Alamprotsessidest, protsesside variatsioonidest ja nendevahelisest koosmõjust: Integreeritud “jaga ja valitse” meetod äriprotsesside ja nende variatsioonide modelleerimiseks

Igat organisatsiooni võib vaadelda kui süsteemi, mis rakendab äriprotsesse väärtuste loomiseks. Suurtes organisatsioonides on tavapärane esitada äriprotsesse kasutades protsessimudeleid, mida kasutatakse erinevatel eesmärkidel nagu näiteks sisekommunikatsiooniks, koolitusteks, protsesside parendamiseks ja infosüsteemide arendamiseks. Arvestades protsessimudelite multifunktsionaalset olemust tuleb protsessimudeleid koostada selliselt, et see võimaldab nendest arusaamist ning haldamist erinevate osapoolte poolt. Käesolev doktoritöö pakkudes välja integreeritud dekompositsioonist ajendatud meetodi äriprotsesside modelleerimiseks koos nende variatsioonidega. Meetodi kandvaks ideeks on järkjärguline äriprotsessi ja selle variatsioonide dekomponeerimine alamprotsessideks. Igal dekompositsiooni tasemel ning iga alamprotsessi jaoks määratletakse esmalt kas vastavat alamprotsessi tuleks modelleerida konsolideeritud moel (üks alamprotsessi mudel kõikide või osade variatsioonide jaoks) või fragmenteeritud moel (üks alamprotsess ühe variatsiooni jaoks). Sel moel kasutades ülalt-alla lähenemist viilutatakse ja tükeldatakse äriprotsess väiksemateks osadeks. Äriprotsess viilutatakse esmalt tema variatsioonideks ning seejärel tükeldatakse dekompositsioonideks kasutades kaht peamist parameetrit. Esimeseks on äri ajendid variatsioonide jaoks – igal äriprotsessi variatsioonil on oma juurpõhjus, mis pärineb ärist endast ja põhjustab protsesside käivitamisel erisusi. Need juurpõhjused jagatakse viide kategooriasse – ajendid kliendist, tootest, operatiivsetest põhjustest, turust ja ajast. Teine parameeter on erinevuste hulk viisides (tegevuste järjekord, tulemuste väärtused jms) kuidas variatsioonid oma väljundit toodavad. Käesolevas töös esitatud meetod on valideeritud kahes praktilises juhtumiuuringus. Kui esimeses juhtumiuuringus on põhirõhk olemasolevate protsessimudelite konsolideerimisel, siis teises protsessimudelite avastamisel. Sel moel rakendatakse meetodit kahes eri kontekstis kahele üksteisest eristatud juhtumile. Mõlemas juhtumiuuringus tootis meetod protsessimudelite hulgad, milles oli liiasust kuni 50% vähem võrreldes tavapäraste meetoditega jättes samas mudelite keerukuse nendega võrreldes enamvähem samale tasemele.Every organization can be conceived as a system where value is created by means of business processes. In large organizations, it is common for business processes to be represented by means of process models, which are used for a range of purposes such as internal communication, training, process improvement and information systems development. Given their multifunctional character, process models need to be captured in a way that facilitates understanding and maintenance by a variety of stakeholders. This thesis proposes an integrated decomposition-driven method for modeling business processes with variants. The core idea of the method is to incrementally construct a decomposition of a business process and its variants into subprocesses. At each level of the decomposition and for each subprocess, we determine if this subprocess should be modeled in a consolidated manner (one subprocess model for all variants or for multiple variants) or in a fragmented manner (one subprocess model per variant). In this manner, a top-down approach of slicing and dicing a business process is taken. The process model is sliced in accordance with its variants, and then diced (decomposed). This decision is taken based on two parameters. The first is the business drivers for the existence of the variants. All variants of a business process has a root cause i.e. a reason stemming from the business that causes the processes to have differences in how they are executed. The second parameter considered when deciding how to model the variants is the degree of difference in the way the variants produce their outcomes. As such, the modeling of business process variations is dependent on their degree of similarity in regards to how they produce value (such as values, execution order and so on). The method presented in this thesis is validated by two real-life case studies. The first case study concerns a case of consolidation existing process models. The other deals with green-field process discovery. As such, the method is applied in two different contexts (consolidation and discovery) on two different cases that differ from each other. In both cases, the method produced sets of process models that had reduced the duplicity rate by up to 50 % while keeping the degree of complexity of the models relatively stable

Analysis templates for identifying improvement opportunities with process mining

Process mining tools help analysts in conducting a data-driven analysis of business processes. However, identifying improvement opportunities is still a manual task that depends largely on analysts’ expertise and experience with process analysis and process mining tools. In this paper, we present a set of templates that aid analysts in systematically identifying improvement opportunities with process mining tools. Based on review studies, we identified 22 improvement opportunities that can be identified from process logs. Then, we conducted a content analysis of 129 business process intelligence challenge submissions to elicit how improvement opportunities can be identified. Based on this data, we developed 21 templates that guide process analysts in identifying improvement opportunities using Apromore as a process mining tool. We evaluated the templates by combining interviews with survey methodology. The survey evaluation indicates that the templates are useful (score 4.37/5) and easy to use (4.65/5) for identifying improvement opportunities with Apromore

Criteria and Heuristics for Business Process Model Decomposition - Review and Comparative Evaluation

It is generally agreed that large process models should be decomposed into sub-processes in order to enhance understandability and maintainability. Accordingly, a number of process decomposition criteria and heuristics have been proposed in the literature. This paper presents a review of the field revealing distinct classes of criteria and heuristics. The study raises the question of how different decomposition heuristics affect process model understandability and maintainability. To address this question, an experiment is conducted where two different heuristics, one based on breakpoints and the other on data objects, were used to decompose a flat process model. The results of the experiment show that, although there are minor differences, the heuristics cause very similar results in regard to understandability and maintainability as measured by various process model metrics

The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

A Meta-analysis of Gene Expression Signatures of Blood Pressure and Hypertension

Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p&lt;0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%–9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension