Computer-based data collection, management, and forecasting

A data collection, management, and forecasting computer system comprising:

• a datastore
• one or more processors;
• and
• one or more non-transitory computer readable memory storing instructions which when executed by the one or more processors causes the computer system to:
• collect data for a plurality of items;
• store the data for a plurality of items in a first part of the datastore;
• categorize each of the plurality of items;
• store a categorization of each of the plurality of items in a second part of the datastore;
• assign at least one of the plurality of items as an index item for at least another of the plurality of items;
• and
• forecast a value, wherein forecast the value comprises using a first factor of the one of the plurality of items needed over the future period of time with reference to a first context parameter of a plurality of context parameters and using a second factor of the index item with reference to the first context parameter, to calculate the forecast value of the one of the plurality of items needed over the future period of time when the period of time for the data collected for the one of the plurality of items needed over the future period of time is below a first threshold with reference to the first context parameter and above a second threshold with reference to the first context parameter and when a period of time for the data collected for the index item with reference to the first context parameter is greater than a third threshold.

A data collection, management, and forecasting computer system comprising:

• a datastore
• a processor;
• and
• a non-transitory computer readable memory storing instructions which when executed by the processor causes the computer system to reduce a data storage capacity requirement for the computer system and increase the processors's processing speed by:
• collecting data for a plurality of items;
• storing the data for a plurality of items in the datastore;
• categorizing each of the plurality of items;
• storing a categorization of each of the plurality of items in the datastore;
• assigning at least one of the plurality of items as an index item for at least another of the plurality of items, wherein the assigning enables forecasting a value;
• collecting data for a plurality of context parameters related to at least one of the plurality of items;
• storing the data for the plurality of context parameters in the datastore;
• and
• forecasting a value for one of the plurality of items needed over a future period of time, wherein forecasting the value comprises using a first factor of the one of the plurality of items needed over the future period of time with reference to a first context parameter of the plurality of context parameters and using a second factor of the index item with reference to an index context parameter of the plurality of context parameters, to calculate the forecast value of the one of the plurality of items needed over the future period of time;
• when the period of time for the data collected for the one of the plurality of items needed over the future period of time is below a first threshold with reference to the first context parameter and above a second threshold with reference to the first context parameter and when the period of time for the data collected for the index item with reference to the first context parameter is less than a third threshold.