Scenario Planning: Human Resource Development's Strategic Learning Tool

The Problem Recent disruptive events introduced high volatility and uncertainty into the contemporary organizational environment whereby well-established organizations found scenario planning (SP) useful to craft strategy. However, because SP is typically a very costly endeavor, it is less accessible to new startups, small businesses, nonprofits, and large-scale organizations that could greatly benefit. The Solution We propose an initial conceptual model whereby sophisticated technologies that typically enable virtual events be utilized to facilitate virtual SP activities for real-time participation from geographically disbursed locations reducing expenses and providing access to one of human resource development’s (HRD’s) strategic learning tools. We posit that HRD professionals be involved in planning and implementation through the scope of technology development within the context of virtual HRD. The Stakeholders This article provides researchers and scholar-practitioners with a conceptualization of current thinking around the notion of utilizing technology to create an online environment conducive for SP. This article will be of particular interest to those involved in formulating organizational strategy including those where costs of face-to-face SP and other forms of strategic initiatives are either time or cost prohibitive.

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The Assignment Problem in Human Resource Project Management under Uncertainty

Risks ◽

10.3390/risks9010025 ◽

2021 ◽

Vol 9 (1) ◽

pp. 25

Author(s):

Helena Gaspars-Wieloch

Keyword(s):

Project Management ◽

Human Resource ◽

Assignment Problem ◽

Combinatorial Problem ◽

Scenario Planning ◽

Binary Programming ◽

Turbulent Times ◽

Time Minimization ◽

Pure Strategies ◽

Weighted Combination

The assignment problem (AP) is a discrete and combinatorial problem where agents are assigned to perform tasks for efficiency maximization or cost (time) minimization. AP is a part of human resource project management (HRPM). The AP optimization model, with deterministic parameters describing agent–task performance, can be easily solved, but it is characteristic of standard, well-known projects realized in a quiet environment. When considering new (innovation or innovative) projects or projects performed in very turbulent times, the parameter estimation becomes more complex (in extreme cases, even the use of the probability calculus is not recommended). Therefore, we suggest an algorithm combining binary programming with scenario planning and applying the optimism coefficient, which describes the manager’s nature (attitude towards risk). The procedure is designed for one-shot decisions (i.e., for situations where the selected alternative is performed only once) and pure strategies (the execution of a weighted combination of several decision variants is not possible).

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Complex Problem Solving and Worked Examples

Zeitschrift für Pädagogische Psychologie ◽

10.1024/1010-0652.23.2.129 ◽

2009 ◽

Vol 23 (2) ◽

pp. 129-138 ◽

Cited By ~ 16

Author(s):

Florian Schmidt-Weigand ◽

Martin Hänze ◽

Rita Wodzinski

Keyword(s):

Problem Solving ◽

Cognitive Load ◽

Learning Experience ◽

Worked Examples ◽

Complex Problem ◽

Complex Problem Solving ◽

Strategic Learning ◽

Learning Behavior ◽

Worked Example ◽

8Th Grade

How can worked examples be enhanced to promote complex problem solving? N = 92 students of the 8th grade attended in pairs to a physics problem. Problem solving was supported by (a) a worked example given as a whole, (b) a worked example presented incrementally (i.e. only one solution step at a time), or (c) a worked example presented incrementally and accompanied by strategic prompts. In groups (b) and (c) students self-regulated when to attend to the next solution step. In group (c) each solution step was preceded by a prompt that suggested strategic learning behavior (e.g. note taking, sketching, communicating with the learning partner, etc.). Prompts and solution steps were given on separate sheets. The study revealed that incremental presentation lead to a better learning experience (higher feeling of competence, lower cognitive load) compared to a conventional presentation of the worked example. However, only if additional strategic learning behavior was prompted, students remembered the solution more correctly and reproduced more solution steps.

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