The objective of Asset Lifecycle Management (ALM) is to optimize the profit generated by assets over the course of their lifecycle. ALM integrates processes and technologies in order to manage asset portfolios, execute projects, and facilitate efficient asset management practices. Whereas Asset Health Management (AHM) deals with monitoring and optimizing the health the asset in real time, ALM extends across the lifecycle of the asset from design, to procurement, commissioning, operations, maintenance, and decommissioning. IoT technologies enable superior visibility, forecasting, and feedback loops across the ALM process.
In 2013, LumenData found itself in need of adding new real-time predictive analytics capabilities to its suite of services. To meet this need, LumenData acquired a state-of-the-art streaming data, capture and real-time predictive analytics company. This solved the pure predictive analytics end, but left LumenData with a need to be able to build IoT-targeted services.From an IoT perspective, LumenData was still missing the means to create suitable applications and dashboards that would make it easy for its customers to effortlessly make sense of whatever predictive analysis they might require.
AEMO needed to modernize of the Gas FRC Hub a B2B platform for the gas retail markets throughout Australia and provide a reliable B2B platform that could scale to support the adoption of B2B procedures in New South Wales (NSW).
The Application Lifecycle Management (ALM) market is expected to grow from USD 2.58 Billion in 2017 to USD 3.63 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 7.0% during the forecast period.