How to stand out in a company’s global manufacturing network

Global manufacturers are constantly revamping their network of plants. Surviving over the long term for a factory—especially one located in a high-cost country—can be extremely difficult. But an exception to the rule—a Pfizer plant in Belgium that ended up producing its mRNA Covid-19 vaccine—demonstrated that it can be done. An extensive study of the steps that the plant’s leaders took beginning in the mid-2000s—revealed how a plant can become indispensable. They took the facility through five stages: 1) improve operational excellence, 2) improve capabilities for making new products, 3) specialize, 4) increase responsiveness, and 5) build a knowledge network

Financiando el Futuro: Capital para Arrancar y Escalar Negocios Exitosos

Este capítulo profundiza en los aspectos técnicos de la planificación financiera de una startup. El plan financiero es el punto de partida para cualquier estrategia en esta área. Su primer objetivo es determinar si la empresa requerirá financiamiento externo y, de ser así, qué cantidad de financiamiento necesitará y en qué momento. Además, este plan sirve como base para la valuación de la empresa. Por último, y probablemente lo más importante, brinda al equipo emprendedor y a los inversionistas potenciales la oportunidad de evaluar críticamente y optimizar el modelo de negocio

Resource allocation models and heuristics for the multi-project scheduling with global resource transfers and local resource constraints

Proposing four models of the RCMPSP with global resource transfers. Improving three classes of priority rule-based heuristics for the new models. Testing and comparing three heuristics with a large amount of priority rules. Verifying the applicability and good performance of priority rules with a case study.The transfer times and costs of global resources between different projects and the choice of transfer modes significantly affect the multi-project scheduling. This paper investigates four versions of the resource-constrained multi-project scheduling problem with global resource transfers and local resource constraints based on four realistic transfer scenarios, in which the global resource transfer times and costs are considered with a single transfer mode or multiple transfer modes. Three classes of heuristics with huge amount of priority rules are adapted and tested for the new problems. The schedule generation schemes of each class of heuristics are improved from two aspects. On the one hand, resource availability checks are divided into global and local phases due to their different characteristics. On the other hand, resource transfer rules and transfer mode rules are introduced to deal with resource transfer and transfer mode issues, respectively. The three class of heuristics are tested on well-known datasets of the multi-project problem, which are extended with transfer data using a transfer time/cost generation procedure. The numerical experiments first evaluate the performance of a set of priority rules, then effectively apply the priority rule heuristics in the genetic algorithm, and finally compare the performance of the priority rule heuristics with CPLEX on small-scale instances. Additionally, a multi-project case study verifies the applicability and good performance of priority rules that perform well in numerical experiments. Furthermore, the best performing rules are used by two machine learning methods in literature to automatically select the most promising ones

The use of IoT sensor data to dynamically assess maintenance risk in service contracts

We explore the value of using operational sensor data to improve the risk assessment of service contracts that cover all maintenance-related costs during a fixed period. An initial estimate of the contract risk is determined by predicting the maintenance costs via a gradient-boosting machine based on the machine’s and contract’s characteristics observable at the onset of the contract period. We then periodically update this risk assessment based on operational sensor data observed throughout the contract period. These sensor data reveal operational machine usage that drives the maintenance risk. We validate our approach on a portfolio of about 4,000 full-service contracts of industrial equipment and show how dynamic sensor data improves risk differentiation

‘Making it Easy to Do Hard Things’: How experts help novices perceive craft as accessible

Craft offers a path to enchantment and meaningful engagement with creation in an increasingly rationalized society. Yet, entering skilled domains where craft is practiced can be challenging for novices, particularly for those less familiar with these domains. While a growing body of research suggests that craft can be made more accessible through nontraditional pathways, the process whereby novices come to perceive craft as accessible remains undertheorized. We explore these ideas through the case of the makers, a diverse DIY movement that embraces all who build, modify, and invent across a variety of skilled domains. Using interview and observational data from Maker Faires—events wherein makers exhibit their projects and engage attendees in making activities—we induce a model of how experts enable novices to perceive craft as accessible. Our findings reveal how experts convey knowledge and skills using a creative craft approach, detailing how experts engage in scaffolding to facilitate novice creation, relax hierarchy, and cultivate fun and whimsy. In turn, this engenders the experience of enchanted engagement for novices who are able to experience how engaging in craft feels without the requisite skills or knowledge. Ultimately, this experience shapes and reinforces novices’ perception that craft is accessible. Our study contributes to the growing scholarship on craft in terms of alternative pathways for entering skilled domains, the role of craft in re-enchanting organizational life, and the emotional rewards of craft

