The use if IoT (internet of things) in industrial sectors and applications is known as IIoT (industrial internet of things). The IIoT has a strong emphasis on machine-to-machine (M2M) communication, machine learning, and robotics. It includes industrial applications like robotics, medical devices, and software-defined production processes.  

Digitization of the world has lead to the eruption of technology and smart devices resulting in constant communication with one another and producing large chunks of data. This data has changed the way businesses are run today and hence creates challenges for business leaders.  

Key reasons for the Industrial Internet of Things to be less effective for businesses are:  

1) Integration of technology

With the emergence of IIOT the worlds of IT (Information technology) and OT (Operational technology) have converged. This convergence creates a possibility of critical data loss. Hence there is a strong need for secure integration without data loss or any vulnerabilities.  

2) Asset Level Visibility and Management 

Manual labor is required to assess assets in real time and also to ensure their optimal functioning.  Resulting in delayed and faulty detections which result in loss of time, money and resources. Hence a strong need for asset performance management.  

3) Aging Workforce 

Once the skilled and learned professionals are retired, it takes a lot of time to educate and teach the younger employees about how to run the system effortlessly. Hence there is a strong need for organizations to prepare for this by utilizing digital technologies for a smooth transition.  

4) Reduced Maintenance 

There is loss of time, resources and money because of manual data organization and review. Hence there is a strong need for a mobile-enabled interface that can increase productivity across the organization so that time, resources and costs can be optimized.  

5) Mismanaged and unorganized data 

In today’s time, there is tons and tons of data to be organized and managed by every organization. Moreover, managing and organizing such a humongous amount of data is tedious. This is resulting in companies struggling with data deluge and opting cost-cutting solutions. Very few companies can leverage data. Data which is neither organized nor contextualized is challenging to analyze and store resulting in data islands. When data gets siloed, it presents complex technical and organizational challenges. When the data is unorganized in an organization, for example, integrating, sorting and analyzing it manually consumes both time and resources of the company.  

6) Cybersecurity 

The digitization has lead to storing information on the cloud; this exposes the data to privacy risks. Cyber threats and attacks can critically damage everything ranging from personal devices to corporate  IT systems leading to vulnerable situations in financial and operational sectors for both individuals as well as organizations. Hence a strong need for solutions that can prevent and mitigate such risks.  

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