Innovating in Internet Computing: A Case Study

1. How do software development firms innovate?- the case of Internet computing Tales from a Research Program American University 11/14/05 Kalle Lyytinen Iris S. Wolstein Professor Department of Information System

2. Agenda • Motivation and background • Internet computing and research questions • A Trinity model of Disruptive IS innovation • Validating / extending the trinity model: case studies and surveys • Hyper-learning and how SW organizations change their innovation capabilities over time • What makes SW organizations innovate radically • Concluding remarks

3. Motivation and background • Internet Computing: a new “technological frame” (Bijker 1987): “Internet computing will drastically change IS services, their delivery and their associated organizational processes” (Lyytinen, et al., 1998, p. 242)

4. Internet computing defined “Internet computing denotes a broad and evolving set of distributed computing models and solutions that rely on open, heterogeneous, and ubiquitous network services and associated protocols and distributed computing architectures” • An aggregate of concepts and techniques for identifying and solving “IS problems” • Established with the convergence of multiple technologies (Multimedia, OO programming, Reflexive programming/ Metamodels, open network architectures) and associated standards in the late 90s • Breaks radically from Client-server, PC, and Mainframe computing

5. Research questions • Can we theoretically analyze when a change in computing capability is substantial as to create a wake of discontinuous IS innovation? • Is Internet computing par excellence an example of disruptive IS Innovation • What are the impacts of such discontinuous change on software development organizations? • Does Internet computing demonstrate impacts of such change? • How do software development organizations innovate during discontinuous technological change? • What makes some organizations more innovative

6. Research questions • Question 1& Question 2: Articulation of a trinity model of disruptive IS innovation • Question 3: A longitudinal field study and a survey of Internet computing adoption and impact • Question 4 and Question 5: A model of hyper-learning and how organizations change their capabilities over time • Question 6: Application of radical innovation theory to predict innovativeness of SW firms

7. A Trinity Model of Disruptive IS innovation • Past IS innovation research abstracts from the kinds of innovations • Focuses on drivers / barriers that explain the extent of innovative activity and adoption rates and patterns • Localized models for specific areas (e.g. software innovation adoption, adoption gaps), or specific phases (early v.s. late)

8. Trinity Model of Disruptive IS Innovation “An Information Technology (IT) innovation can be defined as an innovation in the creation and application of digital and communications technologies (Swanson 1994)” • IT innovation covers a broad range of activities: (a) the creation of new information and communication technology capability; (b) creation of new products or services, and/or transferring them to organizations; (c) creation of new ways to develop products and services and transferring them to organizations; or (d) creation and transfer of new organizational forms to manage and deliver technological artifacts and services.

9. Trinity Model of Disruptive IS Innovation

10. Trinity Model of Disruptive IS innovation • Innovation in the nature of IS as a result of change in the technological capability: type 0 innovation connects to other innovations in processes (type I) and services (Type II) • The extent and tightness of such connections can be used to distinguish disruptive IS innovations from “incremental IS innovations in that in all types innovations are radical: • Unique with regard to contemporary innovations • Novel with regard to prior innovations • Transformative with regard to future innovations A disruptive IS innovation is a major architectural IT innovation (Type 0) which impacts pervasively (both type I/type II) and radically consequent IS innovation.

11. Trinity Model of Disruptive IS innovation • Radical: lead to significant departure in existing ways of doing things (originality, unlearning, predictability) • Pervasive: has to influence nearly all spheres of IS activity: processes and services

12. Radical IT Base Innovations (type 0) Radical Process Innovations(type I) Radical Service Innovations (type II) Trinity Model of Disruptive IS innovation

13. Trinity Model of Disruptive IS innovation • H1. During disruptive IS innovation base, process and service IS innovations occur exhaustively together (in packs), though not necessarily at the same time. • H2.During disruptive IS innovation SW organizations perceive all three sets of IS innovations to be radical.

14. 4Internet computing as disruptive IS Innovation? • Examination of hypotheses both by • Longitudinal replicated multi-site case study (1999-2004) • A survey (2005)

15. Multi-site case study • 5 year study for 8 software firms adopting Internet computing platform (type 0 innovation) • Industry leaders, development for Web, n-tier, thin clients • Covered time between 1997-2004 • Period 1: 1997-2000, Period 2: 2001-2002, Period 3: 2002-2004 • Examined extent and scope of adopting Internet computing and its impact on processes, products and markets • In particular extent, scope, depth and speed of change in software development in light of the research models (theory generating/validating multi-site case, replication logic) • Interviews (700 pages), archival data, company documents

