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Transforming the use and outcomes of big data

Andrew McCloskey, head of research and development at AVEVA

Andrew McCloskey, head of research and development at AVEVA

We have all heard the talk surrounding big data, and what it promises to deliver, but how do you actually capitalise on it for your business? Andrew McCloskey, head of research and development at AVEVA, explains. 

When big data comes to mind, what do you think of? Big data is a term used to describe extremely large data sets that may be analysed to reveal patterns, trends, and impact of human interactions. In most enterprise scenarios the volume of structured and unstructured data is too big, or it exceeds current processing capacity.

Unlocking the power of industrial data is the holy grail for many companies. Big Data has the potential to help companies improve operations and make faster, smarter decisions. But where should you start?

Digital technology can help you design, manufacture, deliver, support and maintain products faster, more efficiently, and at lower costs. By bringing together previously inaccessible data streams, enhancing live visibility and analysis of your operations, and driving actionable insights based on better information, you can improve enterprise performance by: reducing unscheduled downtime; improving regulatory compliance and safety; integrating supply chain logistics with customer operations; optimising maintenance strategies; enhancing situational awareness; reducing waste; and increasing overall equipment effectiveness.

Key to achieving these benefits is creating a seamless and continual stream of process and production data that is integrated with accurate historic operations information and then contextualised into new insights on your overall enterprise. Furthermore, new digital tools can tap into these existing data stores and synthesise them with operational data. This process generates improved insights on how to maximise value creation across asset and operations lifecycles.

Untangled data, new insights

Digital transformation merges the latest innovative tools and processes with your in-house domain expertise. This enables not only the contextualisation of new and existing data but also delivers actionable insights and information. The enterprise can then execute upon these new insights and close the loop towards continuous process improvement. This takes time and often involves adopting many diverse technologies and processes to continually build momentum towards sustained operational excellence.

For example, the National Grid Corporation of the Philippines (NGCP), is responsible for delivering safe and reliable power to customers in the Philippines using more than 21,000 circuit kilometres of transmission lines. Cost, resource and energy optimisation pressure drove NGCP to invest further into actionable intelligence. The average modern plant has tens of thousands of sensor data elements, and organisations need the proper context to take advantage of that information. By using AVEVA’s data management solution, NGCP consolidates data from control, monitoring and business systems in a fully redundant server architecture, protecting the company’s data in the event of an unexpected shutdown. Control centre operators can now access high-fidelity, real-time data to improve decision support while aligning with a strategic initiative to upgrade, expand and strengthen transmission operations.

Collect, visualise and analyse

The faster your team can collect, visualise and analyse data, the faster it is empowered to take insightful action that will benefit your operations and your customers. The overall tactical objective in achieving digital transformation is to create a real-time operational control loop that accurately and efficiently manages your enterprise, based on information and analytics:


  • Real-time operational information to understand what is happening in real-time and enable the condition management of asset and operations lifecycles. For example, a dashboard displaying the vibration frequency of a rotating asset such as a turbine during operation, provides real-time understanding of the asset’s operational behavior and state.
  • Accurate historical information helps you to understand what has happened in the past to create intelligence around operational behavior of assets. Through operational trends, display of KPIs and dashboards, you can create abstract views of operational states. For example, a graph may be displayed on a dashboard showing the turbine’s past vibration frequency during operation. This can be compared to the real-time vibration frequency, creating intelligence on the asset’s long-term operational trends.
  • Predictive analytics is used for what-if type modeling. Integrating up real-time and historical data enables your team to assess potential outcomes of operational states and behaviors, even accounting for tertiary variables. Deterministic or non-deterministic models can then be applied for open-loop simulation and predictive analytics. For example, given the turbine’s current maintenance state, you can now estimate how long it can run before it fails.
  • Prescriptive analytics describes what’s needed to optimise asset and operations lifecycles. Scenario-based guidance is created and delivered through learning elements and closed-loop algorithms to enable your team to calibrate planning and scheduling across the entire enterprise value chain. For example, using a unified supply chain model, scenario-based calculations can be used to optimise maintenance schedules and performance, minimizing impact to your operations.


The use of Big Data is becoming a crucial way for leading companies to outperform their peers. In most industries, established competitors and new entrants alike will leverage data-driven strategies to innovate, compete, and capture value.

Major investments upfront are not required to begin a digital transformation journey. According to McKinsey & Company, when technologies, such as intelligent data management, cloud, advanced analytics, and digital twins are pursued as part of an organisational digital strategy, they can play a role in improving operating margins by as much as 20%.

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