SMART BUSINESS.

Basically, all organisations and players involved in achieving a common objective or business goal, such as ride sharing (example Uber), are coordinated in an online network and in fact use machine-learning technology in order to efficiently leverage data in real time. Using APIs (Application Programming Interfaces) and other interface protocols will ensure a smooth interaction among software systems. So apply machine learning to make sense of data in real time.

Ample computing power and digital data are the fuel for machine learning. Data scientists come up with probabilistic prediction models for specific actions, and then the algorithm churns through loads of data to produce better decisions in real time with every iteration. Machine learning is much more than a technological innovation; it will transform the way business is conducted as human decision making is increasingly replaced by algorithmic output.

To become a smart business, your organisation must enable as many operating decisions as possible to be made by machines fueled by live data rather than by humans supported by their own data analysis. Transforming decision making in this way is a four-step process. (But remember social engineering.)

1. "Datafy" every consumer exchange. Live data is essential to creating the feedback loops (evaluation) that are the basis of machine learning. Consider the bike rental system in China regarding payment and credit systems that use QR codes (Quick response codes.) The app can verify the person's credit history, and when the bike is returned, closing the lock completes the transaction.
2. "Software" every activity. In a smart business, all activities - not just knowledge management and customer relations - are configured using software so that decisions affecting them can be automated.
3. Get data flowing. In ecosystems with many interconnected players, business decisions require complex coordination.Communication standards, such as TCP/IP, and APIs are critical in in getting the data flowing among multiple players while ensuring strict control of who can access and edit data throughout the ecosystem.
4. Apply the algorithms. To assimilate, interpret, and use the data to its advantage, the organisation must create models and algorithms that make explicit the underlying product logic or market dynamics that the business is trying to optimize. Chatbots can also make a significant contribution to a seller's top line.

In a smart business model, machine-learning algorithms take on much of the burden of incremental improvement by automatically making adjustments that increase systemwide efficiency. Thus, leaders' most important function is to cultivate creativity. Their mandate, in fact, is to increase the success rate of innovation rather than improve the efficiency of the operation.

The commercialization of cloud computing and artificial intelligence technologies has made large-scale computational power and analytic capabilities accessible to anyone. So real-time applications of machine learning are now possible and affordable in more and more environments. The rapid development of the internet-of-things technology will further digitize our physical surroundings, providing even more data. As these innovations accumulate in the coming decades, the winners will be organisations that get smart faster than the competition.

Prof Rory Dunn.