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ERES Conference 2009 Stockholm

ERES Conference 2009 Stockholm.

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ERES Conference 2009 Stockholm

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  1. ERES Conference 2009 Stockholm Decision support by Computer Aided Facility Managementspace allocationThomas MadritschInternational Benchmarking Institute, University of Applied Sciences FH KufsteinTirol, Austria; University for Health Sciences, Medical Informatics and Technology, UMIT-HALL, Austria

  2. State oftheart • Lack of transparency in many companiesneed to optimize operating costs / FM cost • Demand: CAFM tools from simple information to multifunctional decision support tools • Space allocation big challenge for FMHardly assisted by IT • Aim • Illustrate the cutting edge relevance CAFM as decision support tool

  3. Benefits of CAFM ImplementationSurvey from 150 Companies in D-A-CH (May 2005)

  4. Examplefordecisionsupport IT-supporteddecisionsupportforspaceallocationandoptimization

  5. How to Arrange a Seating Planfor a Family Celebration ? ? Sympathy / Attraction Proximity Aversion / Repulsion  far off 24! =620,448,401,733,239,439,360,000 possiblevariants (permutations) Let‘sassume 1 mscomputing time per variant  19,674,289,755,620 yearsforfinding an optimal seating

  6. How to Arrange a Seating Plan for a Family Celebration ? 2 PossibleSeatings out of 24! Whichone will result in moreharmony?  

  7. Example for DSS Organisation move in new building How does FM achieve ideal allocation efficiently? Surfaces optimally charge to capacity • analyze • plan €! • calculate • optimize & save costs!

  8. back Example Data Input Selectionfloors, offices, spaces

  9. back Input of relations/frequency Adjusting Communication- relations

  10. Computing space planning Forced brownandpurpledue to highercommunication 6. Floor 5. Floor Considerationshort ways, if necessary overStairs and elevators 4. Floor adjustablereservations forselected areas 3. Floor The occupied space surface is appropriate only3.72%over theoretical.minimum need

  11. Project Results Groundfloor 4th floor 2nd floor Scenario 1: City Administration Building Basement 1st floor 3rd floor

  12. Computer Aided Real Benchmarking • Example: • By surface compression of only 3% • e.g. 100.000m ²(= 3,000 m ²) • Savings renting costs ( 11, - €/m ²month) 396.000, - €/a • Savings operating expenses (3,30 €/m ²month) 118.000, - €/a • Savings 514.000, - €/a

  13. Conclusion: Decision Support DDS • DDS Large area of growth • Simulating real estate processes to support decision processes • Controlling efficiency of REM • Higher degree of transparency – web based (any time and place) • Support Workplacemanagement (FM&REM&PM&..) higher productivity

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