16. Multi-site case study General changes: • Business, • Timeline for development is drastically shorter • Reported timelines reduced by >75% • Partially caused by IPOs in late 1990s • Technological, • Diverse, fast and complex technological change • Learning • Scope, depth and speed of learning changed dramatically

17. Radical changes in Processes (type I) • Changes in skills sets “having specialists in each of these areas, “we prefer to have them. But we cannot currently employ them full time on just one project [at a time]. So they basically travel between project and guide each project.” “don't have enough people yet to say that we have very good expertise on every technology we employ.” • Traditional ways did not work “I did out of shear panic. I spent two days [at a customer site] trying to get [deliverables from using the old methodology] that worked and failed miserably.It was embarrassing” (Architect, Firm 1) • The old solution frames did not work “Where a lot of people in what I call the new economy went wrong was they were looking for a methodologist silver bullet methodology to apply to the problem and actually they are different environments. Even in what you call an Internet software development, there are different environments and there are different approaches to the problem or methodologies that [might] work”

18. Radical changes in Processes (type I) • The speed of technological change unprecedented “Our firm traditionally had extremely good knowledge sharing practices in place…[now we] have just not been able to keep up with technology and the way that technology has been spreading rapidly and diversifying into different subgroups.” • Shorter ISD timelines But it is a different process. We found that the processes we used in Client/Server are no longer applicable. In the Client/Server space, the project life cycle expectation is nearly six or nine months. In e-Business it's six to nine weeks. And that's a huge back and forth change, and that's a totally different process.”

19. Radical changes in Processes (type I) • Shorter timelines lead to SW development as assembly • Five not reusing internal code- either not allowed by clients or don’t have time to build for reuse, but were either: • using more purchased components, middleware, We are “focusing on buying more components and using them as opposed to building them.” • Existing application packages (such as ERP) • Outsourcing coding “Let me say that in the new world I think your gonna have three kinds of programmers. You’re gonna have people who build the infrastructure; the virtual machine that’s gonna run things. You’re gonna have another set of people who build the reusable components to fit into that world. Then you’re gonna have a third set of people who go out and assemble solutions”.

20. Radical IS services(Type II) • Novel IS service features observed among studied companies • Unique types of applications as services

22. Radical IS services(Type II) • Mass markets • Reaches new customers “The web interface [has to be] more forgiving than your, you know, normal client/server application. And the thing that makes it a challenge is to make the user interface so easy to use and so fast that they really don't have to ask [for] help; they really don't have to push the help button…cause it might be your grandmother is using it”. • Problems in services effect their client’s satisfaction, their reputation, and increase their maintenance costs

23. Trinity Model of Disruptive IS innovation • H1. During disruptive IS innovation base, process and service IS innovations occur exhaustively together (in packs), though not necessarily at the same time. (for Internet computing supported) • H2.During disruptive IS innovation SW organizations perceive all three sets of IS innovations to be radical. (for Internet computing supported)

24. Survey Background • Jan. 2005 survey to members of a software association • Mailed to c.a. 300 organizations • Used validated measures of radicalness and pervasiveness related to Internet computing • Examined the extent, forms and factors influencing the adoption of Internet computing • CEO, CIO, CTO, President, chairman, owner, principal, senior developers, or VP of R&D • 33% (88 out of 269 ISD organizations) • Tested for radicalness and pervasiveness

25. Radical Base Innovations (type 0) Time lag Radical Process Innovations(type I) Radical Service Innovations (type II) Research Model (I): Disruptive nature and order effects

26. IT Base Radicalness Time Size Extent of Adoption Service Radicalness Systems Development Radicalness Research Model (II): Order Effect Moderators

27. Pervasive nature and order effects 71% of Companies Heavy Adopters

28. Pervasive nature and order effects Distribution of innovations towards BPS class very significant Test Statistics

29. Pervasive nature and order effects Heavy BaseAdopters adopted significantly more process/Service (Admin.)Innovations than light adopters

30. Order effects: 63 Companies Adopted Process Innovations Later than Base or Service Innovations 14 Companies Adopted Process Innovations Later than Base and Service Innovations

31. Order Effects: # of Process Innovations Adopted was Accounted for by Number of Base/Service Innovations # BaseInnovations .53 # ServiceInnovations # ProcessInnovations .20 process =.65 + .53*base + .20* service

33. Radicalness • establish radicalness measures of Internet computing based on Gatignon et al • Evaluate what explains the observed level of radicalness

