Honeywell since Apr 2009
Manager, Product Marketing
Integrity Windows & Doors Jan 2008 - Apr 2009
Marketing Manager
Integrity Windows & Doors Mar 2007 - Jan 2008
Group Product Marketing Manager
Integrity Windows & Doors Mar 2004 - Mar 2007
Product Marketing Manager
Conwed 2002 - 2004
Marketing Manager
Education:
Colorado State University 2001 - 2005
MBA
University of Northern Iowa 1994 - 1998
BA, Psychology
Skills:
Product Marketing Segmentation Product Management Cross-functional Team Leadership Email Marketing Product Launch Strategic Planning Market Sizing Forecasting Change Management Voice of the Customer Strategy Pricing Product Development Marketing Strategy
Tennant Company
Director, Industrial Products
Honeywell Jul 1, 2014 - Nov 2016
Director of Product Marketing
Sleep Number By Select Comfort Jul 1, 2014 - Nov 2016
Senior Director, General Manager of Development
Honeywell Apr 2009 - Jul 2014
Manager, Product Marketing
Marvin Jan 2008 - Apr 2009
Marketing Manager
Education:
Colorado State University 2001 - 2005
Master of Business Administration, Masters
University of Northern Iowa 1994 - 1998
Bachelors, Bachelor of Arts, Psychology
Skills:
Product Marketing Product Management Product Development Cross Functional Team Leadership Segmentation Management Strategic Planning Marketing Strategy Marketing Management Strategy Forecasting Product Launch Market Research Competitive Analysis B2B Pricing Strategy Pricing Market Analysis Sales Email Marketing Market Sizing Change Management Voice of the Customer Brand Management
Certifications:
New Product Development Professional Pdma
Us Patents
Demand Response System Having A Participation Predictor
- Morris Plains NJ, US Nicholas Dalsin - Minneapolis MN, US Seth Rourke - Lakeville MN, US Edward Koch - San Rafael CA, US
International Classification:
G06Q 30/02 G06N 5/04 G06Q 50/06
Abstract:
A demand response management system having a participation predictor. There may be a storage device having information collected about past behavior, related to participation in a demand response program, about a customer. The information may incorporate determining a period of time since the customer last participated in a demand response program, a frequency of participation in demand response events by the customer, and a size of energy loads of the customer. A model of the customer may be developed from this and other information. A processor may be used to collect and process the information, develop a model, and to make a prediction of a customer's being selected to participate in an event based on the various operator selectable criteria.
Demand Response System Having A Participation Predictor
- Morristown NJ, US Nicholas Dalsin - Minneapolis MN, US Seth Rourke - Lakeville MN, US Edward Koch - San Rafael CA, US
International Classification:
G06Q 30/02 G06Q 50/06 G06N 5/04
Abstract:
A demand response management system having a participation predictor. There may be a storage device having information collected about past behavior, related to participation in a demand response program, about a customer. The information may incorporate determining a period of time since the customer last participated in a demand response program, a frequency of participation in demand response events by the customer, and a size of energy loads of the customer. A model of the customer may be developed from this and other information. A processor may be used to collect and process the information, develop a model, and to make a prediction of a customer's being selected to participate in an event based on the various operator selectable criteria.
Predicting Responses Of Resources To Demand Response Signals And Having Comfortable Demand Responses
- Morristown NJ, US David J. McCurnin - Coon Rapids MN, US Seth Rourke - Lakeville MN, US Nicholas Dalsin - Minneapolis MN, US
International Classification:
G05B 15/02
US Classification:
700 90
Abstract:
An approach where a utility/ISO may dispatch demand response (DR) resources in real time without notification of a DR event. DR dispatches may involve sending specific load level commands to power generators that can respond to such commands in a predictable fashion. DR resources do not necessarily have the same level of control or predictability in their load responses. Accuracy of predicting a DR resource's response to a DR signal may be improved by restricting the DR signal to predefined finite values and, for each predefined finite value, have the DR resource continuously report back what its load response will be if one of those signal values is sent as a DR signal. A DR performed against a home may result in discomfort. But there may be a sufficient recovery rate for regaining the setpoint of a thermostat to attain comfort of the home within a reasonable period of time.
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BE GOOD,BE BAD,BE BRIAN G MICHAEL SETH O ROURKE(THE SOON TO BE 20 YEAR OLD) ... RIAN G MICHAEL SETH O ROURKE DATE OF BIRTH:7TH OF MARCH 1986 AT 15:50 ...