Mind the gap Linking (telco) forecasting to innovation management Drs. Patrick A. van der Duin Delft University of Technology, Faculty of Technology, Policy, and Management Geneva, October 25-26, 2004 p.vanderduin@tbm.tudelft.nl 1
How to improve forecasting? 1. Better and more methods, data, tools, experts, etc. 2. Combining different methods 3. Better linkage to decisionmaking: • context • uncertainty in telco-industry 2
Contents • 1. Forecasting & futures research • 2. Telecom and the future • 3. Managing innovation • 4. Linking innovation & forecasting • Case: Lucio • 5. Concluding remarks 3
1. Paradox of the future “The more turbulent and dynamic our timeframe, the more need there is to know the future, but the more difficult it is to know the future” 4
1. Why look into the future? Relation between need of looking into the future and the (im-) possibility of immediate organisational and strategic change t high low 0 t Need of futures Possibility of research immediate 1 organisational and strategic change low high 2010 2002 5 Depends on type of business TIME
1. The playing field of futures research The future is The future is completely completely knowable : unknowable : history = future: history ≠ future: no need for futures research futures research has no use and is not needed Playing field of futures research 6
1. Forecasting as part of futures research predicting predicting/exploring exploring Forecasting Trend-analysis Scenarios Causal models Cross-impact Trendwatching S-curve Backcasting Visioning ……. ……. ……. Tools: Delphi, brainstorming, Group Decision Room, SPSS, Group Model Building, expert-interviews, 7 workshops, deskresearch. …
1. Forecasting & scenarios The future can The future is be known very difficult to know history ≈ history ≠ future: future: the Scenarios future can be the future can predicted only be explored Forecasting Playing field of futures research 8
1. Scenarios and forecasting Y Scenarios Forecasting now - x TIME now now + x 9
1. Problems with forecasting Clusters of factors: Factor and author: Fascination with the exotic: a bias toward the optimistic and a disregard for reality (Schnaars, Too much 1989); emphasis on Price-performance failures: many technologies deliver lesser benefits at greater costs than technology push: anticipated (idem); Too much influence of peope who have a financial stake in a new technology (Brody, 1991). Enmeshed in the Zeitgeist: too much focused on one technology and its presumed benefits Influence of (Schnaars, 1989); contemporary Ultimate uses unforeseen: rarely do forecasters anticipate applications fully (idem) Market researchers who survey the wrong people, i.e. companies who produce a new thinking or technology (Brody, 1991). interests: Expectations may be biased by the broader cultural concerns of the time (Geels & Smit, 2000). ‘ Assumption drag’: using ‘old’ assumptions in predictive models (Ascher, 1978). Neglect of Ultimate uses unforeseen: rarely do forecasters anticipate applications fully (Schnaars, 1989). change: Sudden new trajectories in technological developments may trigger shifts in future images (Geels & Smit, 2000); Forecasts about new technology are often positioned as replacing old technology (idem); The neglect of of the generation of new activities by assuming that the pool of e xisting activities (idem). Shifting social trends: changing demographic trends and social values are not well Neglect of considered (Schnaars, 1989); social change: Too many stress on ‘functional thinking’ and neglecting the ‘fun’ of doing things, such 10 as shopping (Geels & Smit, 2000); Viewing the societal embedding of new technologies as unproblematic (idem); New technology promise high societal gains but prove later too be unrealistic (idem).
