68,864 research outputs found
Software cost estimation
The paper gives an overview of the state of the art of software cost estimation (SCE). The main questions to be answered in the paper are: (1) What are the reasons for overruns of budgets and planned durations? (2) What are the prerequisites for estimating? (3) How can software development effort be estimated? (4) What can software project management expect from SCE models, how accurate are estimations which are made using these kind of models, and what are the pros and cons of cost estimation models
Application of expert systems in project management decision aiding
The feasibility of developing an expert systems-based project management decision aid to enhance the performance of NASA project managers was assessed. The research effort included extensive literature reviews in the areas of project management, project management decision aiding, expert systems technology, and human-computer interface engineering. Literature reviews were augmented by focused interviews with NASA managers. Time estimation for project scheduling was identified as the target activity for decision augmentation, and a design was developed for an Integrated NASA System for Intelligent Time Estimation (INSITE). The proposed INSITE design was judged feasible with a low level of risk. A partial proof-of-concept experiment was performed and was successful. Specific conclusions drawn from the research and analyses are included. The INSITE concept is potentially applicable in any management sphere, commercial or government, where time estimation is required for project scheduling. As project scheduling is a nearly universal management activity, the range of possibilities is considerable. The INSITE concept also holds potential for enhancing other management tasks, especially in areas such as cost estimation, where estimation-by-analogy is already a proven method
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Predicting with sparse data
It is well known that effective prediction of project cost related factors is an important aspect of software engineering. Unfortunately, despite extensive research over more than 30 years, this remains a significant problem for many practitioners. A major obstacle is the absence of reliable and systematic historic data, yet this is a sine qua non for almost all proposed methods: statistical, machine learning or calibration of existing models. In this paper we describe our sparse data method (SDM) based upon a pairwise comparison technique and Saaty's Analytic Hierarchy Process (AHP). Our minimum data requirement is a single known point. The technique is supported by a software tool known as DataSalvage. We show, for data from two companies, how our approach â based upon expert judgement â adds value to expert judgement by producing significantly more accurate and less biased results. A sensitivity analysis shows that our approach is robust to pairwise comparison errors. We then describe the results of a small usability trial with a practising project manager. From this empirical work we conclude that the technique is promising and may help overcome some of the present barriers to effective project prediction
Double Whammy - How ICT Projects are Fooled by Randomness and Screwed by Political Intent
The cost-benefit analysis formulates the holy trinity of objectives of
project management - cost, schedule, and benefits. As our previous research has
shown, ICT projects deviate from their initial cost estimate by more than 10%
in 8 out of 10 cases. Academic research has argued that Optimism Bias and Black
Swan Blindness cause forecasts to fall short of actual costs. Firstly, optimism
bias has been linked to effects of deception and delusion, which is caused by
taking the inside-view and ignoring distributional information when making
decisions. Secondly, we argued before that Black Swan Blindness makes
decision-makers ignore outlying events even if decisions and judgements are
based on the outside view. Using a sample of 1,471 ICT projects with a total
value of USD 241 billion - we answer the question: Can we show the different
effects of Normal Performance, Delusion, and Deception? We calculated the
cumulative distribution function (CDF) of (actual-forecast)/forecast. Our
results show that the CDF changes at two tipping points - the first one
transforms an exponential function into a Gaussian bell curve. The second
tipping point transforms the bell curve into a power law distribution with the
power of 2. We argue that these results show that project performance up to the
first tipping point is politically motivated and project performance above the
second tipping point indicates that project managers and decision-makers are
fooled by random outliers, because they are blind to thick tails. We then show
that Black Swan ICT projects are a significant source of uncertainty to an
organisation and that management needs to be aware of
Population variability in animal health: Influence on dose-exposure-response relationships: Part II: Modelling and simulation
During the 2017 Biennial meeting, the American Academy of Veterinary Pharmacology and Therapeutics hosted a 1âday session on the influence of population variability on doseâexposureâresponse relationships. In Part I, we highlighted some of the sources of population variability. Part II provides a summary of discussions on modelling and simulation tools that utilize existing pharmacokinetic data, can integrate drug physicochemical characteristics with species physiological characteristics and dosing information or that combine observed with predicted and in vitro information to explore and describe sources of variability that may influence the safe and effective use of veterinary pharmaceuticals
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