Business Process Management Assignment: Transformation With Advancement of Cognitive Computing
Question
Task:
From the Proceedings of the 14th through 16th International Conference on Business Process Management (BPM), select one specific conference track as per your preference and formulate a creative topic of your own. The topic must be directly relevant to business process engineering or business process management.
Your task is to produce a 3500 words research on business process management assignment which discusses the issues relating to the above. The paper should demonstrate a depth and breadth of reading and should be appropriately referenced.
Answer
Introduction:
This report on business process management assignment is going to discuss about Business Process Management with the help of technological computations. With the advancement of new technologies, Cognitive Computing is also increasing and various specialized technologies such as natural language processing as well as artificial intelligence machine learning. These technologies are also merging up with the business. This topic is taken from the 14th International Conference of Business Process Management which had several discussion topics, and this is one of them(Aalst, 2020). “The Transformation of BPM with the Advancement of Cognitive Computing” going to be discussed here. The primary focus of this report will be in three aspects of the transformation (Workshops et al., 2020). They are cognitive computing that enables “knowledge acquisition at scale”, from which the transformation in Knowledge-intensive Processes can be obtained, the study of new process meta-model that will center around “Plan-Act-Learn” cycle and also learning descriptions which are implicit, opening new opportunities from the emerging technology and the support of business processes. Through these discussions, the basic features of Business Process Management are being discussed. Through this report, we will also see how Cognitive Computing is impacting the Business Process Management and how experiential learning is used to improve the ability of systems. The report shall provide an overview of the Cognitive Computing and then shall discuss upon the Effect of Cognitive Computing on Business Process Management. The business process management assignmentshall also discuss the four pillars of the cognitive computing and the impact of Robotic Process Automation Process in BPM and shall provide the challenges faced by the BPM process due to the implementation of cognitive computing.
Overview of Cognitive Computing
Combination of Cognitive computing with several other fields such as knowledge interpretation, as well as automated planning and software-as-a-service can completely transform the ecosystem of BPM in the most basic ways. The “knowledge acquisition at scale” will be enabled by cognitive computing and it is getting the guidance of developingtechniques for understanding the natural language as well as machine learning. Furthermore, the nature of the Knowledge-intensive Procedures will also be changed which includes the process meta-model and the shift related to it. Both design- and run-time are learnt and focussed with the advancement of cognitive learning(Anwer and Siddiqui, 2019). Through all these, new opportunities are being opened for automation at a new level and also supporting several business processes. The research on the BPM has been expanded largely in several directions and also supports the business processes flexibly. The entire business process management assignmentwill go layer by layer discussing, comparing and contrasting different perspectives and presenting arguments to support the purpose of the report by using relevant case studies to illustrate key points. After the entire description of the report in the body structure, lastly, the summary of the points that are already made in the body of the report will be discussed in the conclusion part. This report on business process management assignmentwill mainly describe the advances made in recent research, identifying the key researches and the challenges that are made to go forward with this emerging technology.
Effect of Cognitive Computing on Business Process Management
In this section, discussion will be made about the impact that Cognitive Computing has made on Business Process Management and to do that various processes of trade processes as well asevolving trends in the given field of cognitive computing, are also being discussed. The three types of business processes are transaction-intensive handling, judgment-intensive procedures and layout and planassistanceprocedures. In the transaction-intensive processing, the well-defined processes are being discussed which can be executed several times and to explain it further we can take typical examples which are week-to-workweek payroll handling, accounts receivables and the management of supply chain. All these examples are available within the enterprise and various other examples like online purchasing, self-assistance in the retail shop and also the service businesses are also included. The second type of business processes is judgment-intensive processes which concentrate on the operational work which is driven by human and many judgments are required that involves certain complex information, various organizations and the systems (Ieeexplore.ieee.org. 2020).
explain it further, some of the examples are explained which several processes have included likehandling new sales connections, completing project management for large scale Information Technologyand the investigation of several fraudulent activities. Apart from that, Case Management which is adaptive is also developed so that all these kinds of processes can be supported and also using spreadsheets, several manual procedures can be managed. The third type of business process is the design and strategy support processes in which collaborative work are involved which are creative and open-minded(Asree, Cherikh and Gopalan, 2018). The various stages of mergers and acquisitions which are included early, nature and structure are changed in it because of the research of various new possible directions. Among all these three processes noted in the business process management assignment, both second and third category is known as “Knowledge-intensive Processes”. It is because the knowledge that is used is huge in amount and it is complex. These pieces of knowledge are gathered and manipulated accordingly in every step. These three processes are ranged from the simple to rich variety of processes(Brocke, Zelt and Schmiedel, 2016). These all are processed by humans and in the later stage, it is expected that they should be performed by machines which will be acting as a cognitive agent with a different perspective than a human brain is capable to do even though it is programmed by the human only(Cherikh, Gopalan and Asree, 2018). The transaction-intensive procedures will be dependent on the proper process version. With the combination of the cognitive approach with the BPM, the differentiation between the process model and the process instance can be made.
