kalle lyytinen iris s. wolstein professor e-mail: kalle@case case western reserve university
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Toward a Generalizable ( Sociomaterial ) Inquiry An approach for analyzing patterns of association in routines AoM PDW 8/1/2014. Kalle Lyytinen Iris S. Wolstein Professor E-mail: [email protected] Case Western Reserve University NSF Grants : 0943157 and 0943010 http://designdna.case.edu/. - PowerPoint PPT PresentationTRANSCRIPT
Toward a Generalizable (Sociomaterial) Inquiry
An approach for analyzing patterns of association in routines
AoM PDW 8/1/2014Kalle Lyytinen
Iris S. Wolstein ProfessorE-mail: [email protected]
Case Western Reserve UniversityNSF Grants : 0943157 and 0943010
http://designdna.case.edu/
Socio-technical Roots
• Historic Perspective– Deterministic, separate
• Society Shapes Technology– SCOT, SST, ANT
• Sociomaterial Perspective– Performative co-construction– Emergent affordances
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Social
Technical
Image altered from cartoonstock.com
What current approaches give us
• Within a Single Context based on deep ethnographies (e.g., Leonardi and Barley 2008; Leonardi 2011; Orlikowski and Scott 2008)
– Context is important– IT has different forms– Entanglement produces emergent
affordances in situ
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What current approaches give us
• Across Multiple Contexts based on variance models – Context immaterial– IT has no form (proxy / nominal)– Focuses on covering laws (expressed in
variations)
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What current approaches cannot give us
• Common patterns – Across contexts– Across time– Importance of order
• Generalizable findings for multiple contexts with systematic presentation of context or composition (correlations between phenotype proxies not enough)
• The way in which intertwining happens (as a complex relation)
• Lack of common language: assemblages, imbrications, entanglement, intertwined, sociomaterial, sociotechnical, webs, mangle of practice, configurations and so on it goes.
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Challenges
• We are poor in describing common regularities across multiple contexts or instantiations – Next frontier in sociomaterial studies
(Leonardi and Barley 2008; Pentland et al. 2009; Scott 1990; Williams and Pollock 2009)
• Need a complementary (mixed method) approach that enables more generalizable inquiry and theory
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Implicit call for new methods!
“Do different environments and organizations tend to produce the same patterns, or are there systematic differences? Do different organizations given similar environments, produce similar patterns? Are there characteristics of the persons or team responsible for the [routines] that may predict variation in patterns of actions? In other words, are routines shaped more by the external environment or by internal features of the organization? …answers to these questions seem a long way off at the moment…” (Pentland et al. 2009).
Note that Pentland et al do not dare to raise the possible role of technology. Is it endogeous v.s. exogenous?
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Our Motivation: Studiesof routines
• Past Research focuses on emergent properties of routines at the phenotype level such as formality or frequency (through interview report data / surveys)
• Little focus on generative mechanisms that produce variety and retain selected variety (such as a enforcing a specific routine)-
• Mostly explained by local learning- but explanation is too general and tautological (as it does not say what is being learned)
• No mechanisms to analyze internal composition and variability of routines
Epistemological Route Out
• “Generative Grammar” (Chomsky 1955; 1966; 1980)
– Extract patterns of rule following instantiated in (sociomaterial) practice
– Codify with a common lexicon inherent relationships
– Analyze commonality and variation– Transcends single situations and enables
generalizable theory building• Theory driven “Rational Reconstruction”
(Giddens 1984; Habermas 1979) 9
Methodological Route out
• Current methods for analyzing patterns do not do the job…– Focus solely on phenotype variance or
activity level transitions– Fail to capture context and co-constitutions
(intertwining)– Cannot detect evolutionary patterns
• Contextual data is qualitative, heterogeneous and sparse
• Difficult to analyze on a larger scale, especially systematically 10
Potential Pursuits of Inquiry
• What similarities or differences are observable between routines?– How do such regularities relate to certain outcomes or
antecedents (such as level of digital support)?• How do routines evolve over time? And what is the
cause of that evolution?– Specifically, what effects digital capabilities have on the
evolution?• What can we predict about the presence of
organizational activity based on observed routine patterns?– Do particular sequences of activity consistently lead to other
sequences of activity? What can we learn from this?11
Finding Regularities & Common Elements
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Case 1
Case 2 Case 3
Our methodological response
Event 1 Event 2 Event 3 Event 4Traditional methodology (Sequence Analysis)
Our proposed methodology
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And we need to customize tools for data collection, and written scripts to automate the data analysis.
