With a movement towards the internet of things, more machines and devices find themselves connected to networks in ways that allow them to transfer useful information. Gartner expects the number of IoT devices to rise from 8.4 billion in 2017 to 20.4 billion by 2020. Data is at the center of this development. With the IoT, comes larger amounts of data that can be structured into meaningful forms to help craft more accurate and complete stories about how a business runs. Thus, with IoT equipped machines and devices and a method to organize their data, businesses can take advantage of this information to help improve operations, intelligence, and sales and marketing efforts. Here are seven ways the IoT impacts business.

More Specific Knowledge on Costly Assets

Equipping machines with network-connected sensors allows for the generation of specific information related to their operation, often in real time fashion. Such data provides businesses knowledge into the status of different facets of the machine that certainly would have otherwise been missed under solely human surveillance. Sensors can be set to perceive conditions such as the position, vibration, speed, acoustic emission, or temperature of parts of the asset in order to derive realizations regarding its functioning. These insights help to indicate repair needs in a timely manner. They can also provide evidence hinting at inefficiencies or stress points for a certain machine. Realizing such nuances could lead to the development of more accommodative machine choice or design for certain functions.

Tracking of Inventory

Through RFID sensors, motion trackers, or camera object recognition systems, businesses can monitor parts or inventories as they move through their supply chain or get carried around their store. RFID tracking functions through tags placed onto assets that emit radio waves to a reader. The RFID reader then converts the waves into a more usable form of data yielding insight such as time-stamped location. This technology, therefore, provides additional transparency into the movement of assets; though, it requires tags to be placed onto each item or group of items that move together. Network-connected motion sensors provide a means of more general monitoring of assets without the need for attachments onto the units. Sensors may register signals upon an object passing, generating data as to when locations are transversed by assets, but this IoT technique provides less refined data in the process since it does not track assets themselves. Object recognition camera systems allow businesses to track assets without physical tags, yet the degree of confidence in accurate labelings and tracks and the need to avoid occlusions may make this technology a better option in the future. Some combination of object recognition, stationary sensors, and RFID can be used, but it seems for now that RFID takes the lead in generating inventory accuracies.

Data and Analysis in the Cloud

Since the IoT generates new data for manufacturers, these businesses can then use it for analysis of operations and logistical strategies. This may uncover insights into plant functionings that are useful for increasing efficiencies. Whether it be the ordering of steps in a process or discovery of completely new ways to conduct aspects of operations. Having analyzable IoT data can help create realizations leading to better processes and allocation of resources, reducing labor and capital costs. In order to organize and structure this information to the most useful extent, businesses may store and track it in their enterprise resource planning systems. Thanks to the fact that connected machines and inventories send information over the air, much of this data transfer, storage, and analysis can then conduct in some degree of autonomy via cloud systems integrated with artificial intelligence. Feeding data from connected devices to such an intelligence system further opens the potential to realize previously unrecognized patterns and trends that can lead to new workflow efficiencies. This works the same for manufacturers and retailers. While manufacturers may find insights leading to useful adjustments to production processes, retailers may use A.I. to realize nuance to make better decisions on floor layout, product messaging, or other ways to better accommodate the buyer’s journey.

Predictive Maintenance

Machine learning incorporated into information management systems takes further advantage of data from IoT sensors with its ability to proactively suggestive actions. Through iterations of data coming in from equipment, the system can generate associations between the micro-details of their conditions and their functioning. This allows it to predict, within ranges of confidence, the likelihood of events like equipment breakdowns. Armed with this knowledge, businesses can provide fixes before failures, reducing downtime and the costs associated with it. Unexpected events are inevitable, but equipment-level data provided to intelligence systems via IoT sensors helps to replace some of that uncertainty and risk with predictive analysis.  

Automation of Operations

Connecting hardware associated with machines, doors, lighting, and climate controls to networks operated by intelligence systems allows businesses to automate different aspects of their daily operations. With connected assets providing visibility through data, systems automate parts of production and inventory management to respond to particular conditions. This form of the IoT has actually been underway for some time and consists of things like doors opening for trucks based on schedule or trigger by sensor. It could also involve basing lighting and HVAC on the location and number of items in an inventory. Although building automation systems already help reduce overhead, introducing them to the internet helps to integrate, provide new data sources in their analysis, extra cybersecurity, as well as a means to better visualize their assessments. Beyond building systems, automation advantages resulting from the IoT can also extend to robot fleets and is soon to make its way to vehicle shipping fleets as well.

More Consumer Data

As the consumer IoT continues to expand with internet connected appliances, sensors in stores, and wearables, businesses find more sources of data useful in the analysis of buying experiences and general product demand. Smartphones and smart watches provide activity, health, and interest data. Household products including door openers, locks, thermostats, and even coffee makers capture behavioral data. These IoT products serve as sources of information that can provide visibility into the consumer mindset, while also gauging what individuals may need or desire in the future. The specific balance of sharing and accessing this information is important for the usefulness of insights and privacy. Furthermore, in stores, IoT technologies like wifi foot trackers gauge the number of visitors as well as their approximate locations, those insights can be drawn from traffic heat maps that try to extrapolate the customer experience. Analyzing this data along with that coming from smart shelves, allows businesses to better match their operations and offerings with demand.

Interactional Mediums

Consumer-facing IoT devices offer businesses platforms through which to reach consumers with digital marketing or engagements. Smartphones continue to serve as a popular means for targeted ads and customer experiences. Companies have started to employ their AR capabilities to craft engagements that motion track to surroundings. This form of media will further take advantage of augmented reality glasses that seem to be on the horizon. Internet and motion tracking capabilities have also been put into mirrors, allowing retail businesses to offer virtual try-ons. IoT also brings automated checkout to consumers, reducing the time spent in lines to provide a better experience that in turn reflects positively on the retailer.

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