For many service providers, 2.7 touch points annually would be too few for them to adequately run their business on. Data is integral to improving processes and is being treated with, with it expected to reach 175 zettabytes by 2025 (Swiss Re, 2020). Any company that therefore does not collect data for their users, or, more importantly, actively collects data and utilises feedback information to better inform their service offerings, will be left behind. The most successful companies in the world are those that solve problems and pain points before the user even knows they exist; Amazon, for example, letting us know what people similar to us have also bought so that we know not to forget our batteries, or Asos, offering views of what clothes look like on a variety of body types. These customer informed solutions are informed by the data these companies collect on a second- by- second basis.  

The stakes are rising. Demands and expectations on companies are increasing. In a world that demands ethical business practices, socially minded enterprise, transparency and sustainability, corporations need to keep up to date with the rapidly fluctuating needs and behaviours of their customers. They need to look at innovative solutions that give them a better view of their own supply chains and they need to make sure that what is important to their customers is important to them. Pre-empting consumer needs can only be done by analysing the vast amounts of data these companies collect. Amazon has filed a patent for a shipping system that pre-empts what you will buy and ships products in the individual’s direction before they’ve even bought it (Lomas, 2014). Other companies are getting in on the pre-emptive action; the Rapid team at Myntra, the overseer of Moda Rapido the fashion store, predict what fashion items will be fast sellers, employing more data scientists than they do designers to analyse trends in consumer buying behaviour (Flipkart, 2018). 

Machine learning and artificial intelligence are the latest tools that purport to improve this pre-emptive ability and make better decisions. Currently, in sectors as diverse as finance, law and healthcare, it has been found that technology works best when used in conjunction with humans. Instead of letting machines run wild, we see the most effective companies using augmented human intelligence which combines a human being’s understanding of emotion and their flexibility of thought with the highly logical, analytical skills of machines. Rather than letting a machine detect a condition and then inform a patient about the likelihood of survival after diagnosis, we check with the doctor, who then informs the patient. Rather than letting a machine make bail decisions, the machine makes a recommendation and it is reviewed by a judge who takes contextual factors into account. For insurance, this augmented intelligence could revolutionise almost any area of the value chain; we could see insurers leveraging flexible, product- agnostic and fully integrated digital platforms that engage personally with the consumers.