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Forecasting

Improving Financial Analysis with AMI Data

May 15, 2019

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.

By Paige Schaefer

Sr Forecast Analyst

Paige Schaefer is a Product Marketing Manager in Itron's Outcomes group for the strategy, planning and implementation of projects supporting marketing functions spanning electricity, water and gas business units. She interacts directly with sales, product and corporate marketing to identify new marketing opportunities, recommend actions and the coordination of targeted campaigns to increase brand awareness and market share where she works closely with the teams to develop content and strategies. In addition, she provides website support, event coordination and 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 modeling and forecasting issues. Paige has a B.S. in Business Administration from San Diego State University with an emphasis in Marketing.