Using the principles of MBO and systems theory, and drawing upon the proven strength of the techniques of multiple attribute decision and goal programming, (Prem Vrat et al. 1998) proposed a new methodology of productivity measurement termed as Performance Objectives-
Productivity (PO-P). It is a multi-criteria productivity management technique, which lays stress on performance against the objectivated output. One of the primary and most important tasks of a productivity measurement technique is to provide comparative information, i.e. on the rise or decline in productivity along with the identification of opportunities for improvement Productivity of a system should be an indicator of its efficiency and effectiveness. However, external environment has an impact on productivity, which can get altered without any change in the productive efforts of the organisation. PO-P model meets these requirements.
The PO-P concept is the system productivity. The outputs are the performances of the system (and its sub-systems). These include the tangibles as well as the intangibles covering areas, such as goods produced, services rendered, Organisational goals and values. Also included are performance objectives as service to community, contribution to human habitat, participation in societal welfare so as to provide a specified satisfaction to all members of society who have a stake in the organisation. The performance so achieved (as output) is the result of acquisition, deployment and efficient use of resources in a rationally acceptable norm. Emphasis is on achievement of goals related to a system within the constraints of the resources available.
Productivity measurement by PO-P approach consists of the following steps:
- Identification of sub-systems
- Identification of Key Performance areas (KPAs) in each of the sub systems
- Setting of performance objectives
- Ranking and weighting of sub-systems, KP As and performance objectives
- Determination of objectivated output
- Calculation of productivity index and identification of sub-systems, KPAs with low performance.
Identification of sub-systems is the first step and a major exercise. Bums and, StaJker suggest that a system (or a sub-system) has five basic characteristics:
- A central objective and measure of performance
- Its environment
- Its resources
- Its components
- Its management.
An organisation as a system can have functional sub-systems, such as a production sub-system, a marketing sub-system, etc, as well as management subsystems, such as production subsystems, management information sub-system, personnel management sub-system, etc. These subsystems may be also embedded in other sub-systems.
KPAs as in MBO, deal with positive performance and areas where the management is interested that results be the most performing. McConkey recommends that KPA (Key Result Areas as called by McConkey) can be in one or more of the following categories:
- Quantity, such as revenue/production levels,
- Quality, such as customer satisfaction, product quality,
- Timeliness, such as scheduling and customer demands,
- Cost, such as cost of services and manufacturing cost levels.
While identifying KP As, two more considerations are vital. Firstly, identified KP As should be those which are associated with the sub-system effectively. There are bound to be overlaps and some areas would appear to be belonging to more than one sub-system. However, it is the subsystem that controls the development of inputs and has the responsibility of function/objectives that the KP A should belong to. Secondly, KP A should have basis and relevance to
Organisational objectives. As Organisational objectives can vary from one organisation to another, so should the importance of each of the KPA vary? Business budgets, planning and product strategies of the sub-system have priority over the operational responsibilities of the KPA. A KPA must subordinate to the sub-system.