What data can do for decision making: businesses, customers and the environment

Data and analytics are becoming more and more integral to how businesses make decisions in all areas of their operation, from managing Energy & Utilities and Oil & Gas supply chains to optimising their sales strategy to delivering better customer service.

However, there is a growing recognition that data and analytics are not just useful for making day-to-day business decisions—they can help companies make environmental decisions as well, helping them make better choices about the materials they use, reducing waste, and making more efficient use of their energy resources.

According to research conducted by McKinsey:

“Respondents from high-performing organizations are three times more likely than others to say their data and analytics initiatives have contributed at least 20 percent to earnings before interest and taxes (EBIT) over the past three years” (McKinsey, 2019)


What Data Can do for Businesses

Data visualization & advanced analytics – AI, are a set of tools that companies use to collect, store, organise and analyse data about their businesses. Using business intelligence and automation allows organisations to evaluate data on both an individual basis as well as for large groups of people and one that large utility companies should be leveraging more intently in the current challenging business climate for energy suppliers. For example, using data to understand how different age groups respond to certain promotions like renewals, can help improve future marketing campaigns. Understanding what information might be valuable to your overall business means keeping your eyes open for trends that you can take advantage of or soften your message in difficult times.

However, a tremendous amount of data generated from various sources i.e. processes, employees, and customers, can leave businesses overwhelmed if it is not managed and leveraged strategically. Companies that can extract accurate insights by correlating such data to optimize their operations better will achieve improved business performance and productivity levels will increase while delivering data-driven experiences for better engagements with end-customers

Some of the really advanced analytics questions for the industry are these;

  • Is Artificial Intelligence (AI) the key to unlocking the limitless possibilities in Energy and Utilities?
  • How is machine learning shaping the future of the industry
  • How can Energy & Utility companies understand customer demand better through predictions using machine learning

For those who are starting out on this AI journey you may want read our blog Demystifying Explainable Artificial Intelligence: Benefits, Use Cases, and Models

However, one solution that has already making an impact and has been implemented for many customers facing analytical challenges is Power BI on Microsoft’s Azure Cloud Platform. It takes many real-time data sources, analysing these, and presenting them back data to make better business decisions.

Power BI on Azure is an obvious evolutionary step for Analytical Departments because it offers data preparation and discovery, interactive dashboards and rich visualisations in one solution and is cloud enabled. Its self-service capabilities make it an intuitive tool for interacting especially within the Azure Cloud platform and other Clouds by turning data into insights more effectively. It is a big favourite with data scientists.


What Data Can do for Energy & Utility Customers

Today, companies can actually use data to know what their customers are thinking about and also to predict their likely future energy needs like how many devices in a household are connected to the internet. They can also use that data to understand how customers would like their service experience to be in the future. There is a lot of work involved in getting there, of course. It requires that businesses set up systems that allow them to collect information from customers more easily going forward and if the household is deemed to be a Smart Home then the data analytics strategy should be a two-way relationship in real-time.

Once you have been collecting customer data for some time, it will then be important to create dashboards based on consumers likely power consumption split by a criteria like rooms of a house. As with Open Banking, a government initiative which helps customers move, manage and make more money by opting-in to a world of secure apps and services for more clarity and control over your finances, there should be an equivalent in the energy and utilities arena.

Having more customer interactions with your company in a competitive world is hugely beneficial as you see what your clients think about different aspects of your business – all in one place. Then you will need to harness that data by turning it into actionable insights through analytics and business intelligence software, using tools such as Power BI as mentioned previously.


Reduced Carbon Footprint

In an effort to reduce their carbon footprint, many companies are looking at ways to shift their usage towards renewable energies. This is part of a larger industry trend that is seeing more companies turn away from traditional energy sources like oil or coal in favour of cleaner energy alternatives. One way to assess energy usage for businesses and control devices for enhancing energy creation was first done at scale by the renewable energy industry itself.

Take one renewable energy provider as an example. They wanted to be able to not only be able to control new wind and solar farms more efficiently, but also wanted to get maximum energy at the lowest maintenance risk from a wind turbine by understanding the wind direction through the onboard Lidar sensor and changing the angle of the turbine to reap the most financial reward. If you have 10,000 wind turbines, which one of our customers has, then that is a lot of data to analyse from information concerning the turbine(s) to weather forecasts to even satellite pictures used for offshore wind farms to check sea wave movements thus indicating wind direction which is heavily used on blue sky days. All this is done through harnessing digital technologies for utility industry resilience.

You also want to see dashboards which illustrate turbines that are under performing and so get maintenance out to do fixes like re-oiling the main bearing. Other Analytical factors to understand is the time at which you release the energy to the grid can influence the price that you receive. Too much energy flooded onto the grid at once can reduce the price you receive, plus you must weigh up the age of the turbine against maintenance costs of all the turbines running all at once. The life span of these machines must be factored in and predictive maintenance is a useful tool to manage these machines more effectively. Sometimes these turbines are in remote spots and the cost of maintenance can be high. Birlasoft’s IntelliAsset solution helped our customer solve many of these issues in one solution and with one framework.


Single View of the Truth

For many companies, data can be a powerful tool to make more informed decisions. But even so, big businesses that use legacy systems often find it difficult to uncover potential cost reductions. Although some energy and utility companies have data science teams in place for internal analysis, they also turn to outside consultants to extract relevant information from their data assets. Many companies may believe they do not have much useful information lying around—but while these legacy systems may not have been designed with analytics in mind, it does not mean there isn’t actionable data within them. Sometimes you just need a different perspective, looking at things through fresh eyes—and that is where consultants come in handy. This once again strengthens the case for business intelligence solutions such as Power BI, implemented by Birlasoft.


Legacy System Cost Reduction

With legacy system infrastructure, businesses are typically paying more for less. In other words, they are paying to maintain systems that no longer offer value. But eliminating them is not as simple as flipping a switch; business processes must be integrated into new technology. How can you maximize ROI on transitioning to a new IT environment? There are two questions you need to ask yourself: What do I want my end-state infrastructure to look like, and how long is it going to take me to get there? Once you have those answers, it will be easier for you to figure out how much capital—and time—you’ll need to execute your plan. This also assumes that making an investment in IT infrastructure is important or beneficial enough to warrant any resources at all.

Many businesses today are using data more often to make key decisions. However, in many cases, there is a disconnect between where they collect their data and how it is analysed. The key to getting data-driven decisions right is to ensure you are collecting all relevant information, integrating it into your business intelligence systems, then using an analytical tool to make sense of it. The most important step—integrating data—is often overlooked or done incorrectly. Birlasoft specialise in implementing the right data solutions for energy and utility customers across the world, if you would like to know more then get in touch with us today.

Contact and sales details

For more information please reach out to the Birlasoft team.

Website: https://www.birlasoft.com/

Energy: https://www.birlasoft.com/industries/energy-and-resources

Utilities: https://www.birlasoft.com/industries/utilities

Sales Contact Email: [email protected]

LinkedIn: https://www.linkedin.com/company/birlasoft/

Office: London Office, 4th Floor, 53-54 Grosvenor Street, London – W1K 3HU

Phone: +44 20 7319 5700

Email: [email protected]

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