Mitigate Risks

Statistical Analysis and Forecasting

Improve your forecasting and decision-making by applying powerful statistical analysis to your data, directly in your Excel spreadsheet. With predictive modeling and forecasting techniques, you can gain the insight needed to make critical decisions with confidence for cases such as demand forecasting, pricing, portfolio allocation, load planning, sales forecasting, strategic planning, profit projections, and more.

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Make Better Decisions with Quantitative Insights

When your organization has access to useful and potentially critical data, easy and effective analysis is a must. Competitive advantage can be gained with better knowledge of the potential future outcomes, group comparisons and by measuring dependency. A deep and accurate statistical and visual understanding of key variables is invaluable.

Statistical analysis and forecasting provide this with quantitative and graphical results to display to your key stakeholders.

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What is Statistical Analysis and Forecasting?

The Monte Carlo method is a computerized mathematical technique that allows people to quantitatively account for risk in forecasting and decision-making. At its core, the Monte Carlo method is a way to use random samples of parameters to explore the behavior of a complex system. A Monte Carlo simulation is used to handle an extensive range of problems in a variety of different fields to understand the impact of risk and uncertainty.

Range of Techniques Across Many Industries

Statistical analysis and forecasting represent a broad range of techniques. It is used in all sectors such as manufacturing & consumer goods, healthcare & pharmaceuticals, finance & banking, insurance & reinsurance, pharmaceuticals, aerospace & defense, energy & utilities, and others.

Predict the Future from the Past

Historically observed data can be described in terms of useful summary statistics for each variable, as well as the dependency across variables. Predictive modeling and forecasting techniques are applied to the data set, generating a reliable picture of the future to assist your decision making. Methods of statistical inference, hypothesis tests and quality control fulfill more specialized needs.

Visual Communication

Graphs and charts help to visualize variables and results from statistical methods and are an invaluable resource for effectively communicating outcomes.

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Common use cases include:

Demand forecasting

Load planning

Pricing

Sales forecasting

Portfolio allocation

Strategic planning

Six Sigma and quality control, and much more

Profit Projections

How Does Statistical Analysis and Forecasting Work?

Statistical analysis and forecasting start with a data set. From here you determine which analyses are most relevant to you. Any variable can be described with statistics calculated directly from the data, or shown in graphical summaries such as histograms and box plots. Time series can be forecasted any number of periods into the future using techniques that include trending and seasonality options. Forecasts can be represented graphically, greatly facilitating discussions and decision-making among all stakeholders. Quality control methods can also be applied to time series variables, creating Pareto and X/R charts (among others) to identify the most significant types of defect occurrences as well as the frequency of variation. These types of analyses are important in producing products or services of consistent high quality, such as in Six Sigma work.

When the data set contains related observations of dependent and independent variables, techniques such as regression and cluster analysis become appropriate. Statistical inference work such as ANOVA (analysis of variance) and nonparametric tests on the data form the basis of valid claims of significance. Correlations are calculated between variables to highlight dependencies your organization is exposed to.

An ANOVA statistical analysis comparing the means of different data sets.

100% Microsoft Excel Integration

With PrecisionTree, you never leave your spreadsheet, allowing you to work in a familiar environment, and get up to speed quickly.

Full Statistics Reports and Graphs

See results in risk profile graphs, 2-way sensitivity, tornado graphs, spider graphs, policy suggestion reports, and strategy-region graphs.

Advanced Features

Set up your decision tree in Microsoft Excel exactly as you need it with logic nodes, reference nodes, linked trees, custom utility functions, and influence diagrams.

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Types of Statistical Analysis

There are different types of statistical analysis, employing different mathematical techniques to achieve different goals. Some of the more common types include:

Descriptive Statistics – These summarize a data set and visualize it with charts and graphs.

Statistical Inference – These analyses examine a sample of the entire data set to test a hypothesis and draw conclusions about the entire population.

Regression – These are techniques which model the relationship between a dependent variable and one or more independent variables in order to make predictions.

Forecasting – These are analyses applying statistics to historical data to project what could happen in the future.

Statistical Analysis and Forecasting Software from Lumivero

Lumivero’s StatTools software brings robust statistical analysis and forecasting power to Excel. With StatTools, any Excel user can apply any of over three dozen statistical and forecasting analyses to data directly in their spreadsheet. All StatTools functions behave exactly as native Excel functions do, so there is no learning curve. Furthermore, StatTools is designed to work closely with Lumivero’s NeuralTools product for neural networks prediction, making for a combined data analysis powerhouse unavailable anywhere else.

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