The work measurement standard of a given work is determined from the standard operating procedure of the work at hand, as well as from a work study program that captures the time taken to carry out all related activities. The activities must be both ‘capture-able’ and ‘analyzable’ in order to set the standard time, where specific values are assigned to defined time elements. Conventional assembly production works are routine, repeatable, have discrete cycle times, and have predictable patterns of execution as per the operating specifications. For this type of work, time studies (also known as ‘pre-determined time methods’) are able to capture and analyze time elements efficiently. However, factory works have become increasingly sophisticated and non-conventional. Many portions of the work now possess opposite characteristics of the aforementioned, to the extent that conventional work measurement methods are no longer efficient in the development of the appropriate work measurement standards. In this paper, case studies are used to describe six characteristic attributes of time elements and the pertinent mapping of work measurement methods in a ‘data capture-able versus data analyzable’ quadrant, which can be used in the development of work measurement standards of non-conventional factory works. The purpose of the paper is to provide an insight of the capture-ability and analyzability of work data. This may prove useful in future workforce models, which are becoming more integrated in terms of ‘digital and human’ patterns rather than the routine human-only operations.