How to reshape the supply chain at lockdown and increase the accuracy of demand forecasts by 15%

“Wolta” case
Novo Forecast Enterprise implementation case
  • The company profile
    Wolta is one of the largest manufacturers of lighting systems in Russia and the CIS countries. The assortment range includes interior, industrial, street and commercial lighting.
    Four product brands have a total of about 2,400 SKUs.
    The company purchases production orders in China and then delivers them to Russia and the CIS countries. In addition, Wolta purchases components from Russian suppliers and sells products through the distribution, retail and e-commerce networks.

    The project challenges

    With the start of the lockdown, the company faced higher costs and an unpredictable increase in delivery time:

    • freight rates rose sharply
    • there was a shortage of containers
    • transportation routes have changed.

    External problems were added to the internal ones.

    Demand forecasting at Wolta was done almost manually and did not include some important factors. Moreover, the company has a long delivery "shoulder": 6 months or more can pass from the order to delivery to the warehouse.

    Therefore, Wolta was calculating demand 3 times a year. In normal times, this would have been appropriate, but with the constantly changing economic situation and spiraling demand, it was not enough.


  • What was done

    • Step-by-step implementation of the Novo Forecast Enterprise system
    • The first months were spent working on improving demand forecasting, after which we moved on to implementing the supply chain planning system.
    • Since the integration of Novo Forecast Enterprise, all the necessary data is now in one system, everything is based on data from one source.
  • The project tasks

    The company has set multiple goals for itself:

    • Increase the accuracy of sales forecasts by improving algorithms and taking into account new factors
    • Improve the interaction of departments in the supply chain
    • To start reacting quickly to changes in sales, purchasing, and production
The Results:

Now, the company is using a tool that allows executives see the whole picture of the business for the long term. This makes possible to identify problems in a proper time and to minimize losses.

There is an improvement in many of the company's key business indicators:

  • Forecast accuracy has grown by 15 percentage points: from 49% to 64%.
  • Forecast recalculation speed increased from one week to one hour
  • Now forecasts are calculated on a monthly basis or "by event" instead of three times a year
  • Out-of-stock situations decreased, and service level increased up to 90% (+13%)
  • Stock level is expected to decrease by 1.5 times (from 6 to 4 months)
  • Increased confidence in forecasting by all supply chain participants helped to engage employees from different departments into a unified process. This led to the reduction of disputes in the team and a significant increase in the general level of efficiency.
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