1. The Future of Management Research following Herbert Simon, thus enabling Evidence-Based Management London, October 10, 2012 Joan van Aken

2. Industrial Engineering and Innovation Sciences PAGE 1 10 October 2012 the birth of academic management research  Business education has been transformed on the basis of the Research-Based Model  Herbert Simon (1991): … we perceived American business education as a wasteland of vocationalism, that needed to be transformed into science- based professionalism, as medicine and engineering had been transformed …  This transformation was very successful, but it did not use the model of medicine and engineering, thus creating the relevance problem of management research

3. Industrial Engineering and Innovation Sciences PAGE 2 10 October 2012 a possible future  A possible (desirable) future of management research: design science research as part of main stream research  An interactive session ……  Background of the interacting partners

4. Industrial Engineering and Innovation Sciences PAGE 3 10 October 2012 positioning: relevance and design  This presentation draws on - the continuing relevance discussion (all AoM Presidents since Don Hambrick (1994), the impact of the RBM) - actionable knowledge (AMLE, 2012) Evidence-Based Management (Rousseau, 2012) - Simon (1969) the sciences of the artificial; design - Schön (1983) the reflective practitioner: the high ground of theory, the swamp of practice  Key themes: relevance, design and the desire to link the high ground and the swamp

5. Industrial Engineering and Innovation Sciences PAGE 4 10 October 2012 storyline  The relevance-for-practice issue  Research paradigms: explanatory and design science  Research relevance through research-informed practice  Design Science Research: developing solution-oriented input for research-informed practice  The fundamental methodological problem of DSR in the social world: human agency  Objective and systematic experiential social learning  The future: DSR as part of the main stream

6. Industrial Engineering and Innovation Sciences PAGE 5 10 October 2012 five conversations #1 research relevance for professional practice #2 research paradigms #3 research-informed practice (evidence-based practice) #4 design science research #5 the future of management research

7. Industrial Engineering and Innovation Sciences PAGE 6 10 October 2012 research relevance (1)  The RBM: the codified, generic knowledge one shares with students should be research-based  In a Professional School one trains future professionals (not researchers)  So research in a Professional School should produce knowledge relevant for professional practice

8. Industrial Engineering and Innovation Sciences PAGE 7 10 October 2012 research relevance (2)  The core competence of university trained professionals: knowledge-intensive field problem-solving  Core process: designing solutions and acting on these designs  Research outcomes are relevant to the extent that they are important for this design process

9. Industrial Engineering and Innovation Sciences PAGE 8 10 October 2012 research relevance (3)  Remarks - relevance for practice: not yes/no, but a continuum from very little to very large - research can have substantive relevance or methodological (like informing how to analyse, how to design or how to set op a logical argumentation) - research results can be immediately relevant or after further development

10. Industrial Engineering and Innovation Sciences PAGE 9 10 October 2012 research relevance (4)  Descriptive and explanatory knowledge (diagnostic knowledge) typically plays an important role in designing effective solutions  However, an often even greater role can be played by generic alternative solutions (like generic treatments or constructions, a main focus of research in medicine and engineering)  This solution orientation is the defining difference between the research model of physics and of engineering/medicine

11. Industrial Engineering and Innovation Sciences PAGE 10 10 October 2012 conversation #1: relevance  Should relevance for practice be an important criterion in management research by business schools?  Is the importance of research input in solution design at field problem-solving a sound way of assessing its relevance?

12. Industrial Engineering and Innovation Sciences PAGE 11 10 October 2012 research paradigms (1)  Research paradigms play a key role in the relevance discussion  Research paradigm, following Lakatos(1991): combination of research questions asked, research methodologies allowed (including what is accepted as evidence) and research products pursued

13. Industrial Engineering and Innovation Sciences PAGE 12 10 October 2012 research paradigms (2)  One can distinguish (van Aken, 2004, 2005) - the explanatory research model (e.g. physics and sociology) - the design science research model (e.g. medicine and engineering)  Explanatory research: aims at understanding the world that is  Design science research: aims at developing knowledge to create the world that can be

14. Industrial Engineering and Innovation Sciences PAGE 13 10 October 2012 research paradigms (3)  Explanatory research - driven by pure knowledge problems (knowledge as an end) - mission: to understand, a quest for truth - students are trained to become researchers by researchers - iconic research product: the causal model  Design science research - driven by field problems (knowledge as a means) - mission: to improve the human condition - students are trained to become professionals largely by professionals - iconic research product: the design proposition

