Vanguard Advanced Analytics
Vanguard Advanced Analytics raises enterprise strategy and decision making to a whole new level. Powerful modeling and simulation tools, plus collaborative workflow design, bring expert capability to knowledge workers across the enterprise.
Assess competing courses of action. Compare risk-reward scenarios. Test ideas virtually. And refine short-term forecasts with demand sensing technology that collects and analyzes live-streaming sales orders or POS data from any ERP or transaction system.
Vanguard Advanced Analytics applies an exhaustive range of time-series and model-based methods to not only capture and extrapolate historical patterns, but to simulate and compare innumerable outcomes from seemingly unprecedented events and circumstances. These can include product launches, proposed changes to business plans, or long-range capital and investment decisions with effects that will span an entire product life-cycle, or even generations of products.
Vanguard Advanced Analytics has the capacity for enterprise-scale modeling and the virtuality to unite diverse contributors in the strategic planning process.
Monte Carlo Simulation
Simulate complex systems to model uncertainty and volatility and better manage business opportunity and risk. Reveal the full range of potential business outcomes and the probability of each with expected values for distinct courses of action.
- Incorporate multiple sources of uncertainty into your forecast model
- Run simulations 100 times faster than spreadsheet add-ins — 1,500 times faster with the grid computing option
- Automate sensitivity analysis
- Run reports with distribution graphs and statistics
- Utilize distribution gallery
- Automate distribution fitting using historical data
- User-defined distributions
- Correlated inputs
- Unlimited number of stochastic inputs
In addition to Monte Carlo simulation, Advanced Analytics can apply multiple advanced techniques to new-product forecasting, or combine various methods into a single forecast.
- Comparable Forecasting: Applies the historical pattern of an established product to a new product. In Forecast Server, users can select comparable products by any attribute – product family, SKU code, region, etc.
- Spread Curve: Applies the pattern of a demand factor (e.g. seasonality, decay, life cycle, region) to a new-product forecast
- Supersession: Used when a new product is likely to cannibalize or replace an existing product or set of products
- Adoption Modeling: Captures new-product launch effects and long-range product-life-cycle effects
Forecast Server complements its exhaustive range of time-series forecasting methods with model-based approaches that factor product life-cycle effects into long-range forecasts. Forecast Server’s Model-based methods include
- Monte Carlo simulation
- Decision analysis
- Stochastic optimization