How much does forecasting cost ​ you? ​​
A forecast analyst can cost you $70k to $120k a year when you include salary, benefits, and software.  Typically, less than half of their time is spent forecasting.  By hiring us, you can enjoy the following benefits:
Example price/promo adj seasonal model:

Half the Cost

More Accurate

No Turnover

Our prices adjust to your actual needs. Very few companies should be paying for a full-time forecaster and rarely-used software.

We often  improve forecast accuracy up to 30% and can provide much more detail.

It can take  6 months to train a forecaster making turnover very costly. You wont have to worry about us moving on.

Why are your forecasts so far off?
Forecasting is not a skill taught in college. Forecast analysts are often promoted from sales or analytics and rarely have training in correct modeling techniques. Even senior-level forecasters rarely learn more than one of the available models.  

At Edge, we specialize in forecasting and understand the nuances within the different models.  We even have some models that we have developed.  Please see the list below for more information:
What if your forecast
were 100% accurate?
How would a trusted forecast affect you business buying and production?  Even a modest gain in accuracy will generally far outweigh the costs.  Here are areas that are often impacted by having a solid forecast:

  • Reducing stockouts
  • Warehouse management
  • Scheduling production
  • Lowering safety stock​
  • Transportation efficiency
  • Pricing strategies
  • Promotion selection
  • Managing lead times
Why all the different models?
Each model has different strengths, weaknesses, applications, and requirements.  Most forecasters only utilize smoothing models (in spite of their major drawbacks) because they are relatively simple to implement.  We can implement all of these models and even some custom models that we developed.  We also have experience blending models to capture each of their strengths.
Exponential Smoothing / ARIMA​
The industry standard in forecasting models.  These models do very well at capturing seasonal, local, and global trends.  They do, however, have some notable drawbacks.  Because they only take history into account, forecasts are often up to 6 months late picking up new trends (up or down).
Econometric/Dynamic Regression
A well specified regression model can instantly pick up new trends based on forecasted features (e.g. increased marketing spending).  While they can promise a higher degree of accuracy, they require much more data and an experienced econometrician to avoid common data pitfalls.
Machine (Deep) Learning Models
The future of forecasting.  These models can FAR outperform traditional models but require much more data.  These models also require a skilled data scientist to implement and are generally well beyond the skill level of most forecasters making them very rarely used in practice.

Product Features

Seamlessly connects with your database 

Integrated into Microsoft Excel

Developed by industry experts

Customized to meet your exact needs

Advanced Filters to see key insights at a glance

Affordably priced to keep your margins low

Automated reports and updates

Intuitive and easy to use

Continuous support

Request a free quote or consultation
If you have any questions, please do not hesitate to send us a message. We aim to reply within 24 hours.
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  1. Michael is the best excel tool builder I have ever worked with and he has advanced forecast modeling and programming skills. In short time he figured out ways to automate several processes that had been done manually for years and he has made vast improvements to the accuracy of our forecasts.
    Fritz Van de Kamp Vice President of Analytics at