Research on Disciplined Innovation

MTM SYMPOSIUM:The commercial value of disciplined innovation in fast-moving high-tech ICT Businesses fast- high-Marius van der LeekMobyl Designwww.mobyl.comSupervisor: Prof L Pretorius Sel: +27 83 458 4120 E-mail: marius@mobyl.com 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Structure Introduction Research Problem, Objective, Questions and Proposition Research methodology • Exploratory theory application, testing and building – Small sample with low variability Proposed model or Conceptual method • Initial model: Exploratory theory application and testing • Emerging concept: Theory building Results • Literature Review Summary: Initial proposition • Research Questionnaire Summary: Second round proposition 6. Conclusions and recommendations • Extend research of emerging concepts towards theory building 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Introduction: The more things change, the morethey stay the same Tough economic times raise sensitivity about shareholder value where investments must follow returns. Modern businesses have to display good governance and practice which requires structure and is interwoven in their decision-making fibre. ICT Managers are always searching for practical guidelines on IT investment decision-making. Some believe that effecting change through disciplined innovation efforts can have far reaching benefits. The need to find appropriate innovation concepts, models, methods, approaches and theories are greater than ever. 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Challenge: What are those appropriateinnovation constructs offering real value Problem Statement: • An unstructured management approach does not properly filter ICT proposals effectively enough to ensure sustained systems performance and high ROIs Objective: • To quantify if a more structured approach translate an improvement in the likelihood of performance and shareholder value Questions: • What are the innovation constructs, criteria and performance indicators or measures Propositions: • Appropriate innovation constructs, criteria, indicators and measures offer insight into economic viability and is representative of key business issues related to fast- moving high-tech environments Problem Questions Objective Propositions 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Facing the Challenge: Translate findings intopractical day-to-day application by design day-to- The research study will comprise of the following components (relative weights of the components are indicated in bold): • Theory building research – 20% • Theory testing research – 10% • Theory application research – 20% • Exploratory research – 50% – Some theory in advance but have a hunch – Aimed at formulation of propositions, and at theory development – Cause-effect dynamics, and difference and correlation open questions The research method covered the following: • It is based on executing a survey research coupled with findings from a literature review covering text books, journals and papers creating a consensus view • Although variability between innovation constructs and business areas surveyed, there are common themes across these study units • Motivating consensus as feasible, consistent also with experience and observation, forming some basis for reasonable deductions and generalisation 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Exploratory application research and theory testing and building a challenge in itself Identify gaps in theReview of established innovation and investment Review of established innovation and established innovation and systems, criteria & valuing methods investment systems, criteria & valuing investment systems and methods criteria and indicators methods Identify gaps in the established Follow a critical review, analysis and evaluate innovation and investment existing and established innovation and systems and criteria and investment decision -making practices indicators methods 1 2 Identify the characteristics of Position and profile practices environments associated with associatedwith the objective innovation and investment of successfulPropose a new method with associated valuing / decisionmaking practice - commercialisation scoring system Positioning of existing and established Description of two major distinctions Establish weighting values for the investment innovation and investment decision -making between environments as each relates to criteria – AHP / workshop approach practice and its alignment towards promoting implementation of existing and established qualitativevs quantitative decision -making innovation and investment decision-making and purposeful emergent innovation vs practice processesEvaluate the new innovation method with actual case studies Identify initial findings as to the successful application of Identify business profiles innovation and investment associated with the position decisionmaking practice - of existing and established realtedto each of these innovation and investment Conclude on the distinctive environments and decision -making practice appropriateness of the how it relates to modern IT developed model for valuing of projects purposeful vs emergent innovation and quantified vs intuitive investment decision- making 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Study outcome: Predictable results elude ITinvestment decision makers The findings of this study include: • Conclusions from the Literature Review and Research Questionnaire: – Due to the nature and eventual results emerging from the research study, we provide empirical support for correlation between performance and innovation behaviour typically present in large local corporate environments. • The concepts of linear and non-linear environments (Author, 2010): – Due to time constraints and deviation from initial planning this avenue is not pursued. It does however introduce a controversial and fresh view on performance parameters applied to IT projects that stem from manufacturing which is deeply rooted in industrial era paradigms. The details are available in the final research report. • Positioning and profiling management techniques (Author, 2010): – Due to time constraints and a deviation from the research plan, an initial description of the evaluation matrix and associated profiles associated to the various innovation practices evaluated, are offered. No empirical evidence is presented for this qualitative assessment and resulting adoption profile. The details can be found as part of the final research report. 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Literature review: A process for critical reviewof a subset of constructs Observations Outcome Study Decision-making TRIZ and TOC. Predictability Trade-off Total Factor Uncertainty Studies. Productivity. Business Five Disciplines Cost-Benefit of Innovation ™ Analysis. Investment Capital Seven Innovation Investment Sources for Concepts Theories Decision-making. Function Innovation based Value Opportunity.Technology Analysis. SystemsMarket Strategy. Research Engineering and Objectives for: Product Analysis.Multi-dimensional Methods Commercial InnovationFeasibility Analysis. Value of Constructs Scorecard. Integrated Innovation Sound Reasoning Disciplined Innovation Management . and Decision- making. Innovation Metrics – Information Economics. Measurement to Insight. Models Rational Actor Model. Multi-criteria Analysis. Incremental Processes in Approaches unstable environments. Innovate on Purpose™ Quantitative Decision Consensus Based Decision- Creative Making. making in high uncertain Thinking in the Development Decision- 2010 Symposium: GSTM environments. Decision and making for optimum thinking Quantitative IT Portfolio Management and best practice. Management. Sciences. Copyright © 2011 mobyl design / University of Pretoria

