42
F. Firouzi et al.
In general, the Internet of Things helps to gather data regarding the status of
the physical world. This could be the condition of machines or other equipment,
inventories in a warehouse/whereabouts of goods. Those data can be analyzed
and leveraged by advanced machine learning algorithms and big data analytics
algorithms to optimize a company’s operations.
1.5.4 Important Aspects of Implementation
The three IoT-based business opportunities pose different challenges for companies.
But in general, they require a significant change in the company’s business model.
While changing a business model is a serious management challenge already, business model innovation poses various additional challenges. Bilgeri et al. identified
16 barriers to IoT business model innovation. They are distributed along with the
following innovation phases: idea generation, concept development and evaluation,
technical implementation, and commercialization. Many of these issues are related
to organizational questions. As already discussed, IoT solutions require continuous
efforts, e.g., in back-end operations, maintenance, and development of new features
throughout the whole lifecycle. Most incumbents from the manufacturing industry
do not have units for these tasks in their organization yet. To name another example,
IoT solutions provide the opportunity to sell services in addition to or rather than
products. However, selling services requires different skills as well as controlling
and financial mechanisms compared to selling products.
1.5.5 Data Monetization
Transforming IoT data into a marketable product is a fast-growing trend many
companies are considering as a secondary revenue source; however, the idea of
selling data is not a new one. Gartner has labeled the creation and utilization of data
or information with the term, “infonomics” [29]. With millions of smart devices
connecting to the IoT and collecting data, a new market based on data providers
and data customers has been born (see Fig. 1.7). Profiting from IoT data can be
approached in two ways [30]:
• Direct Data Monetization – Regardless of why you may be willing to offer your
raw data, there are probably consumers interested in using and paying for your
data. While there are many ways to sell data, a primary means is through a data
marketplace. When selling data, direct monetization is generally separated into
two categories [30]:
– Selling Raw Data – Direct access to data (i.e., APIs or data sets) is provided in
trade for cryptocurrency or money. There are two general marketplaces from
F. Firouzi et al.
In general, the Internet of Things helps to gather data regarding the status of
the physical world. This could be the condition of machines or other equipment,
inventories in a warehouse/whereabouts of goods. Those data can be analyzed
and leveraged by advanced machine learning algorithms and big data analytics
algorithms to optimize a company’s operations.
1.5.4 Important Aspects of Implementation
The three IoT-based business opportunities pose different challenges for companies.
But in general, they require a significant change in the company’s business model.
While changing a business model is a serious management challenge already, business model innovation poses various additional challenges. Bilgeri et al. identified
16 barriers to IoT business model innovation. They are distributed along with the
following innovation phases: idea generation, concept development and evaluation,
technical implementation, and commercialization. Many of these issues are related
to organizational questions. As already discussed, IoT solutions require continuous
efforts, e.g., in back-end operations, maintenance, and development of new features
throughout the whole lifecycle. Most incumbents from the manufacturing industry
do not have units for these tasks in their organization yet. To name another example,
IoT solutions provide the opportunity to sell services in addition to or rather than
products. However, selling services requires different skills as well as controlling
and financial mechanisms compared to selling products.
1.5.5 Data Monetization
Transforming IoT data into a marketable product is a fast-growing trend many
companies are considering as a secondary revenue source; however, the idea of
selling data is not a new one. Gartner has labeled the creation and utilization of data
or information with the term, “infonomics” [29]. With millions of smart devices
connecting to the IoT and collecting data, a new market based on data providers
and data customers has been born (see Fig. 1.7). Profiting from IoT data can be
approached in two ways [30]:
• Direct Data Monetization – Regardless of why you may be willing to offer your
raw data, there are probably consumers interested in using and paying for your
data. While there are many ways to sell data, a primary means is through a data
marketplace. When selling data, direct monetization is generally separated into
two categories [30]:
– Selling Raw Data – Direct access to data (i.e., APIs or data sets) is provided in
trade for cryptocurrency or money. There are two general marketplaces from