Technology forecasting

Source: Wikipedia, the free encyclopedia.
Futures studies
Concepts
Techniques
Technology assessment and forecasting

Technology forecasting attempts to predict the future characteristics of useful technological machines, procedures or techniques. Researchers create technology forecasts based on past experience and current technological developments. Like other forecasts, technology forecasting can be helpful for both public and private organizations to make smart decisions. By analyzing future opportunities and threats, the forecaster can improve decisions in order to achieve maximum benefits.[1] Today, most countries are experiencing huge social and economic changes, which heavily rely on technology development. By analyzing these changes, government and economic institutions could make plans for future developments. However, not all of historical data can be used for technology forecasting, forecasters also need to adopt advanced technology and quantitative modeling from experts’ researches and conclusions.[2]

History

Technology forecasting has existed more than a century, but it developed to an established subject until World War II, because American government started to detect the technology development trend related to military area after the war. In 1945, the U.S. Army Air Forces created a report called Toward New Horizons, which surveyed the technology development and discussed the importance for future studies. The report is an indication for the beginning of modern technology forecasting.

alternate reality games, online forecasting communities and obsolescence forecasting.[3]

Important aspects

"I think we have a cultural affinity for technology that reflects optimism, but we all make poor forecasts." — Jim Moore, director of the Transportation Engineering Program at the University of Southern California[8]

Primarily, a technological

transistors
in a chip in the year 2015, etc. The forecast does not have to state how these characteristics will be achieved.

Secondly, technological forecasting usually deals with only useful machines, procedures or techniques. This is to exclude from the domain of technological forecasting those commodities, services or techniques intended for luxury or amusement.

Thirdly, feasibility is a key element in technology forecasting. Forecasters should consider the cost and the level of difficulty of materialization of desires. For example, a computer-based approach “Pattern” is an expensive forecasting method which is not recommended to be used in cases of restricted funds.[2]

Methods

Commonly adopted methods and tools of technology forecasting include the

mission flow diagrams—are also commonly used. Delphi method is widely used in technology forecasts because of its flexibility and convenience. However, the requirement on reaching consensus is a possible disadvantage of Delphi method. Extrapolation can work well with enough effective historical data. By analyzing the past data, forecaster extend the past development tendency in order to extrapolate meaningful outcomes in the future.[14]

Several technology forecasting methods[15][16][17][18] base their prediction on the interaction between markets and technologies.  While technology progress enables firms to launch improved or new products, potential market provides the incentives for R&D investments and market success provides the funding for further R&D.

Combining forecasts

Studies of past forecasts have shown that one of the most frequent reasons why a forecast goes wrong is that the forecaster ignores related fields.[19] A given technical approach may fail to achieve the level of capability forecast for it, because it is superseded by another technical approach which the forecaster ignored. Another problem is that of inconsistency between forecasts. The inconsistency between forecasts reflects on the different locations and time used on controlled experiment. It usually produces inaccurate and unreliable data which leads to incorrect insight and faulty predictions.[20] Because of these problems, it is often necessary to combine forecasts of different technologies. In addition, the use of more than one forecasting method often gives the forecaster more insight into the processes at work which are responsible for the growth of the technology being forecast. Combining forecasts can reduce errors compare with a singular forecast. In the case when researches face troubles to pick a typical forecast method, combining forecasts are always the best solution.[21]

AI in technology forecasting

AI is starting to gain widespread adoption across industries, including technology forecasting. For example, an AI-powered method developed by Focus (company, based in Rotterdam, The Netherlands) uses patent data to estimate how fast emerging technologies are going to improve.