Literature review: Promoting a disciplinedinnovation approach towards delivering value Industrial era business cost-benefit analytics do not fit modern knowledge era innovation efforts and require a review of overall performance measures especially due to the uncertain nature of IT investments. Positioning an IT investment is to obtain the right balance between desired information systems performance and benefits realisation. (Swinkels, 1997:2) Successful innovation is the result from conscious, purposeful search for opportunities (Drucker, 2006). Improved probability of success with purposeful innovation and sound reasoning based on the availability of relevant data and information. (Bourgeois and Eisnehardt,1988) The Rational Actor model (Allison 1971) suggests that strategic success depends on careful analysis and planning before action is taken. • At best, viability of the rational model is seen as contingent upon a stable environment and bureaucratic organization (Mintzberg 1973) Management sciences have always exhibited a bias against quantitative techniques (Brugha 1998), 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Literature review: Promoting a disciplinedinnovation approach towards delivering value Support the idea of creating repeatable, quality outcomes in the innovation process. (Genrich Altshuller, 1946) TOC focuses on improving the value adding performance of an organisation with minimal increase in cost. Sustainable innovation requires defined, repeatable business processes and tools to become part of the business operations breaking down traditional barriers. (Phillip and Hering,2005) Successful implementation of a disciplined approach to innovation process is dependent not only on the availability and application of the appropriate technologies and tools, but also on the proper planning and management of activities required to accomplish overall objectives. (Blanchard and Fabrycky, 2006:50) 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