34. Radicalness measures

35. Measurement model for radicalness (standardized)

36. Radical nature

38. The full model of moderators for strong order effects of radicalness

39. Trinity Model of Disruptive IS innovation • H1. During disruptive IS innovation base, process and service IS innovations occur exhaustively together (in packs), though not necessarily at the same time. (for Internet computing supported) • H2.During disruptive IS innovation SW organizations perceive all three sets of IS innovations to be radical. (for Internet computing supported) • H3 Strong Order Effects :During disruptive IS innovation, perceived radicalness of base innovations is positively associated with the perceived radicalness of process/service innovations.  (supported) • H4 Strong Order Effects: During disruptive IS innovation the adoption of process innovations is driven by the adoption of base (push) and service innovations (pull) and the adoption of process innovations lags behind the adoption of both base and service innovations. (supported) • Strong Order Moderation Effects • H5a During disruptive IS innovation company size will moderate the effect of perceived radicalness of base innovations on perceived radicalness of process and service innovations. (supported)   • H5b During disruptive IS innovation the time of adopting base innovations moderates the effect of perceived radicalness of base innovations on perceived radicalness of process and service innovations. (partially supported)

40. SW innovation as Organizational Learning • Exploration: new opportunities • Search, discovery, experimentation, risk taking • Loose couplings, improvisation, chaos • Returns distant, high variance, uncertain • Exploitation: old certainties • Refinement, implementation, efficiency, trial-error learning • Tight coupling, routinization, stability • Returns short term, higher certainty, low variance

41. IS innovation as exploration& exploitation Technology potential Type 0 innovations Market Push Absorb Base Innovations (Type 0) Dynamic capability Innovate IS Services (Type II) Innovate ISD Processes (Type I) Exploration capability Exploitation capability IS Discovery Type II innovations Market pull

42. Exploration Inefficient zone (Execution failures) Structural separation of effective ambidextrous organizations Trade-off on firm’s absorptive capacity Inefficient zone ( learning myopia, competency traps) Exploitation Hyper-learning

43. Exploitation Enable effective use Active Grafting Simple Patterns Multiple learning stimuli for depth Multiple learning stimuli for breadth Focus and increase flexibility of learning needs Enables fast knowledge transfer and learning Focus and increase flexibility of knowledge transfer Distributed Gatekeeping Peer networks Increase speed and flexibility of exploitation Exploration Hyper-learning mechanisms

44. How SW organizations change capabilities

45. What makes SW organizations more innovative? P(Heavy)= 1.542+ .588* oKDiv + .803*oEPc -.136*oOPP -.744* oOPP*oEPc oOPP: Technology Opportunism (technology sensing/responding) is a pure moderator 82%

46. Technology Opportunism moderates the Effect of Customer Demand Upon Heavy Adoption of Innovations The more a company is engaged in technology sensing/responding, the more discerning it is in adopting innovations. The less a company is engaged in technology sensing, its adoption of innovations is purely driven by customer demand (Bandwagon)

47. Conclusions • Radical innovation theory and organizational learning theories to understand discontinuous IS innovation “changes in IS development can be partly attributed to preceding architectural change in computing and dynamics between various sets of IS innovation and their antecedent technological change” • Internet computing influenced significantly on IS processes and services • Software developers must mobilize a different set of skills and resources

48. Conclusions Conclusions • Implications • How technological change and software development interact (what drives design methods) (push-pull)? • What drives base architectural change, how can it be identified? Can there be major changes in future? • Models of organizational learning- new condition for hyper learning organizations • Radical innovation is driven both by push (enabled by knowledge diversity) and pull (enabled by customer pressure) and moderated by organizational experimentation

49. 2. Publications List of main publications: Lyytinen K. & Rose G. (2003) Disruptive Information System Innovation: The Case of Internet Computing, Information Systems Journal, Lyytinen K. & Rose G (2003) The Disruptive Nature of Internet Computing : A Multi-Site Case Study of in Systems Development Organizations, MISQ Lyytinen K., Rose G. &Yoo Y. (2005): Learning in High Gear: Hyper-learning and Abrorptive Capability in Seven Software Firms, submitted for publication ISR Luo J., Lyytinen K., Rose G. (2005): Not all innovations are created equal- a study of disruptive nature of Internet computing, Procs of 26th ICIS, Las Vegas Lyytinen K., Rose G. (2005): Agility as organizational learning, forthcoming EJIS Lyytinen K., Rose G. (2005): A model of disruptive IS innovation cycles, unpublished working paper Luo J., Lyytinen K., Rose G. (2005): A trinity model of disruptive IS innovation- validation and extension, submitted to MISQ Luo J., Lyytinen K., Rose G. (2005): What explains radical innovation among software firms: a push-pull analysis, under preparation