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May Sobczak
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In what situations would any of you use an asynchronous sub-process as opposed to the start process smart service. Based on my understanding, because the smart service will better balance the execution engines without any other negative impacts - I don't see the scenario where I would ever use an asynchronous sub-process. Can someone please elaborate if there is something that I may be missing?
Asynchronous subprocesses are still a little less painful to actually use, owing to a few potential factors but the biggest (i assume) being that the Start Process smart service is quite a bit newer overall. Given that I spend much of my time monitoring and troubleshooting existing process instances, I build with the consideration that drilling down through subprocess layers (as well as defining subprocess parameters) tends to be a lot more straightforward with the subprocess node. Thus for me at least, the start process node is only prioritized for use in cases where a particularly heavy load will be placed on that particular subprocess call - like bulk instances or things that would typically be fired hundreds of times per day. In most other cases, the performance gain from using Start Process would be so mild that it isn't worth the extra configuration and monitoring hurdles.
The Call Integration smart service allows you to call any integration object from within your process model. This is particularly important for integrations that modify data since they cannot be called in expressions elsewhere in your model.
To speed up development, Appian can preconfigure this smart service for you. Search for your integration object, and drag and drop the integration object to the process model canvas. The Call Integration smart service node is automatically created and configured to reference that integration object. Open the process node's properties to further configure its behavior.
However, a sync will not automatically occur when you use this smart service to update data in any other web service. To sync changes made in other web services (besides Salesforce), use the Sync Records smart service.
The remainder of the paper is structured as follows. Section 2, reviews the core properties of smart products and the Internet of Things and discusses their implications on conceptualizing smart service and smart service systems. Section 3, we provide an overview of the empirical cases we analyzed in order to support and enrich our conceptual arguments. Section 4, presents our conceptualization of smart service systems, which is informed by the preceding literature review and expert interviews. In Section 5, we discuss the theoretical implications of smart service systems on other constructs in service science. Section 6 concludes the paper.
We argue that not all of these properties must be present in each smart product. For instance, smart immobile goods (e.g., manufacturing equipment) might not require being locatable through sensors and might not include invisible computers beyond their operating systems and automation technologies. Similarly, smart consumer goods (e.g., wearables) might not need to have sophisticated actuators to change their physical appearance or data storage and computational capabilities.
Data analysis was conducted in a two-step process. In the first step, we applied open coding (Saldaña 2009) to identify text fragments from the interview transcripts that were potentially relevant to characterizing smart products. This process was open-ended and was not influenced by any a priori constructs. In the second step, we used focused and elaborative coding (Saldaña 2009) to identify and group the identified text fragments and relate them to our a priori categories (i.e., properties of smart products and smart service). The outcomes of the interviews were then used, in combination with the findings of the literature review to conceptualize and illustrate the properties of smart service systems (Section 3).
The first company we studied, Metallurgic Plants, Inc. (all company names in this paper are pseudonyms), offers machinery, services, and entire turnkey solutions for metallurgical plants, especially steel mills. The smart products in focus were machines used in steel factories, each equipped with automation technology and sensor networks that produce a continuous stream of measurements about the production process (e.g., temperatures, velocities) and the machine's status. These these capabilities enable Metallurgic Plants, Inc. to offer various types of smart services, such as condition monitoring, process monitoring, quality documentation, and predictive and remote maintenance. The informant at Metallurgic Plants, Inc. was the Head of Sales and Distribution of Services and the Chief Service Manager.
Automobile, Inc. is one of the best-selling makers of luxury autos in the world. We conducted two interviews, each with a unique focus. The first interview focused on smart connected cars, which assist drivers in finding their routes and parking spaces efficiently and conveniently. Connected cars can be tracked from a distance by electronic means so preventive maintenance measures can be undertaken if anomalies occur, while data can also enable remote unlocking and usage documentation. The informant was the Head of Consumer Management of the Digital Services and Digital Business Models unit.
The smart products that were the focus of the second interview at Automobile, Inc. were automated production technologies for the manufacturing of automobiles, such as robots that insert windows into cars. These machines host dozens of sensors for controlling and documenting the manufacturing processes, which enables Automobile Inc. to offer services like statistical quality control, energy consumption management, and safe human-machine cooperation. The interviewee was a mechanical engineer in the Pre-Development department.
Energy Solutions, Inc. is a multinational company that offers technology for energy grids and home appliances for energy management in buildings. The interviews focused on smart meters that are used for routing energy through the high-voltage energy grid, but additional questions on smart meters in homes extended the scope from the business-to-business to the business-to-consumer domain. The products Energy Solutions, Inc. offers implement all features of smart products. The interviews highlighted that the company envisions implementing even more elaborate data storage and analysis capabilities in its products in the near future in order to make local decisions that impact the routing of energy through the net. Smart meters could also be equipped with invisible computers in order to make data on energy consumption available for managing the energy grid, such that energy supply and demand can be levelled, and personalized pricing models can be established. The interviewee at Energy Solutions, Inc. is a specialist for the analysis of smart data, autonomic computing, and process automation.
In line with the service blueprinting approach (Shostack 1982; Kingman-Brundage 1989), the two roles are divided by a line of interaction and by two lines of visibility. The line of interaction separates the activities service consumers perform from those service providers perform. It delineates the value-in-use captured, the activities performed, and the resources owned by the two roles that can be taken over by actors in a smart service system. The lines of visibility separate activities and resources that are visible to other actors in a service system from those that are not, thereby determining what data and functionality can be enacted by the actors involved.
Our conceptualization of smart service and smart service systems synthesizes and complements earlier thinking by focusing on the inner workings of how value-in-use can be derived from using a smart product as a boundary object between a service's consumers and its provider. With this conceptualization, we contribute to integrating disparate streams of research. On the one hand, the service science literature has focused on the co-creation of value in service systems (Maglio and Spohrer 2008; Maglio et al. 2009; Vargo and Lusch 2004a, b, 2008a, b) without explicitly building on the properties of smart products or their role in service systems. On the other hand, the literature on smart objects in an Internet of Things (Allmendinger and Lombreglia 2005; Acatech 2011, 2015; EPoSS 2008; Estrin et al. 2002; Perera et al. 2014; Satyanarayanan 2001) has focused on the technical aspects of connecting objects with each other and with information systems, without recognizing the implications for provider-customer interactions and value co-creation. In this sense, our paper takes a boundary-spanning role by bridging the gap between previously unconnected communities in research and practice (Wenger 1998).
The second implication has to do with the remote control, re-configuration, updating, and personalization of smart products. Using smart products as platforms for offering additional services facilitates networking activities and resources beyond the one-directional analysis of field data. We argue that closing the loop of monitoring and reacting to field data from a smart product impacts many of the taken-for-granted concepts on which co-creation in service systems is based. In particular, we conclude that using smart products as boundary objects at the interface of service consumers and service providers alters the "line of interaction" between them. In particular, this use of smart products leads to technology-mediated interactions, continuous interactions, and routinized interactions:
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