Going further with the Enterprise plan of Salescast

Going further with the Salescast Enterprise Plan


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Any doubt about how much Salescast would cost you? Just .

Express Plan: Entirely FREE

You can use the Express Plan of Salescast completely free of charge for as long and as much as you like. Certain features are not available, however the accuracy of the forecasts is not affected. We encourage you to make use of this opportunity to work with Salescast risk and cost free. However, please understand that we do not provide any form of support to Express Plan customers.

Enterprise Plan: Flat fee plus Consumption

The Enterprise Plan costs $750 (500€) per month plus consumption; the consumption being related to the number of forecasts generated by Salescast (see below for the detail). This plan activates the full set of features of Salescast and include customer support as well.

Support package

  • Onboarding - we support you during integration (i.e. pushing historical data to Salescast) and make sure you are set up correctly.
  • Concierge - our forecasting experts routinely validate the quality of your numbers and review your data and settings (ex : service levels) looking for issues.
  • Up to 2 hours per month of direct support to help you reach and sustain the highest inventory performance.

We highly recommend considering the Enterprise plan once you have familiarized yourself with Salescast and want to get serious with improving your inventory performance. Our experience shows that a few hours of regular support go a long way to insure our clients avoid common pitfalls and make the most of our technology.

Extra features

The following features are only available with the Enterprise Plan:
  • Processing more than 10,000 items.
  • Creating more than 1 project.
  • Forecasting further than 12 months, 13 weeks and 14 days ahead, respectively for monthly, weekly and daily forecasts.
  • Programmatic export of the results (through TSV files).
  • Rest API for project run automation.

Programmatic export is especially useful to have the results produced by Salescast being imported back into your systems without any manual intervention.

Forecast consumption

When the Enterprise Plan is active, we charge by the number of forecast points computed by Salescast. Here above, on the right, there is a calculator that gives the Salescast monthly consumption cost based on this quantity. In this section, we review how this consumption is measured and calculated. The consumption formula differs between classic and quantile forecasts.

Classic forecasts

Let's assume you have 200 products to be forecast 10 weeks ahead, twice per month, then the total number of forecast points is 200 x 10 x 2 = 4000 forecasts, which results in $38/month of Salescast consumption.

For n forecasts within the month, we charge $0.15 * n2/3. Try with n=4000 on Google.
Lokad's pricing is non-linear, and provides a major discount when the amount of forecasts increases. For example, if the number of monthly forecasts is 4,000,000 (compared to 4,000), the monthly subscription is only $3800/month, instead of $38000/month. The forecast volume has been multiplied by x1000 while the price has increased only by x100. In other words, the price per forecast has been divided by 10 with the volume growth.

Classic forecast consumption calculator

Let's assume that:

  • You have SKUs (product references)
  • Your forecasts are refreshed times per month
  • You are forecasting for periods ahead (period can be day, week or month)

The monthly consumption cost of Salescast is $0 (0 forecasts per month).

Quantile forecasts

In March 2012, Lokad has introduced quantile forecasts as a radically new and better way of computing optimized reorder points. The pricing of quantile forecasts is similar to the one of classic forecasts except it comes with a twist: we charge per forecast value.

Let's assume you have 200 products that have to be forecast twice per month, where all products end up with a reorder point equal to 10, then the total number of forecast points is 200 x 102/3 x 2 = 1856 forecasts which results in $23/month of Salescast consumption.

Each quantile q - the actual quantile value used as reorder point - is charged as q2/3 classic forecast data points (upper rounded, with a minimal value at 1).
This pricing is motivated by two extremes:

  • Slow mover's: Items associated with reorder points lower than 3 were typically not worth to be forecast with our pricing for classic forecasts. In addition to providing a technology that is much more suited to slow mover's, with our quantile pricing we also provide a lower price on slow mover's, thus avoiding to place our clients in a position where they have to exclude slow mover's from the forecasting scope.
  • High rotations: When financial stakes are high, it's worth trying to invest a lot more computing resources to improve the forecasting accuracy. With a higher price on high rotations, Lokad can invest more, use even more advance models, and deliver more accurate results as well.

Then again, our pricing is non-linear and provides a massive volume discount on high rotations.

Optimizing your forecast consumption

As you start testing your own scenarios with our pricing calculator, you might end-up with ridiculously high subscription costs. We believe this situation is typically caused by a slight misunderstanding, the nature of which is lying in the rather unique technology used by Lokad.

Most classical forecasting systems rely on naive forecasting models (moving average, linear regression, exponential smoothing, etc.) and, as a result, recomputing the forecasts for say the next 52 weeks every day is not an issue because the computational processing power involved is extremely low anyway.

With Lokad, you get fully automated advanced forecasts - all forecasting models are auto-configured by Lokad itself and our set of models combines the classical naive forecasting models and other models much more complex and more accurate. This extra-accuracy comes with a drawback: the actual computation of the forecast requires a lot of computing resources.

In practice this means you won't want to recompute everything on a daily basis, and in particular, not to do it for some far distant future. For example, let's assume a company wants to recompute forecasts on a daily basis for 52 weeks ahead for each product. This would generate about 52*30 = 1560 forecasts per product per month, which is quite a lot.

In fact, there is no reason to update the forecast 52 weeks ahead on a daily basis. Indeed, one extra day of sales has little or no impact on the forecast that goes one year ahead. Instead, we typically suggest a weekly 4-week ahead forecasts, and once a month, to update the 52-week ahead forecasts. This way we have 4 x 4.3 + 52 = 70 forecasts per product per month, that is to say more than 20 times fewer forecasts than with the first method.

This constraint is inherent to any non-trivial forecasting method. In case you would be tempted by a Lokad's competitor who claims to deliver millions of forecasts for pennies, then be aware that you're going to end-up with a moving average variant. There is no free lunch: more accurate forecasts do require more intensive computations.