First round propositions: A disciplinedcommercialisation approach have real benefits P1: Value creation is an incremental process (Fredrickson, 1984) which requires review of quantitative business benefits at each stage of the innovation life cycle on all business contexts. • Managers need predictable results. A set of process steps (Jolly,1997) offer to monitor progress towards successful commercialisation which can be aborted where the value seem to be inadequate measured against the cost of resources required to realise it. P2: Disciplined innovation result in the efficient and effective utilisation of resources and is critical to sustainable business development. • Management stake their reputation and careers on their decisions. An innovation process (Morris) in the form of a project pipeline offer managers a dashboard of activity throughout the innovation life cycle and is a useful tool in monitoring effective and efficient resource utilisation. P3: There is correlation between innovation behaviour and financial performance confirming success or failure can be managed through a diligent process of evaluation (Swinkels, 1997). • Managers are willing to be measured on their contribution towards business performance. Improved probability of success with purposeful innovation and sound reasoning and decision-making is based on the availability of relevant data and information. 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Literature review outcome: Disciplinedinnovation should not be too rigid Both quantitative and qualitative analytics offer valuable insight into innovation efforts across the life cycle but accurate results presupposes reliable, accurate and feasible input data. • Quantitative analytics do not necessarily support a successful innovation effort and the results would not be more accurate than implementing qualitative analytics on specifically IT investments. • IT investment decision-making is often the result of business context and less so of initial cost-benefits due to the highly uncertain nature of IT projects – ‘we don’t know what we don’t know’ then make a call based on best effort and an educated guess. After initial data collection and analysis, empirical evidence indicates the revision and introduction of new propositions. 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Research Questionnaire: Multi-dimensional Multi-data items offer insight on value achieved A set of data items was selected to offer emergent correlations or relationships between innovation management practice and specific contexts: • Performance: Financial results • Technology and Business: Innovation initiatives and business life cycle • Innovation: Approach to innovation purposeful or emergent; and • Decision-making: qualitative vs quantitative practices. 20% of 31 past corporate colleagues in top performing corporate companies in South Africa participated in the questionnaire. This offer a level of insight that resonate with observation and experience allowing a basis for generalisation. No direct correlation between contexts to conclude sustainable business is reliant on diligence of IT investment decision-making. 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Research Questionnaire: Decision-making Decision-context offer light on the processes followed Disciplined innovation processes are followed 87.5% respondents indicated that they are 3.5 diligent and possibly disciplined 3 2.5 incorporating good governance and quantify 2 their investment decisions. 1.5 1 0.5 0 62.5% agree that no proper evidence can be Strongly agree Agree Neutral Disagree Strongly disagree No opinion presented why decisions are made regarding investments. Qualitative decision-making 4.5 4 3.5 Drucker (1996) also suggest that practices 3 2.5 co-exist especially within non-linear 2 1.5 environments as qualitative decision-making 1 is as critical in highly uncertain 0.5 0 environments where quantitative measures Strongly agree Agree Neutral Disagree Strongly disagree No opinion do not offer all the answers. 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Second round propositions: Investmentdecision-decision-making is supported by proper data P1: IT investment decision-making requires more consideration of the nature of knowledge era type dynamics and innovation efforts, specifically the application and relevance of decision and management sciences developed from the industrial era. • Managers are reluctant to commit to performance measures set against their innovation targets due to its highly uncertain nature. P2: Concepts, models, methods and theoretical constructs comprising modern management science are inadequate to deal with the management of innovation efforts within the new knowledge era • Decision and management sciences evolved to address predictability in traditional linear environments and not more non-linear knowledge era environments • Managers are not committed to follow a particular decision practice. P3: Performance measures created for linear environments are being applied loosely to non-linear problems and may no longer be relevant to IT investments. • Managers are not necessarily equipped to distinguish between linear (predictable) and non- linear (highly uncertain) environments. 