__________________________________________________________________________________________________ Supply Chain
Across most industries today , data is king , and utilities firms are no exception . By 2025 , there will be 175 zettabytes of data in the global datasphere – this equates to every person on earth producing at least 1.7MB of data every second . From humans , machines and Internet of Things ( IoT ) devices to edge systems and beyond , data is everywhere . It ’ s the fuel powering everything we do , and if used to its full advantage , has the potential to greatly improve operations and services for energy providers .
However , with different approaches to data – namely utilizing data products or approaching data with a project mindset – which is it that enables energy companies to make the most of their data investments and build greater resilience in global supply chains ?
Limitations and challenges of the traditional data project methodology
With a project mindset , each time a business function has a problem that it wants to solve with data , an organization must start a project to acquire the data , cleanse and prepare it , then analyze it for that specific use case . And each time a new business problem or use case arises , it follows a similar process for its specific need . This
Other benefits included cost reductions
approach , however , has significant drawbacks across the breadth of the energy industry supply chain . Not only is it often slow and leads to duplicated work , but the outputs from each project typically can ’ t be repurposed to solve other use cases .
Despite these obvious limitations , many utilities firms still approach data this way , which can result in a lack of integration between different data sources and tools – not to mention make it difficult to get a complete picture of operations and customer needs .
This methodology can also hinder collaboration and communication , and limit scalability . As new data sources are added , it can become difficult to manage and analyze the data effectively . This approach can be costly , with each project requiring dedicated resources and tools , and can slow down the pace of innovation . This makes it very difficult for utilities firms to respond quickly to changing business needs .
Is managing data like a product the answer ?
In comparison - and taking a bird ' s eye view for the moment – a data product delivers a high-quality , ready-to-use set of data that people across an organization can easily access in ( near ) real-time and apply to different business challenges . Teams using data products don ’ t have to waste time searching for
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