Before clubbing it up with the BPM and talking about the various benefits, comparisons, and contrast of it, which differentiates from the normal BPM, it is important to discuss the overview of the cognitive computing. With the advancement of technology, the new technologies are emerging which is slowly replacing the work of the human and making the business and other sectors profitable(Coccoli, Maresca and Stanganelli, 2020). One such type is Cognitive Computing. This is of technology is still emerging and there is no fixed definition to describe it informally.
It is stated herein business process management assignmentthat many multinational companies like IBM, Hewlett Packard, Deloitte and KPMG are offering opportunities and a broad scope of using Cognitive Computing and also explains how it is going to impact the whole world by emerging it and constantly updating it for making it more and more efficient for the smooth running of the businesses and the related process management. It is defined as the system that learns in a broader sense, reason with purpose and naturally interacts just like humans (Ieeexplore.ieee.org. 2020). They are not programmed explicitly. Rather through their interactions they learn and reason from the environmental experiences and interaction with humans. This technology combines with the traditional processes and overall inculcates the capabilities of becoming accessible as conventional in-store functioning systems.
When the BPM is combined with Cognitive Computing, it will be transformed in the coming years. It has a wide range of capabilities in the BPM industry and can be described efficiently through the description of four pillars(Hsin Chang, Hong Wong and Sheng Chiu, 2019). Unstructured data, Internet of Things data and new kinds of smart devices are the part of the Cognitive Computing. It will enhance on human-to-human partnership and the reason is that the innovativeabilities to consume and to reason on matters relating to natural language communication. It will also bring improvementat the time of collaborating with human-machine and this can be done through effective communication.
The understandings of the machines are done which is much better and reasoning is done. Along with it, human goals and intentions are carried out efficiently(Janiesch and Kuhlenkamp, 2019). This was all about the first layer. In the next layer, several facts are highlighted which primarily includes the applications of Cognitive computing. This is relevant in the conventional BPM and Case administration context. It will also ask for and will also allow new classes of Business Process which is not backed by process mechanisation(Miri-Lavassani and Movahedi, 2018). The next generation of BPM will be accelerated at the time of arrival by the Cognitive Computing and fundamentally developed by enabling a new family of process concepts. This will help much richer, more adaptive, more active,and more user-responsivetypes of the synchronization of processes.
What are the pillars of cognitive computing described in the business process management assignment?
Among the four pillars that are associated with it, every pillar has a certain perspective. Cognitive Decision Support is the first pillar(Mofokeng and Chinomona, 2019). In this, it can be illustrated that several processes in this current period, from structured to unstructured is dependent on the efforts of human to undertakeeffective decisions and this can be based on deep experience as well as large volumes of unstructured data. With the indulgence of Cognitive Computing, it will become efficient enough to increase the quality and breadth of the decisions, broadly. The next pillar discusses about the Cognitive Interaction. The BPM is associated with human interaction as it is limited to screens and they are also dependent on restrictive sequencing of steps. Human-computer interactions, which are multi-modal, are advanced and the opportunity of Cognitive computing is becoming richer(Pattanayak and Punyatoya, 2019). These are because of the improvements with interactions dramatically and all these are done by supporting new interaction channels and devices.
The new styles of work which are done in collaboration are enabled and the formulations of goals are done. Also, the decisions are made with the participation from cognitive agents who are active. The third pillar mentioned in this section of business process management assignment is related to Cognitive Process Learning. In this, the implicit description of processes is done in various ways like purpose-built records as well as digital exhaustand system logs(Pradabwong et al., 2017). Cognitive Computing is implemented in the structured to unstructured processes, and it can help to capture and the specifications of processes are codified. It also enables automation more and more while retaining the flexibility requisitely. In the last or fourth pillar, Cognitive Process Enablement is discussed. In this, process model and process instance are separated and is found in classical BPM and Case Management. It is cognitively rich. Different styles of the business process are supported that puts the users back in charge(Szelagowski and Berniak-Wo?ny, 2019). The event-driven of the underlying process model is high and the ongoing formations of goals are focused on, relevant pieces of knowledge including constraints are learnt and also the making of efficient decisions and planning are done.