15. Industrial Engineering and Innovation Sciences PAGE 14 10 October 2012 the design proposition  The generic design proposition follows the basic pragmatic logic: if you want to solve this type of problem-in-context, you may use this generic solution/intervention (which will produce the desired outcome through this mechanism)  The design proposition puts the solution/intervention in context  A design proposition is not prescriptive (in management research the term prescriptive or normative is a legacy from the time of the one best way of organizing)

16. Industrial Engineering and Innovation Sciences PAGE 15 10 October 2012 conversation #2: research paradigms  Can the distinction between the paradigm of the design sciences (engineering, medicine) and the one of the explanatory sciences (physics, sociology) be relevant for the discussion on the future of academic management research?

17. Industrial Engineering and Innovation Sciences PAGE 16 10 October 2012 research-informed practice (1)  The core competence of university trained professionals: knowledge-intensive field problem-solving (working effectively in the swamp)  (This concerns both dealing with problems and seizing opportunities)  Core process in field problem-solving: designing solutions (including their implementation) and acting on these designs

18. Industrial Engineering and Innovation Sciences PAGE 17 10 October 2012 research-informed practice (2)  Basic steps problem-solving project (van Aken, 2012) : - Fuzzy Front End - Project definition with problem defintion - Analysis (context and dignosis) - Design (solution and change plan) - Change (and learning to perform) - Evaluation and learning  Not a phase-model, but a step-model (with explorations and iterations)  Designing: sketching, outline design, detail designs  Core process: designing in synthesis-evaluation iterations

19. Industrial Engineering and Innovation Sciences PAGE 18 10 October 2012 research-informed practice (3)  Designing involves abduction, i.e. a creative jump (a design cannot logically be derived from the input; a solution cannot be derived from the problem analysis)  Professional designing is characterized by a careful collection of the input to the design process: - problem definition - model of present system - context analysis and problem diagnosis - design specifications - generic input

20. Industrial Engineering and Innovation Sciences PAGE 19 10 October 2012 research-informed practice (4)  Types of generic input to the design process - descriptions of the industry and of the type of organization in question - explanatory knowledge on the causes of the type of problem and on the factors influencing outcomes (the past; science of the averages; variance models) - design knowledge on alternative generic solutions (the future; process models on how to realize desired outcomes; science of the particular, developed through case-studies)

21. Industrial Engineering and Innovation Sciences PAGE 20 10 October 2012 research-informed practice (5)  Examples of generic alternative solutions (developed by PhD-DSR-studies) - how to create an effective virtual team - how to find overseas partners for cooperative arrangements (for SMEs) - how to involve end users in product innovation - how to promote intrapreneuring - how to deal with setbacks (CMOREs) in radical innovation  This can be really interesting, intellectually rewarding research …..

22. Industrial Engineering and Innovation Sciences PAGE 21 10 October 2012 evidence-based management?  In management rather research-informed practice than evidence-based practice (like in medicine) : - not evidence on known interventions (in management the interventions have to be context-specific designed) - nor practice based on codified knowledge ( medicine, engineering and law can be regarded as knowledge-driven, management rather as knowledge-supported)

23. Industrial Engineering and Innovation Sciences PAGE 22 10 October 2012 conversation #3: research-informed practice  Can research-informed practice be a valuable addition to traditional, more experience and intuition-based practice?  What should be done to realize this?

24. Industrial Engineering and Innovation Sciences PAGE 23 10 October 2012 maybe ….. 1.Create awareness 2.Provide access to the literature 3.Give courses in systematic review (light) 4.Give courses in research-informed problem- solving

25. Industrial Engineering and Innovation Sciences PAGE 24 10 October 2012 the design proposition (1)  A major objective of DSR is to develop alternative generic solutions/interventions for types of field problems  These can be formulated in terms of design propositions: “if you want to solve this type of problem-in-context, you may use this generic solution/intervention (which will produce the desired outcome through this mechanism)”

