Bringing power to the people with data-driven insights
Reduction in service material costs
Cost reduction target achieved
Hours of productivity saved
Aggreko is a supplier of temporary power generation and temperature control equipment for over 265 locations worldwide –all generating vast amounts of data. In order to optimize its supply chain and logistics and improve customer experiences, Aggreko realized that it had to break down data silos to empower its global organization with data-driven insights. With the Databricks Data Intelligence Platform, Aggreko has a unified view into all their data for downstream analytics, embedding machine learning across operations to enhance and augment human decision-making, and enabling better alignment with business strategy. This will also play an integral role in reaching Aggreko’s goals of being net-zero from their own operations by 2030, and by 2050 with their customers’ operations.
Putting trusted insights at the heart of decision-making for their team is core to Aggreko’s corporate and data strategy. “It’s not about replacing human decision-making, it’s about empowering people. We gather all internal and relevant external data for our people to use it to make better insight-driven business decisions,” said Elizabeth Hollinger, Director of Insight at Aggreko.
To achieve a more data-driven approach to decision-making, they analyze IoT data streaming in real time from tens of thousands of assets in the field. These actionable insights allow them to identify if an asset is performing as expected, or to anticipate when it might be at risk of failure. In addition, they are predicting maintenance issues in order to prevent catastrophic failures — avoiding health and safety issues while also providing better service to customers.
However, disparate data sources served as a major challenge to accelerating innovation. “We wanted to create one holistic place for data, enabling everyone to work in the same space so that we can be consistent with the data we utilize.” Access to up-to-date information was also a challenge, and Elizabeth wanted the ability to create more timely insights that could be trusted. They realized that the key to achieving their technology and business goals was to leverage the agility and scalability of the cloud.
Driving efficiency in supply chain and logistics operations
Aggreko selected Azure Databricks as their centralized platform for data and AI. Delta Lake has allowed Aggreko to bring their data together into a modern lakehouse with a scale and economy that makes business sense, and reduces the number of previously complex data transformation tasks. Through automated cluster management, Aggreko’s data team is able to streamline data engineering processes and simplify the way data is presented to data scientists and BI developers. With Databricks, the team can react quickly to changing demands. “We can spin up or spin down clusters as and when required. Auto-scaling allows us to start small and scale only when required – it’s an efficient use of resources. None of the other platforms could give us the same level of flexibility as Databricks,” Elizabeth explained. “With a centralized platform, we can ensure that all the data functions, including data science and machine learning are not siloed functions and that the team constantly drives business value.”
Collaboration across the data disciplines is also key and the single unified development environment inside the Databricks workspace has naturally led to a more collaborative approach to cross-team working, encouraging different teams to openly share ideas from both technical and development approach perspectives. “There is now process alignment through the full lifecycle of many data projects, which has dramatically increased our impact on the business and customers,” Elizabeth said.
Behind the story: The Data Team Effect
Data teams are the united force that are solving the world’s toughest problems.
Becoming energy net-zero with improved operations
Aggreko has boosted operational efficiency within their manufacturing processes by reducing time to insight through the Databricks Data Intelligence Platform – enabling more effective inventory management and guidance to help prioritize the manufacturing effort in the right way. Through data automation activities, such as automated manufacturing reporting, they were able to achieve over 30,000 hours of productivity savings across their global business. Additionally, the Databricks Data Intelligence Platform on the Azure cloud provided the agility and efficiency to significantly reduce overall costs — lowering service material costs by 10% which contributed to attaining 140% of their cost-reduction target within the first half of 2020.
In addition to streamlining operations, Aggreko has set ambitious targets in line with the Paris Agreement to reduce its environmental footprint and become net-zero by 2050 or sooner. The organization has committed to offering cleaner technologies and fuels to support their customers through their energy transition, using flexible and competitive energy solutions to meet their sustainability goals. By 2030, Aggreko’s aim is to reduce the amount of fossil diesel fuel used in customer solutions and local air quality emissions of their solutions by at least 50%, as well as achieving net-zero across their own business operations. “Using data-driven insights, we will be able to deliver a right-sizing (forecasting) methodology to optimize and balance our customers’ costs and carbon emissions,” explained Elizabeth. “This will enable us to track performance against our own and our customers’ emission reduction targets.”
Looking into the future, Aggreko plans to use data insights more effectively in customer touchpoints, for example to right-size customer energy solutions based on data-driven intelligence requirements. “We want to enhance our customer portal to run simulations and what-if scenarios so we can recommend more appropriate services and help our customers make better decisions,” Elizabeth explains. Another goal is to empower their people with clean data to enable self-service, insight-driven decision-making.
