Controlling Change Within Complex Systems Through Pliability
Name
esd-wp-2012-09.pdf
Size
631.38 KB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Mekdeci, Brian
Ross, Adam Michael
Rhodes, Donna H.
Hastings, Daniel E.
Date Issued
March 2012
Publisher
Massachusetts Institute of Technology. Engineering Systems Division
Series/Report no.
ESD Working Papers;ESD-WP-2012-09
Abstract
As systems become larger, more complex, and operate for longer periods of time, some change within the system often becomes inevitable. Particularly in systems of systems, with diverse stakeholders, evolutionary development and managerial independence, it is not unusual for constituent systems to change in form or the way they operate. Changeability, the ability of a system to change, is often considered to be a desirable attribute that allows systems to be robust and to adapt in response to changes in context. However, involuntary changes, such as those that occur as a result of a disturbance, are more often problematic than favorable. In some ways, the survivability of a system depends on its ability to prevent, mitigate and recover from unintentional changes within the system brought about by disturbances. For certain large systems of systems, where there are complex interactions and a diverse set of stakeholders, even voluntary changes may be frowned upon, since it may be an expensive and time consuming process to approve changes. This paper discusses pliability, a new “-ility” that places constraints on the changes a system is allowed to make. Pliability is the ability of a system to change, without “breaking” or violating an architecture that the system architects intended and validated. Like changeability, pliability increases robustness by allowing systems to voluntarily change in response to changing contexts, and increases survivability by increasing the likelihood that unintentional changes are still within the set of allowable instances. It also distinguishes allowable changes from those that would require validation and approval from decision makers, making it easier to actually implement those changes in large, complex systems.
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