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2013 Conference for Organisational Learning,
Knowledge and Capabilities
Washington D.C.
April 26-27, 2013
Pamela A. Posey, RamkrishnanV.Tenkasi (presenters)
and Douglas Austrom, Betty Barrett, Bert Painter, and Betsy Merck
Socio-Technical Systems Roundtable
Sociotechnical Systems inVirtual
Organizations:
The Challenge of Coordinating Work and
Knowledge AcrossTime and Space
This material is based upon work supported by the National Science Foundation
under grant number NSF OCI 09-43237.  Any opinions, findings and conclusions
or recommendations expressed in this material are those of the author(s) and
do not necessarily reflect the views of the National Science Foundation.
STS inVirtual Organization 2013
  Virtual organizations that span institutional and
national boundaries have become central to
emerging practice of science and engineering
  Challenge: how to design effective work systems
in contexts that are:
◦  Highly Interdependent
◦  Virtual, not co-located
◦  Non-linear, involving non-routine knowledge based work
  NSF funded study of 3 on-going virtual R&D
projects across different stages of the R&D
Continuum
STS inVirtual Organization 2013
•  Research Questions: How can we best coordinate
work and knowledge across time and space? What
are the most appropriate coordinating mechanisms
that enable effective knowledge sharing and learning
in key deliberations at different stages in the R&D
continuum?
•  Key Premise: Nature of deliberations (complexity
of key choice points) and the coordinating
mechanisms required to effectively manage them
will vary based on the level of task uncertainty and
degree of equivocality at different points along the
R&D continuum.
STS inVirtual Organization 2013
•  Selection of virtual organizations to include in study
•  Scoping interviews/secondary data to place each
project on R&D continuum
•  In-depth structured interviews/observations to
gather information on;
–  Types of deliberations
–  Knowledge barriers that impeded deliberations
–  Identification of emergent and purposive coordination
mechanisms
•  Detailed case study write-ups of each case
•  Comparative analysis within and between cases
•  “Extreme exemplar” cases (Eisenhardt and
Graebner, 2007).
STS inVirtual Organization 2013
  Caltech- Orchid Project: fundamental research
◦  Optical Radiation Cooling and Heating in Integrated Devices
◦  Tightly-Linked Collaboration for Design of Experiments & Device Fabrication
among Laboratories using 3 Technology platforms
◦  Pasadena, Switzerland and Austria
◦  Major challenge: creative research and design and knowledge generation in a
complex virtual setting
  NACC: a virtual R&D eco-system
◦  Comprised of 29 NIA-funded Alzheimers Disease Centers (ADCs) and the
National Alzheimers Coordinating Center Center (NACC)
◦  Major challenge: Create Uniform Data Set agreeing upon and compiling data
from the 29 different centers as the basis of research
  LVG: a large video game developer
◦  Core team with distributed vendors in Philippines, China, India, Switzerland,
North America and across the parking lot
◦  Major challenge: Cost effective game development work with high quality
and timeliness completed at a distance for art production, engineering and
testing STS inVirtual Organization 2013
HIGH Uncertainty LOWER Uncertainty
‘Orchid’	
  Project	
   ‘Uniform	
  Data	
  Set’	
  Project	
   ‘Large	
  Video	
  Game’	
  Project	
  
Pure	
  Research	
  
Work	
  
DON’T	
  KNOW	
  
	
  WHAT	
  	
  
we	
  are	
  looking	
  
for	
  
DON’T	
  KNOW	
  	
  
HOW	
  	
  
to	
  carry	
  out	
  the	
  
research	
  
Applied	
  
Research	
  Work	
  	
  
DON’T	
  KNOW	
  	
  
WHAT	
  
(i.e.	
  end	
  state	
  
or	
  objec?ve)	
  
KNOW	
  
	
  HOW	
  	
  
to	
  carry	
  out	
  the	
  
research	
  
Exploratory	
  
Development	
  
Work	
  
KNOW	
  
	
  WHAT	
  	
  
DON’T	
  KNOW	
  
	
  HOW	
  
	
  to	
  achieve	
  it	
  
Advanced	
  
Development	
  
Work	
  
KNOW	
  	
  
WHAT	
  
DON’T	
  KNOW	
  	
  
HOW	
  	
  
IN	
  DETAIL	
  	
  
to	
  achieve	
  it	
  
Start-­‐Up	
  	
  	
  (pilot	
  
plants,	
  	
  beta	
  
tes?ng)	
  
