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: kalle@case.edu

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

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Cre

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PH

2 s

10 S

et u

p S

TR

DB

PH

5 s

35 M

ake

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PH 2

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Gat

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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

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PH

2 s

11 C

heck

Pro

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PH

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15 T

estin

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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?