Practitioners can assess the accuracy of forecasts using control charting and analysis of variance (ANOVA). Screening a corporation’s forecasts with these two tools will reveal the evolution of forecast bias and consistency over time.
The demand for business intelligence is increasing at a rapid pace across all industries in today’s tough economic climate. As senior executives look to optimize existing business processes that can lead to bottom-line and top-line benefits, one option is to tap into predictive analytics, a type of data mining that can be used to make reliable predictions of future events based on analysis of historical data.
For short-term forecasting, Black Belts can benefit from analyzing moving average plots and looking for special causes of variation. When making long-term forecasts, a method that uses a normal curve and Z-scores may be the better bet.
Nobody knows what the future holds, but a shared uncertainty about tomorrow creates a forward-leaning opportunity for reinvention. Future-ready reengineering helps companies move from doing what is most effective today to meeting tomorrow’s challenges.
The goal of code inspection is to identify software faults early in the software development lifecycle, but it is not always known if those inspections are effective. A prediction model can be applied to evaluate this process and refine the achieved quality level.
Part 1 of this article will help practitioners understand the key drivers for the growth of statistics and introduce some leading analytics competitors.
Forecasting is a business and communicative process and not merely a statistical tool. Basic forecasting methods serve to predict future events and conditions and should be key decision-making elements for management in service organizations.