Determine sample and collect field data
Encode data into graphical / lexical model of routine
Analyze data using frequency tables and sequence analysis
Data corpus
Encoded graphical /
lexical model
Pivot tables, alignment
trees, Markov models
High Level Overview Data Collection and Analysis
Organizational Genetics(getting to the “genome”)
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Interviews & observations ofprocess
1Diagram process
including all elements2
3
Generate ProcessDNA Sequences
PH
1 s
1 Id
ea
Cre
atio
n
PH
2 s
10 S
et u
p S
TR
DB
PH
5 s
35 M
ake
Ske
tche
sP
H 1
s2
Gat
e M
eetin
g D
ecid
e S
PH 2
s7
Gat
e M
eetin
g
PH 3 s2
0 G
ate
Mee
ting
PH 4 s29 G
ate Meetin
g
PH 5 s40 Closeout Meeting
PH 2 s19 Materials Research Re
PH 5 s34 Gate Meeting
PH 2 s18 Review Meeting
PH 3 s25 Tear down analysisPH 2 s16 Tear down analysis
PH 1 s5 Refine Models
PH 2 s9 Test Plan Meeting
PH 1 s4 Refine Specifications
PH 1 s6 Design Review
PH
5 s36 Make D
rawings
PH
2 s8 Generate P
rototype
PH
3 s21 Vendor M
anufactures M
PH
1 s3 Kick off M
eeting
PH
3 s
22 In
com
ing
Exp
ectio
n
PH
5 s
37 V
erify
Dra
win
gs
PH
2 s
11 C
heck
Pro
toty
pes
PH
2 s
15 T
estin
g
PH 3
s24
Tes
ting
PH 3 s2
7 Tes
ting
PH 4 s31 Testi
ngPH 4 s32 Testing
PH 2 s14 Prepare test samplesPH 3 s23 Prepare test samples
PH 3 s26 Prepare test samples
PH 4 s30 Prepare successful sa
PH 2 s13 Assemble Hoses
PH 2 s12 Heat Treatment
PH 5 s38 Request Approval
PH 5 s39 Drawing Release Notif
PH 4 s33 U
nlimited approval
PH
3 s28 Preproduction approva
PH
2 s17 Finite E
lement A
nalys
Compare Sequences
using ClustalG and other tools
4Validate
4b
Validate
2b
1. Build a theory-based taxonomy of sociomaterial
routines
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High level overview
2. Build lexical grammar
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High level overview
Extracted Common Elements (taxonomy)
• Activity Type– Generate, Transfer, Choose, Negotiate, Execute, Validate, Training
• Activity Location– Collocated, Local, Remote, Mixed
• Actor Configuration– 1 individual, 1 group, many individuals, many groups, individuals and
groups• Tool Modality
– Physical, Digital• Tool Affordance
– Representation, Analysis, Transformation, Control, Cooperative, Storage• Artifact Type
– Specification, Prototype, Implementation, Process planning, Knowledge• Dataflow
– Input, Update, Output 18
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Actor Configuration
Activity Location
Activity Type
Affordance
Tool Modality
Data flow
Object Type
Diagram Notation for Process AnalysisUnit of Analysis:
Activity
2007
2008
2009
2011
3. Utilize tools for systematic and objective data collection and analysis&
4. Make analysis automated in order to enable ease of escalation
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High level overview
Borrowing from Biology
• Genetic elements as part of a taxonomy• Structural Hierarchy• Nested structures
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Learning what we can learn…
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How do different activities cluster (relate)?
What is the rate of change over time?
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Technology VariationAcross four firms
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Sequential VarietyLikelihood of one activity following another
Limitations of this Approach
• Lose richness of context– Cannot explain motivations for engaging in
activities or affordances• Variation due to randomness• Risk type II errors
– We may neglect to find valuable insights that do exist, simply because we are searching for a fixed list of elements.
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Conclusions
• We are removing the barriers to engaging in generalizable sociomaterial inquiry.
• Our approach is deeply rooted in philosophic and theoretical foundations.
• Our approach is repeatable and scalable sine fine (depending on resources…).
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Questions?