26. Industrial Engineering and Innovation Sciences PAGE 25 10 October 2012 the design proposition (2)  Prison problem C – locked door, bars, guards I – no escapes O – physical constraining of movements M  Theft in car park C – introduction CCTV I – less theft O – deterrence, allocation of personnel, less careless behaviour of parkers M  Virtual team C – FtF kick-off meeting I – effective team O – collective insight and collective commitment M  Desire to promote intrapreneurship C – gaming I – insight and commitment O – experiential learning M

27. Cranfield Seminar 26 the methodological problem of DSR (1)  The basic scientific claim of a design proposition is that the proposed solution/intervention will indeed produce in the given context the desired outcome  So the question is how to establish this claim: one has to predict the outcomes of interventions

28. Cranfield Seminar 27 the methodological problem of DSR (2)  In the material world this demand for prediction does not pose specific methodological problems,  because in this world there are universal, invariant, individual behaviour determining mechanisms  A machine, developed, produced and tested in Helsinki will also work next year in Barcelona

29. Industrial Engineering and Innovation Sciences PAGE 28 10 October 2012 the methodological problem of DSR (3)  Because of human agency no universal, invariant and individual behaviour determining mechanisms  This makes the prediction of the outcome of interventions in the social world difficult  However, there are patterns and regularities in human behaviour

30. Industrial Engineering and Innovation Sciences PAGE 29 10 October 2012 research as experiential learning (1)  Prediction of the behaviour of others is an almost universal human competence (without this competence intentional social behaviour would be almost impossible, as can be seen with autism)  This competence is developed by personal experiential social learning  The basic research strategy for DSR is experiential learning; more precisely objective and systematic experiential social learning through series of case-studies

31. Industrial Engineering and Innovation Sciences PAGE 30 10 October 2012 research as experiential learning (2)  Experiential learning is the basis for crafts and trade schools, including the business school of the past; this is not what we want  Research as experiential learning is to produce valid, objective generic knowledge  It involves rigorous case studies, using methods like controlled observations, triangulation, rich descriptions, careful cross-case analyses, member checks, beta testing, etc.

32. Industrial Engineering and Innovation Sciences PAGE 31 10 October 2012 research as experiential learning (3)  In DSR one works alternately in the ‘practice stream’ and the ‘knowledge stream’  In the practice stream (the swamp) one develops specific solutions for (series of comparable) specific field problems, interacting with stakeholders and other practitioners (e.g. collaborative research)  In the knowledge stream (the high ground) one develops generic solution oriented knowledge by generalizing across cases, interacting with other researchers

33. Industrial Engineering and Innovation Sciences PAGE 32 10 October 2012 DSR-projects (1)  Every DSR-project starts with an explanatory part; the more there is already known, the larger the design science part of the project  The design science part typically develops a process model to realize a desired direct outcome (science of the particular)  Where available, explanatory research outcomes link this direct outcome with the desired final outcome (science of the averages)

34. Industrial Engineering and Innovation Sciences PAGE 33 10 October 2012 DSR-projects (2)  Explanatory research may be complementary to design science research: - explanatory large N research (science of the averages, not context-specific variance models) determines the factors/interventions producing desired final outcomes - these factors/interventions become desired direct outcomes (e.g. factors influencing job satisfaction) - design science research (small n research, science of the particular, process models) determines how to realize these direct outcomes in the swamp of practice  For instance DSR develops a system for decreasing innovation throughput times, explanatory research shows that this is good for market share

35. Industrial Engineering and Innovation Sciences PAGE 34 10 October 2012 conversation #4: DSR  DSR is based on the paradigm of medicine and engineering. Its defining characteristic is its objective to develop generic solutions for field problems  Can this paradigm also be used in management research?  Would this have added value?

36. Industrial Engineering and Innovation Sciences PAGE 35 10 October 2012 conclusions  Relevance for practice should be an important issue in (future) management research  Relevance means importance in designing solutions (and change plans) for field problems  Next to descriptive/explanatory knowledge one also needs well tested and understood generic solutions  A key research strategy to develop these is objectified and systematized experiential social learning (working alternating in the practice and the knowledge stream)  (Supervising student field problem solving projects is an exciting way to master this type of research)

37. Industrial Engineering and Innovation Sciences PAGE 36 10 October 2012 conversation #5  “In the future design science research will belong to the main stream of academic management research” (thus using both the classical research paradigm of most social sciences an the one of medicine and engineering)  Is this desirable? Is this possible? Should we do something to realize it?