Internet Of Things and Process Yields Big Dividends
Combining the Internet of Things (IoT) with process will be a big deal throughout the next five years or more. I have already seen the benefit of the combination of the two of these, even in early days (see the two case studies highlighted at the end of this article). The IoT has three basic interactions with process.
1. Incoming Signals and Patterns
Processes can act on any signal or pattern, either through internal or external complex event processing (CEP) technologies. Today, the number of signals and patterns that processes have to deal with are pretty low in number, but the prognosticators are predicting at least an order of magnitude increase in the number of incoming signals and patterns. This is the traditional sense of a response design pattern, which is reactive in nature.
2. Outgoing Signals
Processes can direct or orchestrate a variety of resources, from machines to people. Also, smart processes can run predictive analytics to send out signals to any of these resources, which can act independently or in collaboration with other resources. In this pattern the process is the proactive initiator of the need for resources to respond.
3. Interactive Behavior
With interactive behavior, the process can sense or emit signals interactively. In advanced situations resources can collaborate in a machine-to-machine (M2M) fashion, a human-to-human fashion (H2H), a human-to-machine fashion (H2M), or a machine-to-human fashion (M2H). All of these styles can interact with each other to accomplish business outcomes.
Net; Net
The type and amount of intelligent business operations that can be created by the combination of process and the Internet of Things is being expanded. This is one of the key new enablers in the digital organization's tool box for optimizing operations and raising more revenue.
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Smart Farm Operations One of my favorite smart processes manages farm production levels. The process optimizes moisture/fertilizer balance for specific terrains and plants. The Challenge: In order to step up food production in a significantly arid area of the world, new methods and processes will have to be established to apply fertilizer in optimum ways, considering present and future moisture levels customized by crop type. The Solution: By leveraging point measurements throughout the terrain of the farm, combined with local and national moisture models, five large farms have increased crop production up to 40% by having processes direct fertilizer applications and, in some cases, apply mechanical watering techniques. This is a highly summarized and anonymous case study provided by Appian. |
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Smart Medical Operations Another of my favorite smart processes is one that manages an outpatient surgical center. The Challenge: This organization wanted to find a balanced optimization that leveraged resource utilization with the best patient care. Quite often one of these suffers at the expense of the other. In fact, this organization defined an extended patient care that included the people accompanying the patient, in that they were given visibility into progress in near real time. The Solution: Each resource is tagged with sensors that were readable throughout the facility. This included patients, relatives/friends, medical personnel, and equipment. A visual simulation is run to show optimal throughput and positive outcomes. Once a goal (one amongst many) is sensed to be in jeopardy, a re-simulation with adjusted goals is run with a new visual dashboard representing the new goal balance. There are many reasons for optimal goal balances to be in jeopardy, including medical personal being interrupted, equipment not being ready, patients being late, expected recoveries being slower than expected, etc. But this process is smart enough to deal with re-balancing and real time visibility. This is a highly summarized and anonymous case study provided by Bosch. |
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