Managed Analytics
and Market Insights

USE CASES

Internval vs. External

General Examples (Cana Advisors)

Improve organizational operations management, planning, and use of data to make decisions.

Craft analytics/operations research-based decision support planning solutions in logistics, maintenance, and supply chain operations.

Enhance organizational data quality, processes, and planning through analytics assessments and action plan execution.

Apply statistical, simulation, and optimization-based tools and analysis to support improvements to decision making.

Establish cost savings and significant investment returns with a focus on improving performance, readiness, and capabilities.

Provide operations research and studies analysis for concept development and employment support course of action analysis and decision making.

DESCRIPTIVE STATISTICS

"What has happened?"

Charts & Graphs

  • Histograms

  • Scatter Plots

Numerical Presentations

  • Mean

  • Median

  • Mode

  • Variance

  • Standard Deviations of Distributions of data

  • Cross tabulations

PREDICTIVE STATISTICS

"What could happen?"

Forecasting (Time-series)

  • Moving averages

  • Auto regression

Simulation

  •  Discrete event

  • Agent-based modeling 

Regression (Linear, logistic, step-wise)

Statistical Inferences

  • Confidence Intervals

  • Hypothesis Testing

  • Analysis of Variance

  • Design of Experiments

 

Classification

Clustering

Artificial Intelligence

Game Theory

PRESCRIPTIVE STATISTICS

"What do we do about it?"

Optimization (see solver.com examples)

  • Linear programming: Restaurants use linear programming for menu planning. It optimizes meal production and thereby increases restaurant profits. It uses varying material cost, material supply, and profit from each menu item. This way management can determine the cost of preparing different menu items to decide how many of each menu item to prepare for optimal profit.

  • Integer programming

  • Nonlinear programming

  • Mixed integer programming

  • Network optimization: a shoe manufacturer has 3 production facilities where they create their product and 4 stores where they sell them. They must transport their shoes from the production facilities to the stores with a limited number of truckloads over varying distances between each facility and store. Network optimization shows them how many truckloads should move between each facility and designated stores to minimize fuel and transportation costs while meeting inventory demands at each store.

  • Dynamic programming

  • Metaheuristics

    • Rich portfolio optimization, index tracking, enhanced indexation, credit risk, stock investments, financial project scheduling, option pricing, feature selection, bankruptcy and financial distress prediction, and credit risk assessment.

    • Market basket analysis: checkout recommendations from Amazon

  • Simulation-optimization

  • Stochastic optimization

Examples by Modeling Technique (CAP Examination Guide)