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Combination degree forecasts
The first forecast of this sub-team is the aggregate-level gross sales forecast. With this undertaking, we forecast the gross sales for the upcoming X weeks, each on the weekly and each day ranges. To provide a little bit of context round aggregation, one attainable degree of aggregation could possibly be the gross sales of the corporate as an entire. Such a forecast can assist with making company-level selections and dealing on setting targets and expectations. One other attainable degree can be gross sales that come by means of the warehouses of bol, which is essential for operations and workforce allocation.
An necessary widespread attribute of most aggregate-level forecasts in our workforce is that in addition they depend upon 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 undertaking, we offer an estimate of what number of interactions our buyer assist brokers can anticipate inside the subsequent weeks. This forecast is essential for the enterprise, as we don’t need to over-forecast, which might result in overstaffing of buyer assist. Alternatively, we additionally don’t need to under-forecast, as that might result in prolonged ready instances for our prospects.
To be sure that our companies (webshop, app) scale effectively through the peak interval (November and December), we additionally present a request forecast, that’s, what number of requests the companies can anticipate through the busy intervals.
Lastly, we offer a spread of logistics-related forecasts. Bol has a number of warehouses by 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 totally different forecasts associated to logistics.
The primary one is logistics outbound forecasts, that’s, a forecast indicating what number of objects will go away 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 necessary as these totally different sorts of packages are processed by totally different stations inside the warehouses and we want to ensure 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 manner, we attempt to anticipate the wants of our prospects and order any objects they could require effectively prematurely in order that we are able to ship it to them as quickly as attainable.
Moreover, the workforce offers 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 in the future earlier than the discharge and inside the subsequent month after the discharge. This manner, we are able to be sure that now we have sufficient copies of FIFA or Stephen King’s newest novel.
Lastly, our workforce additionally developed a promotional uplift forecast, which helps to guage the uplift in gross sales of a given merchandise primarily based on the value low cost and the period of the promotion. This forecast is utilized by our specialists to make higher, data-driven selections with regards to designing promotions.
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