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Kristine A Arneson, 4423901 Alluring Pine Dr, Nisswa, MN 56468

Kristine Arneson Phones & Addresses

Nisswa, MN   

Brainerd, MN   

Osseo, MN   

Minneapolis, MN   

Saint Paul, MN   

Social networks

Kristine A Arneson

Linkedin

Work

Company: Cavu corporation Aug 2012 Position: Vp, marketing

Education

Degree: Master of Business Administration, Masters School / High School: University of St. Thomas 2016

Skills

Interactive Marketing • Interactive Marketing Strategy • Website Creation • Website Design • Website Development • Online Advertising • Seo • Sem • Display Advertising • Email Marketing • Sms Marketing • Social Media Marketing • Mobile Marketing • Web Analytics

Industries

Photography

Mentions for Kristine A Arneson

Kristine Arneson resumes & CV records

Resumes

Kristine Arneson Photo 13

Vp, Marketing

Location:
23901 Alluring Pine Dr, Nisswa, MN 56468
Industry:
Photography
Work:
Cavu Corporation
Vp, Marketing
Allen Interactions Aug 2009 - Jul 2012
Producer
Target Jun 2008 - Jan 2009
Interactive Marketing Producer
City Pages Oct 2004 - Jun 2008
Account Manager
Education:
University of St. Thomas 2016
Master of Business Administration, Masters
North Dakota State University 2004
Bachelors, Bachelor of Science, Communication
Skills:
Interactive Marketing, Interactive Marketing Strategy, Website Creation, Website Design, Website Development, Online Advertising, Seo, Sem, Display Advertising, Email Marketing, Sms Marketing, Social Media Marketing, Mobile Marketing, Web Analytics

Publications & IP owners

Us Patents

Payroll System Optimization

US Patent:
2012010, May 3, 2012
Filed:
Nov 1, 2010
Appl. No.:
12/917119
Inventors:
Collin COOK - Eagan MN, US
Thad HELLMAN - Inver Grove Heights MN, US
Kristine ARNESON - Minneapolis MN, US
Kevin NOONAN - St. Paul MN, US
Assignee:
TARGET BRANDS, INC. - Minneapolis MN
International Classification:
G06Q 10/00
US Classification:
705 713
Abstract:
In one preferred implementation, a business rules engine optimizes staffing decisions by accepting as inputs top-down constraint as well as bottom-up constraint rules to dynamically determine short to medium term optimal staffing patterns. The business rules engine of this embodiment optionally utilizes a Holt-Winters algorithm which factors in both seasonal and annualized trend information. In certain embodiments, the business rules engine is able to more accurately estimate necessary minimum staffing based on business constraints at both the strategic and operations levels. For instance, strategic (top-down) factors may include intentional overstaffing of stores during certain time periods or in certain key geographic regions, sales forecasts, aggregate margin enhancement, etc. Operational (bottom-up) factors can, in selected embodiments, include time-to-unload, time-to-stock, product throughput and related factors.

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