Development	
  
Work	
  
KNOW	
  	
  
WHAT	
  
KNOW	
  	
  
HOW	
  	
  
CONCEPTUALLY	
  
to	
  achieve	
  it	
  	
  
Scale-­‐Up	
  (volume	
  
&	
  costs)	
  
Development	
  
Work	
  
KNOW	
  	
  
WHAT	
  
KNOW	
  	
  
HOW	
  
OPERATIONALLY	
  
to	
  achieve	
  it	
  
R
1
R
2
D
1
D
4
D
2
D
3
STS inVirtual Organization 2013
•  Orchid
–  What experiment shall we run?
–  How shall we design the experiment?
–  How shall we execute the experiment?
–  How do we make sense of the results?
•  NACC
–  What data will go in the UDS?
–  What diagnostic instruments shall we use?
–  Who will have access to the data?
•  LVG
–  What new features shall we develop?
–  What contractor shall we use for this work?
–  What will the requirements be for the contractor?
STS inVirtual Organization 2013
Lack of knowledge
Example: Need to invent a new methodology so devices created at
Caltech could run on different experimental equipment in Europe
(ORCHID)
Failure to use knowledge
Example: failure to use knowledge that other divisions had about
vendors capabilities (LVG, Inc.)
Failure to share knowledge
Example: desire to collect data related to a particular research interest
did not address need for shared standardized data (NACC)
Lack of a common frame of reference
Example: related but quite different disciplinary roots in ORCHID
project
  Standards - rule based
◦  Example: data formats, process standardization)
  Plans – result based
◦  Example: delivery schedules, project milestones
  Formal mutual adjustment
◦  Example: hierarchy, task force
  Informal mutual adjustment
◦  Example: informal meetings, temporary co-location
SocialSystemTechnicalsystem
STS inVirtual Organization 2013
  All categories of coordinating mechanisms were used to
some degree by all 3 sites
  Technical (structural) coordinating mechanisms were used
more in activities and projects with lowest uncertainty and
equivocality
  Social (mutual adjustment) coordinating mechanisms were
used more in activities and projects with higher uncertainty
and equivocality about process and outcomes
  Identifying the location of a virtual work project on the R&D
continuum helps us anticipate the nature and degree of the
coordination challenge and the mechanisms most likely to
help
•  Knowledge barriers increase as task uncertainty
increases
•  Appropriate coordinating mechanisms can help
overcome knowledge barriers that hamper
deliberations
•  Coordinating mechanisms should match the
information processing complexity demanded
by task uncertainty of the deliberation

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Presentation: Sociotechnical Systems in Virtual Organizations: The Challenge of Coordinating Work and Knowledge Across Time and Space