The Palgrave Encyclopedia of Private Equity

Mergers and acquisitions (M&A) by venture capital-backed companies have witnessed a surge in popularity in recent years. This article aimed to comprehensively examine this subject from the buyer perspective. Firstly, we demonstrate that venture capitalists assume multiple roles in M&A deals, including traditional screening, monitoring, advising, and coaching. Secondly, drawing from signaling, agency, resource-based, and organizational learning theories, one might anticipate a higher propensity for VC-backed companies to engage in acquisitions. However, the existing literature presents conflicting findings regarding the likelihood of VC-backed takeovers. Likewise, the assessment of short-term and long-term performance outcomes, typically measured through stock returns, yields inconclusive results

Bringing microaggressions from the shadows to the spotlight: Unveiling silencing mechanisms and distinct patterns in coping

While many organizations work intensively to implement gender equity policies, women's experiences remain heavily marked by covert forms of bias, with microaggressions being the most ubiquitous. Microaggressions (which subtly but persistently manifest prejudice at the behavioral level), persist in workplaces despite growing awareness of their negative impacts. This qualitative study examines why they are often met with silence, exploring the interplay between silencing mechanisms rooted in inequality regimes and individual coping strategies. One hundred twenty-five participants (three-quarters of whom were women) shared nearly 700 incidents of microaggressions on an online platform in a Western European setting. Findings highlight five distinct stages individuals cope with microaggressions: ignorance, awareness, hypervigilance, resignation, and psychological control. Each of these coping mechanisms was influenced by structural silencing mechanisms, the individual's understanding of what was happening to them, and the frequency with which they encountered microaggressions. The study underscores how structural inequalities perpetuate microaggressions and their subsequent silencing, emphasizing that the harm of microaggressions goes beyond the initial incident to include the inability to address them effectively. This demonstrates that addressing microaggressions requires a twofold approach: dismantling silencing mechanisms rooted in inequality regimes and empowering individuals with tailored strategies to confront these subtle yet damaging forms of discrimination. This research provides key insights into fostering more inclusive and equitable workplaces

Automatic selection of the best performing control point approach for project control with resource constraints

The risk, network, and subnetwork control point approaches are proposed. New project parameters are introduced to model realistic project features. A classification model is built to select the best approach given project features. The classification model outperforms any single proposed control point approach. Resource variability is the main driver for detecting the best approach.During project execution, the actual project progress shows deviations from the baseline schedule due to uncertainty. To complete the project timely, project monitoring is performed at discrete control points to identify project opportunities/problems and take possible corrective actions. These control points affect the quality of project monitoring and corrective actions, but little guidance is available on identifying situations where the control points pay off the most in terms of project duration. This paper proposes new control point approaches considering the risk, the complexity of the network, and subnetwork information to determine the timing of project monitoring and action taking. Moreover, new parameters are proposed to model more realistic project characteristics. Subsequently, a classification model is developed to select the best performing control point approach given project characteristics. An extensive computational experiment is conducted on a set of 3,810 artificial projects with diverse project characteristics to evaluate the performance of the classification model and further validate it on empirical project data. The computational results indicate that the classification model outperforms the average performance of any proposed control point approaches. The results also show that the resource variability that indicates the resource usage deviations between project activities is the primary driver for detecting the best control point approach for projects with resource constraints

Synchromodal replenishment under non-stationary demand: An illustrative case study

Synchromodal replenishment aligns transport mode decisions with inventory replenishment needs. We present a case study considering the simultaneous use of road and rail transport to replenish a distribution center in Belgium from a supplier in Spain, aiming for a modal shift from road to sustainable rail transport. Product demand is non-stationary, meaning the demand distribution changes over time. Although the underlying demand distribution is not directly observable, demand observations provide partial information. We apply the synchromodal replenishment policy proposed in Yee et al. (2024) that combines a committed, stable rail order with flexible short-term orders on rail and road. The short-term orders are based on inventory levels and partial information about the non-stationary demand. The case study demonstrates the value of adding short-term flexibility to rail orders to induce a modal shift. Our analysis shows how the proposed policy improves the modal shift compared to a benchmark policy without flexible rail orders. The retailer can reduce the carbon footprint of its replenishments without compromising service levels or costs. We also show how offering the flexible rail option increases the rail operator’s revenues. These findings highlight the potential of synchromodal replenishment with flexible rail orders to facilitate a modal shift