By Michael Gilliland, Len Tashman, Udo Sglavo
A finished selection of the field's such a lot provocative, influential new work
Business Forecasting compiles a few of the field's very important and influential literature right into a unmarried, finished reference for forecast modeling and approach development. it truly is jam-packed with provocative principles from forecasting researchers and practitioners, on themes together with accuracy metrics, benchmarking, modeling of challenge info, and overcoming dysfunctional behaviors. Its assurance comprises often-overlooked matters on the vanguard of study, reminiscent of uncertainty, randomness, and forecastability, in addition to rising parts like info mining for forecasting.
The articles current severe research of present practices and attention of latest principles. With a mixture of formal, rigorous items and short introductory chapters, the booklet offers practitioners with a complete exam of the present kingdom of the enterprise forecasting box.
Forecasting functionality is eventually restricted by way of the 'forecastability' of the knowledge. but failing to acknowledge this, many organisations proceed to squander assets pursuing unachievable degrees of accuracy. This ebook presents a wealth of principles for bettering all features of the method, together with the avoidance of wasted efforts that fail to enhance (or even damage) forecast accuracy.
- Analyzes the main favorite concerns in company forecasting
- Investigates rising methods and new equipment of analysis
- Combines forecasts to enhance accuracy
- Utilizes Forecast worth additional to spot procedure inefficiency
The company setting is evolving, and forecasting equipment needs to evolve along it. This compilation provides an array of recent instruments and examine which may let extra effective tactics and extra exact effects. Business Forecasting offers an expert's-eye view of the field's most modern advancements that will help you in achieving your required enterprise results.
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Extra info for Business Forecasting: Practical Problems and Solutions
Example text
S. election forecasts improved accuracy of poll share forecasts. Goodwin (2009) summarized evidence from three studies on economic forecasting, all of which showed that combining forecasts is likely to improve accuracy. The M1 and M3 competitions also showed combination methods to perform well, making them a natural choice to include in estimating the lower bound of forecast error. In some cases, such as new-product launches, it is not possible to compare methods, or combinations of methods, based on historical data.
International Journal of Forecasting 29, 354–366. , D. Önkal, and M. Thomson (2010). Do forecasts expressed as prediction intervals improve production planning decisions? European Journal of Operational Research 205, 195–201. , and D. Markland (2010). Assessing uncertainty in new-product forecasts. Foresight, t Issue 16 (Winter), 32–39. , Y. M. Goh, L. B. Newnes, and P. Goodwin (2012). Approaches to displaying information to assist decisions under uncertainty. Omega 40, 682–692. Machete, R. L. (2013).
5% Notes: All factors displayed were statistically significant. All predictors have been centered and standardized (subtract the overall mean and divide by the standard deviation). This simplifies the determination of relative factor importance. Only selected factors from the full model have been disclosed, since the detailed forecastability model is not transportable from one business to the next. Building a forecastability model for your particular business will provide more insight than reproducing the model shown.