The emerging internet of things (IoT) is an extension of digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere. This innovation means that virtually any appropriately designed device can generate and transmit data about its operations, which can facilitate monitoring and a range of automatic functions. To do this IoT requires a set of event-centered information and analytic processes that enable people to use that event information to make optimal decisions and take act effectively.
To better understand how this technology is being deployed and used Ventana Research is launching benchmark research on The Internet of Things. The research will explore organizations’ experiences with IoT initiatives and with attempts to align IT projects, resources and spending with new business objectives that demand real-time intelligence and event-driven architectures.
In many industries, organizations can gain competitive advantage if they can reduce the elapsed time between an event occurring and being able to take action or make decisions in response to it. Existing business intelligence (BI) tools provide useful analysis of and reporting on data drawn from previously recorded transactions, but organizations now areconcluding that employees and processes in IT, business operations and front-line customer sales, service and support also need to be able to detect and respond to events as they happen.
Our previous Internet of Things benchmark research found that both business objectives and regulations are driving demand for new technology and practices. By using them many activities can be managed better, among them manufacturing, customer engagement processes, algorithmic trading, dynamic pricing, yield management, risk management, security, fraud detection, surveillance, supply chain and call center optimization, online commerce and gaming. Success in efforts to combat money laundering, terrorism or other criminal behavior also depends on reducing information latency through the application of new techniques.
As with any innovation, embracing IoT may require substantial changes to any organization. These are among the challenges business leaders face as they consider adopting this evolving technology:
- They find it difficult to evaluate the business value of enabling real-time sensing of data and event streams using radio frequency identification (RFID) tags, agents and other systems embedded not only in physical locations like warehouses but also in business processes, networks, mobile devices, data appliances and other technologies.
- They lack an IT architecture that can support and integrate these systems as the volume and frequency of information increase.
- They are uncertain how to set reasonable business and IT expectations, priorities and implementation plans for important technologies that may conflict or overlap. These can include BI, event processing, business process management, rules management, network upgrades and new or modified applications and databases.
- They don’t understand how to create a personalized user experience that enables nontechnical employees in different roles to monitor data or event streams, identify significant changes, quickly understand the correlation between events, and determine the right decisions or actions to take.
This research will continue our investigation of how organizations are dealing with these challenges and increasing their responsiveness to events by rebalancing the roles of networks, applications and databases to reduce latency; it also will explore ways in which they are using sensor data and alerts to anticipate problematic events. We will benchmark the performance of organizations’ implementations, including IoT, event stream processing, event and activity monitoring, alerting, event modeling and workflow, and process and rules management.
Click here to participate in this research, and here to learn more about Ventana Research’s methodology and large body of business research. Ventana Research also has conducted research in related areas including Data Preparation, Machine Learning, Data and Analytics in the Cloud, Next-Generation Predictive Analytics and Big Data Analytics and Integration.