With every passing day, as the need for energy is increasing exponentially, coal and other fossil reserves are depleting at the same pace. Energy efficiency has become a hot topic for discussion and implementation, not only at forums, but also at corporate and individual household levels. Energy efficiency at companies essentially means using lesser energy to provide the same service. It can be done by a number of methods like better usage of electronic equipment, less energy guzzling devices, daylight saving, more usage of solar and renewable energy resources etc.
Business intelligence (BI) helps in collating, measuring and analysing the data collected for this purpose and giving actionable intelligence, which can save energy. The BI solution should be such that it suffices the needs of all business users without compromising on the flexibility or ease of usage of neither the devices nor affect the quality or timing of product delivery.
Business intelligenceIn the corporate sector, there is widespread need to use a range of software with different databases. We are generating a lot of data every day from software, web services etc. The sheer volume, variety and velocity of data coming in at any terminal are reaching unprecedented levels now. But this data is useless if we are not able to draw insight from it. Data becomes information only after it has been processed to add context, relevance and purpose. This is where BI comes into the picture. BI can connect to different databases and Web services and collate the data into use-worthy information. It can pull up screens for in-depth analysis that help make the right decisions. It can provide different kinds of reports, dashboards, data visualisation, what-if analysis etc. It also help management in coming up with the right solutions. If I have to talk about the energy sector, a lot of data is collected from different smart devices, DISCOM, electronic meters etc. By properly analysing this data, we can get a lot of insight on problems as well as come up with new energy efficient processes in a corporate set-up. We can manage electricity usage better by tapping into data to understand the risks of theft and loss of energy. Any BI solution that is generally used in the energy domain needs to help in better decision making in business areas that include:
Demand intelligence: Reports and historical trends from data to be used to analyse energy usage, examine energy costs, track and monitor service availability, downtime and utility demand, distribution etc. A proper BI can also help in analysing and developing sustainable distribution models.
Risk intelligence: A good BI solution should be able to analyse predictive models and risk-reward curves to determine risks associated with energy trading.
Asset intelligence (AI): BI helps in analysing energy generation and outages leading to better management of field employees, partners and affiliates. AI monitors equipment usage and helps resolve issues real-time. It also facilitates in tracking and monitoring equipment for preventive maintenance and replacement, track asset usage and thus increase efficiency.
Customer service intelligence: Provides dashboards to monitor and streamline call centre operations, analyse call and service centre response wait and time to minimise cost and increase efficiency.
According to a survey, Energy Insights found that BI is the No 1 IT investment for energy companies. More and more companies in the energy domain are realising the importance of BI and the value addition it makes for successful cost economisation through increasing efficiency of business operation.
Trends in the energy sectorHere are a few segments from the energy domain that are seeing increasing adoption of BI in their operation:
Information qualityData mining is done from various kinds of devices and software. This multitude of data collection and data-related issues are existent through the entire vertical of companies, i.e. exploration, production and trading. Sifting through this data for accurate information and using that for decision making can unlock immense business value.Importance of information quality is being recognised by organisations and being given higher priority now. Poor information quality hinders proper decision making and efficiency. To achieve superior information quality, traditional data cleansing and profiling need to be supplemented with data governance, master data management, meta data management, auditability and data certification, apart from data protection.
Master data managementMaster data management (MDM) market has been growing at a rate of 14 per cent per year. Master data consists of information about an organisation’s key business entities such as customers, products, vendors etc. with the goal of ensuring semantic consistency across organisational and business process. This simplifies the process and data integration while sustaining superiority in quality of information and availability of information from across segments is seamless.
Energy companies need to rely on critical data from different places like partners, clients, commodities, supplier, transmission, distribution, devices etc. Unfortunately, this data is managed by very disparate, redundant and often external information systems. MDM should be able to address this complex data assimilating process and make working easy with disintegrated data sources.
Data governanceData governance is responsible for providing a strategic direction for information quality efforts, sets standards and processes, and ensures that information quality goals are achieved.
Most companies still consider enterprise information management as a technology solution involving data warehouse, data migration, ETL (Extract, Transform Load) and data visualisation/presentation via BI. However, an ideal solution should encompass IT and business needs. Although data governance is not an easy task, it is very important for good enterprise information management.
Enterprise level BIEnterprise BI technologies are finding more adoption of late as the need for quicker decision making is escalating, hindered by more and more disparate data sources and increasing mobile workforce. Enterprise BI should take care of all the reports, dashboards, analysis, analytics and requirement of the different department/hierarchies in an organisation. Achieving enterprise-level BI requires significant process and organisational restructuring, and often a solid enterprise-level BI strategy and architecture that address the goals and objectives of both the business and IT.
Enterprise level data transparencyData transparency helps in tracking data to its source, and understanding the evolution/changes of the same over its journey. Metadata management helps in achieving better data transparency. As far as energy companies are concerned, data transparency is even more important because of the regulatory, health and safety compliance requirements.
Actionable business intelligenceMany still believe that BI is used only for historical reporting and trend analysis, whereas BI is actually much more than that. A proper BI system can help in real-time operational or tactical metrics, and managing and presentation of KPIs (Key Performance Indicators). Several companies find it difficult to provide a set of KPIs to be used and followed. KPI has to be set right at the start of the BI suite implementation. Also, the operational metrics should be perfectly aligned with company’s mission and vision for effective execution.
BI basicsThere are a number of companies which provide BI software such as SAS, Microsoft, IBM, SAP, Pentaho and Jaspersoft. The BI software can be used in any sector and often system integrators or software companies then provide services and produce a sector-specific solution for their end clients.
Installation and securityOnce a sector specific solution has been developed, the solution can be then integrated with any software, website, portal or application. Hence, the software does not really depend on the platform; via Web services the solution can be integrated with any platform. Also, user access-based data security can be provided. Hence, a user will be able to view only the relevant data.
LimitationsThe biggest drawback of proprietary software provided by SAS, SAP etc. is costs. Their license costs go up in crores of rupees. On the other hand, we do have open source BI software like Pentaho and Jaspersoft that are not that expensive. Moreover, often to implement these BI solutions, the client has to take the services of a software company, specialising in the BI software, which is also in a way a limitation in usage.
Cross-departmental advantagesA well-implemented BI can help a company in areas like predictive analytics, optimising investments and data-driven decisions. The BI software can be implemented across all departments. A brief summary of its highlights in some departments are:
Marketing: helps in growing its top-line with features like analysing campaign returns, promotional yields, and provide solutions to expenditure for profitable ROI and tracking social media marketing.
Sales: finding the best path and practices, customer acquisition cost and improvement in yearly turnover and sales.
Inventory: monitoring and adjusting inventory levels.
Human Resources: tracking and managing employee turnover, attrition rates and recruitment processes.