SAS® for Sustainability Management

Focus on Green IT

In the global green economy, manually collecting energy data from building meters, putting it into spreadsheets and making assumptions about IT electricity consumption won't suffice. The future requires reliable methods to reflect fully burdened costs of IT in order to survive changing carbon regulations and stakeholder scrutiny. The days where informal "good enough" estimates were used are over; maximum efficiency, resource optimization and total compliance are the new rules in achieving energy and cost savings.

Strategic IT leaders have started to include environmental criteria like energy consumption, greenhouse gas emissions, computing efficiency and product recycling in planning for their IT operations. As growth accelerates, leaders must justify the cost and emissions of new capital expenditures. At the same time, they are looking for more accurate measurements of capacity, demand and energy consumption.

To begin, you need reliable, granular information on what devices and processes are affecting current energy performance, and you need the ability to drill down and analyze that information to make fact-based decisions instead of estimated calculations. In addition to monitoring tools, to go from reactive to proactive management requires an overall view of IT performance (such as PUE and other green metrics) – which is more effectively derived from automated data collection and analysis.

How SAS® Can Help

SAS goes beyond capacity planning to understand true energy and efficiency of IT resources so that you can monitor, manage and control the energy consumption and carbon footprint of your IT infrastructure assets and operations. Designed for large private and public sector organizations, SAS for green IT provides a business analytics framework for evaluating energy consumed and emissions produced by an IT ecosystem. SAS helps you:
  • Improve data collection. With SAS, electronically capture energy and capacity data from  physical and virtual IT resources, third-party measurement tools and device monitoring applications across the entire IT infrastructure (networks, applications, Web servers, appliances, databases, security sensors, call centers, etc.) to create a "green IT" baseline.
  • Track performance to goal for organization-specific or globally recognized sustainability measurement standards. SAS gives you access to the information needed to understand why performance is at its current levels and what factors are correlated with that performance. It also models forecasts of future performance. By increasing utilization, you can control energy-related carbon emissions while freeing up power and cooling capacity for the future. SAS dashboards provide role-relevant insight and reporting for key stakeholders to manage performance against sustainability targets with transparency throughout the organization.
  • Optimize IT infrastructure by evaluating benefits of alternative strategies and mitigating risks. SAS' embedded analytics provide performance forecasts, correlation analyses and scenario modeling so you can identify candidates for server consolidation or virtualization to reduce power and cooling-related carbon emissions. SAS gives you the tools to accurately quantify energy and cost savings based on facts rather than estimates.

How SAS® Is Different

  • Integrated IT asset optimization AND energy management. SAS offers a solution from which you can perform both capacity planning and energy and emissions management.
  • Predict performance on KPIs, including energy consumption. Even though your organization may be energy-constrained, with SAS Analytics you can still predict how long you have to operate without significant risks to your ability to deliver IT services. SAS provides the foresight into planning scenarios for demand, capacity and licensing.
  • Data integration. With SAS' award-winning data integration, establish an integrated, consistent source of quality information that employs predefined data models. Use SAS' library of prepackaged data transformations for aggregation and report-ready data sources to create IT data marts containing statistically enriched and time-organized information.

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