Rethinking BPM in Cognitive World

Running head: RETHINKING BPM IN COGNITIVE WORLD
RETHINKING BPM IN COGNITIVE WORLD
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RETHINKING BPM IN COGNITIVE WORLD
Table of Contents
Introduction....................................................................................................................2
Discussion......................................................................................................................2
Cognitive computing and business process management..........................................2
Capabilities of cognitive computing in business process management.....................3
Advances of BPM with the Human centric processes...............................................4
Evolvement of BPM platforms..................................................................................5
Framework for cognitive BPM..................................................................................6
Conclusion......................................................................................................................7
References......................................................................................................................8

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RETHINKING BPM IN COGNITIVE WORLD
Introduction
This report aims to discuss rethinking BPM in cognitive world using relevant articles
and other materials. A brief discussion of how cognitive computing is helping in transforming
the business process management is presented in the report. Finally, this report settles with an
suitable conclusion for the report.
The assurance that is provided by the cognitive computing in the present world is to
primarily transform the corporate data and the problem answering. Cognitive computing
intends to convey the continuous learning and autonomous reasoning by considering the
natural interaction of the machines and humans and the contextual insights (Hull and Nezhad
2016).
Discussion
Cognitive computing and business process management
In the present world, significant importance has been given to the Cognitive
Computing in the businesses and in several industries. Cognitive Computing generates the
insights that are context aware from the unstructured and structured data by leveraging the
continuous learning and the autonomous reasoning on the basis of the expanding of the base
of knowledge and by building on latest developments on data, computer science and
cognitive. The area of BPM comprises of the topics of context awareness, automation of the
unstructured tasks and flexibility and it is commonly believed that the features of cognitive
computing have immense impact on the transformation of the BPM and the practices in
future (Nezhad and Akkiraju 2014). For the effective lifecyle of BPM that is based on the
paradigm and it is essential to understand the potential of the cognitive computing in context
of BPM. The new lifecycle of BPM integrated with cognitive computing would support the
processes that ranges from the extensively standardised processes of routine for lower
predictable processes of ad-hoc. The aspect of cognitive BPM includes the aspects of BPM
where the cognitive computing provides the innovative opportunities either with the
alteration of the methods how the processing of data is done, the presentation of the data and
the designing of the processes is done (Roeglinger et al. 2017).
As an instance, it can be considered that the cognitive management of data would fuel
the automation of process with the integration of machine learning, providing the businesses
with the potential of massive returns in the area of the SMAC (social, mobile, analytics,

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RETHINKING BPM IN COGNITIVE WORLD
cloud), the processes that are smarter are more than any tool for the planning and execution;
they are the intelligence engine that provides decision making with cognitive intelligence that
is based on the operational insights in the context (Kannengiesser et al. 2014). With the
combination of the business process with machine learning, the cognitive solutions are
obtained that has the ability of enhancing the experiences of customers. The solutions has the
ability of comparing the data that is generated by the activities of business with the data from
several other sources, providing the dynamic and the decision making that is sensitive to the
context. In any process of predictive maintenance, the algorithms of machine learning are
applicable for the data of sensor for identifying the situations that indicates whether the
breakdown of any machine is imminent (Hull 2017). The cognitive process of business would
ensure the insights from several devices undergoes efficient processing and that the field
service team is completely utilised in most suitable way. These insights would help in the
improvement of the optimisation of the processes by the automatic releasing of any remote
patch for any device or by offering guidance to the customers with steps of self-service.
Capabilities of cognitive computing in business process management
The bifurcation of the capabilities of cognitive computing can be done by:
Enhancement of the optimisation and decision making: The introduction of cognitive
computing provides the processes of businesses to undertake decisions on the behalf of
humans on the basis of the rich experience and the huge amount of unstructured data
(Lapouchnian et al. 2017). While dealing with huge unstructured information, the cognitive
systems has the ability of injecting the insights based on intelligence in the processes of
decision making. With the exploitation of the capabilities of adaptive and predictive decision,
value is added to the preventive decision making. The cognitive interactions improves the
communication channels by supporting the new devices and channels. For example, the
individuals can be guided by the system through a conversation or process and then
effectively leverage the channel preferences of the person. Afterwards, the interaction is
done, the results can be communicated for an orderly and clear post-analysis (Motahari and
Shwartz 2017).
Advancement in the intelligent automation: The cognitive process has the capability
of processing the interactions among the humans over several preferred channels of
communication. Exploiting the ML and AL, the systems can effectively capture the insights
and then codify the specifications of process and then reveal the new opportunities of