208
From one perspective, these challenges are daunting and may seem insurmountable. Yet this setting is not new to mankind and, from a historical perspective, is
more the norm rather than the exception. If society is to maintain itself and advance,
agricultural innovation is essential. Indeed, 50 years ago, eminent scholars employing sophisticated mathematical models confidently predicted that within a decade
massive famine caused by chronic food scarcity would characterize the world’s
future (Meadows et al. 1972). However agricultural innovation, along with other
changes in society, rose to the challenge and led to reductions in the number of
malnourished in the world.
Today, new tools such as digital technology and big data are being developed and
applied within agricultural production systems. Effective implementation of these
tools offers unprecedented capabilities to fuel innovation and contribute to our
response to the challenges just noted. (These terms will be described more fully
later in this chapter.) It is important to recognize both (1) that their implementation
is itself a key form of innovation and (2) that the use of these technologies can foster
additional innovation by making existing innovation systems even more effective
(Sonka 2016).
While an exciting prospect, the extent and impact of the use of these technologies are themselves uncertain. The purpose of this chapter is to explore that potential for effective implementation. A managerial, not a technological, perspective
will be employed as the primary lens for this chapter.
1
A key premise of this perspective is that the existence of a technology does not guarantee immediate or future
adoption nor value creation for its users and the market. Rather, the extensive use of
technology will hinge on its ability to enable managers to better achieve their goals.
These managers can be operating in either the public or private sector or in developed or developing agricultural settings.
Framed by this perspective, this chapter contains the following five sections.
First, key elements of digital technology and big data will be described and the most
profound decision-making aspect of their application will be identified. This element can be captured by a simple question, “What is, or can be, agricultural data?”
While the capabilities of technologies being developed are continually more
advanced, the use of what is commonly known as precision agriculture has been in
process for the last two decades. Those experiences and lessons learned will be the
subject of the second section which follows. The term “big data” has become common throughout much of society, although the term’s meaning is not well defined.
In next section of this chapter, the characteristics of big data are identified and particular attention is devoted to the central role of analytics. The fourth section of this
chapter will depict the digital agriculture that is emerging. Also, that concept will be
linked to the broader needs and opportunities associated with the adoption of digital
technologies throughout the food system. A brief concluding section ends this
chapter.
1 Other perspectives are relevant to the application of digital technologies and big data in agriculture. Space limits preclude their analysis here. For example, Weersink et al. (2018) explore environment implications and Wiseman et al. (2018) consider data ownership and management issues.
S. T. Sonka
From one perspective, these challenges are daunting and may seem insurmountable. Yet this setting is not new to mankind and, from a historical perspective, is
more the norm rather than the exception. If society is to maintain itself and advance,
agricultural innovation is essential. Indeed, 50 years ago, eminent scholars employing sophisticated mathematical models confidently predicted that within a decade
massive famine caused by chronic food scarcity would characterize the world’s
future (Meadows et al. 1972). However agricultural innovation, along with other
changes in society, rose to the challenge and led to reductions in the number of
malnourished in the world.
Today, new tools such as digital technology and big data are being developed and
applied within agricultural production systems. Effective implementation of these
tools offers unprecedented capabilities to fuel innovation and contribute to our
response to the challenges just noted. (These terms will be described more fully
later in this chapter.) It is important to recognize both (1) that their implementation
is itself a key form of innovation and (2) that the use of these technologies can foster
additional innovation by making existing innovation systems even more effective
(Sonka 2016).
While an exciting prospect, the extent and impact of the use of these technologies are themselves uncertain. The purpose of this chapter is to explore that potential for effective implementation. A managerial, not a technological, perspective
will be employed as the primary lens for this chapter.
1
A key premise of this perspective is that the existence of a technology does not guarantee immediate or future
adoption nor value creation for its users and the market. Rather, the extensive use of
technology will hinge on its ability to enable managers to better achieve their goals.
These managers can be operating in either the public or private sector or in developed or developing agricultural settings.
Framed by this perspective, this chapter contains the following five sections.
First, key elements of digital technology and big data will be described and the most
profound decision-making aspect of their application will be identified. This element can be captured by a simple question, “What is, or can be, agricultural data?”
While the capabilities of technologies being developed are continually more
advanced, the use of what is commonly known as precision agriculture has been in
process for the last two decades. Those experiences and lessons learned will be the
subject of the second section which follows. The term “big data” has become common throughout much of society, although the term’s meaning is not well defined.
In next section of this chapter, the characteristics of big data are identified and particular attention is devoted to the central role of analytics. The fourth section of this
chapter will depict the digital agriculture that is emerging. Also, that concept will be
linked to the broader needs and opportunities associated with the adoption of digital
technologies throughout the food system. A brief concluding section ends this
chapter.
1 Other perspectives are relevant to the application of digital technologies and big data in agriculture. Space limits preclude their analysis here. For example, Weersink et al. (2018) explore environment implications and Wiseman et al. (2018) consider data ownership and management issues.
S. T. Sonka