated reporting, safety monitoring and environmental tracking.
• Plan use-case sequencing. Build foundation capabilities that support multiple advanced applications.

3. Define measurable success criteria

Specific, measurable metrics guide deployment details. This attention to detail typically precedes successful IoT initiatives.

• Create SMART goals with specific timelines and accountability.  The SMART framework creates, as its acronym suggests, specific, measurable, achievable, relevant and time-bound goals. SMART IoT goals clearly define expected outcomes and their benefits. For example, an enterprise's SMART IoT goal reduces facility energy consumption by 25% within 12 months, employing IoT-enabled smart building systems and automated HVAC optimization.
• Establish both leading and lagging performance indicators. Beyond SMART goals, key performance indicator (KPI) metrics are also useful. These metrics include leading indicators, signaling a change is in progress, as well as lagging indicators, confirming a change has occurred. The benefits of IoT adoption take time to appear, so it's important to understand and track these indicators. Leading indicators include user adoption rates and device connectivity percentages. Common lagging indicators include cost savings, revenue increases and customer satisfaction surveys.
• Plan milestone-based success frameworks. SMART goals and KPIs are important metrics, but time-based milestones during deployment enable businesses both to track progress and adjust strategies based on real-world results.

4. Conduct a comprehensive infrastructure assessment

With goals and success criteria defined, the next task is to inventory organizational assets and capabilities. Before beginning any IoT initiative, it's critical to evaluate these areas in particular:

• Technology infrastructure. IT infrastructure includes network bandwidth, computing power and data storage capabilities.
• Operational processes. An organization's business processes, from existing workflows to integration points, must be scrutinized.
• Data management. Data collection, storage and analysis fall under the data management umbrella.
• Security posture. Review existing cybersecurity measures and regulatory compliance requirements.

These assessments not only identify needed infrastructure investments, but they also limit costly surprises during deployment.

5. Select optimal technology architecture and platforms

IoT deployment isn't simply about new sensors. It combines an organization's existing assets and processes identified in step four with additional technology that addresses the objectives in step one.

• Design for enterprise scale from project inception. Think big. Design a scalable architecture that defines the project beyond its pilot and grows with an organization's changing needs.
• Choose technology stacks based on specific use-case requirements. IoT is not a one-size-fits-all approach. In particular, IoT connectivity is not uniform and presents different types of challenges. For example, real-time applications requiring sub-second responses need edge computing and ultra-low latency connectivity. In contrast, batch processing applications make use of cloud-based analytics and more cost-effective IoT connectivity options.
• Evaluate connectivity options. A complex array of connectivity options supports IoT. 5G RedCap, or 5G NR-Light, enables high bandwidth and low latency, while Wi-Fi 6 is highly effective for certain indoor bandwidth capacities. Other options include low-power wide area network (LPWAN) technologies, such as LoRaWAN, that remain cost-effective for sensor networks requiring long battery life across large areas.
• Ensure interoperability through the adoption of standards. A successful IoT strategy requires device agility and interoperability. To accomplish this, use technologies with a demonstrated history of multi-vendor interoperability that support existing industry standards.

6. Conduct risk assessment and mitigation planning

There are clear and measurable benefits to IoT deployment, but risk assessment remains a critical step in the process. Businesses must consider and enumerate existing organizational risks, leading to a more refined risk management strategy.

• Perform multi-dimensional risk analysis. Risk is not just security. Technical risks include integration challenges and scalability limitations, while business risks encompass market changes and vendor dependencies.
• Mitigate shadow IoT risks. Among the most common IoT risks is shadow IT, or devices not deployed or managed by an organization's IT department. Unsanctioned devices raise configuration and security concerns.
• Address the critical skills shortage proactively. Many organizations lack the skilled employees needed to deploy and maintain a successful IoT strategy properly. Gauge this risk and its relevance closely, then plan for and invest in training programs to build necessary capabilities internally.

7. Strengthen security architecture and device management

Risk assessment inevitably identifies IoT security concerns. A business must then consider the following tactical elements to ensure optimal IoT security:

• Introduce zero-trust security. One IoT security best practice is zero-trust network access (ZTNA). With zero trust, every IoT device identity is verified and authenticated every time it connects.
• Exceed basic security controls. ZTNA is a solid start, but organizations must layer their defenses, from advanced threat detection to network segmentation that reduces the attack surface.
• Use device lifecycle management. IoT devices often have long lifecycles in the field – 10 years or more. From a security perspective, mechanisms for firmware updates and security patches are absolute necessities.
• Establish IoT-specific security governance. IoT is unlike other technologies, needing unique security protocols, plus the specialized resources and staff to match. Organizations with IoT cybersecurity specialists improve their overall cybersecurity and the chances of IoT project success by creating catalogs of IoT projects, developing IoT-specific security policies and establishing dedicated IoT security budgets.

8. Execute in phases with rapid iteration

With these processes complete, rollout begins.

Similar to any other IT initiative, IoT benefits from a phased approach, including piloting and validation, before enterprise-wide deployment.

• Use rapid prototyping to validate assumptions. A prototype lets an organization test and compare a technology's capabilities to expectations for that technology. This includes proof of concept deployments or minimum viable product iterations; both provide an opportunity to refine tactics before full-scale deployment.
• Mirror piloting environments to production conditions. IoT devices operate in all kinds of locations. Match environmental factors, network conditions and user behavior in pilots to eventual full-scale deployment scenarios.
• Establish clear criteria for pilot advancement. Define specific metrics for pilots that clearly indicate the technology is mature and ready for broader deployment. Metrics include minimum device connectivity rates, data quality thresholds, user adoption targets and business outcomes.

9. Deploy advanced analytics and performance optimization frameworks

Following a successful pilot project migration to broader deployment, verify that the IoT strategy meets or exceeds the objectives described in step one.

Components that support this positive outcome include:

• Advanced analytics. Design data analytics architectures for current and future scale, ensuring they have the ability to handle large amounts of data with time series databases across a distributed computing framework.
• Comprehensive analytics platforms. Comprehensive platforms include a dashboard or other data visualization tool, report generation, machine learning and AI integration.
• ROI review. Use continuous ROI monitoring with real time dashboards and automated stakeholder alerts.

10. Scale to drive continuous improvement

Finally, a core element of any successful IoT strategy is scalability. Scalability refers to the ability to expand the number of deployments and the number of devices and capabilities in each deployment.

The organization, armed with iterations that successfully completed the previous nine steps, must choose where and how to scale. Consider the following suggestions for scaling and driving continuous improvement:

• Monitor and measure. As defined in step three, continuously track the KPIs. But don't just track them; adjust them when and as needed.
• Upskill teams for ongoing management. Provide continuous training on IoT management, analytics and cybersecurity.
• Foster a feedback loop. Create channels for employees, customers and partners to provide feedback on the IoT system, enabling further iterative improvements.

Sean Michael Kerner is an IT consultant, technology enthusiast and tinkerer. He has pulled Token Ring, configured NetWare and been known to compile his own Linux kernel. He consults with industry and media organizations on technology issues.