To remain competitive in today’s complex and volatile markets, commodities companies need to be able to make better, faster, smarter decisions with the huge quantity of data that is available to them. First- and second-generation commodity management systems are mainly transaction-based with limited analytics and support for real-time decision making. These systems are not equipped to handle the increasing quantities and types of data generated by commodities companies.
Next-generation systems need to include decision support and advanced commodity analytics to provide value to the business. This post will cover the 5 must-haves to look for in an effective commodity analytics solution.
1) Commodity Specific
A generic business intelligence application on its own is not an adequate solution for commodities companies. Specific knowledge of commodities markets and algorithms to run commodity analytics needs to be incorporated in order to provide a complete solution. This will allow users to find opportunities otherwise unavailable and reveal invisible risks faster and more effectively.
2) Speed
The ability to gain insights from your data in a timeframe that is useful is critical. Most first-generation systems do not have the capability to process huge volumes of data and perform real-time analysis for decision making. A commodity analytics solution should be able to process millions of data entities in minutes, if not seconds, to provide immediate insights. This allows users to take action before competitors.
3) Self-Service
Business users should be able to create their own analytics and update them on an ongoing basis as the requirements of the business change. The solution should allow users to find and share answers instantly without relying on the IT department or other specialists.
4) Mobility
Business is no longer conducted solely in the office. A commodity analytics solution should be built for mobile-first, with all functionality of the system easily accessible whether working on a smartphone, tablet, or desktop computer.
5) Data Eco-System
Most commodities companies have large volumes of data from different sources—internal systems such as ETRM, CTRM, ERP, CRM, and spreadsheets, plus external sources such as market curves and weather data. The solution should be able to bring all of this data together in one place to perform real-time analysis.
Analytics: The Way Forward
To meet the current needs of commodities companies, Eka has developed Commodity Analytics Cloud, an advanced analytics solution that brings commodity specific analytics to all business users. The solution allows users to focus on data analysis instead of data collection. It provides a series of apps designed for the commodities markets, addressing high value business issues. Commodity Analytics Cloud provides the real-time analytics needed to make better business decisions.
