The Economics Of Intelligent Enterprises

Itzhak Shoshan

The economic foundations of the classic value management approaches are still valid. However, edge technologies have specific ways to generate value, which need to be considered throughout the lifecycle and especially in value identification.

How do intelligent technologies create business value differently? Professor Michael Porter first coined the term “value chain” in his 1985 best-selling book Competitive Advantage: Creating and Sustaining Superior Performance. He described the value chain as the set of activities a firm operates to deliver a valuable product or service to the market. The value is generated by moving through the different steps of the value chain.

Some remarkably different dynamics happen with edge technologies. Rather than a chain with a beginning and an end, we tend to think of the value cycle that generates the value. A machine learning value cycle starts with data that is processed to generate predictions. These predictions inform human judgment (optional step) to execute actions, which in turn generate new data that is used to generate better predictions, and the cycle continues to generate value through usage.

This phenomenon exists for most machine learning models that learn from experience. The value cycle helps drive adoption of machine learning since users understand that the performance and value will always increase over time. Additionally, you can design multiple prediction engines on top of the same data set, leading to additional use cases and further increasing the value generated through the value cycle.

One final step completes this line of thinking. By integrating the contribution of the other intelligent technologies (Internet of Things and blockchain), the machine learning value cycle becomes the foundation of what we can call an intelligent enterprise value cycle.

Part of the data that feeds predictive models may come from connected things. In other words, devices can be a data source for machine learning. Moreover, machine learning enables robotic process automation and autonomous actions for smart devices. As an immutable and decentralized data store, blockchain can extend the validity of data exchanged in business configurations where multiple parties act as peers in a business network without a third-party intermediary.

Download the “Economics of Intelligent Enterprise” thought leadership paper and understand in further detail how to identify and assess value generated by the intelligent technologies value cycle.


Itzhak Shoshan

About Itzhak Shoshan

Itzhak Shoshan is Head of Business Service Ventures at SAP, developing service business ideas to the point of scale into the SAP portfolio. He is an expert in assessing business use cases tht leverage technologies such as machine learning, blockchain, and the Internet of Things. Shoshan holds a bachelor’s degree in computer science and an MBA from IDC Herzliya.