Kalle Lyytinen Iris S. Wolstein Professor E-mail: kalle@case Case Western Reserve University

1. Toward a Generalizable (Sociomaterial) InquiryAn approach for analyzing patterns of association in routinesAoM PDW 8/1/2014 Kalle Lyytinen Iris S. Wolstein Professor E-mail: kalle@case.edu Case Western Reserve University NSF Grants : 0943157 and 0943010 http://designdna.case.edu/

2. Socio-technical Roots Technical Social • Historic Perspective • Deterministic, separate • Society Shapes Technology • SCOT, SST, ANT • Sociomaterial Perspective • Performative co-construction • Emergent affordances Image altered from cartoonstock.com

3. 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

4. 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)

5. 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.

6. 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

7. 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 endogeousv.s. exogenous?

8. 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

9. 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)

10. 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

11. 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?

12. Finding Regularities & Common Elements Case 1 Case 2 Case 3

13. Our methodological response Traditional methodology (Sequence Analysis) Event 1 Event 2 Event 3 Event 4 Our proposed methodology And we need to customize tools for data collection, and written scripts to automate the data analysis.

14. High Level Overview Data Collection and Analysis Data corpus Determine sample and collect field data Encoded graphical / lexical model Encode data into graphical / lexical model of routine Pivot tables, alignment trees, Markov models Analyze data using frequency tables and sequence analysis

15. Organizational Genetics(getting to the “genome”) Interviews & observations of process Generate Process DNA Sequences 1 3 2 Diagram process including all elements 4 Compare Sequences using ClustalG and other tools 4b 2b Validate Validate

16. 1. Build a theory-based taxonomy of sociomaterial routines High level overview

17. 2. Build lexical grammar High level overview

18. 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

19. Unit of Analysis: Activity Diagram Notation for Process Analysis Actor Configuration Activity Location Activity Type Affordance Tool Modality Data flow Object Type

20. 2007 2008 2009 2011

21. 3. Utilize tools for systematic and objective data collection and analysis&4. Make analysis automated in order to enable ease of escalation High level overview

22. Borrowing from Biology • Genetic elements as part of a taxonomy • Structural Hierarchy • Nested structures

23. Learning what we can learn…

24. How do different activities cluster (relate)?

25. What is the rate of change over time?

26. Technology Variation Across four firms

27. Sequential Variety Likelihood of one activity following another

28. 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.

29. 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…).

30. Questions?