Robotic Process Automation in BPM:
The use of Cognitive Computing in the BPM at the marketplace is made these days. The industry incorporates automation into business operations. Robotic Process Automation is the term that is used overall and the three classes of automation are referred. Firstly, the Basic Process Automation is used which mainly focuses on the automation of the manual tasks and the rules engines are also applicable to structured data(Page, Soyata and Sharma, 2020). This is made available to the company for many years. Secondly, Enhanced Process Automation is used as the Cognitive Decision Support pillar and is used essentially. It is made available and is still maturing. The third stage identified herein business process management assignment is Autonomic or more appropriately Cognitive and is the pillar of process learning and Process Enabling. Different industries adopted this in different periods depending upon the work which they do in their respective companies. Cognitive Computing, also, helps to enable the abstractions for cognitively-enabled BPM(Mahmood and Aloul, 2020). It also identifies various features that are taken part in this paradigm. Judgment-Intensive and Design and Strategy are the main criteria which are described here in this area of discussion. Also, Transaction-Intensive processes are described which has more knowledge-intensive portions. Also, it is known that cognitive techniques can be used for automatically shifting through vast amounts of data which is unstructured and correspondingly harvested for the knowledge in huge amount related to the process instance. Hence, the readings covered in this segment of business process management assignment signify that it brings the possibility of knowledge at scale. Abstraction can also be defined to enable the support in a systematic process for the wide range from structured to unstructured processes.
Also, cognitively-enabled business processes has several key building blocks which includes knowledge, including Constraints, goals or sub goals, agents which includes both human and machine, decisions, actions, plans and events. All these can be explained in a proper manner to become easier to understand. The first building block is knowledge, which also includes constraints and is a new element that is brought by the Cognitive Computing to BPM. This is mainly related to costs, resource availability, timing, limits are allowed and behavior. Along with these various other factors are involved. Other factors such as time, decisions that affect impact and planning are the constraints. The next key building block is goal or sub goals which is the main concept and is cognitively-enabled business processes. Advancement of the initial top level goals are made, the goals are added and formulation of sub-goals are done dramatically, environmental related events are also based on, the context are currently made, learning’s are all newly created, practices are done in the best way possible and the other factors are also given. Another key building block is agent. This agent is including both human and machine as it is the key on which cognitively-enabled processes will be centered around. They have several features like intentions which are varying, rolesand all the specialties(Anbar and Alieyan, 2020). These agents can be collaborated and is rich and on-going. In this, the communication may be analyzed after capturing and the future aspects of the processes are also used. These agents will further make decisions depending upon the information and the knowledge that can be acquired through the processes. Various new goals can be created and achieved through these decisions to take actions and also for planning (Brocke, Zelt and Schmiedel, 2016).
Automation and enhancement of processes are needed to be geared from the learning and it also includes the Project Management which is semi-automated, acquisition of knowledge which is proactive and activities of human which can be guided. The next is the supporting flexibility through the Plan-Act-Learn cycle, which have a context of acquisition of knowledge at scale and a huge distance is there between the high-level proposals as well as the context which is robust in nature and technology base on which the benefits are supported. The next is the Trust which includes explanation, testing and the adjustments that are made manually. The element called trust is very vital for the successful automation of any processes. With the help of cognitively-enabled BPM, these tools and techniques are developed and along with that confidence building components are also included at broader levels. Overall, all the findings that this business process management assignmenthas derived from the decided topic are properly mentioned in this conclusion and thus it can be seen how the cognitive Computing creates an impact in the Business Process Management and is which manner they does that. It also explains in details the concept of Cognitive Computing in depth to make the reader understand how they help the businesses and its process management in several ways.
Agents take the actions in a cognitively-enabled process and can have the corresponding side-effects in the environment externally and also the new learning can be derived from it. Plans are also made as the part of the planning procedures and they consists of several actions depending upon the work which is to be done in the company who is associated with this to make profits in their businesses by using this technology and its advantages. Several new information are derived with every new decisions that are made over the time period. Plans are created often in lesser times, modified and can also be updated after the action is taken, within the plan (Janiesch and Kuhlenkamp, 2019). This is the major reason mentioned in the business process management assignment why the decisions are made. Another key building block is the events as these kinds of processes which are clubbed with the cognitive computing are highly event-driven and is also feasible because of the high flexibility process model. Because of the automated cognitive agents, also, they are feasible and will rapidly analyze the significance of the events which are incoming, rapidly (Pradabwong et al., 2017). External environment can be the place from which they are derived from and the analysis of information or acquisition of knowledge or the agent’s decision can be the results which are derived from.
