Formal Workflow Research Articles

Effect of Time Pressure on Informal Advice Relations Across Organizational Units: Evidence from a study of collaboration within a Formula One racing team

Informal advice relations across units in an organization are beneficial for knowledge sharing and problem solving. Prior research suggests that despite their benefits, there are costs to informal advice relations across units. However, the mechanisms by which these costs are mitigated remain unclear. We theorize that this lack of clarity is because work factors have not been sufficiently considered. We examine one such work factor, specifically time pressure, and develop a cost-based explanation for how time pressure influences cross-unit advice relationships. We investigate two time-pressure levels. In the first, work is conducted under lower time pressure, and there is less likelihood of a negative outcome. In the second, work is conducted under higher time-pressure conditions, and there is a greater likelihood of a negative outcome. We theorize that under lower time-pressure conditions, the costs of advice relations across units are mitigated by reciprocal advice relationships. However, under higher time pressure, the cost of informal advice relations across units is higher owing to the need for quick coordination of advice, and these costs are mitigated by reciprocal advice relationships in conjunction with cross-unit formal workflow relationships. To test our hypotheses, we examine the informal advice network and formal workflow network in lower and higher time-pressure conditions among 118 members of the Information Technology and Systems division of a Formula One racing team. Our results indicate that under lower time-pressure conditions, reciprocal advice ties are sufficient to overcome costs. However, under higher time-pressure conditions, cross-unit advice ties are facilitated by reciprocal advice ties embedded in the workflow ties between units. Thus, our findings have implications for how knowledge is managed and how problems are solved in organizations.

A FAIR and modular image‐based workflow for knowledge discovery in the emerging field of imageomics

Abstract Image‐based machine learning tools are an ascendant ‘big data’ research avenue. Citizen science platforms, like iNaturalist, and museum‐led initiatives provide researchers with an abundance of data and knowledge to extract. These include extraction of metadata, species identification, and phenomic data. Ecological and evolutionary biologists are increasingly using complex, multi‐step processes on data. These processes often include machine learning techniques, often built by others, that are difficult to reuse by other members in a collaboration. We present a conceptual workflow model for machine learning applications using image data to extract biological knowledge in the emerging field of imageomics. We derive an implementation of this conceptual workflow for a specific imageomics application that adheres to FAIR principles as a formal workflow definition that allows fully automated and reproducible execution, and consists of reusable workflow components. We outline technologies and best practices for creating an automated, reusable and modular workflow, and we show how they promote the reuse of machine learning models and their adaptation for new research questions. This conceptual workflow can be adapted: it can be semi‐automated, contain different components than those presented here, or have parallel components for comparative studies. We encourage researchers—both computer scientists and biologists—to build upon this conceptual workflow that combines machine learning tools on image data to answer novel scientific questions in their respective fields.

Automated imaging and identification of proteoforms directly from ovarian cancer tissue

The molecular identification of tissue proteoforms by top-down mass spectrometry (TDMS) is significantly limited by throughput and dynamic range. We introduce AutoPiMS, a single-ion MS based multiplexed workflow for top-down tandem MS (MS2) directly from tissue microenvironments in a semi-automated manner. AutoPiMS directly off human ovarian cancer sections allowed for MS2 identification of 73 proteoforms up to 54 kDa at a rate of <1 min per proteoform. AutoPiMS is directly interfaced with multifaceted proteoform imaging MS data modalities for the identification of proteoform signatures in tumor and stromal regions in ovarian cancer biopsies. From a total of ~1000 proteoforms detected by region-of-interest label-free quantitation, we discover 303 differential proteoforms in stroma versus tumor from the same patient. 14 of the top proteoform signatures are corroborated by MSI at 20 micron resolution including the differential localization of methylated forms of CRIP1, indicating the importance of proteoform-enabled spatial biology in ovarian cancer.

A Collaborative Emergency Medicine and Radiology Pulmonary Nodule Program: Identification of Associated Efficacy and Outcomes

