People Innovation Excellence

Forecasting Innovation

by Deva P. Setiawan S.T., M.M. and Anoint Aurora Trisya (1901528160)

Everyone, every organization, and every nation are changed. In human life, nothing is never changed, except change itself. These changings are boosted through innovation in technology. It makes forecasting innovation relevant with us.
Forecasting is a valuable input to strategic and policy decision making and planning especially under conditions of environmental uncertainty.
Forecasting the future from the track records makes debated responses, but still has a central role in business planning for innovation. In the right spirit, forecasting should provide a framework for data collection and sharing; debating the interpretation; and make assumptions, challenges, and risks more explicit.
There are many different methods to support forecasting, each with different benefits and limitations: trend extrapolation, product and technology roadmapping, regression, econometric models, simulation, customer or market surveys, brainstorming, benchmarking, delphi or experts opinion, and scenario development.
There is no single best method. There will be a trade-off between the cost, time and robustness of a forecast method. Delphi method is a most favorite forecasting technique in practice as being the most reliable. However, when surveyers consider the cost of implementation, the scenario development method is rated higher.
Forecasting methods based on extrapolating past trends or based on feedback from customers or segmentation of markets are useful in the short to medium term, but fail to identify longer-term opportunities and uncertainties.
Benchmarking is useful to identify product and process improvement and innovation in the medium term, but needs relevant competitor or best-in-class candidates against which to compare systematically.
Scenario development is a powerful method to explore potential futures based on the interaction of current trends and possible future events. It can be resource-intensive, but is inclusive and transparent and therefore persuasive and support action.
In implementation, we see by employing the Innovation Readiness Level – a model integrating extant studies considering technology development and market evolution – and using the TF (Technology Forecasting), Hyoung Joon An and Sang-Jin Ahn (2015) have assessed the innovation performance of the 10 Emerging Future Technologies in Korea reported in 2009. Overcoming the chasm was considered a strategy to turn these technologies into the drivers of the national economy.
Organizational innovations become the most important determinant of success in the future. Forecasting by analogy involves the systematic comparison of the technology that will be predicted with any previous technology, which is believed to have been similar in all or most important things. Top management opinion, Delphi method and group interviews anonymous are primary approaches in new product forecasting. We also can use forecasting by analogy for web search traffic. Using the structured analogy approach, Green and Armstrong (2007) describes the judgmental procedure which uses information from conflict situations to make decisions in a way that is structured. Delphi method is used where the consensus opinion is required at the time of hope, probability and identification of the purpose of future technology or consumer needs and factors that may affect their achievement.
(References are on writers)

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