Challenges faced in implementing Cognitive Computing
The challenges that are faced and are implicitly described are the causes of the significant impediment to the business process automation that are occurring these days. Many aspects of these processes can be learnt automatically by the cognitive agents through cognitive computing. Also, these kinds of learning can be merged with the process enablement through which are judgment-intensive and design and strategy support. They also provide recommendations and guidance throughout (Mofokeng and Chinomona, 2019). Apart from this processes of learning in three dimensions can be considered from various sources like the data which was structured, documents which are built with purpose and also from digital exhaust which are unstructured. In this business process management assignment, regarding this topic, the several cases like the structured and the unstructured ones are separated. But when they were practically implemented, these are combined and the data sources which are structure were available in a variety. It is connected with the processes which are described implicitly (Asree, Cherikh and Gopalan, 2018). The core processes are logged and also provides the wealthy information. Apart from this, process mining techniques can also be applied so that process models can be learnt in which both the core processes are underlined. Along with these processes, ancillary processes are also learnt and applied. Cognitive learning is very important to get a broad understanding holistically of the process in overall even though the process mining work is mostly focused into. These are inclusive of the manipulation of data and the data and processing constraints (Cherikh, Gopalan and Asree, 2018).
In case of transaction-intensive and design and policy support procedures also, similar techniques can be applied, even if the log data is available in less amount. Less or semi-structured information’s can be contained in the logs and log data which is available may be difficult to derive and find. Till now, the report on business process management assignment described the structured data perspective. Purpose-built documents are also one kind which the unstructured data is consisted of. And it is the creation of documents to describe various processes specifically and documents are also included to give certain guidelines which are highlighted including the descriptions which are in best practice, policies are made in a formal manner for corporate use and also the regulations made by the respective government (Ceur-ws.org. 2020). Digital exhaust is another kind of data which is considered an unstructured and all sort of documents and other digital records which are made available. For executing the process instances these are created while execution and can also include process emails by the participants. From both these kinds of unstructured data, techniques can be emerged for these processes which are in the learning processes. Applying text analyst to the regulations made by the government to derive the rules and process constraints for ensuring compliance is the sub-area that is emerging. In the natural language processing, the combination of both statistical and rules-based approaches are made in which the sentences are classified for holding regulatory information and also the rules-based approaches are used in these processes.
To look after the actual processes that aims at carrying out tradeprocessesin an effective way, Cognitive Process Enablement is used and the process modeling level is considered here. Both classical BPM process can be impacted by the cognitive computing and the Plan-Act-Learn is followed by these processes as a meta-model (Mahmood and Aloul, 2020). Also, it is seen that cognitive BPM constructs is of much higher level than that of conventional BPM which also includes goals, planning, rules and the constraints. This constructs will be understandable by the human and executed by the machine directly or indirectly. Cognitive Computing capabilities in combination with the Pay-Act-Learn cycle can be the second element which is impacting the overall business. These can also be used in other ways through the knowledge of process that can be described implicitly and BPM constructs which is cognitive in nature can be provided in a different perspective. In this the setting of the classical BPM is made, Plan-Act-Learn can be set and can hold the efficiency of functioning the project management automatically in a larger perspective.
Conclusion:
This entire business process management assignmentis made from the topic that was taken from the 14th International Conference of Business Process Management. It describes the cognitive Computing which can be impact the overall business Process Management in several years from the present year and the emerging perspectives for abstracting the cognitive processes are primarily focused, learning of the cognitive processes, enabling cognitive processes and the findings that are made in this business process management assignmentare related to the business processes in a broader perspective, and all the three types of business proceduresand these are transaction-intensive as well as judgmental-intensive. This report on business process management assignmentalso describes various areas of challenged related to research that were brought by the Cognitive Computing to BPM. Most important research themes are related to the BPM community. First theme is the automatic learning on matters relating to Business Processes which will be learnt with the aim to design and the runtime.
Reference List
Aalst, W., (2020). Business Process Management: A Personal View | Emerald Insight. [online] Emerald.com. business process management assignmentAvailable at: https://www.emerald.com/insight/content/doi/10.1108/bpmj.2004.15710baa.001/full/html?journalCode=bpmj[Accessed 5 September 2020].
Anbar, M. and Alieyan, K., (2020). Internet Of Things (Iot) Communication Protocols: Review - IEEE Conference Publication. [online] Ieeexplore.ieee.org. Available at: https://ieeexplore.ieee.org/abstract/document/8079928[Accessed 5 September 2020].
