module-name
Screenshot
Value proposition
The Traffic Forecast sheet is the sheet that allows you to make forecasts about officinal traffic.
This sheet is based on the OpenSource Python library Prophet made by Facebook. The PyTools 5.1 connector was integrated with QLIK to perform this decomposition. The decomposition method used in this library is based on the ARIMA calculation method.
This module is for you if:
You want to estimate the impact of an event on pharmacy traffic
You want to perform advanced analysis on a market
Data source
Geographic territories
Data for Metropolitan France
Market
No limitation on market size
Applicable on human medicine, veterinary medicine and non-medicinal product
Staut
Subscription
Freemium
Objects-present-in-the-sheet
Functional cartridge
Dispensing/Volume/Volume per dispensing/GTIN per dispensing selector button
Dispense Mode Selector Button Additive/Multiplicative Dispensing
Learning period selector
Time period selector
Confidence level slider
Prescription type selector
Prediction curve
Supernumerary accumulation KPIs for volume and dispensations
KPIs of average supernumeraries for volume per dispensation and GTINs per dispensation
Supernumerary analysis bar chart
Limitation
Quarterly and yearly forecasts do not have enough training data to be sufficiently reliable
It is imperative to choose a training period to get a visualization
Versions
Adding different temporalities, granularity to the product
Adding KPIs, changing bar chart sorting
First version