Retrospective Analysis of Technology Forecasting: In-Scope Extension

Abstract

The purpose of this study is to obtain a larger data set of verified technological forecasts than was obtained during the previous effort (at least 1,000), which will allow us to achieve the sample size necessary to identify predictive trends and causal relationships associated with forecast accuracy if they exist. A previous study of 310 verified forecasts revealed that technology forecasts developed using quantitative methods were more accurate than were other methods, forecasts about autonomous systems and computers were more accurate than were forecasts about other technology area tags, and that while forecasts tended to be neither optimistic nor pessimistic, there was not a strong correlation between the nine attributes we studied and the accuracy of a forecast. It is the purpose of this study to reevaluate and add to those findings using a larger sample size. The Assistant Secretary of Defense for Research and Engineering (ASDR&E) is focused on developing tools and techniques to improve technological forecasting to guide future technology development. In support of these efforts The Tauri Group conducted an analysis of technology forecasting methods. The analysis will inform current and future efforts to improve forecasting, support automated methods of forecasting and, and establish a performance baseline against which new forecasting methods and tools can be compared.

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Document Details

Document Type
Technical Report
Publication Date
Aug 13, 2012
Accession Number
ADA568107

Entities

People

  • Carie Mullins

Tags

Communities of Interest

  • Advanced Electronics
  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Transportation
  • Computers
  • Data Mining
  • Data Science
  • Data Sets
  • Databases
  • Geographic Regions
  • Information Science
  • Land Transportation
  • Metal Matrix Composites
  • Neural Networks
  • Predictive Modeling
  • Regression Analysis
  • Statistical Analysis
  • Supervised Machine Learning
  • Surveys
  • Technology Forecasting

Readers

  • Computational Modeling and Simulation
  • Economics
  • Regression Analysis.

Technology Areas

  • Autonomy