Anwer, S. and Siddiqui, D., (2019). Business Process Management Organizational Performance and Competitiveness: The Mediatory Role of Supply Chain Collaboration. SSRN Electronic Journal,.
Asree, S., Cherikh, M. and Gopalan, S., (2018). The impact of supply chain responsiveness and strategic supply chain collaboration on innovation performance. International Journal of Business Performance and Supply Chain Modelling, 10(2), p.131.
Brocke, J., Zelt, S. and Schmiedel, T., (2016). On the role of context in business process management. International Journal of Information Management, 36(3), pp.486-495.
Ceur-ws.org. (2020). [online] Available at: http://ceur-ws.org/Vol-2420/paperDC1.pdf[Accessed 5 September 2020].
Cherikh, M., Gopalan, S. and Asree, S., (2018). The impact of supply chain responsiveness and strategic supply chain collaboration on innovation performance. International Journal of Business Performance and Supply Chain Modelling, 10(2), p.131.
Coccoli, M., Maresca, P. and Stanganelli, L., (2020). Cognitive Computing In Education. [online] Learntechlib.org. Available at: https://www.learntechlib.org/p/173468/[Accessed 5 September 2020].
Hsin Chang, H., Hong Wong, K. and Sheng Chiu, W., (2019). The effects of business systems leveraging on supply chain performance: Process innovation and uncertainty as moderators. Information & Management, 56(6), p.103140.
Ieeexplore.ieee.org. (2020). Distributed Continuous-Time Fault Estimation Control For Multiple Devices In Iot Networks. [online]business process management assignment Available at: https://ieeexplore.ieee.org/abstract/document/8613014[Accessed 5 September 2020].
Janiesch, C. and Kuhlenkamp, J., (2019). Enhancing business process execution with a context engine. Business Process Management Journal, 25(6), pp.1273-1290.
Mahmood, R. and Aloul, F., (2020). Internet Of Things (Iot) Security: Current Status, Challenges And Prospective Measures - IEEE Conference Publication. [online] Ieeexplore.ieee.org. Available at: https://ieeexplore.ieee.org/abstract/document/7412116/[Accessed 5 September 2020].
Miri-Lavassani, K. and Movahedi, B., (2018). Achieving higher supply chain performance via business process orientation. Business Process Management Journal, 24(3), pp.671-694.
Mofokeng, T. and Chinomona, R., (2019). Supply chain partnership, supply chain collaboration and supply chain integration as the antecedents of supply chain performance. South African Journal of Business Management, 50(1).
Page, A., Soyata, T. and Sharma, G., (2020). Health Monitoring And Management Using Internet-Of-Things (Iot) Sensing With Cloud-Based Processing: Opportunities And Challenges - IEEE Conference Publication. [online] Ieeexplore.ieee.org. Available at: https://ieeexplore.ieee.org/abstract/document/7207365[Accessed 5 September 2020].
Pattanayak, D. and Punyatoya, P., (2019). Effect of supply chain technology internalization and e-procurement on supply chain performance. Business Process Management Journal, ahead-of-print(ahead-of-print).
Pradabwong, J., Braziotis, C., Tannock, J. and Pawar, K., (2017). Business process management and supply chain collaboration: effects on performance and competitiveness. Supply Chain Management: An International Journal, 22(2), pp.107-121.
Szelagowski, M. and Berniak-Wo?ny, J., (2019). The adaptation of business process management maturity models to the context of the knowledge economy. Business Process Management Journal, 26(1), pp.212-238.
Workshops, C., Management, B., Rosa, M., Loos, P., Pastor, O., Business Process Management - 14th International Conference, 2., Science, L., Hull, R., Nezhad, H., Processes., R., Guizzardi, G., Guarino, N., Almeida, J., Models., O., Dongen, B., Carmona, J., Chatain, T., Anti-alignments., A., Koninck, P., Weerdt, J., Techniques., A., Janssenswillen, G., Jouck, T., Creemers, M., Depaire, B., Study., M., Lu, X., Fahland, D., Biggelaar, F., Aalst, W., Labels., H., Pedro, J., Cortadella, J., Models., D., Mannhardt, F., Leoni, M., Reijers, H., Aalst, W., Toussaint, P., Approach., F., Eck, M., Sidorova, N., Aalst, W. and Processes., D., (2020). Dblp: Business Process Management (2016). Business process management assignment[online] Dblp.org. Available at: https://dblp.org/db/conf/bpm/bpm2016.html[Accessed 5 September 2020].