1. 16.01.2009 © Thomas.Madritsch@hsk-edu.at ERES 2009 Stockholm DECISION SUPPORT BY COMPUTER AIDED FACILITY MANAGEMENT SPACE ALLOCATION Thomas Madritsch International Benchmarking Institute, University of Applied Sciences FH KufsteinTirol, Austria; University for Health Sciences, Medical Informatics and Technology, UMIT-HALL, Austria ERES Conference 2009 Stockholm

2. 16.01.2009 © Thomas.Madritsch@hsk-edu.at ERES 2009 Stockholm ► Lack of transparency in many companies need to optimize operating costs / FM cost ► Demand: CAFM tools from simple information to multifunctional decision support tools ► Space allocation big challenge for FM Hardly assisted by IT Aim ► Illustrate the cutting edge relevance CAFM as decision support tool State of the art

3. 16.01.2009 © Thomas.Madritsch@hsk-edu.at ERES 2009 Stockholm Benefits of CAFM Implementation Survey from 150 Companies in D-A-CH (May 2005)

4. 16.01.2009 © Thomas.Madritsch@hsk-edu.at ERES 2009 Stockholm IT-supported decision support for space allocation and optimization Example for decision support

5. 16.01.2009 © Thomas.Madritsch@hsk-edu.at ERES 2009 Stockholm Sympathy / Attraction  Proximity Aversion / Repulsion  far off ? 24! = 620,448,401,733,239,439,360,000 possible variants (permutations) Let‘s assume 1 ms computing time per variant  19,674,289,755,620 years for finding an optimal seating How to Arrange a Seating Plan for a Family Celebration ?

6. 16.01.2009 © Thomas.Madritsch@hsk-edu.at ERES 2009 Stockholm 2 Possible Seatings out of 24!  Which one will result in more harmony? How to Arrange a Seating Plan for a Family Celebration ?

7. 16.01.2009 © Thomas.Madritsch@hsk-edu.at ERES 2009 Stockholm How does FM achieve ideal allocation efficiently? Surfaces optimally charge to capacity calculate plan optimize & save costs! analyze €! Example for DSS Organisation move in new building

8. 16.01.2009 © Thomas.Madritsch@hsk-edu.at ERES 2009 Stockholm Selection floors, offices, spaces back Example Data Input

9. 16.01.2009 © Thomas.Madritsch@hsk-edu.at ERES 2009 Stockholm Adjusting Communication- relations back Input of relations/frequency

10. 16.01.2009 © Thomas.Madritsch@hsk-edu.at ERES 2009 Stockholm Forced brown and purple due to higher communication 3. Floor 4. Floor 5. Floor 6. Floor adjustable reservations for selected areas Consideration short ways, if necessary over Stairs and elevators The occupied space surface is appropriate only 3.72% over theoretical. minimum need Computing space planning

11. 16.01.2009 © Thomas.Madritsch@hsk-edu.at ERES 2009 Stockholm Basement Ground floor 1st floor 4th floor 3rd floor 2nd floor Scenario 1: City Administration Building Project Results

12. 16.01.2009 © Thomas.Madritsch@hsk-edu.at ERES 2009 Stockholm 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 Computer Aided Real Benchmarking

13. 16.01.2009 © Thomas.Madritsch@hsk-edu.at ERES 2009 Stockholm ► 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 Workplace management (FM&REM&PM&..) higher productivity Conclusion: Decision Support DDS