How the Enterprise of Things is Turning out to be a Waste of Money
The Internet of Things (IoT) has had a significant impact on the Enterprise industry. In this digital age, businesses that can leverage the vast benefits of IoT technology will be the ones that thrive.
However, research shows that most Enterprise of Things initiatives implemented in the business paradigm will end up a waste of money. This is because the deployment of off the shelf consumer-oriented devices such as wearables, AR/VR headsets, and sensor-based products is not always enough.
Instead, most companies need a more specialized approach than just deploying silo devices into their environment if they wish to receive all the benefits of EoT.
Research has indicated that nearly 75 to 85 percent of all the data gathered from devices is never fully utilized. Enterprises often fail to leverage the long-term advantage of EoT to collect disparate data from multiple sources/processes, which can then be aggregated and processed into a form of actionable intelligence, making it a strategic asset to the organization.
This can be implemented by integrating information gathered from all data sources (not just the 15 to 25 percent) into a consolidated data engine that is tied closely into corporate backend systems such ERP, sales, service management, to name a few.
Organizations should not see EoT as a siloed stand-alone capability for a single process, instead, as an extension of the existing corporate system. Although deployment of EoT is necessary to stay competitive, organizations need to come up with a strategy to fully exploit the potential insights that the input devices provide. Furthermore, they must fully utilize the output capabilities tied to the corporate back-office systems to achieve the comprehensive benefits of EoT.
Many current back-office vendors such as IBM with Watson AI, and SAP with Leonardo initiative, are enabling companies to accomplish the same. Amazon, Google, Microsoft, and others are also developing EoT initiatives to allow efficient data acquisition and analysis for improved corporate insight and application.