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In project management, a schedule is a listing of a project's milestones, activities, and deliverables. Usually dependencies and resources are defined for each task, then start and finish dates are estimated from the resource allocation , budget , task duration , and scheduled events.
An aggregate project plan (APP) is the process of creating development goals and objectives and using these goals and objectives to improve productivity as well as development capabilities. The purpose of this process is generally to ensure that each project will accomplish its development goals and objectives.
Aggregate planning is a marketing activity that does an aggregate plan for the production process, in advance of 3 to 18 months, to give an idea to management as to what quantity of materials and other resources are to be procured and when, so that the total cost of operations of the organization is kept to the minimum over that period.
Inputs: Schedule management plan, schedule baseline, performance reports, approved change requests; Tools: Progressive elaboration reporting, schedule change control system, performance measurement, project management software, variance, analysis, schedule comparison bar charts
The schedule is divided into a number of separate time periods (timeboxes), with each part having its own deliverables, deadline and budget. [citation needed] Sometimes referred to as schedule as independent variable (SAIV). [1] "Timeboxing works best in multistage projects or tasks that take little time and you can fit them in the same time slot.
The royal kids might not be allowed to keep some of their Christmas presents from the public this year thanks to the family's strict rules about gift giving.
Aggregate data is high-level data which is acquired by combining individual-level data. For instance, the output of an industry is an aggregate of the firms’ individual outputs within that industry. [1] Aggregate data are applied in statistics, data warehouses, and in economics. There is a distinction between aggregate data and individual data.
Bayesian structural time series (BSTS) model is a statistical technique used for feature selection, time series forecasting, nowcasting, inferring causal impact and other applications. The model is designed to work with time series data. The model has also promising application in the field of analytical marketing. In particular, it can be used ...