  • 1. 2013 Conference for Organisational Learning, Knowledge and Capabilities Washington D.C. April 26-27, 2013 Pamela A. Posey, RamkrishnanV.Tenkasi (presenters) and Douglas Austrom, Betty Barrett, Bert Painter, and Betsy Merck Socio-Technical Systems Roundtable Sociotechnical Systems inVirtual Organizations: The Challenge of Coordinating Work and Knowledge AcrossTime and Space This material is based upon work supported by the National Science Foundation under grant number NSF OCI 09-43237.  Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. STS inVirtual Organization 2013
  • 2.   Virtual organizations that span institutional and national boundaries have become central to emerging practice of science and engineering   Challenge: how to design effective work systems in contexts that are: ◦  Highly Interdependent ◦  Virtual, not co-located ◦  Non-linear, involving non-routine knowledge based work   NSF funded study of 3 on-going virtual R&D projects across different stages of the R&D Continuum STS inVirtual Organization 2013
  • 3. •  Research Questions: How can we best coordinate work and knowledge across time and space? What are the most appropriate coordinating mechanisms that enable effective knowledge sharing and learning in key deliberations at different stages in the R&D continuum? •  Key Premise: Nature of deliberations (complexity of key choice points) and the coordinating mechanisms required to effectively manage them will vary based on the level of task uncertainty and degree of equivocality at different points along the R&D continuum. STS inVirtual Organization 2013
  • 4. •  Selection of virtual organizations to include in study •  Scoping interviews/secondary data to place each project on R&D continuum •  In-depth structured interviews/observations to gather information on; –  Types of deliberations –  Knowledge barriers that impeded deliberations –  Identification of emergent and purposive coordination mechanisms •  Detailed case study write-ups of each case •  Comparative analysis within and between cases •  “Extreme exemplar” cases (Eisenhardt and Graebner, 2007). STS inVirtual Organization 2013
  • 5.   Caltech- Orchid Project: fundamental research ◦  Optical Radiation Cooling and Heating in Integrated Devices ◦  Tightly-Linked Collaboration for Design of Experiments & Device Fabrication among Laboratories using 3 Technology platforms ◦  Pasadena, Switzerland and Austria ◦  Major challenge: creative research and design and knowledge generation in a complex virtual setting   NACC: a virtual R&D eco-system ◦  Comprised of 29 NIA-funded Alzheimers Disease Centers (ADCs) and the National Alzheimers Coordinating Center Center (NACC) ◦  Major challenge: Create Uniform Data Set agreeing upon and compiling data from the 29 different centers as the basis of research   LVG: a large video game developer ◦  Core team with distributed vendors in Philippines, China, India, Switzerland, North America and across the parking lot ◦  Major challenge: Cost effective game development work with high quality and timeliness completed at a distance for art production, engineering and testing STS inVirtual Organization 2013
  • 6. HIGH Uncertainty LOWER Uncertainty ‘Orchid’  Project   ‘Uniform  Data  Set’  Project   ‘Large  Video  Game’  Project   Pure  Research   Work   DON’T  KNOW    WHAT     we  are  looking   for   DON’T  KNOW     HOW     to  carry  out  the   research   Applied   Research  Work     DON’T  KNOW     WHAT   (i.e.  end  state   or  objec?ve)   KNOW    HOW     to  carry  out  the   research   Exploratory   Development   Work   KNOW    WHAT     DON’T  KNOW    HOW    to  achieve  it   Advanced   Development   Work   KNOW     WHAT   DON’T  KNOW     HOW     IN  DETAIL     to  achieve  it   Start-­‐Up      (pilot   plants,    beta   tes?ng)   Development   Work   KNOW     WHAT   KNOW     HOW     CONCEPTUALLY   to  achieve  it     Scale-­‐Up  (volume   &  costs)   Development   Work   KNOW     WHAT   KNOW     HOW   OPERATIONALLY   to  achieve  it   R 1 R 2 D 1 D 4 D 2 D 3 STS inVirtual Organization 2013
  • 7. •  Orchid –  What experiment shall we run? –  How shall we design the experiment? –  How shall we execute the experiment? –  How do we make sense of the results? •  NACC –  What data will go in the UDS? –  What diagnostic instruments shall we use? –  Who will have access to the data? •  LVG –  What new features shall we develop? –  What contractor shall we use for this work? –  What will the requirements be for the contractor? STS inVirtual Organization 2013
  • 8. Lack of knowledge Example: Need to invent a new methodology so devices created at Caltech could run on different experimental equipment in Europe (ORCHID) Failure to use knowledge Example: failure to use knowledge that other divisions had about vendors capabilities (LVG, Inc.) Failure to share knowledge Example: desire to collect data related to a particular research interest did not address need for shared standardized data (NACC) Lack of a common frame of reference Example: related but quite different disciplinary roots in ORCHID project
  • 9.   Standards - rule based ◦  Example: data formats, process standardization)   Plans – result based ◦  Example: delivery schedules, project milestones   Formal mutual adjustment ◦  Example: hierarchy, task force   Informal mutual adjustment ◦  Example: informal meetings, temporary co-location SocialSystemTechnicalsystem
  • 11.   All categories of coordinating mechanisms were used to some degree by all 3 sites   Technical (structural) coordinating mechanisms were used more in activities and projects with lowest uncertainty and equivocality   Social (mutual adjustment) coordinating mechanisms were used more in activities and projects with higher uncertainty and equivocality about process and outcomes   Identifying the location of a virtual work project on the R&D continuum helps us anticipate the nature and degree of the coordination challenge and the mechanisms most likely to help
  • 12. •  Knowledge barriers increase as task uncertainty increases •  Appropriate coordinating mechanisms can help overcome knowledge barriers that hamper deliberations •  Coordinating mechanisms should match the information processing complexity demanded by task uncertainty of the deliberation