SEMINAR: Using New Forecasting Tools To Analyze The Future of Energy
Technology does not evolve randomly. It is a self-assembling system. By understanding the rules of assembly, it is possible to anticipate future technology based change as well as the disruption that results from that change. During this presentation, two of the most commonly occurring structures will be briefly described; linear evolution (lines of progression) and the intersection of two or more lines of progression (convergence). A multi-sector convergence event centered on consumer consumption / the smart home is on deck. Energy is one of the sectors involved in the upcoming convergence and will experience significant disruption because of it. During the presentation, a majority of the time will be spent focusing on significant new technologies, trends and business models that will be injected into the energy sector as a byproduct of these processes.
Specifically, the introduction of the whole home personal assistant in the smart home in two to three years is positioned to act as a trigger event in a convergence between energy, automobiles, telecommunications, retail, insurance, banking and advertising. Each of these converging market segments will bring with them technical and business model assets that have the potential to result in rapid change/disruption to the energy market. As an example, natural language processing that is a core portion of the whole home personal assistant will act as a primary user interface as part in support of dynamic pricing mechanisms. A limited selection of technologies, business models and trends similar to this will be described during the presentation.
Entrepreneur in Residence at Itron Idea Labs
Stephen is an entrepreneur-in-residence in Itron’s Idea Labs business incubator. In that role, he is investigating non-traditional business models and revenue streams for the utility sectors with a specific focus on data trading. Prior to working with Itron, Stephen spent sixteen years mapping the evolution of the smart home/IoT and developing short range wireless technologies. While at Intel, Stephen developed a series of behavioral models that explain the evolutionary forces driving technology and technology markets. Using these models, it is possible to forecast disruptive change up to approximately 15 years in advance with actionable resolution.