Business Strategy and Innovation Framework
reside ( at machine level , at the edge , or in IT ), the security of systems , resources , and data , and likely changes to business organization models or operational processes .
These elements will evolve over time , which means that enterprises implementing IIoT methodologies must put governance structures in place that factor in the IIoT impact across the entire business . This system of governance must focus on determining the value of IIoT within the enterprise at strategic and operational levels , and ensure a consistent implementation approach in affected areas . See section 6.1.6 for additional discussion of this topic .
3.2.3 ENHANCED DEVELOPMENT AND PRODUCTION
To ensure the continued evolution of its product and service offerings , and strengthen its competitive position , an enterprise must gain an understanding of customer needs , market needs and usage behavior . Today , in all market segments , this cycle has accelerated . Enterprises must transform their business models to reflect the way in which IIoT will enhance product development and production processes .
Within service industries , a combination of connected devices , data collection from numerous sources , and analytics will provide business insight into areas not previously considered . In the railroad industry , for example , the monitoring of railroad track and train conditions , signals , customer travel patterns and fuel consumption can produce insights that enable new or improved service offerings , enhanced safety and more efficient operations . Incorporating this potential into the business model help enterprises develop new services .
In manufacturing environments , the collection and analysis of data from connected internal devices and internal systems , and the integration of these sources , can provide similar insight to increase production efficiency and operational effectiveness . This is especially true in combining manufacturing data from connected devices with business data ( from sales , services , or supply chain contexts , for example ) to provide real-time and historical insight . Factoring this back into operations , whether historical , real-time or predictive , helps optimize production .
3.2.4 INCREASING CUSTOMER VALUE
While many advantages of IIoT solutions relate to enhancing operational efficiency and enabling new product development , a significant transformational value of IIoT lies in gaining insight that will improve overall consumer value in terms of service and product usage and overall customer experience . Those companies looking to implement IIoT projects should consider both the operational benefits and strategic value such projects bring to their business . This requires thinking outside the operational context into a view of the business and its exposure to the customer .
As an example , consider an application on a tractor . Operationally , sensors could provide information to optimize operations . Coupling in data from external sources ( such as weather , sensor data from fields , predictive yield calculations , infestation , pricing , data from local farmers ) can each add value . The combination could enhance the farmer ’ s business and operations giving a more complete and even predictive picture of how , when , what the farmer does for planting , harvesting , impacting the environment and other farm activities .
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