Research on Disciplined Innovation

MTM SYMPOSIUM:

The commercial value of disciplined innovation
in fast-moving high-tech ICT Businesses
fast- high-

Marius van der Leek
Mobyl Design
www.mobyl.com

Supervisor: 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


Introduction: The more things change, the more
they 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.


Challenge: What are those appropriate
innovation 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


Facing the Challenge: Translate findings into
practical 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


Exploratory application research and theory
testing and building a challenge in itself
Identify gaps in the
Review 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 successful
Propose 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
processes

Evaluate 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


Study outcome: Predictable results elude IT
investment 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.


Literature review: A process for critical review
of 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.
Systems
Market Strategy. Research Engineering and
Objectives for: Product Analysis.
Multi-dimensional Methods Commercial Innovation
Feasibility 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-

environments. Decision and making for optimum thinking
Quantitative IT Portfolio Management and best practice.
Management. Sciences.


Literature review: Promoting a disciplined
innovation 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),


Literature review: Promoting a disciplined
innovation 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)


First round propositions: A disciplined
commercialisation 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.


Literature review outcome: Disciplined
innovation 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.


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.


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.


Second round propositions: Investment
decision-
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.


Recommendations: Extend the study and units
although 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.


Questions


Meandering exploration outcome

Finding nr1:
Linear and
Non-Linear
Environments

Finding nr2:
SWOT and
Profile

Conclusion:
Context based
innovation
behavior
contributes to
ROIE


Three Horizons of Growth – Near, Mid- and Long Term
Mid-
Profit Targets
Source : 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


Mid-
Profit Targets
Adapted 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


Mid-
Profit Targets

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

Development



Mid-
Profit Targets

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.

Development



Lucas, H.C. Jr., 1999. Information Technology and the Productivity
Paradox: Assessing the Value of Investing in IT. Oxford University
Press, 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 cost
Required Cost of doing business Stay in business 0 – 0.5 (0.2) Lowest-cost route to enable
Managerial 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 realisation
Direct return from Structure, cost-benefit, NPV Marginal if IT investment 0.7 – 1.0 (0.9) Linear quantitative plus real
IT and IRR not leveraged OPM (non-linear evaluation)
Indirect returns Potential return but Substantial but not easily 0 – 1.0 (0.5) Evaluate non-linear
from IT qualitative benefits quantifiable
Competitive Ticket to the match – cost Follower / Reactive model 0 – 1.0 (0.2) Business value vs cost
necessity of not investing? offer marginal benefit benefit analysis
Strategic Return or benefits High potential Leader 0 – 1.0 (0.5) Future benefit non-linear
application 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-benefit
IT company philosophy model high risk non-linear evaluation


Purposeful

3 1
Innovation
Approach Evaluation
Matrix, Author
2011

4 2
Emergent

Qualitative Quantitative
IT Investment Decision-making
Approach


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


Non-
2011

Linear Environments Non-Linear Environments

Characteristics and •Industrial era •Knowledge era
nature •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


Non-
2011 Linear Environments Non-Linear Environments

Associated evaluation •Capital Investment Decision-making Creative thinking in decisions and management
and assessment •Business cost-benefit analysis sciences
techniques •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

value chain or funnel and gates
Product line practice


Purposeful

3. 16.

3 1
4.
2. 21. 26.
5. 19.
25. 30.
20. 10.
8. 24.
6. 14.
Innovation 13. 15. Populated
Approach
11. 22. 17. Evaluation
9. 23.
Matrix, Author

29.
4 7. 1.
2 28. 31.
2011

12. 27.
Emergent

Approach


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. Populated
Approach
22.
A
11. 17. Adoption Matrix,
9. 23.
Author 2011

29.
4 7. 1.
2 28. 31.
12. 27.
Emergent

D C B
Approach


C B A
Purposeful

D
3 1
Innovation
Approach A Adoption Matrix,
Author 2011

4 2
Emergent

D C B
Approach


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