PurposeIncidental radiologic findings are commonplace, but the episodic nature of emergency department (ED) care makes it challenging to ensure that patients obtain appropriate follow-up. Rates of follow-up range from 30% to 77%, with some studies demonstrating that more than 30% have no follow-up at all. The aim of this study is to describe and analyze the outcomes of a collaborative emergency medicine and radiology initiative to establish a formal workflow for the follow-up of pulmonary nodules identified during ED care. MethodsA retrospective analysis was performed of patients referred to the pulmonary nodule program (PNP). Patients were divided into two categories: those with follow-up and those who do not have post-ED follow-up. The primary outcome was determining follow-up rates and outcomes, including patients referred for biopsy. The characteristics of patients who completed follow-up compared with those lost to follow-up were also examined. ResultsA total of 574 patients were referred to the PNP. Initial follow-up was established in 390 (69.1%); 30.8% were considered lost to follow-up, and more than half of these patients did not respond to initial contact. There were minimal differences in characteristics between patients in these two categories. Of the 259 patients who completed PNP follow-up, 26 were referred for biopsy (13%). ConclusionsThe PNP provided effective transitions of care and potentially improved patient health care. Strategies to further enhance follow-up adherence will provide iterative improvement of the program. The PNP provides an implementation framework for post-ED pulmonary nodule follow-up in other health care systems and can be modified for use with other incidental diagnostic findings.

Edge-Cloud Blockchain and IoE-Enabled Quality Management Platform for Perishable Supply Chain Logistics

In perishable supply chain logistics, even a small departure from the required storage conditions at any distribution link can compromise the quality of transported products, such as food, pharmaceuticals, and other bioproducts, resulting in big losses for the businesses involved or even threats to public health. To enhance quality management (QM) and consumer confidence, an edge-cloud blockchain and Internet of Everything (IoE)-enabled QM platform is proposed to achieve low delay and rapid response for sensor data acquisition, authentication, consistency, and transparency in cold supply chain logistics. Then, we design an adaptive data smoothing and compression (ADSC) mechanism to reduce IoE data size, and analyze and store those data in the edge gateways with limited computation and storage capacity for correctly characterizing logistics operations and transactions. Moreover, to ensure the data integrity during last-mile delivery, the mobile edge gateway is adopted when the goods are temporarily off the communication range of the fixed edge gateway in the truck. Then, we propose a synchronization engine with a formal workflow applied at mobile and fixed edge gateways where data blocks are generated, validated, and synchronized with the cloud. Finally, a real-life case study on vaccine logistics is introduced to verify our proposed approach with results presented.

Creating lightweight FAIR Digital Objects with RO-Crate

Creating lightweight FAIR Digital Objects with RO-Crate

Overcoming the Challenges of Bottlenecking: Individuals’ Desire for Reducing Their Dependencies

In a field social network study of 141 employees in an international organization, I examined individuals’ future desires to either collaborate more intensely with existing network partners or seek out new partners based on the latent value of these social ties – the potential social capital that will be generated from strengthening or building a tie in terms of reducing their formal workflow dependencies on others. Employees tended to desire more intense collaboration with a constraining existing tie (i.e., a bottleneck in their existing workflow network) when they trusted the person, suggesting they believed that the partner would provide high-quality work inputs in a reliable manner once a stronger relationship was built, thus increasing the tie’s latent relational value. Building new ties was more likely to happen when it would reduce one’s workflow dependencies by detouring around the constraining person and closing disadvantageous structural holes, suggesting those new potential ties had greater latent structural value as they allow the focal individual to reach out to other workers further upstream in the workflow network. When comparing the intentions to use both approaches, the bypassing, structural approach was more prevalent than the tie strengthening approach for reducing workflow dependencies, in spite of the inherent additional costs of searching and building a new tie. The study illustrates how informal networks are used intentionally to ameliorate the deficiencies of the formal organizational workflow network and suggests the relative prominence of the latent structural value of ties as compared to their relational value.

Complex model calibration through emulation, a worked example for a stochastic epidemic model

Uncertainty quantification is a formal paradigm of statistical estimation that aims to account for all uncertainties inherent in the modelling process of real-world complex systems. The methods are directly applicable to stochastic models in epidemiology, however they have thus far not been widely used in this context. In this paper, we provide a tutorial on uncertainty quantification of stochastic epidemic models, aiming to facilitate the use of the uncertainty quantification paradigm for practitioners with other complex stochastic simulators of applied systems. We provide a formal workflow including the important decisions and considerations that need to be taken, and illustrate the methods over a simple stochastic epidemic model of UK SARS-CoV-2 transmission and patient outcome. We also present new approaches to visualisation of outputs from sensitivity analyses and uncertainty quantification more generally in high input and/or output dimensions.

Giving Your Electronic Health Record a Checkup After COVID-19: A Practical Framework for Reviewing Clinical Decision Support in Light of the Telemedicine Expansion.

