Business Architecture Flexibility as a Result of Knowledge-Intensive Process Management

Gromoff, Alexander; Bilinkis, Yulia; Kazantsev, Nikolay

doi:10.1007/s40171-016-0150-4

Cited by 19 publications

(5 citation statements)

References 21 publications

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“…BPM use several standards for process design, deployment, execution, maintenance and optimisation of processes that can be divided into a structure, semi-structured and non-structured processes (Gromoff et al, 2017). One of the standards used to facilitate BPM is achieved by the BPM, which is specialised on describing how activities interact and relate with each other (Martins and Zacarias, 2017).…”

Section: Business Process Managementmentioning

confidence: 99%

Return of investment initiatives in business process management

Pereira¹,

Sabido²,

Santos³

2021

IJBIR

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This study aims to verify the perception of business process management (BPM), namely benefits, maturity, budget in the company and qualitative factors that make it difficult to measure and to understand the relevance of return on investment (ROI). It is also intended to create a conceptual model that makes it possible to evaluate the valorisation of BPM within an organisation. The results indicate that BPM has gained higher relevance and maturity in organisations, being noticed through the high range of budget that is allocated to BPM initiatives, as well as the higher outsourcing services and internal teams. Regarding the barriers of ROI's implementation, the one which is the most common one was the top managers. This study had limitations at the sample level and for future research these limitations should be overcome with the study of the dependency between economic value added and earnings per share and BPM budget variables using ROI.

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Section: Business Process Managementmentioning

confidence: 99%

Return of investment initiatives in business process management

Pereira¹,

Sabido²,

Santos³

2021

IJBIR

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“…Sallos, Yoruk, and García‐Pérez () presented a framework of process improvement based on knowledge intensity and knowledge management concepts. Gromoff, Bilinkis, and Kazantsev () reviewed two concepts knowledge‐intensive processes and process management for developing a new compound approach. In last, Sarnikar and Deokar () developed a knowledge management system based on knowledge‐intensive processes.…”

Section: Literature Reviewmentioning

confidence: 99%

Applying clustering and classification data mining techniques for competitive and knowledge‐intensive processes improvement

Khanbabaei

Alborzi

Sobhani

et al. 2019

Knowl Process Manag

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Processes as one of the valuable knowledge resources can create sustainable competitive advantages in organizations. There is a large number of processes in organizations. They generate a high volume of process data that leads to the high‐dimensionality problems, complex relationships, dynamic changes, and difficulties in the understanding of the process by human resources. Traditional process improvement methodologies have weaknesses in environment with the large number of processes. Data mining techniques can support process improvement in this environment. They can recommend the improvement suggestions through extracting valuable patterns from a high volume of the process dataset. Recently, knowledge‐intensive processes have been increasingly concentrated in the field of process improvement. These types of processes can induce a competitive behavior over the other processes. The main problem is the improvement of competitive and knowledge‐intensive processes in a high volume of process dataset. The main purpose of this paper is to present a model to identify the behavior of competitive and knowledge‐intensive processes and recommend improvement suggestions. For this purpose, data mining techniques are applied to extract valuable patterns hidden in a high volume of process dataset. In this regard, K‐means clustering and C5 classification algorithms are applied to extract valuable patterns. A real process dataset was used to evaluate the effectiveness and applicability of the model. The results confirmed that the proposed model can apply data mining techniques to support competitive and knowledge‐intensive process improvement in a high volume of process dataset.

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“…Gromoff et al [37] outline multiple problems around KIP management in a survey made on 98 russian companies. The problems concerned the process transparency, missing links between KIP events from one instance to another one, few knowledge-intensive control making reporting inefficient, absence of knowledge-intensive change management reducing the predictability, and no system approach hindering the support from the other parts of the organizations.…”

Section: A Extension Of Bpm For Kipmentioning

confidence: 99%

“…Supporting collaboration and creativity is not a priority for them. An excess of control or formalization has a negative impact on knowledge workers and KIP [37]. [22] offers help for informal communications, but solutions for collaboration support in highly-controlled environments are yet to be developed.…”

Section: B How To Support Collaboration and Context-specific Decision Making For Kip?mentioning

confidence: 99%

Challenges in Knowledge Intensive Process Management

Boissier

Rychkova

Grand

2019

2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW)

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Processes where knowledge is a key characteristic are called knowledge intensive processes (KIP). A successful KIP has to adapt for the situation and to treat each customer's request as unique rather than to follow some predefined sequence of actions. The discipline of Business Process Management (BPM) defines solutions for modeling, development, analysis and improvement of processes with a predefined flow of activities. From the traditional, activity-centered point of view, KIP are challenging to automate, to control and to test for compliance.In this article we present the overview of recent works that address the challenges and explore different ideas, including extension of BPM, theoretical foundations for KIP management and execution support for KIP. We also outline some research perspectives in KIP management and discuss one particular idea that exploits the data-centered point of view on KIP.

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Business Architecture Flexibility as a Result of Knowledge-Intensive Process Management

Cited by 19 publications

References 21 publications

Return of investment initiatives in business process management

Return of investment initiatives in business process management

Applying clustering and classification data mining techniques for competitive and knowledge‐intensive processes improvement

Challenges in Knowledge Intensive Process Management

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