QQdemand.forecast&QQpurchase.orders

Short version of following concepts

Challenges to handle

During the last 15 years we have received multiple request to provide a smart tool for supporting product purchase decisions in various industries, including pharma, FMCG, durables (incl ElectroIT), medical supplies, automotive, clothing & sport, etc.

Based on all the experiences we’ve accumulated, we have developed a set of QQsolutions able to address the following challenges:

Predict future demand as a base point for any purchase logic
Identify the proper purchase reorder frequency
Handle a wide range of purchase scenarios within the same environment
Put together all the data about the past, present and future to define the right purchase quantity
Include immediately the latest purchase orders prepared to revisit the expected future
Provide prescriptive answers, but allow human over-ride

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Main & Additional Parts

In order to handle the above mentioned challenges,  we have developed a set of solutions hereby presented.

QQdemand.forecast is responsible to collect historical sales data, plus additional  historical and forward looking influencers of customers behavior & demand in order to have the best possible demand prediction.

This includes:

  • various automatic forecasting models to be applied on historical data, 
  • an area to qualitatively evaluate the automatic predictions,
  • an area to manually override the automatic forecast (including some comments & override classification options to remember the reasoning at the manual input moment).

QQpurchase.order is the natural step forward, that collects all the pre-existing data regarding current inventory, previous purchase orders &  forecasted demand, plus all the  logistic constraints (lead time, packaging, minimal order, targeted reorder frequency, etc) and generates a purchase order proposal based on all these. 

The automatic proposal can be also manually adjusted prior to final launch. 

Once the order has been launched, it is included in the existing set of previous orders.

Expected orders can also be edited afterwards when the supply confirmation or further adjustments are received from the supplier or the shipper.

QQstrategic.purchaser, together with  QQinventory.healthcheck allows the product/purchase  managers to understand the big picture, how good the previous decisions proved to be and what can be improved, both in automatic predictions and proposals and in the manual inputs taken from now on.

QQinventory.prioritize QQinventory.basic can be used to identify purchase & relocation emergencies & priorities

Data coming from QQpricing and/or  QQpromo can help also in a better understanding of previous and future promotions planning and influence.

QQdemand.elasticity is corroborating the promo & pricing decisions with the purchase decisions. It allows automatic extraction of elasticity and cross-elasticity. But in order to do that, a wide set of data is required.

Integration Diagram

QQdemand.forecast

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Diagram

Interface

QQpurchase.orders

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Diagram

Interface