Case Studies
$1 million saved in one year
Overview
Analytics & Modeling - Real Time Analytics Platform as a Service (PaaS) - Data Management Platforms | |
Professional Service Software | |
Business Operation Quality Assurance | |
Predictive Maintenance Real-Time Location System (RTLS) Remote Asset Management | |
System Integration Training | |
Operational Impact
| Real-time visibility accelerates troubleshooting and improves software release quality. With the Sumo Logic platform, Infor’s DevOps team uses data and dashboard analysis to monitor development and release cycle impact on product performance. Using an agile software release cadence, the company introduces monthly product updates, which allows Infor to continuously innovate across the complete enterprise software spectrum. Before adopting Sumo Logic, it was challenging for DevOps teams to investigate newly arising issues and to pinpoint a code change that was introduced three months earlier as the root cause of the problem. The platform’s flexible and fast-performing search capabilities enable the engineers to efficiently troubleshoot and determine the root cause, saving time and enabling the team to deliver fast product fixes. As a result, accelerated analyses mean increased productivity for developers and improved customer experience. Using Sumo Logic to troubleshoot and address development issues, Infor saved more than 3,300 hours in a year, and through these efficiencies, was able to redeploy DevOps resources to other value-added tasks. | |
| Empowering users with a decentralized governance model. Using a self-service strategy, Infor empowers employees with a decentralized governance model, allowing users across the organization to easily spin up monitoring in Sumo Logic to access the data and insights they need to make more informed, effective and intelligent business decisions. As Infor matured its cloud adoption within the service portfolio, log data analysis also matured and moved to a model of providing operational support at the business level. As a result, the company’s Sumo Logic usage evolved from predominantly product analysis to proactive and holistic analysis of the customer experience, enabling continual improvements to quality and customer satisfaction. “Our move to a business-centric data analysis approach required our Sumo Logic users to adopt the same standards and conventions, which ensures that logs created by one team can be processed by other teams,” said Eising, adding that “a centralized approach to defining the standards and evangelizing them gives us an effective way to do this.” The company measures the model’s success in terms of user adoption of Sumo Logic as a strategic operational tool. Based on this metric, Infor is experiencing great success. Today, 4,000 users across 120 DevOps teams within the company rely on Sumo Logic’s data analysis and dashboards to perform their job functions. | |
| Cost efficiency with thoughtful use of Sumo Logic’s data tiering. As part of the decentralized, self-service model, there was a concern that data ingestion costs could grow exponentially without an oversight process. To manage this, Infor created a collaborative model where each of the 120 department leads is held responsible for analyzing, adjusting, and managing their group’s data ingestion budget. Each lead strategically leverages Sumo Logic’s Data Tiers to optimize costs while maintaining the right level of data access and search capabilities by targeting the Continuous Tier to drive real-time dashboards and taking advantage of the more cost-effective Infrequent Tier to store vast amounts of data in an always-available, easily searchable manner. By leveraging Sumo Logic’s tiering capabilities in this way, the company can optimize analytics on a variety of growing data sources without the fear of explosive cost spikes. “By empowering our leads to decide what data is most important to them, we’ve seen a 60% reduction in the price per GB in the last 12 months,” said Eising. “We see that the product logs that are re-tiered following our recommendation have a cost reduction of up to 80%. Our approach resulted in a doubling of our log ingestion in 2021 at an ingestion cost increase of only 10%, saving us around $1 million.” | |
Quantitative Benefit
| Saved $1 million by applying data tiering to 12 TB per day log ingest. | |
| Reduced price per GB by 60% in the last 12 months. | |
| Enabled scalable data analysis for 4,000 users. | |