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Recommendations: Extend the study and unitsalthough multiple sources are used Extend exploration into the characteristics of linear and non-linear environments for the purpose of establishing appropriate performance measures for each environment type. Review the subjective assessment on the positioning of innovation constructs within the evaluation matrix. Extend the study to better match organisation type or characteristics to adopt the appropriate set of innovation constructs to enable commercial value from innovation efforts. Launch a full blown case study involving local industries over and above the financial and telecommunications sectors to extend the sample size and obtain proper unit measure to achieve an appropriate representation of innovation and value creation activities within IT departments. 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Meandering exploration outcome Finding nr1: Linear and Non-Linear Environments Finding nr2: SWOT and Profile Conclusion: Context based innovation behavior contributes to ROIE 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Three Horizons of Growth – Near, Mid- and Long Term Mid-Profit TargetsSource : Adapted Horizon Growth Model, SystemicLogic, 2004 (Ref : The Alchemy of Growth) TTB* Strategy-Orientated Horizon 3 *Running, growing Create viable and transforming the GTB* business, translates options Focus Tactics-Oriented Horizon 2 into the building / extending internal / external IT Service Build RTB* provider capabilities emerging in order to help Horizon 1 capabilities Target-Oriented achieve profit and growth goals set by Extend and the business, within defend core the specific horizon. capabilities 6 – 24 months 2 - 5 years > 5 years Time 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Three Horizons of Growth – Near, Mid- and Long Term Mid-Profit TargetsAdapted from Systems Engineering and Analysis , Figure 2.12 (Blanchard and Fabrycky, 2006:46) Innovation Life Cycle 100% Commitment to technology or solution direction Significant Commitment to funds Commitment 75% Value Add High Commit to costs incurred proportional to value add 50% Medium 25% Commit to ease of change Low Idea or Conceptual Detailed Build and Operations and Need Design Design and Production End-of-life Development 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Three Horizons of Growth – Near, Mid- and Long Term Mid- Profit TargetsAdapted from Systems Engineering and Analysis , Figure 2.12 (Blanchard and Fabrycky, 2006:46) Reducing levels of uncertainty 100% through the phases of the life Risk and Uncertainty Significant cycle Confidence and 75% High Benefit Increasing levels of confidence 50% Medium 25% Interim points or gates for critical review Low Idea or Conceptual Detailed Build and Operations and Need Design Design and Production End-of-life Development Innovation Life Cycle 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Three Horizons of Growth – Near, Mid- and Long Term Mid- Profit TargetsAdapted from Systems Engineering and Analysis , Figure 2.12 (Blanchard and Fabrycky, 2006:46) 100% cycle cost committed Percentage of life Detailed design and development 75% System analysis, evaluation of alternatives (trade-offs), systems 50% definition, etc. Market analysis, feasibility study, operations requirements, maintenance 25% concepts, etc. Idea or Conceptual Detailed Build and Operations and Need Design Design and Production End-of-life Development Innovation Life Cycle 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Lucas, H.C. Jr., 1999. Information Technology and the ProductivityParadox: Assessing the Value of Investing in IT. Oxford UniversityPress, New Yprk Oxford. 1999.Investment type Notes Benefit Probability of Evaluation return (margin)Infrastructure Support the business – may Allows new initiatives 0.2 – 1.0 (0.5) Option for future include future investments applications Initial investment costRequired Cost of doing business Stay in business 0 – 0.5 (0.2) Lowest-cost route to enableManagerial Control features of the application(No return)No alternative Enabling new task or Improves customer 0.5 – 1.0 (0.75) Cost reduction against process experience potential benefits realisationDirect return from Structure, cost-benefit, NPV Marginal if IT investment 0.7 – 1.0 (0.9) Linear quantitative plus realIT and IRR not leveraged OPM (non-linear evaluation)Indirect returns Potential return but Substantial but not easily 0 – 1.0 (0.5) Evaluate non-linearfrom IT qualitative benefits quantifiableCompetitive Ticket to the match – cost Follower / Reactive model 0 – 1.0 (0.2) Business value vs costnecessity of not investing? offer marginal benefit benefit analysisStrategic Return or benefits High potential Leader 0 – 1.0 (0.5) Future benefit non-linearapplication realization after model high risk investment evaluation implementation (OPM)Transformational Combined with changes in High potential Innovator 0 – 1.0 (0.5) Change impact cost-benefitIT company philosophy model high risk non-linear