Measuring Performance in Knowledge-intensive Processes

Estrada-Torres, Bedilia; Richetti, Pedro H. Piccoli; del–Río–Ortega, Adela; Baião, Fernanda; Resinas, Manuel; Santoro, Flávia Maria; Ruiz–Cortés, Antonio

doi:10.1145/3289180

Cited by 10 publications

(8 citation statements)

References 40 publications

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“…Although a business process may change from one context of implementation to another, the way in which its performance is measured can be standardized [37]. Several frameworks and notations have addressed the definition and management of PPIs and performance measures [23], [24], [38]- [43].…”

Section: B Process Performance Indicators and Their Variability Managementmentioning

confidence: 99%

“…They also allow the analysis of whether the objectives of an organization are met and help the decision making within the organization. The modeling of PPIs seeks to provide structures and notations that allow the user to define, in a complete, understandable, verifiable and unambiguous way, how the performance of the processes will be measured [24]. Like other perspectives of business processes, the performance perspective is also susceptible to variability [25].…”

Section: Introductionmentioning

confidence: 99%

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Modeling Variability in the Performance Perspective of Business Processes

et al. 2021

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The modeling and management of business processes often leads to the definition of several variants of the same process. This variability can be reflected in different process perspectives such as control-flow, data, resources or performance. The management of process variants can be a laborious, timeconsuming and error-prone task since they require a high coordination in the management of each variant and in most cases this management is done manually. For this reason, many proposals have been developed to deal with the variability of business processes. However, none of them covers in detail the variability in the performance perspective, which is concerned with the definition of performance requirements usually specified as a set of Process Performance Indicators (PPIs). This variability can be reflected in the form of repetitive and redundant PPI definitions, and can lead to errors and inconsistencies in PPI definitions. To address this problem, in this article we propose a detailed PPI variability classification and a formalization of how PPIs can be modeled together with the variability of other process perspectives. To this end, we considered variability management approaches, called by restriction and by extension, and we illustrated our proposal by integrating it with existing variability modeling languages. An evaluation conducted in two scenarios shows the feasibility and usefulness of our proposal.

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Section: B Process Performance Indicators and Their Variability Managementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling Variability in the Performance Perspective of Business Processes

et al. 2021

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“…KIOs are based on knowledge‐intensive BPs, defined as processes in which the value is generated only by drawing on the knowledge of their performers, who perform interrelated tasks requiring making decisions on the basis of their knowledge (Vaculin et al, ; DiCiccio et al, , p. 5; Ariouat et al, ; Estrada‐Torres et al, ; Sallos et al, ). Given the unpredictability of BPs, processes to an increasing degree require the use of tacit knowledge or the creation of a new knowledge, the measure of which is knowledge intensity.…”

Section: Bpm In the Kementioning

confidence: 99%

The knowledge and process continuum

Szelągowski

Berniak-Woźny

2019

Knowl Process Manag

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The aim of the paper is to propose the concept of the Knowledge and Process Continuum, which corresponds to the changing role of Business Process Management (BPM) in Knowledge Intensive Organizations in the Knowledge Economy. The paper is conceptual in nature and is grounded in the theories of Knowledge Management (KM) and BPM. The systematic literature review method was used in order to employ a manual search of peer-reviewed papers available in the Springer and ProQuest databases. Seventeen articles were chosen for in-depth analysis, which shows the research gap with respect to the integrated application of KM and BPM. The article is an inspiring contribution to the theoretical reflection on the current state and further evolution of BPM in the Knowledge Economy and its inseparable connection with KM. The proposed conceptual framework may facilitate the management of Knowledge Intensive Organizations to effectively capitalize on the relationship between knowledge and business processes of different nature.

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“…We add the new unit of measure in our schema:C with use of rdfs:comment since each measure can have it's own unit. For future work, we plan to incorporate more advanced state-ofthe-art techniques to integrate measures into the IMD through either formal representation of the measures dependencies by means of specific predicates [13,4] or through the semantic representation of the calculation formulae of such measures [3].…”

Section: Factual Alignmentmentioning

confidence: 99%

Multidimensional Integration of RDF Datasets

Behan

Romero

Zimányi

2019

Big Data Analytics and Knowledge Discovery

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Data providers have been uploading RDF datasets on the web to aid researchers and analysts in finding insights. These datasets, made available by different data providers, contain common characteristics that enable their integration. However, since each provider has their own data dictionary, identifying common concepts is not trivial and we require costly and complex entity resolution and transformation rules to perform such integration. In this paper, we propose a novel method, that given a set of independent RDF datasets, provides a multidimensional interpretation of these datasets and integrates them based on a common multidimensional space (if any) identified. To do so, our method first identifies potential dimensional and factual data on the input datasets and performs entity resolution to merge common dimensional and factual concepts. As a result, we generate a common multidimensional space and identify each input dataset as a cuboid of the resulting lattice. With such output, we are able to exploit open data with OLAP operators in a richer fashion than dealing with them separately.

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Measuring Performance in Knowledge-intensive Processes

Cited by 10 publications

References 40 publications

Modeling Variability in the Performance Perspective of Business Processes

Modeling Variability in the Performance Perspective of Business Processes

The knowledge and process continuum

Multidimensional Integration of RDF Datasets

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