1. Forecasting & market research Diffusion-process Innovation- process ? Forecasting 11 Market research
1. Futures research & market research = futures research = market research “Globalization” “Have & Have Transactional not’s” environment competitors Contextual environment organisation organisation legislation “Moore’s unions Law” actors & suppliers developments from other industries “Low econ. growth world 12 trade”
1. From process-experts to content-experts: a continuum Process- Content- expert expert Forecaster Innovator Process-experts: ?? Content-experts: Naisbitt, Toffler, Negroponte, etc. Competences: Competences: • knowledge and access to much • knowledge of methods and data/information their application • communication skills • process and facilitating • high status (sometimes even capabilities capable of realizing self-fulfilling prophecies) • organizational distance 13
2. Gartner’s hype cycle “E” is Best 2006-2008 E-business Ends European Dot.Com Share IPOs 1999 Fall-Out US Xmas Investor Disillusion 1998 Bricks & Mortar US IPOs Post Net Failures 1997/8 Businesses Dot.Com Shake Out Dot.Com Starts Business Disillusion Optimized Internet E-Business WWW “True” E-Business Emerges Peak of Technology Inflated Trough of Slope of Plateau of Trigger Expectation Disillusion Enlightenment Profitability 1990-96 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 14
2. Divergence and/ or convergence Telephony, fax Mobile telephony “Telecom” “Telecom” Video- teleshopping/ phony -working Mobile VoD Devices office MM desktop Video automation telecom Interac- Personal tive TV Computer Television digital TV Movie MM PC “Computer” “Computer” “Media” “Media” 15
2. Telecom layers MARKET SERVICES/ DEVICES MIDDLEWARE TECHNOLOGY 16
2. Different time horizons telco-industry/ company Network operator 10 years ‘ unbundling’ doesn’t ? solve this problem! Service provider 5 years ? 1 –2 years 17 Retail
2. Different uncertainties telco market shares ‘Old’ 4G network planning 18 Four notions of uncertainty theorized by Courtney, Kirkland and Viguerie 1997
2. Pearson’s uncertainty map high Applications engineering: Exploratory research: New 3G services 4G services Uncertainty about output (ends) Combining market Development opportunities with engineering: technical capabilities: Telco standards new SMS-services 19 low high low Uncertainty about process (means)
2. Forecasts and their consequences Consequences: Uncertain consequence: Certain consequence: Type of trend: Uncertain trend: ‘unbundling’ ‘telco network crash’ Certain trend: ‘millenium-problem’ ‘lower investments in telco networks’ 20
2. Forecasting & decisionmaking Correct forecast Incorrect Quality of forecast forecast Usage of forecast Forecast is used Correct decision Wrong! Type II for decision error Forecast is not Wrong! Correct decision used for Type I error decision 21
3. Futures research & innovation: I nnovation takes time!! forecasting How will the future look like? Will my current idea still be a good idea in the future ? backcasting So, what do I have to time start developing now? 22 Based on: Brian Twiss (1992)
3. Things are going fast….. 23
3.…but not always that fast…. “If, over the past 30 years, the automotive and aircraft industries developed at the same rate as have chips that power PCs, a Rolls-Royce would cost $ 2.75 and a Boeing 767 would cost $ 500 and could circle the globe in 20 minutes on 5 gallons of gas.” 24
3. Forecasting and innovation Twiss, 1992: Stage of the Technology forecasts innovation process Importance Accuracy Financial effect of error Idea generation High Medium Low Technical High Medium Low feasability Design & Low High Medium development Preparation for Very low High High production & marketing Post launch - - - 25
3. Forecasting and the innovation-proces (1 st gen.) : Trend analysis Forecasting idea concept plan pilot roll-out Scenarios Backcasting 26
3. Historical overview of generations of innovation- management (1): • 1e generation: 1950 – 1970 • technology (science) push; linear innovation-process; R&D institutes resemble organisational structure of universities; no link with strategy; market-aspects implemented too late; no professional project- management • 2e generation: 1960 – 1980 • market pull, linear innovation-process, project-management, R&D is re- active, not enough attention for the long term (‘incrementalism’) 27 Based on: Rothwell (1994), Niosi (1999), Liyanage, Greenfield & Don (1999)
3. Historical overview of generations of innovation- management (2): • 3e generation: 1970 – 1990 • combination market pull & technology push; link with strategy; interaction within intra- and extra organisational netwerks; only focus on product & process innovation; only focus on creation instead on exploitation • 4e generation: 1980 – now • …… 28 Based on: Rothwell (1994), Niosi (1999), Liyanage, Greenfield & Don (1999)
Recommend
More recommend
