know what lies ahead
know what lies ahead

Demand Planning with Prevail

Prevail is a state-of-the-art demand planning application that can be used to create accurate Weekly Sales Forecasts. Prevail was developed to provide an integrated forecasting solution that is flexible, powerful, responsive, secure and measurable. Detailed forecasts developed within Prevail are designed to roll-up to highly accurate operational forecasts which are utilized within a Replenishment Planning System.

Flexible Forecasting Models

More Dimensions of Data
Prevail features six dimensions of sales data in order to produce the best possible forecast models and results. The lowest level of data granularity within Prevail is the Detail Combo, which is a unique combination of a warehouse, product, channel, account, territory, and distributor. Though the use of all six data dimensions is not required, dimensionality will be adapted to fit specific material, market and delivery information for each client.

Sophisticated Methodologies for Bundling and Slicing Data
Bundling is an intelligent way to group Detail Combos into Model Combos across dataset dimensions using different rules to produce optimal forecast models. Bundling is flexible, allowing multiple levels at which to model forecasts.

Powerful Forecasting Techniques

Enhanced Ability to Handle Exceptions
Prevail features eight configurable Exception event types (e.g. Special Events, Summer Holidays, Winter Holidays, Special Packaging, Hot Price Promotion, etc.) and supports simultaneous occurrences of exceptions during a given sales week. Exception model calculations utilizes outlet participation percentage in the specific exception to better predict the effects of promotion. These and other Prevail features help facilitate product market launches in a time-phased fashion.

Advanced Statistical Tools
Prevail provides a sophisticated statistical method for detecting sales outliers which should then be excluded from the Model-level data used to create forecasts. The application performs numerical analysis to evaluate multi-collinearity of data more efficiently.

Improved management of Seasonality
Seasonality patterns are identified within any data dimension rather than just warehouse-product. Prevail readily recognizes non-seasonal dips and spikes in sales and will utilize alternative smoothing parameters for weekly seasonality computations. Users can choose to apply separate smoothing algorithms for weekly forecasting versus monthly planning for flexibility and accuracy.

 
 
 
 
 
 
 
 
 
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In most industries, scheduling processes must be very agile and require the ability to calculate Safety Stock levels on-the-fly based upon dynamic replenishment times. SafeGuard provides this agility by pre-calculating parameters for a wide range of scheduling possibilities. Completely integrated with Prevail, SafeGuard’s sophisticated methodology develops accurate and optimal Safety Stock policies.

Café
 

At the heart of Prevail sits Café, a powerful automated forecasting engine specifically developed to achieve the highest levels of forecasting accuracy. Through the use of configurable forecasting models and model hierarchies, Café works behind the scenes to create remarkably accurate forecasts. Café methodically looks for both obvious and subtle relationships between different types of market information (Pricing, Promotions, Exceptions, Trends, Seasonality, etc.) and constructs multi-level models based on those that have in combination historically predicted sales consistently.

 
 

Vantage Dash is a tool made for reporting the forecast performance and related metrics from Prevail. These metrics allow demand planners and managers to view forecast accuracies from different perspectives and identify opportunities of forecast improvement. Vantage Dash generates Functional Metrics and Process Metrics using forecast and sales data from a Prevail database.

 
 

Prevail implementation is a five-stage process. Each stage of the implementation process is described in the Standard Implementation Plan. Click here to view a pdf version of the Standard Prevail Implementation Plan.

 

Sales Planning with Marquee

Marquee is a new concept in demand planning that generates and manages Rolling Estimates and Annual Business Plans using strong statistical models and macro-economics variables.

Marquee tightly integrates with Prevail, with which it shares common pre-processes, interfaces, and master data, as well as detailed sales and promotional histories. Marquee offers side-by-side comparisons of Weekly Forecasts from Prevail and Sales Plans from Marquee.

Marquee Key Features

Dimensioning of Sales Plans

Some clients forecast by package, others by brand/flavor, most by SKU.  The plans may be broken out by sales organizational unit (territory, territory, division, etc.), delivery warehouse, channel and/or major key account.  Each client has the flexibility to define the resolution at which the plans will be structured and reviewed.

Weekly Forecasting Integration

Compare the most recent weekly forecasts to the Sales Plans (the rolling estimates and annual business plans) through our detail-level solution which greatly facilitates the integration of Prevail and Marquee.

Workflow and Authorization Control

Sales planning is a complex and collaborative process, thus Marquee provides a very well defined workflow, including adjustment of plans in defined stages and hand-offs.  Stakeholders typically include Commercial Planning, Sales & Marketing, Replenishment Planning, Operations and Financial areas.  Roles are defined and authorization rights to review and adjust granted to Plansets (subsets of the Sales Plans).

Sales Plan Editioning

Each period (or month) the rolling estimate sales plan is approved and published.  Each published plan is saved as an “edition”.  When reviewing plans, the planner is able to visualize and compare plans from previous editions.  Also accuracy is measurable by both edition and lag (based on the lag time between edition and actual sales).  Similarly, the annual business plan may be saved into editions as it is being developed for later comparison and analysis.

Promotion Campaign Management

Each Marketing and Trade Promotion Campaign can be flexibly defined based on its scope and timeframe. The campaigns may define promotional type (exception), net and retail pricing plans, buy-get cases, outlet participation, new product introductions, sales targets, etc.

Alternate Scenarios

Create alternate hypothetical scenarios for the Sales Plans, e.g. optimistic, best estimate, and pessimistic scenarios, and work within these hypotheticals to compare projections based on alternative pricing or other promotional considerations.

Financial Projections

Sales volume projections must be extensible to sales revenue and ideally to margin. This requires net pricing, standard costs, tax rates, “incidence” rates be available. Depending on the complexity of the local-client cost model, financial projection calculations may be customized. The ability to instantly project revenue and margin without exporting sales plans for external financial analysis is a major benefit.

Hierarchical Review and Adjustment

The Sales Plan editors provide great flexibility, strong comparative context and quick response-time.  This is the core and most powerful feature of the Marquee application. 

Flexibly defining multiple hierarchies to review and adjust rolling estimates is critical to accuracy and accountability.  It also allows the planner to undertake the vital task of comparing plans with historical actual sales, previous rolling estimate editions, business plan, the roll-up weekly forecasts, alternate scenarios and prior stages. 

Transition Management and Restatement

Over time the business environment inevitably changes: new products replace old products, customers acquire or are acquired by other customers, etc.  It is critical that the sales history used to update forecasting models be “restatable” to reflect these changes in the product portfolio, the market hierarchies or the supply network.  The detailed sales and promotional history are specifically designed to facilitate such restatements, allowing the forecasting models to reflect the current (and future) business environment.