Business Decisions based on Intuition & Experience are Passé

March 29th, 2016 by

Time to base decisions with meter data management and energy data analytics – Industry News

Business decision-making based on big data is representing a fundamental shift in the energy sector. Still, there is little knowledge of how to use the growing data available for business analysts, product and marketing managers and others. A shortage of data experts does not help to overcome this issue. Moreover, changes to operating business models are required to realize benefits from these new insights. Handling big data is complex and the process of learning from it requires an agile approach including careful tests and evaluations – over and over again.

What is data analytics? Data analytics is the science of examining raw data with the purpose of drawing conclusions about that information. Data analytics is used in many industries to allow companies and organizations to make better business decisions and in the sciences to verify or disprove existing models or theories.

Why big data? Businesses prioritize the analysis of external data as well as internal data such as sales to gain more insights into customer behavior, the energy market and operations with the end goal of creating a smart(er) grid. They do this, because real insight comes from business intelligence and analytics that correlate data from the enterprise and external sources. New insights are possible by moving from business intelligence to comprehensive analytics, a fundamental shift in managing your business. Data analytics is the best tool for the energy sector to transform and become more prepared for the fight against increased competition and fluctuating market demand.

“The first step is to join forces with big data experts that use customized and intuitive application programming interfaces (APIs).”

How to exploit big data? It’s clear that tomorrow’s winners will be the organizations that succeed in exploiting big data. Now, the question is how to exploit big data for your energy business instead of using it as an add-on tool for decisions making. The first step is to join forces with big data experts that use customized and intuitive application programming interfaces (APIs).  The customized API will facilitate significant opportunities for energy incentive programs for all departments. The accuracy of key planning activities, such as measuring costs and efficiency of distributions will greatly improve if big data is leveraged to guide energy efficiency efforts. Such activities can be supported by applying advanced predictive analytic techniques in real-time. Energy companies that exploit big data can predict the required amount of energy needed by taking into account the weather, forecasted and current renewable energy generation and various consumer consumption profiles. This reduces large consumption/generation discrepancies, saving energy and reducing CO2 emissions. Your business will reduce costs and do less harm to the environment.

“Energy companies that exploit big data can predict the required amount of energy needed.”

How does Energyworx use the weather to predict how much energy will be needed? First, we compare historical data of energy consumption on certain days with similar weather (e.g. sunny hours, temperatures and wind forces). We create graphics to visualize the trends between energy consumption and these weather patterns. We analyze the visualizations and identify days when the same weather and energy consumption patterns occurred, allowing you to make assumptions for the required energy needed during the period of your analysis. Then we forecast the required energy consumption and minimize biases by testing assumptions.

“Prevent getting lost in the immense amount of data sets.”

Now, we are not finished because we did not take the consumer profiles into account. Prevent getting lost in the immense amount of data sets. We must differentiate consumer profiles based on characteristics such as heavy consumers, light consumers, and specify which consumers have a pool, electric car and other influential loads. How can we decipher this in practice? As you give your customers access to a personal application that visualizes their energy consumption, you create energy awareness among consumers by advising how to save on energy and give ‘tips and tricks’ on how to reduce energy consumption. Create a dialogue and learn what ‘tips & tricks’ are most popular and work best. Stimulate consumers by creating campaigns to invite neighbors and friends to use the personal energy app. To encourage participation, you ask them to complete their user profile before they can access their energy report.

Note that you need to be patient when building your consumer profile platform based on historical data of the weather and their energy consumption data. Consumers need time to become interested in energy and become aware of their energy consumption (and generation). Similarly, your company needs time to change employee mindset towards data analytics, since achieving sustainable value from analytics requires new approaches to information management.

Exploiting big data is a process of analyzing data, making assumptions, testing these assumptions and evaluating the results, again and again. In the end, your company will become smarter and learn more from new insights based on the data.

Are you ready to start implementing these awesome features? We will be more than happy to help you. Contact us!

 


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