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Article
Publication date: 19 January 2015

Kai Engel, Voletka Dirlea, Stephen Dyer and Jochen Graff

This article reports on the findings of the Best Innovator competition, which was launched in Germany in 2003, to identify and communicate the best practices of innovation…

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Abstract

Purpose

This article reports on the findings of the Best Innovator competition, which was launched in Germany in 2003, to identify and communicate the best practices of innovation management of the country’s businesses. After ten years of research, the contest has not only been expanded to identify the most innovative companies in much of the developed world but also to document the success of their best practices over time.

Design/methodology/approach

This article details five tested sets of best practices.

Findings

A major research finding is the strong correlation between superior innovation management capabilities and sustainable, profitable growth. Another finding was that, given the mix of industries, the diversity of businesses and the range of sizes in the Best Innovator club, it is striking that there is no correlation between R&D budget and innovation.

Practical implications

Best Innovators first develop and then manage their innovation portfolios. All of them pursue clarity on a fundamental question: what do we want our innovation strategy to do for us?

Originality/value

The researchers found that to get their innovation strategies right, Best Innovators invest upfront in understanding market, technology and service dynamics. They are investing time more than money. Leaders can learn how Best Innovators address innovation management “from the market to the market” and manipulate five areas to improve their innovation performance and propel sustainable and profitable growth.

Details

Strategy & Leadership, vol. 43 no. 1
Type: Research Article
ISSN: 1087-8572

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Article
Publication date: 16 March 2015

Kai Engel, Voletka Dirlea, Stephen Dyer and Jochen Graff

– The authors have collected key insights from the Best Innovator competition, launched in 2003. Six early-stage practices are critical.

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507

Abstract

Purpose

The authors have collected key insights from the Best Innovator competition, launched in 2003. Six early-stage practices are critical.

Design/methodology/approach

The Best Innovator competition, annual benchmarking against the best in innovation management, focuses on the how-to of innovation and examines what leading companies are doing to achieve better yield with their innovation strategies.

Findings

By studying the competition winners, the researchers found a strong correlation between specific innovation management practices and sustainable, profitable growth.

Practical implications

Best Innovators establish explicit expectations for making the business case for innovation. They name a specific set of deliverables to which they are committed.

Originality/value

The article offers specific guidelines for setting the stage for continuous innovation that results in profitable offerings and services.

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Article
Publication date: 16 March 2015

Robert M. Randall

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93

Abstract

Details

Strategy & Leadership, vol. 43 no. 2
Type: Research Article
ISSN: 1087-8572

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Article
Publication date: 19 January 2015

Robert Randall

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132

Abstract

Details

Strategy & Leadership, vol. 43 no. 1
Type: Research Article
ISSN: 1087-8572

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Article
Publication date: 16 March 2015

Catherine Gorrell

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145

Abstract

Details

Strategy & Leadership , vol. 43 no. 2
Type: Research Article
ISSN: 1087-8572

Content available
Article
Publication date: 19 January 2015

Catherine Gorrell

Downloads
134

Abstract

Details

Strategy & Leadership, vol. 43 no. 1
Type: Research Article
ISSN: 1087-8572

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Book part
Publication date: 15 March 2021

Jochen Hartmann

Across disciplines, researchers and practitioners employ decision tree ensembles such as random forests and XGBoost with great success. What explains their popularity…

Abstract

Across disciplines, researchers and practitioners employ decision tree ensembles such as random forests and XGBoost with great success. What explains their popularity? This chapter showcases how marketing scholars and decision-makers can harness the power of decision tree ensembles for academic and practical applications. The author discusses the origin of decision tree ensembles, explains their theoretical underpinnings, and illustrates them empirically using a real-world telemarketing case, with the objective of predicting customer conversions. Readers unfamiliar with decision tree ensembles will learn to appreciate them for their versatility, competitive accuracy, ease of application, and computational efficiency and will gain a comprehensive understanding why decision tree ensembles contribute to every data scientist's methodological toolbox.

Details

The Machine Age of Customer Insight
Type: Book
ISBN: 978-1-83909-697-6

Keywords

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