Tools for Innovation Management – Introduction & Technology Forcasting

1. Tools for Innovation Management – Introduction & Technology Forcasting Prasada Reddy Lund University, Sweden

2. Introduction – Concepts 1 • Technology and Competitiveness? • What is Technology? • What is Technological Change? • What is Innovation? • What is Research and Development (R&D)?

3. Introduction – Conepts 2 • Basic Research – aimed to increase scientific knolwdge relating to a phenomenon purely for its own sake. • Applied Research – research aimed at increasing knowledge for a specific application or need. • Development – aimed at applying knowledge to produce tangible devices, materials, or processes.

4. Types of Innovations 1 • Product Innovations – embodied in the outputs of an organization, e.g. goods & services. • Process Innovations – innovations in the way an organization conducts its business, e.g. Manufacturing process or a service delivery. • Incremental Innovations – relatively minor changes to existing practices. • Radical Innovations – very new and different from previously known solutions.

5. Types of Innovations 2 • Competence Enhancing/Destroying Innovations – innovations that make the existing knowledge obsolete. For some they are competence enhancing and for some competence destroying (e.g. Digital photography). • Component (or modular) Innovations – innovations to one or more components that does not affect the overall configuration much. • Architectural Innovations – innovations that changes the overall design of a system or interface among components (e.g. High-wheel bicyle & Safety bicycle.

6. Innovation Management 1 • Evolutionary Forces - Technology Strategy • Generative mechanisms: a) strategic action (internal environment) - induced and autonomous; b) technology evolution (external). • Integrative mechanisms: a) organizational context (internal) - internal selection mechanism; b) industry context (external) - Porter’s five forces. • Source: Burgleman, R.A. & Rosenbloom, R.S. (1989)

7. Innovation Management 2 • Innovation Complexity • Systematic - • Scanning • Focusing • Resourcing • Implementing • Learning

8. Innovation Management 3 • Scanning: • Detection of signals in the environment about emerging developments - e.g. technological changes, market development. • Focusing: • Choosing from among a variety of emerging technology and market opportunities. • Resourcing: • Combining existing and new knowledge to offer better solutions.

9. Innovation Management 4 • Implementing: • Establishing close interaction between marketing and technical functions to transform an idea into a marketable product or service. • Learning: • Analyzing the successes and failures to fine-tune the innovation processes.

10. Selected Tools for Scanning • Market Analysis - ‘Lead-User’ Technique. • Benchmarking - comparing with the competitors and/or best-managed firm. • Competence and patent analysis - systematic analysis of patent data. • Technology forecasting - investigation of new trends. • - Foresight (creative thinking about future trends). • - Scenario writing (collection & analysis of data using various techniques).

11. Technology Forecasting 1 • Technology Trajectory – the path a technology takes through its life time. It may refer to rate of performance improvement or rate of diffusion. • S-curves: • - the rate of a technology’s performance improvement and the rate at which the technology is adapted in the market place have been shown to conform to an S-shaped curve. • - it typically shows slow initial improvement, then accelerated improvement and them diminishing improvement.

12. Technology Forecasting 2 • S-curve as a Forecasting Tool? • Firms can use data on the investment and performance of their own technologies, or data on the overall industry investment in a technology and average performance achieved by multiple producers. • Managers could then use these curves to assess whether a technology appears to be approaching its limits or to identify new technologies that might be emerging on s-curves that will intersect the firm’s technology s-curve. • Managers could then switch s-curves by acquiring or developing the new technology.

13. Technology Forecasting 3 • S-curve as a Forecasting Tool? - Limitations • It is rare that true limits of a technology are known in advance. Firms also disagree on what a technology’s limits will be. • S-shape is not fixed. Unexpected changes in the market, component- and complementary-technologies can shorten or extend the life cycle. • Firms can also stretch the s-curves through new development approaches or revamping the architecture design of the technology. • Difficulties in gathering data, particularly for the initial stages of the curve.

14. Technology Forecasting 4 • Trend Extrapolation as a tool for forecasting: • Assumes continued exponential growth. • Useful for many purposes. • Suffers from overstatement when projections are made far ahead.

15. Technology Forecasting 5 • DELPHI as a Tool for forecasting: • - Technique to collect opinions of experts in a systematic manner (same questionnaire). • - Avoids face to face interaction and thus, mutual influencing. • - Iterative: several rounds until consensus is reached.

16. Technology Forecasting 6 • DELPHI as a Tool for forecasting: • Advantages: • - avoids influence of other variables (e.g. hierarchy, commercial interests, etc.); • - based on consensus. • Disadvantages: • - time consuming (several rounds); • - retaining the interest of the experts; • - highly subjective; and • - needs complementary techniques for corroboration.

17. Technology Forecasting 7 • Modified DELPHI (Chakravarti et al., 1989): • Combination of: Scenario Writing; Delphi Questionnaire; and Response Analysis using additional written inputs; followed by a seminar for fine-tuning and short listing. • Logistic Approach - opinions should reflect the time frames in terms of introduction of new technology, its survival capacity, and its maturity. • Incorporate at the initial stages of Delphi while forming the technology scenarios by including introduction, induction and wide-scale deployment of a given technology. • Step function-based growth for ICT - technology development in these sectors does not follow sequential growth, but occurs in spurts and moves rapidly.

18. Technology Forecasting 8 • Modified DELPHI (Chakravarti et al., 1989): • Questionnaire: • - All questionnaires in each sub-area to be structured in the same way and cover variables such as time of realization, constraints for realization, prioritization of fields, etc. • - Logistic model of growth: the questions can be divided into categories: development, introduction/induction, widespread use, exploration of new technologies, and general applications for common use.

19. Technology Forecasting 9 • Modified DELPHI (Chakravarti et al., 1989): • Analysis of Responses: • - responses, both numerical and text forms to be collated and filtered for relevance to make generalizations reflecting consensus. • - numerical answers giving the probabilities to be analyzed using statistical methods, mean, median, mode and interquartile range.

20. Technology Forecasting 10 • Mean - defined as arithmetic average, used as a measure of the location for a frequency or probability distribution. • Median - the value of the middle item and higher values reflect the certainty of occurrence. • Interquartile Range (IQR) - the range of responses that includes the middle 50% and excludes the top and bottom 50% of the response; low IQR means high degree of consensus and vice versa. • Mode - represents collection of responses with similar answers and is used as an enumeration of respondents who had given 75% or more probability of an event to occur. If this value is above 50% of the total respondents, then consensus is assumed.

21. Technology Forecasting 11 • Summary of the session: • Native Indian and the Weather Forecaster