Boehlje, Michael

Gramig, Benjamin M.

Gray, Allan W.

Roucan-Kane, Maud

English

Research Papers in Economics

The Innovation Process:  
Practices in Food and Agribusiness Companies 
 
 
 
 
 
Authors 
Maud Roucan-Kane (mroucan@purdue.edu) 
Allan Gray 
Benjamin M. Gramig 
Michael Boehlje 
 
 
 
 
 
 
 
Department of Agricultural Economics 
Purdue University 
403 West State Street 
West Lafayette, IN 47907 
 
 
 
 
 
 
Poster prepared for presentation at the Agricultural & Applied Economics Association 2010 
AAEA,CAES, & WAEA Joint Annual Meeting, Denver, Colorado, July 25-27, 2010 
 
 
 
 
Copyright 2010 by Roucan-Kane, Gray, Gramig, and Boehlje. All rights reserved. Readers may 
make verbatim copies of this document for non-commercial purposes by any means, provided 
that this copyright notice appears on all such copies. The Survey
The survey was created and administered online using software called Qualtrics. The survey was extensively pre-tested with different people of 
diverse expertise. It was administered in December 2009 and sent out to 849 top executives of agribusiness companies. The survey included a 
number of questions about the innovation process (the functional areas and the selection methods used), the portfolio, and the company. 136 
people filled out the survey, resulting in a response rate of 16%. Of the 136 surveys, 109 surveys were usable. These respondents represented 
several ag sub-industries, revenue ranges, governance structures, and scopes. 
Cross-functional Teams
Respondents were asked to select all the functional areas involved in the selection of innovation projects for their company. The categories offered 
to them were executives, marketing, research and development (R&D), sales, and other. The results are presented in Figure 2. On average, 
respondents selected 3.36 functional areas (out of 5) suggesting the existence of somewhat cross-functional teams with the most likely pairs being 
sales and marketing (correlation of .285) and executives and marketing (correlation of .226). Nonetheless, seven respondents reported involving 
only one functional area (R&D or executives) in the selection process.
Introduction
Brown and Teisberg (2003; p1) stated that “Innovation is the lifeblood of successful businesses. […] [It] has become every firm’s imperative as 
the pace of change accelerates.” Executives acknowledge the strong need for innovation; they are still challenged by translating great ideas into 
revenue sources (Huurinainen, 2007). Figure 1 presents a framework that summarizes some of the theories that have been brought forward to 
help executives deal with this challenge. Cross-functional teams have been defined in the literature as a group of people with different functional 
specialties or skills that are responsible for carrying out all phases of the innovation process. The innovation literature has been advocating the 
use of cross-functional teams to allow for a smoother and higher-performing innovation process (e.g., Cooper et al., 2004; Christensen et al., 
2004). In addition, numerous R&D project selection methods such as graphical analyses, structured assessments, and economic models have 
been proposed to help organizations. The ultimate goal of cross-functional teams and selection methods is to assist companies in their innovation 
process and help them achieve a portfolio of innovation projects that is diversified. 
Company  
and Industry  
Characteristics
Cross-functional Teams Selection Methods
Innovation Portfolio
Figure 1. A Conceptual Framework for the Innovation Process
Figure 2 hides some significant differences by company and industry characteristics. Specifically, the sales department is more likely to be selected 
by smaller firms (in terms of revenue, scope, and governance structure) likely because smaller firms tend to be more sales focused. Surprisingly, 
firms committed to innovation differ from other companies only by the fact that they are less likely to involve the sales department maybe because 
they are concerned that sales representatives will be biased by being too short term and sale focused. 
The table below provides five different levels of uncertainty in the 
potential return of innovation projects. What is your estimate of 
the proportion of your company’s R&D budget that is invested in 
projects at each level of uncertainty?
What are the percentages of your company’s product innovation projects with:
Figure 4. Innovation Portfolio of Food and Agribusiness Companies
Selection Methods
Figure 3 shows the distribution of answers to the question “Which of the following portfolio management selection methods best describe 
your company’s primary selection process? (Please check the 3 most important methods.)” The majority of the respondents (53%) 
selected 3 methods, 23% selected 2 methods, and 24% selected 1; resulting in an average of 2.27 selection methods. Nonetheless, 23% 
of the companies rely on one method: 12% reported using only informal methods; 6% checked only economic models; 5% selected only 
structured assessments. 