BackgroundThe transformation of health care during COVID-19, with the rapid expansion of telemedicine visits, presents new challenges to chronic care and preventive health providers. Clinical decision support (CDS) is critically important to chronic care providers, and CDS malfunction is common during times of change. It is essential to regularly reassess an organization's ambulatory CDS program to maintain care quality. This is especially true after an immense change, like the COVID-19 telemedicine expansion.ObjectiveOur objective is to reassess the ambulatory CDS program at a large academic medical center in light of telemedicine's expansion in response to the COVID-19 pandemic.MethodsOur clinical informatics team devised a practical framework for an intrapandemic ambulatory CDS assessment focused on the impact of the telemedicine expansion. This assessment began with a quantitative analysis comparing CDS alert performance in the context of in-person and telemedicine visits. Board-certified physician informaticists then completed a formal workflow review of alerts with inferior performance in telemedicine visits. Informaticists then reported on themes and optimization opportunities through the existing CDS governance structure.ResultsOur assessment revealed that 10 of our top 40 alerts by volume were not firing as expected in telemedicine visits. In 3 of the top 5 alerts, providers were significantly less likely to take action in telemedicine when compared to office visits. Cumulatively, alerts in telemedicine encounters had an action taken rate of 5.3% (3257/64,938) compared to 8.3% (19,427/233,636) for office visits. Observations from a clinical informaticist workflow review included the following: (1) Telemedicine visits have different workflows than office visits. Some alerts developed for the office were not appearing at the optimal time in the telemedicine workflow. (2) Missing clinical data is a common reason for the decreased alert firing seen in telemedicine visits. (3) Remote patient monitoring and patient-reported clinical data entered through the portal could replace data collection usually completed in the office by a medical assistant or registered nurse.ConclusionsIn a large academic medical center at the pandemic epicenter, an intrapandemic ambulatory CDS assessment revealed clinically significant CDS malfunctions that highlight the importance of reassessing ambulatory CDS performance after the telemedicine expansion.

A modern method of multiple working hypotheses to improve inference in ecology.

Science provides a method to learn about the relationships between observed patterns and the processes that generate them. However, inference can be confounded when an observed pattern cannot be clearly and wholly attributed to a hypothesized process. Over-reliance on traditional single-hypothesis methods (i.e. null hypothesis significance testing) has resulted in replication crises in several disciplines, and ecology exhibits features common to these fields (e.g. low-power study designs, questionable research practices, etc.). Considering multiple working hypotheses in combination with pre-data collection modelling can be an effective means to mitigate many of these problems. We present a framework for explicitly modelling systems in which relevant processes are commonly omitted, overlooked or not considered and provide a formal workflow for a pre-data collection analysis of multiple candidate hypotheses. We advocate for and suggest ways that pre-data collection modelling can be combined with consideration of multiple working hypotheses to improve the efficiency and accuracy of research in ecology.

Globally networked: Intraorganizational boundary spanning in the global organization

Multinational corporations (MNCs) need to sense, source, and mobilize knowledge when and where it arises, whether at home, or elsewhere in the world. For this reason, MNCs benefit from employee networks of relationships that span across intraorganizational barriers, allowing for the efficient mobilization of knowledge across boundaries. Yet, which organizational members are more likely to be able to develop these boundary spanning networks? We leverage a unique data set from a large multinational corporation to empirically test a comprehensive model that captures the effect of an employee’s mandate, expertise, and behavioral orientations on her likelihood to span intraorganizational boundaries that manifest themselves in the form of hierarchies, intra-functional domains, and geographic territories. We find that the employees that are more likely to be boundary spanners are those having mandates with a global impact, high levels of expertise, and a collaborative orientation in their networking behaviors. In addition, we find that these effects are stronger for those employees that have large formal workflow networks.

Service-based information extraction from herbarium specimens

On herbarium sheets, data elements such as plant name, collection site, collector, barcode and accession number are found mostly on labels glued to the sheet. The data are thus visible on specimen images. With continuously improving technologies for collection mass-digitisation it has become easier and easier to produce high quality images of herbarium sheets and in the last few years herbarium collections worldwide have started to digitize specimens on an industrial scale (Tegelberg et al. 2014). To use the label data contained in these massive numbers of images, they have to be captured and databased. Currently, manual data entry prevails and forms the principal cost and time limitation in the digitization process. The StanDAP-Herb Project has developed a standard process for (semi-) automatic detection of data on herbarium sheets. This is a formal extensible workflow integrating a wide range of automated specimen image analysis services, used to replace time-consuming manual data input as far as possible. We have created web-services for OCR (Optical Character Recognition); for identifying regions of interest in specimen images and for the context-sensitive extraction of information from text recognized by OCR. We implemented the workflow as an extension of the OpenRefine platform (Verborgh and De Wilde 2013).

