44th Annual Meeting – Collections Care, May 15, "Comprehensive Collection Risk Assessment at Museum Victoria" by Maryanne McCubbin and Robert Waller

This presentation focused on using the Cultural Property Risk Analysis Model (CPRAM) at the Museum Victoria in Melbourne, Australia. If you scroll to the bottom of this web page you can obtain a free e-copy of CPRAM from Protect Heritage.
Museum Victoria, founded in 1854, specializes in a large range of materials and disciplinary types; natural sciences, indigenous cultures, history and technology. Less than 1% of collection is on exhibit at any given time. The museum complex has a wide range of facilities and each contain very different operational management and environments, and therefore different challenges:

  • Melbourne Museum – newest building – half of collections storage is in this space
  • Royal Exhibitions building – World Heritage listed building; paleontology and geology collection are stored in basement of this facility. They are being moved out of space currently because of the risks associated with storing them here (part of the CPRAM process)
  • Emigration museum – state registered building – just exhibits in this space
  • Off site collections storage – 50% spatially of our collections
  • Pumping stations – contains collection items
  • Science works – 3rd of their exhibition facilities

Summary of Museum Victoria’s experience of working on the CPRAM:
There are a lot of different risks in Museum Victoria’s collections. Before doing the CPRAM, it is important to recognize boundaries between collections and divide collections into discrete units, with exhibits being its own discrete collections unit. In total, there were 38 collections assessment units, with the assessments about 2/3rds of the way completed; 1/4 was completed by September of 2014 (unsure about beginning date). The initiative utilize a lot of staff time, but the Museum considered it a “Redirection” of time spent by staff instead of an extraordinary demand. In other words, they made this work a priority.
Museum Victoria’s main interest in doing the CPRAM was to assess the loss in utility value of collections over time. Value of course is considered in the context of the Museum, including historical/technological; exhibition; scientific; and cultural values to the Museum.
The remaining information below is only somewhat valuable if you are not familiar with the CPRAM model. I recommend getting the CPRAM document from Protect Heritage to understand the context of some of the information below (I was typing information that was on the PowerPoint slides that Robert was showing, and I added some additional information):
Risk Model Enhancements Completed at Museum Victoria:

  • Comprehensiveness
    • Source of risk + type of risk = generic risk – then broken down into specific risk – creating a quantitative sense of risk
  • Accountability
    • Ratio of other elements – 0 – 1 scale
    • Accountable for proving this is not the case?
  • Instrumental power
    • 200 page emergency plan = symbolic of the amount of risk, but who is going to read a 200 page emergency plan? Especially in an emergency.
    • Show risks that are within the control of the facility manager
    • Customized information
  • Extensive external critical reviews
    • Comprehensiveness
    • Clarity
    • Evidence
    • Appropriate model
    • Data sourcing
    • Benchmarking
    • Introduce to a range of benchmarks from other institutions
    • Done own research
    • External input is critical in adoption – to become self sufficient
  • Ongoing reporting
    • Implementing and gaining support at an institution-wide level including the Board – this is the hardest part
    • Reporting at all levels – templates that Robert provided
    • Aggregate and detailed data
  • Integrated incident reports into museum facilities
    • Redeveloped incident reporting
      • Online collection incident reporting
    • We don’t report all incidents – not realistic
    • Consistency of logic to encourage consistency of result, e.g. number scale, etc.
    • Evidence of data – put effort toward that instead of assuming the problem