Economics

Fundamentals of labor rationing and job grading in agribusiness

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ECONOMICS E

Competent labor rationing allows for establishing a clear shift schedule in the field and on the farm, avoiding equipment downtime during the season, and objectively calculating the payroll fund. The practical basis for this work is provided by the provisions of Chapter 22 of the Labor Code of the Russian Federation. At the same time, working time remains the primary measure for all production costs in agriculture; therefore, all existing standards are derived from the time standard.

Types of labor standards and calculation of output on farms

All indicators used for rationing in agribusiness are divided into several main categories. They allow for calculating both the individual output of a machine operator or a milking machine operator and the farm's staffing requirements.

  • Time standard — the amount of working time in man-hours or man-days required to perform a unit of work by one worker or a team of the appropriate qualification under specific organizational and technical conditions.
  • Output standard — the volume of work in natural units (tons, kilograms, hectares, meters) or conditional units that must be completed per shift or hour.
  • Service standard — the number of pieces of equipment, hectares of area, or workstations assigned to one worker or brigade.
  • Span of control standard — a variety of service standards that determines the number of employees or subdivisions reporting to one manager.
  • Staffing standard — the number of employees of a specific profile required to complete a shift or seasonal assignment.
  • Rationed task — the established volume of work for a specific period.

To calculate the time standard ($H_{вр}$), all categories of shift costs are summed up using the formula:

$$H_{вр} = T_{пз} + T_{оп} + T_{орм} + T_{тд} + T_{пт}$$

where $T_{пз}$ is the preparatory-concluding time, $T_{оп}$ is the operational time, $T_{орм}$ is the time for servicing the workstation, $T_{тд}$ is the time for rest and personal needs, and $T_{пт}$ is the breaks caused by technology and production organization.

The time standard and the output standard are inversely related: reducing the time spent per unit of work leads to an increase in output. To determine the output standard ($H_{выр}$), the ratio of the shift time fund to the time standard per unit of production is used:

$$H_{выр} = \frac{T_{см}}{H_{вр}}$$

where $T_{см}$ is the shift fund of working time, and $H_{вр}$ is the time standard per unit of production (for example, per 1 ton of harvested grain or 1 head of livestock). In conditions where it is difficult to establish an exact time and output standard, service and staffing standards are applied in production.

Methods of measuring working time costs

Historically, rationing methodologies were built on a detailed analysis of micro-movements (hands, feet, torso) and the elimination of non-productive losses. In modern labor rationing practice, two fundamentally different approaches are used: analytical and summary.

Analytical methods involve a preliminary breakdown of the technological process into elements, the design of optimal machine operating modes, and working conditions. The most demanded in practice is the analytical-research method, where time costs are studied directly in production conditions.

  1. Conducting a chronometry. The method serves to study the time costs for cyclically repeating manual and machine-manual operational elements. The process includes breaking down the operation into elements, analyzing observations, and designing the optimal duration for each step. Chronometry is performed using continuous or selective methods.
  2. Compiling a work day photograph. The measurement records absolutely all costs and losses of time during the entire shift or a part of it. Depending on the tasks, individual, group, brigade photography, or self-photography are applied.

Summary methods (experimental and statistical) establish the standard for the entire operation without breaking it down into elements — based on the personal experience of the rater or actual statistical data from past periods.

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