US 2020/0401967 A1 · IMPROVED RESOURCE NEED FORECASTING TOOL

Abstract

An improved resource need forecasting tool enables more accurate forecasts by leveraging models (e.g., machine learning models) of short-term phenomena such as rapid growth that, if not properly accounted for, can distort forecasts. Improved forecasting provides more reliable labor need projections, and includes receiving activity data for a facility; producing normalized activity data adjusted for the short-term phenomena; forecasting, based at least on the normalized activity data, predicted activity data; adjusting, based at least on an activity cannibalization index, the predicted activity data for the first facility to produce adjusted predicted activity data; adjusting, the adjusted predicted activity data based at least on the short-term phenomena; and generating a resource need report.

Claims20

Dependent claims

A system for resource need forecasting, the system comprising:

a data acquisition sensor located at a first facility;
a processor;
and
a computer-readable medium storing instructions that are operative when executed by the processor to:
receive activity data for the first facility from the data acquisition sensor;
de-seasonalize, based at least on a seasonality index, the activity data for the first facility to produce normalized activity data for the first facility;
forecast, based at least on the normalized activity data for the first facility, predicted activity data for the first facility;
adjust, based at least on an activity cannibalization index, the predicted activity data for the first facility to produce adjusted predicted activity data for the first facility;
adjust, based at least on the seasonality index, the adjusted predicted activity data for the first facility to produce re-seasonalized predicted activity data for the first facility;
and
generate, based at least on the re-seasonalized predicted activity data for the first facility, a resource need report.

8 more elements

One or more computer storage devices having computer-executable instructions stored thereon for resource need forecasting, which, on execution by a computer, cause the computer to perform operations comprising:

collecting historical data from a plurality of facilities;
determining, for each facility within the plurality of facilities, an expected activity;
determining, for each facility within the plurality of facilities, a variation between actual activity and the expected activity;
determining, based at least on the variations for the plurality of facilities, a seasonality index;
receiving activity data for a first facility from a data acquisition sensor, wherein the first facility is not within the plurality of facilities, and wherein the data acquisition sensor comprises at least one sensor selected from the list consisting of:
a sales transaction register, an instrumented e-commerce website, a container sensor, and an automobile drive-up sensor;
de-seasonalizing, based at least on the seasonality index, the activity data for the first facility to produce normalized activity data for the first facility;
forecasting, based at least on the normalized activity data for the first facility, predicted activity data for the first facility;
adjusting, based at least on an activity cannibalization index, the predicted activity data for the first facility to produce adjusted predicted activity data for the first facility;
adjusting, based at least on the seasonality index, the adjusted predicted activity data for the first facility to produce re-seasonalized predicted activity data for the first facility;
generating, based at least on the re-seasonalized predicted activity data for the first facility, a resource need report;
using at least one machine learning (ML) model to perform a task selected from the list consisting of:
forecasting predicted activity data for the first facility, determining the seasonality index, and determining the activity cannibalization index;
and
training the at least one ML model, based at least on the historical data collected from the plurality of facilities.

12 more elements

Dependencies are inferred from the claim text.

Improved resource need forecasting tool

Life of this patent

Improved resource need forecasting tool

Life of this patent

Abstract

Claims20