{"id":2886,"date":"2019-03-05T11:33:50","date_gmt":"2019-03-05T11:33:50","guid":{"rendered":"https:\/\/www.kovair.com\/blog\/?p=2886"},"modified":"2025-09-03T11:06:07","modified_gmt":"2025-09-03T11:06:07","slug":"leverage-iot-analytics-for-business-opportunities","status":"publish","type":"post","link":"https:\/\/www.kovair.com\/blogs\/leverage-iot-analytics-for-business-opportunities\/","title":{"rendered":"How to Leverage IoT Analytics for Business Opportunities"},"content":{"rendered":"

Over 2.5 quintillion bytes of data is created around the world each day, and about one-tenth of it is contributed by IoT devices. So, what can be done with such a huge load of IoT data? Here are a few ways to understand how you can leverage IoT analytics for business opportunities.<\/p>\n

\"IoT<\/p>\n

The Internet of Things is helping us build a connected world where information and services could be accessed at the click of a button. However, the data generated by such building blocks of IoT networks are way more significant than any other conveniences it could provide.<\/p>\n

\"IoT<\/p>\n

Caption: Global Market size of IoT analytics from 208-2022 (Source: Statista)<\/em><\/p>\n

As per reports from Statista, by 2022, the global market size for IoT analytics will reach a valuation of US $18. Billion \u2014 a good opportunity to find business opportunities using IoT analytics. What you really need to know is how it must be done.<\/p>\n

Follow the 3-step process to finding the best ways you can leverage IoT analytics for business opportunities.<\/p>\n

1. Combining OT data with IT data<\/h2>\n

For an IoT ecosystem to work perfectly across a business ecosystem, synchronization between data generated by operational technology and information technology is paramount.<\/p>\n

Data generated from Information Technology or IT refers to all the data of the organization \u2014 enterprise systems, finance systems, CRMs and all data collected by other enterprise software for various purposes such as employee records, client records, project data to name a few.<\/p>\n

On the other hand, data collected by Operational Technology or OT includes everything software and hardware that facilitates the operations. The IT data of an enterprise comes from its various hardware and software devices, sensors, and of course, not to forget IoT devices.<\/p>\n

So, if you are willing to leverage IoT analytics for your business<\/a>, you need to understand how you can combine both OT and IT to analyze new opportunities for your business.<\/p>\n

For example, car manufacturers can use IT data from enterprise systems to verify the past service records of a customer\u2019s vehicle and use the same to combine with OT data from IoT sensors for understanding what parts of the vehicle require the highest amount of maintenance. The combination of both OT and IT data can then be used to notify the customer about the next service due date and inform them about the parts that need immediate maintenance.<\/p>\n

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2. Finding an appropriate business case with IoT analytics<\/h2>\n

The most essential step for leveraging IoT analytics, as mentioned above, is combining OT and IT data for identifying appropriate business problems that can be solved through IoT. Once you\u2019re done with that, the next step is to find out an appropriate problem that can be understood\/resolved with IoT analytics.<\/p>\n

To help you understand just that, here are a few suggested use cases with IoT analytics across different industries:<\/p>\n

IoT analytics in Healthcare<\/strong><\/h3>\n

Using IoT in the healthcare sector is relatively simpler in comparison to other industries mainly due to the high application of sensors on medical equipment. However, eHealthcare solutions implemented with IoT analytics require more than mere sensor data.<\/p>\n

Doctors can leverage IoT analytics to track patient records through IoT data from IT systems of the hospital and combine it with OT data produced by sensors that track patients\u2019 movements and activities.<\/p>\n

To make matters even easier, the work of interpretation can be handed over to machine learning solutions, which can complement a doctor\u2019s expertise and help diagnose symptoms and design treatments at a much quicker pace.<\/p>\n

IoT analytics in Retail<\/strong><\/h3>\n

One of the most perplexing issues faced by retailers is visual merchandising. Visual merchandising refers to everything that a retail store sets up to grab the attention of customers and influence them just as the business intends to.<\/p>\n

It is often difficult for retailers to identify areas within the store that receive the maximum amount of attention from customers. IoT analytics can track customers\u2019 movements within the store and track the hotspots where customers assemblage is the highest at any given time.<\/p>\n

Similarly, IoT analytics can also help owners to identify spots where stocks need to be refilled and expired products on the shelves need to be replaced.<\/p>\n

Another intelligent use case for IoT analytics in retail comes yet again by combining OT and IT data. Store owners can have users download an app and use it as the medium of transactions for purchasing goods. In this way, long queues at the store counter could be cleared away quickly and store owners would be able to capture relevant customer data on their IT systems.<\/p>\n

The collected data can be further leveraged by OT systems across the store by drawing a relation between the users\u2019 smartphones and the identity of the customer. Based on the relation drawn based on the previous shopping sprees of the customer, salesmen could be quickly notified about any specific needs that the customer may have the next time he or she enters the store.<\/p>\n

Of course, IoT analytics has an even wider variety of use cases. But my goal with this blog is to help you understand how you can leverage it for your business rather than suggesting use cases.<\/p>\n

3. Understanding your goal with IoT analytics<\/h2>\n

The above-mentioned use-cases with IoT analytics convey a clear meaning that the ultimate purpose of interpreting all these data collected through IoT devices is to understand or gain control either over people or on business processes.<\/p>\n

Gaining control requires independence and self-reliance. Applications with IoT are perhaps the most independent way of gaining control. Data collection from IoT devices and using it for IoT analytics involves the use of 100% untampered data \u2014 a kind of data that can deliver incredibly useful interpretations at a scale that is impossible to achieve by anything but IoT.<\/p>\n

So, the third step to finding appropriate business opportunities with IoT analytics is to understand what you want to control. The answer to this depends entirely on the kind of industry and the business that you are involved in, but what is certain, is that these three steps will help you gain better clarity on finding a use case with IoT analytics.<\/p>\n

Takeaways<\/h3>\n

I tried my best to highlight the importance of IoT analytics with this blog and how the amalgamation of Operational data from IoT devices and sensors with Information from enterprise systems is important.<\/p>\n

In the second step to this 3-step process, I highlighted a few use cases with reference to two major industries to help you understand how you can leverage IoT analytics for the benefit of customers.<\/p>\n

In the final step, I tried to convey the need for a clear goal when using IoT analytics. It can be used either to understand end consumers of a businesses\u2019 product\/services or to gain control over business processes.<\/p>\n

My final recommendation would be to develop an IoT ecosystem in your organization with the support of an IoT development company, as such companies already have the experience of developing IoT solutions for a vast number of clients and may offer the best consulting based on your specific needs.<\/p>\n

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