If you have seen the Netflix documentary ‘The Social Dilemma’, you might be familiar with the concept of IoB, which regards using and analyzing data that is collected about individuals to predict and influence their behavior. The first things that may come to mind when thinking about IoB, are social media companies such as Facebook. However, IoB has many different applications and is relevant for nearly all industries. In this article, I will discuss the context, possibilities, and limitations of IoB.
Context
With the ever-increasing computing power of computers and technological developments, business information and data are becoming more and more relevant. In the future, data will be collected even more efficiently, as more and more products are being digitally linked through the internet of things (IoT). Furthermore, advancements in AI and machine learning improve the accuracy of predictive models and simulations. Therefore, businesses and organizations that have a lot of data are increasingly able to more accurately monitor individual stakeholders and make predictions regarding their behavior.
Opportunities
As the technology behind IoB is improving, the amount of opportunities it brings is not slowing down. Not only can IoB be used for businesses to better understand customers and increase sales and customer experiences, but it can also be used for organizations such as hospitals to better monitor individuals and understand their behavior. Action can then be taken to provide individuals with the optimal experience and improve customer relationships. Moreover, the physical and mental health of individuals within a society can be monitored and predicted to try to maintain high well-being. Furthermore, new products and services can be created by businesses, organizations, and governments based on the predicted demands of individuals. Accordingly, IoB is not just a concept that focuses on increasing sales, but it could also have great opportunities for society as a whole.
Limitations
However, there are certain limitations regarding IoB. The most prominent one is that of privacy, which limits organizations in their collection and usage of customer data. In some cases, privacy will hinder organizations to collect the data they need to pursue certain value creation activities with high potential. Another limitation is the quality of the collected data. While many organizations collect large amounts of data, the quality of the data is often hard to verify, which could seriously impact the accuracy of the predictions and models for the behavior of individuals. Moreover, one of the most important limitations is ethics. Even though data collection and analysis can create a lot of value, unsolicited data collection and analysis can be unethical. Before collecting and analyzing every data point we can find, we should think about the impact it can have on an individual and if our actions are morally acceptable. Finally, responsibility is arguably the most important limitation. Customers do not know what happens with their data and who is responsible for it. As data brokers are becoming more prominent and the sizes of most major companies do not seem to slow down, the responsibility for the handling of data is often unclear, especially for individuals outside the organizations.
References
Kidd, C. (2019). What Is the Internet of Behaviors? IoB Explained. Retrieved from https://www.bmc.com/blogs/iob-internet-of-behavior/ (Accessed 9 October 2021)
Mishra, U. (2021). Introduction to Internet of Behaviour (IoB). Retrieved from https://www.analyticssteps.com/blogs/introduction-internet-behaviour-iob (Accessed 9 October 2021)