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Microsoft Operations Management Suite Cookbook
Microsoft OMS is a one stop IT management solution used to gain visibility and control over hybrid environments with simplified operations management and security. With Microsoft-based solutions in Azure, OMS helps organizations make the most of their IT investments. This book offers practical and hands-on recipes to gather real-time.
eBook
Who Lives in the C-Suite? Organizational Structure and the Division of Labor in Top Management
Top management structures in large U.S. firms have changed significantly since the mid-1980s. The size of the executive team-the group of managers reporting directly to the CEO-doubled during this period. This growth was driven primarily by an increase in functional managers rather than general managers, a phenomenon we term \"functional centralization.\" Using panel data on senior management positions, we show that changes in the structure of the executive team are tightly linked to changes in firm diversification and information technology investments. These relationships depend crucially on the function involved; those closer to the product (\"product\" functions, e.g., marketing and R&D) behave differently from functions further from the product (\"administrative\" functions, e.g., finance, law, and human resources). We argue that this distinction is driven by differences in the information-processing activities associated with each function and apply this insight to refine and extend existing theories of centralization. We also discuss the implications of our results for organizational forms beyond the executive team.
This paper was accepted by Bruno Cassiman, business strategy.
Journal Article
Surgical Suites' Operations Management
Surgical suites are a key driver of a hospital's costs, revenues, and utilization of postoperative resources such as beds. This article describes some commonly occurring operations management problems faced by the managers of surgical suites. For three of these problems, the article also provides preliminary models and possible solution approaches. Its goal is to identify open challenges to spur further research by the operations management community on an important class of problems that have not received adequate attention in the literature, despite their economic importance.
Journal Article
Executive Suite Independence: Is It Related to Board Independence?
The executive suite and the board are closely bound to each other through their fiduciary responsibility to the same shareholders. With chief executive officers’ (CEOs) prominent role in both governing bodies, their independence from CEOs’ self-serving behavior might be related to each other. We explore the interdependence using an external shock increasing board independence. The shock weakens executive suite independence by increasing CEO connectedness within executive suites through appointments and preexisting social ties. We also uncover interesting dynamics between the two governing bodies: (1) the spillover does not occur when treated firms increase CEO-independent director social ties, suggesting CEO-executive connections and CEO-director connections are substitutes; (2) consistent with theories of board independence, when an information environment calls for dependent boards, increasing CEO-executive connections, which helps negate the shock effect on the board, has positive marginal effects on firm performance. Our findings are not driven by the Sarbanes–Oxley Act and are robust to a battery of other tests. We conclude that independence in the board and executive suite are inversely related; inferring the overall independence from board independence alone can be highly misleading.
The online appendix is available at
https://doi.org/10.1287/mnsc.2016.2603
.
This paper was accepted by Amit Seru, finance
.
Journal Article
How difficult is nonlinear optimization? A practical solver tuning approach, with illustrative results
Nonlinear optimization (NLO) encompasses a vast range of problems, from very simple to theoretically intractable instances. For this reason, it is impossible to offer guaranteed—while practically meaningful—advice to users of NLO software. This issue becomes apparent, when facing exceptionally hard and/or previously unexplored NLO challenges. We propose a heuristic quadratic meta-model based approach, and suggest corresponding key option settings to use with the Lipschitz global optimizer (LGO) solver suite. These LGO option settings are directly related to estimating the sufficient computational effort to handle a broad range of NLO problems. The proposed option settings are evaluated experimentally, by solving (numerically) a representative set of NLO test problems which are based on real-world optimization applications and non-trivial academic challenges. Our tests include also a set of scalable optimization problems which are increasingly difficult to handle as the size of the model-instances increases. Based on our computational results, it is possible to offer generally valid, practical advice to LGO users. Arguably (and mutatis mutandis), comparable advice can be given to users of other NLO software products with a similarly broad mandate to LGO’s. An additional benefit of such aggregated tests is that their results can effectively assist the rapid evaluation and verification of NLO solver performance during software development phases.
Journal Article
Integrated scheduling of elective surgeries and surgical nurses for operating room suites
Facing an acute shortage of surgical nurses, operating room suites in China are more and more aware of the need to use surgical nurses efficiently. This goal is hard to achieve due to the strong interactions between the nurse and the surgery scheduling process. This paper addresses the benefit of integrating elective surgery and surgical nurse scheduling in terms of nurse utilization. First, an integer programming (IP) model is proposed to schedule elective surgeries and surgical nurses simultaneously. Then an efficient genetic algorithm (GA) is proposed based on the IP formulation due to the computational complexity of the integrated scheduling problem. A case study using real-life data is presented to validate the performance of the integrated approaches (the IP model and the GA) by comparing them with a two-stage approach that schedules elective surgeries and surgical nurses sequentially.
Journal Article
Is traditional, open-source, or on-demand first choice? Developing an AHP-based framework for the comparison of different software models in office suites selection
Until recently, organizations planning to acquire application software (AS) have had no choice but to adopt proprietary, on-premises software. With the advent of open-source and on-demand solutions, new models for developing and distributing software have entered the stage providing IS managers with more options in AS selection. On the basis of an Analytic Hierarchy Process model, we propose a framework including software package and implementation attributes on different hierarchy levels to examine how IS managers evaluate the relative fulfilment of key selection criteria by traditional, open-source, and on-demand office suites. By testing the framework with a random sample of 254 IS managers of 166 smaller and 88 mid-sized/larger firms, we validate its validity and usefulness in evaluating different software delivery models. Our empirical results show that open-source office suites were consistently perceived to be superior in meeting ease of customization (i.e., extensibility and adaptability) and cost criteria (i.e., acquisition and maintenance cost), whereas traditional software models were superior in fulfilling functionality, ease of use, and support requirements. On-demand office suites excelled in the fulfilment of time-to-value and data recoverability. We discuss further results of the comparison of the three software models, and derive practical and research implications for office suite selection.
Journal Article
Integrated experimental design and nonlinear optimization to handle computationally expensive models under resource constraints
In many real-world applications of optimization, the underlying descriptive system model is defined by computationally expensive functions: simulation modules, numerical models and other “black box” model components are typical examples. In such cases, the model development and optimization team often has to rely on optimization carried out under severe resource constraints. To address this important issue, recently a Regularly Spaced Sampling (RSS) module has been added to the Lipschitz Global Optimizer (LGO) solver suite. RSS generates non-collapsing space filling designs, and produces corresponding solution estimates: this information is passed along to LGO for refinement within the given resource (function evaluation and/or runtime) limitations. Obviously, the quality of the solution obtained will essentially depend both on model instance difficulty and on the admissible computational effort. In spite of this general
caveat
, our results based on solving a selection of non-trivial global optimization test problems suggest that even a moderate amount of well-placed sampling effort enhanced by limited optimization can lead at least to reasonable or even to high quality results. Our numerical tests also indicate that LGO’s overall efficiency is often increased by using RSS as a presolver, both in resource-constrained and in completed LGO runs.
Journal Article