Metabolomic spectral libraries for data-independent SWATH liquid chromatography mass spectrometry acquisition.

High-quality mass spectral libraries have become crucial in mass spectrometry-based metabolomics. Here, we investigate a workflow to generate accurate mass discrete and composite spectral libraries for metabolite identification and for SWATH mass spectrometry data processing. Discrete collision energy (5-100eV) accurate mass spectra were collected for 532 metabolites from the human metabolome database (HMDB) by flow injection analysis and compiled into composite spectra over a large collision energy range (e.g., 10-70eV). Full scan response factors were also calculated. Software tools based on accurate mass and predictive fragmentation were specially developed and found to be essential for construction and quality control of the spectral library. First, elemental compositions constrained by the elemental composition of the precursor ion were calculated for all fragments. Secondly, all possible fragments were generated from the compound structure and were filtered based on their elemental compositions. From the discrete spectra, it was possible to analyze the specific fragment form at each collision energy and it was found that a relatively large collision energy range (10-70eV) gives informative MS/MS spectra for library searches. From the composite spectra, it was possible to characterize specific neutral losses as radical losses using in silico fragmentation. Radical losses (generating radical cations) were found to be more prominent than expected. From 532 metabolites, 489 provided a signal in positive mode [M+H]+ and 483 in negative mode [M-H]-. MS/MS spectra were obtained for 399 compounds in positive mode and for 462 in negative mode; 329 metabolites generated suitable spectra in both modes. Using the spectral library, LC retention time, response factors to analyze data-independent LC-SWATH-MS data allowed the identification of 39 (positive mode) and 72 (negative mode) metabolites in a plasma pool sample (total 92 metabolites) where 81 previously were reported in HMDB to be found in plasma. Graphical abstract Library generation workflow for LC-SWATH MS, using collision energy spread, accurate mass, and fragment annotation.

Most computational hydrology is not reproducible, so is it really science?

Reproducibility is a foundational principle in scientific research. Yet in computational hydrology the code and data that actually produces published results are not regularly made available, inhibiting the ability of the community to reproduce and verify previous findings. In order to overcome this problem we recommend that reuseable code and formal workflows, which unambiguously reproduce published scientific results, are made available for the community alongside data, so that we can verify previous findings, and build directly from previous work. In cases where reproducing large-scale hydrologic studies is computationally very expensive and time-consuming, new processes are required to ensure scientific rigor. Such changes will strongly improve the transparency of hydrological research, and thus provide a more credible foundation for scientific advancement and policy support.

Blending Ad Hoc and Formal Workflow Models in Support of Different Stakeholders Needs

Workflow management systems (WfMSs) also known as business process management systems (BPMSs) are increasingly popular in today’s large organizations. In spite of this popularity, many processes are still supported by ad hoc systems based, for example, on spreadsheets and homegrown databases. In particular, there is a lack of flexible process automation approaches that are able to bridge the gap between these ad hoc solutions and large-scale systems. This paper reports on a flexible WfMS and approach that blends formal and informal workflow modeling and execution, thus supporting different types of processes. We validate our work by discussing its design and implementation, and by analyzing its use in four different use cases within Siemens business units. We also discuss the role of action items as important flexibility mechanisms behind our model. Showing its ability to handle exceptions and ad hoc workflows.

Co-worker Mistreatment in a Singaporean Chinese Firm: The Roles of Third Party Embeddedness and Network Closure

This study integrates research on social networks and interpersonal counterproductive behaviours to examine the role of third party relationships in predicting an individual's susceptibility to co-worker mistreatment, and in moderating the relationship between co-worker mistreatment and job performance. Third party embeddedness and network closure are examined in the formal workflow network and the informal liking network. Results obtained from employees in a family-owned Chinese business in Singapore indicate that an individual is more likely to be mistreated by a co-worker when both parties are strongly embedded in mutual third party relationships in the workflow network, and that the individual is less likely to be mistreated when both parties are strongly embedded in the liking network. At the individual network level, network closure (i.e., the extent to which an individual's contacts are themselves connected to one another) in the workflow network increases the likelihood that a co-worker will mistreat the individual, but closure in the liking network weakens the negative relationship between mistreatment and performance. The findings offer a network-based perspective to understanding interpersonal mistreatment and counterproductive work behaviours, particularly in the context of Confucian Asian firms, and provide practical implications for organizations and individuals to reduce counterproductive behaviours at work.

