How Reaton company - the largest product distributor from Baltics increased the forecasting accuracy from 45% to 85% with Novo Forecast Enterprise?

Three years ago, during the hard times of COVID (yes we almost forgot about it )))) we got an interesting request from our partner to our company Novo BI to help him to increase the forecast accuracy, minimize people involvment (human mistakes) and survive in difficult times when the market was shaken. Someone wanted toilet paper, another - flavour and grains and the customer demand was so unstable. The compamy name is - Reaton, big chain of supermarkets if Baltic states.

The company profile

Reaton has worked since 1998. The company supplies products for HoReCa (80%) and for such retailers as Rimi and Maxima (20%). Reaton cooperates with 3000+ stores in Latvia, Lithuania and Estonia.

The project problems

Before August 2019 the customer used his own methods of sales forecasting using the simplest ERP systems. The employees of the planning department used to make calculations for each SKU or product group. They also communicated with suppliers and customers regarding documents and logistics.

The calculations considered trends and seasonality, but such particularities as delivery time management were not regarded although they were necessary for the customer.

For example, at Reaton stock 100 kg of cheese with a shelf life of 30 days are kept. A large customer places an order for 80 kg of cheese. It seems that everything is perfect and one can make a sale, but then it turns out that the needed shelf life is 60 days. If one doesn’t order a new batch, a shipment will disrupt and that will bring the service level down.

With all this data the forecast accuracy amounted to 40%. It meant that the company was losing money on write-offs and customers’ loyalty whose needs couldn’t be met in time.

In the current situation it would be reasonable to plan on a daily basis. It would help to provide the HoReCa segment with necessary products and exclude stop-positions. However, it would inadequately increase the load on managers and they would have to recalculate the data permanently.

The project tasks

• to increase the accuracy of a daily demand forecast for each SKU
• to set up an automated purchase order to the suppliers on the basis of a daily forecast
• to implement joint planning among the company departments
• to take each customer’s particularities into account

Execution of these tasks would help the customer

• to reduce the amount of expired products and therefore to reduce business expenses
• to increase customer loyalty
• to increase employees’ loyalty, therefore they would concern themselves with more important and interesting tasks

Who Am I?

Larisa Chernova

Chief Business Development Officer in Novo BI.

We help to increase the profit of the companies in 5% annualy with forecasting system.

12 years experience in B2B sales

What was done

• Novo Forecast Enterprise system was implemented and the forecast accuracy was adjusted till August 2019
• In February the forecast accuracy increased to 85%
• When the pandemic came, we refocused ourselves and kept the forecasts on the level of 75-80%

How Novo BI solved the customer’s problem

The system on the basis of historical data with the help of ML algorithms and technologies of editing big data forecasts demand with high accuracy, regarding the necessary factors and also makes actual plans for the departments inside the company and other participants of the supply chain. It means that Reaton can save hundreds of millions of euros a year.

The project’s particularities

• The pandemic and the lockdown of 2020 influenced the world business processes and global supply chains started to break
• Consumer habits of people have also changed, due to income reduction they tend to eat at home more
• Cafes and restaurants closed due to the lockdown. They had to refocus on delivery. Demand was unpredictable – HoReCa lost up to 40% of customers
• Not only restaurants, but all participants of supply chains had to change their approach. For example, they refocused on local suppliers to minimize the risk of supply disruption
• We programmed Novo Forecast Enterprise for reallocation of consumer preferences. The process during the pandemic was as follows: a territorial manager got information from a customer about the status of the work, if the customer stopped the work, the territorial manager entered the blocking function into the forecasts and calculated the purchase forecast with consideration to changes. Then a procurement specialist for inbound logistics made a decision regarding the product purchase

Results

• The forecasting accuracy before the lockdown raised from 45% to 85%, i.e. by 40%
• The forecasting accuracy during the lockdown remained on the level of 80%
• The customer got more detailed and transparent information for each SKU to proceed rotations and introduce promo activities
• We additionally implemented delivery time management and automatic follow-up order, that had been so necessary for the customer
• The customer got the opportunity to consider the needs of each customer on the daily basis and to plan demand by days
• The forecast calculation speed has grown multifold
• The employees of the planning department have switched to more important issues such as business analysis and communication with suppliers.

What Next?

Why don’t we have a quick call, so I could share with you how to increase the profit of your company with forecast of demand automation? I promise not to sell you anything :)

You can just write me to LinkedIn linkedin.com/in/larisachernova