The Internet of things is remarkably impacting business operations and processes, and the huge volume of IoT-generated data can help businesses learn where to innovate. When IoT is integrated with other technologies and processes, such as data intelligence, machine learning, and artificial intelligence, it can help businesses better utilize real-time data, and create insights that can be implemented in the development of intelligent business strategies.
As per the marketsandmarkets, the global loT analytics market size is predicted to grow from USD 7.2 billion in 2017 to USD 27.8 billion by 2022, at a CAGR of 26% during the forecast period. The key factors driving the loT analytics market include a huge rise in loT data generation due to the improving deployment of loT devices and the requirement for advanced analytics and automation for businesses to stay Competitive.
By combining IT and OT data, IoT analytics helps to take out actionable and remarkable insights to enhance the overall business value.
Rise of edge analytics
With the emergence of edge analytics, loT Analytics has seen a great boost in its overall market. Many business processes do not need significant analytics; thus, the data gathered, processed, and monitored on or near the edge can drive automated decisions. For example, a local valve can be turned off upon detection of a leak. This has provided a huge opportunity for loT Analytics as it includes loT devices and has minimized demands on the bandwidth of the network and storage requirements.
Automated Work Management System Maintenance
Automation is now becoming a backbone for many industries. When automation is combined with IoT, it can make the way for major improvements taking place in the work environment such as remote-field-force connectivity.
Also, IoT sensors are highlighted to let the employees know when a particular machine is most likely to fail, which reduces the burden on employees to move the machine off manually for maintenance purposes. This also minimizes the workload of employees who previously had to maintain a continuous check to assure whether any machines require maintenance or not.
Extended Business Operations
Business owners can rely on their smartphones to keep track of critical business operations. This is because of IoT and analytics-driven cloud solutions that have been integrated with cross-platform mobile apps to give real-time insights remotely even on mobile devices. That will assist business owners to make better decisions in real-time without having to rely on or wait for the physical report.
For instance, consider cloud-based Smart Metering systems which are developed around water meters mostly and help the customers with their water utilization data in real-time.
Predictive Analytics
Predictive analytics changes data into valuable insights, helping enterprises to optimize business processes, improve process efficiencies, and improve customer satisfaction. Predictive analytics utilizes real-time and historic data to come up with futuristic outcomes before the actual event occurs.
The predictions that come from predictive analytics are converted into a set of recommended actions that will create business value. This helps procurement professionals to view business scenarios and build future operational strategies. Companies are also focusing on offering predictive maintenance and asset maintenance using predictive analytics to interpret the device repair time, reduce downtime, and take quick corrective actions. Predictive analytics when integrated into loT Analytics helps a manufacturing unit to assure continuous operations by implementing asset maintenance.
Below are a few steps included in processing data for IoT analytics and obtaining business value from it.
Data Ingestion
This is the first step and in that, the data from IoT devices are taken in and processed. Real-time alert notifications can also be created. In the end, data is kept in its natural format in a centralized cache.
Clear and Complete Visibility
The IoT data from all sources are combined into the data hub before being categorized for better interpretation and thorough visibility. The data which is asked after the specific intervention will be made available to support analytic data analysis.
Discovery
The processed data from the data hub is then moved to the Business Intelligence tools to create interactive dashboards. These interactive dashboards drive data into readable-human insight. This enables decision-makers to make more instructed decisions.
Prediction
Predicting future results with the help of several machine-learning techniques (predictive maintenance) is the current norm leveraged by businesses. As the store of available data develops over time, IoT predictive analytics can use longitudinal data to recognize trends and predict future scenarios.
How IoT Analytics helps in getting Essential Business Insights
IoT analytics drives data generated from OT and IT data sources and processing, visualization, and analytics to create useful and remarkable business insights. There are various use cases for which IoT analytics can be applied. For instance, In the case of home security and automation, data received from various sensors likewise temperature, humidity, alarm, etc., can be integrated with customer data to enhance customer lifestyle experience, supply proactive data-driven services, and increase operational efficiencies via visualization, remote monitoring, and troubleshooting.
In a smart building case, energy utilization dashboards can assist in sensor control, identifying specific times to heat or cool rooms, finding air quality risks, and positioning predictive fixes and maintenance. Texas Instruments study reveals that in HVAC and lighting IoT solutions, energy utilization can be limited to 40% just with the help of sensor control.
Benefits of IoT analytics
IoT analytics provide various benefits for businesses that use them:
- Visibility on the complete IoT network – IoT analytics allows businesses to organize the performance of their IoT network in real time.
- Quick identification and resolution of concerns in business operations – Businesses can utilize diagnostic analytic abilities to quickly rectify performance problems and utilize prescriptive analytics to resolve such concerns.
- Better asset utilization – Businesses can utilize IoT analytics to analyze the performance of their assets, likewise machinery, and improve their utilization to assure the long-term health of assets.
- Cost optimization – IoT analytics help recognize areas of cost reduction and steps to execute to achieve such cost reduction.
- Evolution into new markets – IoT analytics provide valuable insights on operations and consumer behavior to help expand into new markets.
- Increase product development – Manufacturers can study historical trends in product usage by consumers to recognize areas of improvement for future versions of their products.
- Better customer experience – IoT analytics assist businesses to recognize customer problems in real-time and react quickly to resolve those problems, thus improving customer experience.
Rather than collecting and utilizing all data, IoT analytics tools know how to gather the most significant data points, execute quick analysis, and give insights relevant to the products and services. Thanks to IoT and analytics platforms, it is changing the business view by collecting quality insights and allowing data-driven solutions.
Take a look at KNEO Automation’s MAPP Solution, or contact us today to find out more about how we can help you.
The advent of internet has fundamentally changed the course of action of almost every industry.
Even though internet has been around for a while, it wasn’t until the emergence of Industry 4.0 that the digital transformation started helping the industries to evolve.
Pharma 4.0 emphasizes on building a single virtual network that connects human, data and machines.
Looking at the past trends of manufacturing, it seems that the technological transformation is much needed for pharma manufacturing as they have been facing challenges such as:
Shift from “one drug that fits all” to personalized therapies
Complex supply chains due to outsourcing activities which results in high cost of drugs
