In a recent project, we helped one of our customers assess and implement a new data foundation and road map. During the project the client stated, “We must drastically improve our data strategy. Information has become the currency of energy trading”. My first reaction was subtle disagreement, but I couldn’t really say why. Haven’t energy traders had access to data since the beginning? Weren’t data related jobs in quantitative risk, modelling and structuring always common?
To further evaluate my client’s statement, I looked back and tried to assess at which point in time things might have changed from a data standpoint. I concluded, that there were pivotal developments in the energy market like Fukushima and the energy transition. But from a data perspective, the financial crisis, which initiated regulatory waves across finance and energy trading markets worldwide, was the game changer and was further driven by technological developments, which we now call the ‘digital transformation’. Ten years ago, market players who had access to certain assets (i.e. production, consumption, storage, any kind of capacity), dominated market shares or employed certain specialists (e.g. meteorologists), who could obtain exclusive information and could create and maintain a competitive advantage. Today, all information which significantly impacts energy market prices must be published and technological developments now allow access to any kind of information, useful or not.
Figure 1 – Categorization of Energy Data
From the sole standpoint of data access, things have changed dramatically, and one could argue that there might actually be a common currency. However, looking at the various data sets available (fig. 1) and ignoring the effects of commercial interests, certain data might still not be accessible to every single market participant. In order to make information today’s currency, it is not purely about the data and having access to it. Looking purely at new data sources and access, will create excitement in the very short-term, but in the long-term, cause mere frustration. More important is the ability to transform data into relevant and readily available information.
To generate the required level of information, an effective data governance strategy must be in place. An organization can assess its data fitness level utilizing a self-assessment across various data dimensions. These dimensions include data management, IT/data architecture, analytics and methodologies, data strategy, data governance and finally, people and skills. This requires the commitment from upper management, governance and a respective approach to manage the data. But foremost, it requires a modern IT environment and the right people, skills- and mindset to properly process the data and apply the required analytical methodologies.
Figure 2 – Data Dimensions utilized to conduct the Data Assessment
If information truly is today’s currency, any company can make use of it. This isn’t a quick win, but the companies currently investing in their data strategies and road maps are creating future capabilities as well as a competitive advantage.
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