The Internet of Things (IoT) has been an enterprise buzzword for a number of years, but the trend is not relegated solely to the tech world. Connected devices and systems are becoming more prevalent in all aspects of life, bringing with them new opportunities for mining data to make better decisions. While the opportunities are clear, many organizations are still in “experimental mode” with IoT data and have not fully integrated these information sources into their business intelligence (BI) and analytics initiatives.
This hesitance is understandable—the connected enterprise brings with it a significant influx of data from myriad sources and in a variety of formats. Many companies assume they will need to reengineer their BI environments in order to successfully integrate, cleanse and operationalize this information. However, that’s not the case—with the right information management strategy, organizations can begin incorporating IoT data into their existing framework and begin reaping the benefits.
What to consider:
To ensure IoT success, information must integrate seamlessly with existing business systems and processes. The best approach for achieving this is by deploying a comprehensive platform that combines all the elements organizations need for success, among them:
- Robust reporting: Numerous new tools have emerged to meet the IoT demand, but many lack a proper metadata layer, increasing the potential for errors and making it difficult to validate and audit the outcomes they generate. It’s critical that companies be able to produce robust, reliable reports on IoT data—otherwise too much time and resources will be devoted to trying to correct inconsistencies rather than acting on information.
- Capabilities for business users: To be successful, IoT projects must include intelligent data preparation and collaboration capabilities for the business user. Without this functionality, organizations are promoting analytics in silos and generating information discrepancy.
- Information apps: Many IoT initiatives are designed to empower a non-technical end user group—for example, giving retail store associates real-time customer information or providing marketers with data on website clicks and visits. As such, highly analytical apps that operationalize insights to a wide range of non-technical users are a critical element of IoT data success.
These considerations ensure that the entire enterprise is able to visualize and operationalize information, rather than reserving analytics for a select group of power users. With this improved access to information, many companies are actually monetizing their data and uncovering new revenue streams.
The advertising industry is a great example. Companies are increasingly investing a lot of money in digital initiatives, but need to understand how these campaigns are performing and their impact on the business. A digital media agency could answer these and other related questions by developing a customer-facing portal enabling users to track metrics like page views, interactions/clicks and site visitors. Combining this information with additional digital advertiser assets like Facebook fan pages would provide a holistic view of campaign performance and translate into measurable value for the business.
This is just one example to illustrate the potential of analyzing IoT data. Information generated by machines and meters, location tracking devices, wearable fitness gadgets and other forms of unstructured text can all become operationalized for a more effective and efficient organization. The key to accomplishing this is relying upon a comprehensive BI and analytics platform that can easily integrate IoT data with existing business systems and guarantee the accuracy, consistency and quality of the information.
With this framework in place, organizations can confidently share IoT data with a wide array of users and capitalize on all of the possibilities inherent in our connected world.