Formalizing and Verifying Workflows Used in Blood Banks

Abstract Blood banks use automation to decrease errors in delivering safe blood for transfusion. The Food and Drug Administration (FDA) of the United States and other organizations recommend blood banks to validate their computer system process, which is resource and labor intensive. For this reason, we have created a formal workflow model for blood bank operations and used an automated tool to verify that it satisfies safety properties. Our methodology started by understanding and gathering information about blood bank procedure. Then we mapped all procedures into processes in a workflow engine. Then we used the verification packages provided by the workflow engine to check the safety properties.

Orthopedic Resident Work-Shift Analysis: Are We Making the Best Use of Resident Work Hours?

Surgery programs have been tasked to meet rising demands in patient surgical care while simultaneously providing adequate resident training in the midst of increasing resident work-hour restrictions. The purpose of this study was to quantify orthopedic surgery resident workflow and identify areas needing improved resident efficiency. We hypothesize that residents spend a disproportionate amount of time involved in activities that do not relate directly to patient care or maximize resident education. We observed 4 orthopedic surgery residents on the orthopedic consult service at a major tertiary care center for 72 consecutive hours (6 consecutive shifts). We collected minute-by-minute data using predefined work-task criteria: direct new patient contact, direct existing patient contact, communications with other providers, documentation/administrative time, transit time, and basic human needs. A seventh category comprised remaining less-productive work was termed as standby. In a 720-minute shift, residents spent on an average: 191 minutes (26.5%) performing documentation/administrative duties, 167.0 minutes (23.2%) in direct contact with new patient consults, 129.6 minutes (17.1%) in communication with other providers regarding patients, 116.2 (16.1%) minutes in standby, 63.7 minutes (8.8%) in transit, 32.6 minutes (4.5%) with existing patients, and 20 minutes (2.7%) attending to basic human needs. Residents performed an additional 130 minutes of administrative work off duty. Secondary analysis revealed residents were more likely to perform administrative work rather than directly interact with existing patients (p = 0.006) or attend to basic human needs (p = 0.003). Orthopedic surgery residents spend a large proportion of their time performing documentation/administrative-type work and their workday can be operationally optimized to minimize nonvalue-adding tasks. Formal workflow analysis may aid program directors in systematic process improvements to better align resident skills with tasks. III.

Formal workflow design analytics using data flow modeling

Workflow design has become a critical function in enterprise information management. However, only scant research attention has been paid to formal workflow design methodologies. As a result, existing design methods in business process management remain a manual and experiential effort and result in inefficiency in design tasks and potential errors in workflow models. Considering that there are hundreds and thousands of business processes in organizations worldwide, overcoming this deficiency will have an enormous technical and economic impact on enterprise information management. In this paper, we investigate the possibility of incorporating formal analytics into workflow design, thus alleviating the intellectual challenge faced by business analysts when creating workflow models. The workflow design analytics we propose helps construct a workflow model based on information about the relevant activities and their associated data. In addition, our workflow design approach also helps determine whether the given information is sufficient for generating a workflow model and ensures the avoidance of certain workflow anomalies. The significance of our study is to enable the transformation of workflow design from a manual and experiential effort into a more systematic and rigorous approach.

A meaningful workplace: Framework, space and context

An attempt was made to describe and to eventually implement work space that can be defined as psychologically meaningful and which has increased during the past 5−10 years. Indications are that various researchers on different continents have embarked on a journey to describe the meaningful workplace. Such a workplace is more than a geographical location, it is psychological space; space where the individual employee performs tasks that construe his or her work role, in collaboration with other individuals, within a framework of predetermined time frames, according to certain procedures, based on identified needs and within a formal workflow structure that is normally referred to as the organisation. Within this framework employees become alienated as a result of which the organisation as well as the individual suffer. The organisation experiences a loss of productivity, quality, innovation, et cetera, and the employee a loss of meaning in life and work. Yet, the workplace remains the space where meaning can be gained. It is both the framework and context for meaningfulness at work. Within this framework certain factors and constitutive elements play a facilitating role in experiencing meaningfulness. Various factors including values, and imbedded therein, the Protestant Ethic (PE), (and various other factors, such as for instance spirituality, culture, leadership and management style, etc.), play an important role as facilitating factors towards the experience of meaningfulness at work. Developing a framework and context, on a conceptual level for the positioning of these factors as contributories towards the meaningful workplace, is a first priority. This is what this article is about: to conceptualise the workplace as psychological space, framework and context for understanding the contributory role of PE (and other factors) towards the experience of meaningfulness at work. The positioning of values and the PE as Max Weber understood the concept will be presented in a follow-on article.