Smaller firms (in terms of revenue) use more informal methods, while larger firms use more economic and structured methods maybe 
because of differences in resources. Publicly traded firms are more likely to use economic models and structured methods and less likely to 
use informal methods, potentially because of the shareholder’s interest for dividends. Surprisingly, firms committed to innovation do not 
differ from firms not committed to innovation, which was not expected. 
The selection process is also found to be different by sub-industry. The food sub-industry is less likely to use graphical models. The crop 
protection sub-industry is more likely to use economic models, while the animal nutrition sub-industry is more likely to use graphical 
methods and less likely to use structured methods. The animal nutrition sub-industry also tends to use more selection methods. A 
discussion of these results with an executive in the food and agricultural sector suggests that the food sub-industry tends to focus on 
incremental innovation (e.g., a line extension), which is not too risky and may not require complex, formal analyses. In animal nutrition, 
products are often regional and may not justify lengthy analyses. Finally, crop protection is highly regulated and approvals are expensive and 
time consuming, which may explain the additional emphasis on modeling.
Characteristics of the Innovation Portfolios
The portfolio is analyzed over five dimensions: return, capability, time to market, risk of technical/regulatory failure, and sunk costs. These 
five dimensions and their levels (low/high, the five distributions, …) were chosen based on an extensive review of the innovation literature, 
as well as intensive phone interviews with top executives of eight agribusiness companies in different sub-industries and of different size. 
The return dimension is expressed with a distribution relative to the hurdle rate (=desired rate of return on R&D projects set by the 
company.) To the knowledge of the researcher, this study is one of the rare ones, if not the only ones, that provides such quantitative 
findings on innovation portfolio characteristics. 
On average, companies in the food and agricultural sector have a diversified portfolio with regards to return, with some bias toward high 
returns, low-risk of technical/regulatory failure, and in-house projects. An analysis by company and industry characteristics shows that 
smaller firms are more biased against risky projects; they have more short-term projects and fewer technically risky projects. The results did 
not show a higher likelihood for firms committed to innovation to have more diversified portfolios over any of the five dimensions. The use 
of several selection methods, several functional areas, specific functional areas, and specific selection methods does not have much effect on 
innovation portfolios. Companies involving the sales department in the selection process are likely to have more short-term projects and 
fewer technically risky projects. 
Conclusion
Given the critical need to invest in innovation for the survival of companies, it is with no surprise that most companies report being 
committed to innovation. But, developing an efficient selection process is no small task for companies. This paper shows strong evidence 
that the innovation theory is not applied to its fullest in the food and agribusiness sector. The fact that there is extensive literature on cross-
functional teams, selection methods, and portfolio diversification suggests that either companies need more training on the theories or the 
theories are not adapted to the real world. Future research should therefore focus on determining the difficulties companies are facing when 
trying to apply the theory and when the theory is failing. This research provides a significant contribution to the literature through the 
portfolio characteristic, showing that food and agribusiness companies have diversified portfolios at least over some dimensions.  
The characteristics of the portfolio, as well as the practices in terms of functional areas and selection methods, do vary with company and 
industry characteristics.
References
Brown, J. S. and E. Olmsted Teisberg (2003). “Options Thinking for Leading Innovation.” University of Virginia, Darden School of Business.
Christensen, C. M., S. D. Anthony, E. A. Roth (2004). “Seeing what’s next: Using the Theories of Innovation to Predict Industry Change.”  
  Harvard Business School Press, Boston Massachussets. 
Cooper, R.G., S. J. Edgett, E. J. Kleinschmidt (2004). “Benchmarking best NPD practices—II.” Research-Technology Management, 47 (3), 50–59.
The Innovation Process: Practices in Food and Agribusiness Companies
by Maud Roucan-Kane, Dr. Allan Gray, Dr. Benjamin Gramig, and Dr. Michael Boehlje
Contact Author: Maud Roucan-Kane | mroucan@purdue.edu
Center for Food and  
Agricultural Business
Figure 3.
Figure 2.

The Innovation Process: Practices in Food and Agribusiness Companies

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