evaluation 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Purposeful 3 1InnovationApproach Evaluation Matrix, Author 2011 4 2 Emergent Qualitative Quantitative IT Investment Decision-making Approach 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Linear vs Non-Linear Environments, Author Non-2011 Investment Decision-making Investment Decision-making continuum extreme: Qualitative continuum extreme: Quantitative Innovation Approach continuum Quadrant 3: The innovation process is Quadrant 1: The innovation process is extreme: Purposeful institutionalized however, analytics and institutionalized and diligence exist in data collection happen in an ad-hoc analytics and data collection with fashion with investment decision-making formalized investment decision-making based on some future benefit aligned to methods offering insight into realistic immediate business needs investment returns Innovation Approach continuum Quadrant 4: Innovation is driven by need Quadrant 2: Innovation is driven by need extreme: Emergent and happens from necessity coupled to and happens from necessity coupled to intuitive decision-making based on future decision-making based on analytics and benefits timed to match business needs data collection with formalized investment that may exist at the time decision-making methods offering insight into realistic investment returns 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Linear vs Non-Linear Environments, Author Non-2011 Linear Environments Non-Linear EnvironmentsCharacteristics and •Industrial era •Knowledge eranature •Manufacturing and production •Service and software development •Process oriented rigour •Process maturity •Disciplined engineering approach •Flexible and adaptive approach •Measurable •Measurable •Benchmarked •Benchmarked based in available data •Predictable •Unpredictable and fluid •Manageable and simple •Highly uncertain •Repeatable •Intuitive and future orientated •General and broad application •Fuzzy and complex •Fixed period project portfolios •Highly contextual and narrow application •Commoditised •Variant period project portfolios •High levels of liquidity i.e. low entry and exit •Disruptive barriers •Low levels of liquidity i.e. low entry barriers and high exit barriers 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Linear vs Non-Linear Environments, Author Non-2011 Linear Environments Non-Linear EnvironmentsAssociated evaluation •Capital Investment Decision-making Creative thinking in decisions and managementand assessment •Business cost-benefit analysis sciencestechniques •Quantitative decision-making techniques i.e. Entrepreneurship linear programming Analysis-intensive decision-making i.e. future studies, •Systems engineering and analysis following a trends and competitor analysis disciplined approach to innovation Business value pricing •Trade-off studies for application design Future benefit-based analysis i.e. Real Option •Theory of constraints removing bottlenecks in calculations, NPV, IRR the process to streamline production that Qualitative decision-making techniques i.e. fuzzy logic translate in increased levels of performance Applying innovation metrics i.e. qualitative and quantitative innovation measures through the phases Software engineering and analysis following a structured approach to innovation i.e. specific life cycle phases activities Trade-off studies for application design in feasibility stage Transformation techniques for translating non-linear into linear problems in order to apply quantitative techniques IT portfolio management Balanced scorecard approach i.e. management by deviation from objective Integrated approach to innovation i.e. CMMI for services incorporating product development, systems and software engineering practices to manage innovation Supporting management techniques i.e. change management, project management, etc. Gated innovation approach i.e. IBM framework a) BRR, b) CDR, c) TRR, and d) PRR review process or IT 2010 Symposium: GSTM value chain or funnel and gates Product line practice Copyright © 2011 mobyl design / University of Pretoria

Purposeful 3. 16. 3 1 4. 2. 21. 26. 5. 19. 25. 30. 20. 10. 8. 24. 6. 14.Innovation 13. 15. PopulatedApproach 11. 22. 17. Evaluation 9. 23. Matrix, Author 29. 4 7. 1. 2 28. 31. 2011 12. 27. Emergent Qualitative Quantitative IT Investment Decision-making Approach 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

C B A Purposeful 3. 16. 3 1 4. 2. 21. 26. 5. 19. 25. 30. 20. 10. D 8. 6. 24. 14.Innovation 13. 15. PopulatedApproach 22. A 11. 17. Adoption Matrix, 9. 23. Author 2011 29. 4 7. 1. 2 28. 31. 12. 27. Emergent D C B Qualitative Quantitative IT Investment Decision-making Approach 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

C B A Purposeful D 3 1InnovationApproach A Adoption Matrix, Author 2011 4 2 Emergent D C B Qualitative Quantitative IT Investment Decision-making Approach 2010 Symposium: GSTM Copyright © 2011 mobyl design / University of Pretoria

Research on Disciplined Innovation

by mariusvanderleek on Feb 16, 2011

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Research on Disciplined Innovation — Presentation Transcript