In a previous post, I covered the 5 must-haves to look for in an effective commodity analytics solution. One of the key areas was self-service analytics. In the commodity management business, it is becoming more and more common for business users to be more self-reliant and less dependent on IT departments for data analysis. These users, including traders, risk managers, analysts, back office personnel, and executives, want to eliminate the bottleneck of relying on IT every time they need a new report run or a new question answered.
With the democratization of analytics, companies are able to gain easy access to analytics with out-of-the-box software built specifically for their industry. As noted in the recent TDWI Best Practices Report: Predictive Analytics for Business Advantages, “a market goal has been to make the software easy enough to use to enable business analysts to build predictive models and make them consumable enough so that a host of end users can utilize them.” The trend towards self-service and democratized analytics is a good thing for businesses that are exposed to volatile commodity prices, as more companies are realizing that advanced predictive analytics are a must-have for managing risk and making the best business decisions. We will be writing more on the democratization of analytics and how it relates to commodities in future posts.
Get timely insights
For truly useful analytics, business users should be able to create their own analytics, then be able to customize those analytics on an ongoing basis as the needs of the business change. In fast moving markets, the delays caused by relying on the IT department or other specialists to create analytics render the results useless. Additionally, employees need to have access to decision support wherever and whenever they are working. Being tied to a desktop only creates further delays and bottlenecks. An analytics solution should be accessible from all locations including mobile devices, tablets, and home office workspaces.
Answer the most common questions easily
Commodity analytics need to be built around the way users want to ask questions, not around the limits of legacy technology. Information should be displayed in a way that is intuitive and allows every user to find and share answers instantly. In the commodities markets, there are hundreds of different questions that may need to be answered every day, such as how will a certain market scenario impact my coverage? What transactions are driving the biggest change to my P&L? When should I inject or withdraw at my natural gas storage facility? A commodity analytics tool employs algorithms specific to the commodities markets to enable you to answer these types of questions faster.
When commodities companies try to adapt other generic BI or analytics tools to fit their needs, these answers do not come as quickly or easily. Companies that use solutions that are not fit for purpose, such as ERP or spreadsheets, tend to rely on instinct or outdated information and cannot make data driven decisions. Learn more in, “An ERP Solution in Place of CTRM Software! Really?”
Agile data handling capability
Business users need to be able to bring together all of their data sources including ETRM, CTRM, ERP, CRM, spreadsheets, market curves, weather data, IoT sensors, and unstructured data into one centralized system to get answers and solve their most important problems. Users should have the ability to ask any question without being restricted by predefined requirements or data models.
Visual, intuitive, and interactive
Eka’s Commodity Analytics Cloud solution changes everything you think you know about commodity management. It gives you the ability to find and share answers instantly with interactive and intuitive visualizations. It empowers all business users to access the analytics they need at the right time to make insightful decisions without requiring an IT team. Learn more about how Eka is redefining the commodity management software industry.
