Qualitative Analysis and Forecasting

Qualitative Analysis and Forecasting: is performed by human opinions rather than event-based data. A.k.a Judgmental Forecasting, vs. statistical forecasting. Needs for Qualitative Analysis and Forecasting: – No data is available. Difficult data collection. Statistical knowledge required. – Long horizons of forecasting (forecasting for the next 2-3 years, wihle only 1 year of data is available).[…]

Correlation Analysis and Dimensionality Reduction

Correlation Analysis is meant for analyzing how two ordinal variables co-variate (increase and decrease together). It helps in at least two fields: 1. Regression analysis: By choosing which variables should be included. 2. Dimensionality reduction: If 2+ independent variables are correlated (this is called: multi-collinearity), we can keep one of them for the regression or[…]

Lean Concepts

Lean: smoothening processes & eliminating waste. Lean principles: • Identify your Customer and their concept of what value is, that’s what they would pay for. • Identify the value stream & thus what is not, i.e. what is waste. • Enable value to flow by removing waste. • Customer to Pull, to avoid waste. •[…]

Six Sigma DMAIC: Control

Six Sigma DMAIC Control: Monitor the variation of the process after applying the improvement. Control what: performance, cost, and risks. Statistical Process Control: Statistical methods to control the process, using control charts. Statistical Process Control-SPC: Any control system must have: – A measurable goal/standard. – A mean to measure improvement. – The (potentially automatic) comparison between[…]

Six Sigma: Analysis 2

Detecting a change/difference between sample and population/another sample: Steps: 1. Check: Is data Variable or Proportional. 2. Check: If data needs discrimination. 3. Determine minimum Sample size. 4. Then perform qualitative analysis: check difference in Distribution- 5. Then Sigma – quantitiative analysis: Excel chi^2 for proportional, and Anova= Ftest for variable. 6. Then comparison of Average: probability, Zt[…]

Six Sigma: Analysis

Six Sigma Analysis: Asking Why problems occur and where are opportunity to improve them. Finding Y=f(x). ¤ Qualitative Analysis: Process Mapping. Process flow (information, material, money). Cause&Effect- Fishbone. 5 Why’s. ¤ Quantitative Analysis-Statistics: First, data collection then: •Descriptive: Profiling. ▪Numeric: Mean, deviation, min/max .. ▪Graphic: Histogram. Etc. •Inferral: point Estimation(mean, etc.). Confidence interval. Estimating distributions:[…]

Six Sigma DMAIC: Measuring and Sampling

Types of Metrics: Discret: Countable, e.g. integer. Continuous: The degree of conformance to specifications. Effective metrics: SMART: Simple. Measurable. Actionable. Related. Timely. Select the right metrics (QTC, a.k.a. KPIs): identify the customer, requirements, processes, then evaluate measure usefulness. • Data collection (entry): Ask: What: questions. What: data can answer them. Where: is the data. Who: provides access to[…]