The method leverages machine learning to scan existing technologies in specified areas, filters out irrelevant ones based on user context, and finally estimates improvement speeds for each technology based on indicators hidden in patent data. The methodology behind it is based on scientific research and was developed in a collaborative effort with MIT[22]

Relative researches and Applications

Forecasting institutes

Scientific Journals

Uses in manufacturing

Technology forecasting heavily relies on data and data makes contributions to manufacturing and

Industry 4.0. IoT System provides a strong platform to make predictive analysis in the post-Industry 4.0. The advanced technologies will increase forecasting accuracy as well as reliability. As the rapid development of IoT technology, more and more industries will be equipped with sensors and monitors. The emergence of modern manufacturing changes the appearances of factories. IoT system helps managers to monitor and control the production process by collecting, tracking and transferring data. Data is powerful. Managers also can do business analysis based on marketing data. Information such as customer buying preference and market demanding could be collected and used for production estimation.[23]

Trend analysis based on current growth assumption could be used in manufacturing. The analysis strongly helps the cycle time reduction of manufacturing process and energy consumption. In this case, modern technology increases production efficiency as well as economic efficiency.[24]

Technology forecasting with technology radar

Companies often use technology forecasting to prioritize R&D activities, plan new product development and make strategic decisions on technology licensing, and formation of joint ventures.[25] One of the instruments enabling technology forecasting in a company is a technology radar. Technology radar serves to identify technologies, trends and shocks early on and to raise attention to the threats and opportunities of technological development as well as to stimulate innovation.[26]

Technology radars have successfully been implemented for the purpose of identifying, selecting, assessing and disseminating a company-wide technology intelligence.[27][26] These Technology Radars follow a certain radar process which itself brings significant value for a company:[27]

  • Identification: employees acting as technology scouts from all over the world submit novel technologies to the platform.
  • Selection: based on the technology, its potential impact and novelty, a radar team revises submitted technologies and selects the most valid ones.
  • Assessment: selected technologies are then assessed on the basis of market opportunity and implementation risk.
  • Dissemination: radar displays assessed technologies according to maturity, position in the value chain, and relevance.[28]

See also

References

  1. ISSN 0017-8012
    . Retrieved 2019-12-07.
  2. ^
    ISSN 1474-6670
    .
  3. ^
    ISBN 978-0-309-11660-2
    .
  4. JSTOR 30076717
    .
  5. ISBN 978-1-85302-104-6
    .
  6. ISSN 0040-1625
    .
  7. S2CID 16720975
    .
  8. ^ Lufkin, Bryan (6 July 2016). "Five transport promises that never quite changed the world". BBC. Archived from the original on 2016-07-09.
  9. ^ Brock, David C. (2006). Understanding Moore's Law: Four Decades of Innovation. Chemical Heritage Foundation.
  10. ISSN 0148-6411
    .
  11. doi:10.1016/j.techfore.2016.09.014
    .
  12. ISSN 0360-3199
    . Retrieved 21 March 2021.
  13. ^ Sylak-Glassman, Emily J.; Williams, Sharon R.; Gupta, Nayanee (2016). "Appendix C". Current and Potential Use of Technology Forecasting Tools in the Federal Government: C-1–C-4.
  14. ISBN 978-0-309-11660-2
    .
  15. ISSN 0143-2095
    .
  16. ISBN 978-0-7735-7106-8
    .
  17. ISSN 0143-2095
    .
  18. ISBN 978-965-7632-40-6
    .
  19. ISBN 978-0-470-44090-2
    .
  20. ISSN 1812-2116
    .
  21. ^ Armstrong, J. (2001-06-17). "Combining forecasts". Marketing Papers (34).
  22. ISSN 0040-1625
    .
  23. ISSN 2095-8099
    .
  24. ISSN 1877-7058
    .
  25. S2CID 14340682. Archived from the original
    (PDF) on 2019-02-28. Retrieved 24 February 2020.
  26. ^
    S2CID 27061994
    .
  27. ^
    doi:10.1016/j.techfore.2014.07.014
    .
  28. ^ "Technology Radar | An opinionated guide to today's technology landscape". Thoughtworks. Retrieved 2024-06-05.

External links

Wikimedia Commons has media related to Technology forecasting.
Retrieved from "https://en.wikipedia.org/w/index.php?title=Technology_forecasting&oldid=1227424692"