Demand Forecasting: Evidence-Based Methods

In recent decades, much comparative testing has been conducted to determine which forecasting methods are more effective under given conditions. This evidence-based approach leads to conclusions that differ substantially from current practice. This paper summarizes the primary findings on what to do – and what not to do. When quantitative data are scarce, impose structure by using expert surveys, intentions surveys, judgmental bootstrapping, prediction markets, structured analogies, and simulated interaction. When quantitative data are abundant, use extrapolation, quantitative analogies, rule-based forecasting, and causal methods. Among causal methods, use econometrics when prior knowledge is strong, data are reliable, and few variables are important. When there are many important variables and extensive knowledge, use index models. Use structured methods to incorporate prior knowledge from experiments and experts’ domain knowledge as inputs to causal forecasts. Combine forecasts from different forecasters and methods. Avoid methods that are complex, that have not been validated, and that ignore domain knowledge; these include intuition, unstructured meetings, game theory, focus groups, neural networks, stepwise regression, and data mining

Time Predictions: Understanding and Avoiding Unrealism in Project Planning and Everyday Life

time predictions; human judgement; overoptimism; uncertainty; project managemen

A Neuro Fuzzy Algorithm to Compute Software Effort Estimation

Software Effort Estimation is highly important and considered to be a primary activity in software project management The accurate estimates are conducted in the development of business case in the earlier stages of project management This accurate prediction helps the investors and customers to identify the total investment and schedule of the project The project developers define process to estimate the effort more accurately with the available mythologies using the attributes of the project The algorithmic estimation models are very simple and reliable but not so accurate The categorical datasets cannot be estimated using the existing techniques Also the attributes of effort estimation are measured in linguistic values which may leads to confusion This paper looks in to the accuracy and reliability of a non-algorithmic approach based on adaptive neuro fuzzy logic in the problem of effort estimation The performance of the proposed method demonstrates that there is a accurate substantiation of the outcomes with the dataset collected from various projects The results were compared for its accuracy using MRE and MMRE as the metrics The research idea in the proposed model for effort estimation is based on project domain and attribute which incorporates the model with more competence in augmenting the crux of neural network to exhibit the advances in software estimatio

Time Predictions

This book is published open access under a CC BY 4.0 license. Predicting the time needed to complete a project, task or daily activity can be difficult and people frequently underestimate how long an activity will take. This book sheds light on why and when this happens, what we should do to avoid it and how to give more realistic time predictions. It describes methods for predicting time usage in situations with high uncertainty, explains why two plus two is usually more than four in time prediction contexts, reports on research on time prediction biases, and summarizes the evidence in support of different time prediction methods and principles. Based on a comprehensive review of the research, it is the first book summarizing what we know about judgment-based time predictions. Large parts of the book are directed toward people wishing to achieve better time predictions in their professional life, such as project managers, graphic designers, architects, engineers, film producers, consultants, software developers, or anyone else in need of realistic time usage predictions. It is also of benefit to those with a general interest in judgment and decision-making or those who want to improve their ability to predict and plan ahead in daily life

Time Predictions: Understanding and Avoiding Unrealism in Project Planning and Everyday Life

time predictions; human judgement; overoptimism; uncertainty; project managemen

Heuristics to Improve Human Factors Performance in Aviation

This paper reviews literature related to heuristic cognitive strategies as they are used by flight crews. A review of heuristic and naturalistic cognition is presented. An example set of heuristics and cognitive biases are presented and where possible exemplified by 19 airline accidents. The paper suggests two tentative research designs which could be pursued to quantitatively study heuristics and its impact on aviation decision making. The paper concludes that aviation pilot training would benefit by introducing pilots to the concepts and constructs of heuristic thinking