With internet-enabled devices and cloud-based computing becoming a more integral part of the business and consumer landscape, the daily collection and transmission of large amounts of personal data has become increasingly commonplace. Online storage of personal data has raised concerns over the ability of these systems to safeguard user privacy, leading some consumers to seek extra protection from the misuse or unintended disclosure of sensitive information.
One of the rising services powered by the Internet of Things (IoT) is the development and growth of companies that offer Mobility as a Service (MaaS) solutions. According to a report from Allied Business Intelligence, revenue growth from ride-sharing companies such as Uber and Lyft is expected to go from $30 billion in 2017 to $250 billion in 2022.
A digital twin is a near real time digital copy image of a physical object or a process that is used to optimize business performance. It can be defined as a virtual representation or a digital profile that is undergoing a process of evolution fed by data from the historical and present behavior. The constantly evolving profile uses an array of measurements providing key insights on overall performance which could serve as inputs to change a part of the process or design in the physical world. It’s been predicted that more than 80 percent of all IoT platforms will have some form of digital twin functionality within the next five years.
As Pareto’s Principle states, roughly 20% of a system’s given input is responsible for 80% of the outcome. In a business context (as highlighted by Forbes and many economists over the years), Pareto’s Principle means that about 80% of a business’ revenue comes from 20% of its customers. In retail, for example, the majority of profits come from those few loyal customers that tend to purchase more than one-time shoppers. In some cases, especially for B2B companies, this ratio is closer to 90/10.
In the world of automotive fleets, downtime most often occurs as a result of mechanical breakdowns or accidents. When a service vehicle is incapacitated through accident or breakdown, a temporary replacement may be difficult to acquire quickly, extending downtime and increasing the likelihood that the vehicle will exceed its allocated operations budget. According to Automotive Fleet, downtime results in an average cost of $79.32 per hour, per driver, without factoring in the expenses incurred by rolling trucks and making repairs.