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Infor > Case Studies > Optima Energy Systems Enhances Analytics with Infor Birst

Optima Energy Systems Enhances Analytics with Infor Birst

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 Optima Energy Systems Enhances Analytics with Infor Birst - IoT ONE Case Study
Technology Category
  • Platform as a Service (PaaS) - Application Development Platforms
  • Sensors - Utility Meters
Applicable Industries
  • Buildings
  • Cement
Applicable Functions
  • Product Research & Development
Use Cases
  • Energy Management System
  • Time Sensitive Networking
Services
  • System Integration
The Customer
About The Customer
Optima Energy Systems, established in 1988, develops and supports advanced software for managing and analyzing energy data. The company's software is used by some of the most significant energy users and consultants in the UK, managing energy data for over 22,000 organizations and 250,000 sites. Optima Energy Systems' core product is an energy management solution that validates bills sent from suppliers to customers. Its customers are large, multi-site organizations like supermarkets, water companies, telecom companies, and universities. The company helps these organizations manage their energy portfolios and control costs.
The Challenge
Optima Energy Systems, a leading energy management software provider, was facing challenges with its existing reporting system. The company had built an extensive collection of bespoke reports for its customers, which included large, multi-site organizations like supermarkets, water companies, telecom companies, and universities. However, every new customer required a different report, leading to a messy pile-up of options and settings that became increasingly cumbersome and difficult to support. The original reporting technology was unfamiliar to many, causing Optima Energy Systems to spend a disproportionate amount of time manually building reports rather than focusing on future product enhancements. The company sought to replace its existing reporting capability to improve development efficiency and transform its manual and resource-intensive reporting environment into a customer self-service reporting infrastructure.
The Solution
Optima Energy Systems decided to replace its existing reporting system with a modern self-service reporting and dashboard platform. The company shortlisted three different business intelligence vendors and ultimately chose Infor Birst due to its ease of application embedding, ease of development, and scalability as a cloud-based platform. The adoption of Infor Birst allowed Optima Energy Systems to avoid the lengthy process of submitting report specifications and the subsequent design, development, testing, and release work. Customers and their consultants could create reports in a fraction of the time. Optima Energy Systems also aimed to improve the look of its reporting offering with a modern web-based user interface to improve ease-of-use and appeal to future customers. The company also took advantage of Birst's multi-tenant architecture, which significantly sped up the process of onboarding new customers and reduced the administrative costs of maintaining and growing the customer base.
Operational Impact
  • The adoption of Infor Birst has led to significant operational improvements for Optima Energy Systems. The company has been able to transform its manual and resource-intensive reporting environment into a customer self-service reporting infrastructure. This has not only improved development efficiency but also allowed the company to focus on future product enhancements. The modern web-based user interface has improved ease-of-use and made the platform more appealing to future customers, driving increased sales and further adoption. The multi-tenant architecture of Birst has also significantly sped up the process of onboarding new customers and reduced the administrative costs of maintaining and growing the customer base. Furthermore, Optima Energy Systems is planning to grow its implementation of Birst's smart analytics technology by integrating weather data in the analytics process, which could lead to more accurate predictions of future costs.
Quantitative Benefit
  • 30% reduction in report development overhead
  • 50% increase in customer adoption
  • £1,000s of pounds of energy cost savings for customers

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