Innovation talent as a predictor of business growth

Abstract

Purpose

The purpose of this paper is to explore whether innovation talent is predictive of business results. This question is important because companies exist to generate business results such as profitability and market expansion. To study this question, the authors conducted four phases of international research. They found that innovation talent is statistically predictive of business results. The Innovation Profiler (“the instrument”) is a web-based assessment tool based on the research. It was designed to detect the full array of specific innovation skills in individuals, skills that correlate with real-world business results.

Design/methodology/approach

The research presented in this paper follows four phases: a qualitative phase followed by two correlational studies; and finally, a validation research phase. The researchers wanted to answer the questions: “Is innovation talent predictive of business results?” “Which dimensions of innovation talent are most predictive of business results?” The research compares the attitudes, value and beliefs of innovators (both entrepreneurs and intrapreneurs) to the business results they achieved and compares innovators to the general population.

Findings

The research findings are that: innovation talent is highly correlated with positive business results. Innovators have significantly higher Innovation Profiler scores than the general population. Within the population of innovators, top scorers are associated with a larger number of positive business results than bottom scorers. Intrapreneurs, while sharing many characteristics with entrepreneurs, tend to score higher on innovation skills. The Innovation Profiler does not produce adverse selection bias with respect to gender or ethnicity.

Research limitations/implications

Most psychographic instruments are normative, including the Innovation Profiler; they rely on scaled responses that measure the extent to which individuals consider statements to apply to them personally. Normative instruments are faked more easily than ipsative (forced choice) measures, which ask people to choose from two to four answer options that are usually perceived as equally desirable. However, it has also been argued that the relative standing of respondents (i.e. their relative scores) in the samples is relatively unaffected by normative instruments.

Practical implications

This study provides significant statistical support for the validity of the Innovation Profiler as a predictor of innovation talent and of business results from innovation. The authors hope that by identifying the innovation characteristics that correlate with business outcomes, the authors have contributed to the field. Companies can use this knowledge to accelerate their organizational transformation.

Social implications

This research, and the Innovation Profiler based on it, enable companies to see and measure innovation talent for the first time. This talent is not held by the few and the privileged. In fact, women score as high as men and non-whites score slightly higher than whites. Innovation talent, as measured by the Innovation Profiler, can be an equalizer in the workforce. Finally, we hope that this paper helps companies attract more innovators into their workforce and to recognize and use more of their valuable skills.

Originality/value

To the authors’ knowledge, this is the first study to ask. “Can we predict the business results from innovation based on who is involved?” After extensive review of the literature, the authors have not found any other study asking this question. This study is also novel for: including intrapreneurs and entrepreneurs; and for including samples across the Americas, Europe, Asia and Africa. The study demonstrates a strong relationship between innovation talent and positive business results, with effect sizes that appear to exceed personality and other factors.

Citation

Briganti, S.E. and Samson, A. (2020), "Innovation talent as a predictor of business growth", International Journal of Innovation Science, Vol. 11 No. 2, pp. 261-277. https://doi.org/10.1108/IJIS-10-2018-0102