Every IoT system has a large number of stakeholders. Each is interested in a unique set of outcomes from the system. Discovering and balancing the needs of these stakeholders is a huge part of the challenge to creating a commercially viable IoT system.
In fact, it’s so important that we created a methodology called Zero Waste Engineering™ to help organizations through each step of their digital transformation journey. By designing and delivering strategies and solutions that address the needs of each stakeholder, their shared outcomes drive the whole enterprise forward. While this methodology starts by addressing the critical people and processes challenges, there are also many design, implementation, and tooling challenges to creating a revenue-driving IoT system.
This blog post series provides insight into the common outcomes and tools desired by each stakeholder, along with considerations for designing the data processing infrastructure required to support those outcomes.
Before getting into the details of infrastructure and tools, it’s important to have an understanding of the different Stakeholder Personas and some of their common desired outcomes.
Key stakeholders of an IoT system include:
- Executives
- Finance
- Product Management/Marketing
- Operations
- Sales
- End Customers
- Customer Support/Service
- Engineering
- IT
- Legal
- Data Science
Each of these classes of stakeholders is interested in different outcomes for the business. Each will use different tools to achieve those outcomes. These varied and constantly evolving requirements put tremendous pressure on the data processing infrastructure of the enterprise. Once Zero Waste Engineering™ has helped you validate a business case for the system, the next most critical step in building a long-term commercially viable IoT system is creating an adaptable, expandable and economical data processing system for your enterprise.
Stakeholder | Common Outcome Requests |
---|---|
Executive | Dashboards showing performance against business case |
Finance | Billing Information Subscription Churn Rate Projected Infrastructure Costs |
Product Management/Marketing | Product Usage Data Service Usage Data New Offering Development |
Operations | OEE KPIs Alerts |
Sales | Cross Sell Opportunities Up Sell Opportunities |
End Customers | Dashboards Data Feeds Diagnostic Alerts |
Customer Support/Service | Diagnostic Alerts Warranty Issues Parts Replacement Device Management |
Engineering | Product Performance Data Root Cause Analysis |
IT | Infrastructure Health Monitoring System Health Alerts |
Legal | Data Integrity Validation Data Security Validation |
Data Science | Sanitized Data & Metadata |
Building an infrastructure that can take IoT data and other enterprise data and provide outcomes to all of the various stakeholders is no small undertaking. As our series continues we’ll be publishing posts on how to build a data processing infrastructure, and on the outcomes and tools for each class of stakeholder. Our next post discusses the utility of an IoT data pipeline platform.
To learn more, contact us today and we’ll be happy to dive deeper into best practices and provide an initial evaluation for how we can help you achieve your goals.