Smart meter data is more granular and more timely than monthly billing data. Access to this data supports a paradigm shift in forecasting processes, allowing analysts to develop more powerful methods and to implement new approaches.

In our next brown bag, we focus on the shift from monthly to daily modeling and show how this shift can improve clarity and visibility in forecasting and variance analysis processes. Join Stuart McMenamin in this second brown bag of the year on Tuesday, May 21 at noon PDT for “Improving Financial Analysis with AMI Data”.

You can register for this brown bag and other forecasting events at www.itron.com/forecastingworkshops.

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Paige Schaefer
Sr Forecast Analyst - Itron
Paige Schaefer directs various web-based projects, including brown bag seminars, internet surveys, and other web-based projects and services. Schaefer manages Itron’s Energy Forecasting Group (EFG), which supports end-use data development, the Statistical End-use Approach (SAE) and coordinates their annual meeting for discussing end-use modeling and forecasting issues. In addition, Schaefer develops, manages and executes marketing campaigns for forecasting products and services and provides software support and documentation. She is responsible for project accounting and support, financial budgeting, accounting and invoicing. Schaefer received a B.S. in Business Administration from San Diego State University with an emphasis in Marketing.