Combination degree forecasts
The first forecast of this sub-team is the aggregate-level gross sales forecast. With this mission, we forecast the gross sales for the upcoming X weeks, each on the weekly and day by day ranges. To offer a little bit of context round aggregation, one doable degree of aggregation may very well be the gross sales of the corporate as a complete. Such a forecast can assist with making company-level selections and dealing on setting objectives and expectations. One other doable degree can be gross sales that come by means of the warehouses of bol, which is essential for operations and workforce allocation.
An essential widespread attribute of most aggregate-level forecasts in our staff is that in addition they rely on the gross sales forecast (making them downstream forecasts), as gross sales are sometimes the first driver of many different metrics that we’re forecasting.
This leads us to a different essential forecast, which is the buyer assist interplay forecast. With this mission, we offer an estimate of what number of interactions our buyer assist brokers can anticipate throughout the subsequent weeks. This forecast is essential for the enterprise, as we don’t wish to over-forecast, which might result in overstaffing of buyer assist. Alternatively, we additionally don’t wish to under-forecast, as that may result in prolonged ready instances for our clients.
To be sure that our providers (webshop, app) scale effectively through the peak interval (November and December), we additionally present a request forecast, that’s, what number of requests the providers can anticipate through the busy durations.
Lastly, we offer a spread of logistics-related forecasts. Bol has a number of warehouses through which we retailer each our personal objects, and the objects of our companions who wish to use bol’s logistical capabilities to make their enterprise function easily. As such, we offer a couple of completely different forecasts associated to logistics.
The primary one is logistics outbound forecasts, that’s, a forecast indicating what number of objects will depart our warehouses within the coming weeks. Equally, we offer an inbound forecast, which focuses on objects arriving in our warehouses. Moreover, we additionally present a extra specialised inbound forecast that additional divides the incoming objects by the kind of bundle they arrive in (for instance, a pallet vs a field). That’s essential as these completely different sorts of packages are processed by completely different stations throughout the warehouses and we want to verify they’re staffed appropriately.
Merchandise degree forecasts
The second sub-team focuses on item-level forecasts. Bol presents round 36 million distinctive objects on the platform, and for many of these, we do want to supply demand forecasts. These predictions are used for stocking functions. This fashion, we attempt to anticipate the wants of our clients and order any objects they may require effectively prematurely in order that we will ship it to them as quickly as doable.
Moreover, the staff supplies a devoted forecast that may deal with newly launched objects and pre-orders. With this forecast, the stakeholders can anticipate what number of objects will promote someday earlier than the discharge and throughout the subsequent month after the discharge. This fashion, we will be sure that we have now sufficient copies of FIFA or Stephen King’s newest novel.
Lastly, our staff additionally developed a promotional uplift forecast, which helps to guage the uplift in gross sales of a given merchandise primarily based on the worth low cost and the length of the promotion. This forecast is utilized by our specialists to make higher, data-driven selections on the subject of designing promotions.