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Prenova’s data warehouse contains over 5 years of energy performance details by sector, region, and market covering the operating history for tens of thousands of facilities.  Information for any participating company is held strictly confidential. Only summary level information is published. Customer specific information is not shared with, published, or provided to any other customer. Prenova’s extensive history of operational data is combined with industry specific benchmarks and manufacturer operating specifications.  This creates a powerful data set for assisting customers in evaluating operational results, assessing relative performance, and setting improvement goals.

Problem: Baselining and benchmarking performance to best practices requires rigorous processes for assimilating and assessing large amounts of historical and real time data. How does a company establish a baseline of its energy consumption and related carbon emissions? How does a company benchmark current performance to focus on what is being done right, and where results are less favorable?

Solution:  A Best Practice is a process, method, technique, or activity that is most effective at delivering a particular outcome than any other process used.  Because of proper processes, checks, and testing, a desired outcome can be delivered with fewer problems and complications. Best practices is also defined as a most efficient (least effort) and effective (best results) way of accomplishing a task.  This is learned from repeatable procedures that prove themselves over time.

Prenova’s Data Warehouse contains historical data outlining the operational results and experiences from years of testing and evaluation techniques for reducing energy consumption and carbon emissions. This extensive history of information on facilities and operations combined with Prenova’s Statistical Portfolio Profiler (SPP) process assists customers both in setting a baseline median of energy usage and carbon emissions and in evaluating performance goals.

Prenova’s standing processes for data quality management and techniques for establishing baselines and benchmarks are the set points from which all subsequent improvements and cost analyses can be examined, measured, and verified.  The Statistical Portfolio Profile defines the relative performance (kWh/SqFt) of all sites within a portfolio, as well as the carbon emissions footprint of that portfolio.  Prenova categorizes facility performance into operational bands grouped around the median. This categorization assists in the identification of priority performance conditions (e.g. facilities shown to be highly inefficient) and to begin the analyses of correlating factors contributing to these results.  The SPP delivers metrics down to the site level which can be used to chart progress and improvements in energy efficiencies.  The Statistical Portfolio Profiler also verifies, through the combination of these processes, the effective movement of both the overall portfolio’s median, and each facility to the median.  Improvements are tracked, measured, and results verified through subsequent iterations of these processes.

Steps are currently underway to certify Prenova’s processes for qualification under ISO 9000 and ISO 14000.  

Outcome: Participation as a Prenova customer offers businesses access to its extensive database of operational performance statistics and results as well as use of its proven processes for setting baselines and benchmarks. These processes and tools are effective in setting best practice goals, and accurately measuring and verifying results.