Suppose I want to asses employee's job satisfaction, so for the same, I have to develop a new scale or I can use Minnesota job satisfaction or some other scale.
Should you wish to compare your results with other published studies, it is incumbent upon you to use the same measuring instruments others have used. To fail to do so, would just introduce another variable -- unless that is your objective.
There's a saying that a scientist would rather use another scientist's toothbrush than his methods. I heartily agree with earlier comments that by custom-creating your own psychometric instrument in lieu of a an already-published instrument (that ideally has had its psychometric properties assessed), you are preventing the ability for an apples-to-apples comparison with other similar research. Also, at least at the NIH, the wave of the future is Big Data and data sharing, where large sample sizes for secondary data analysis are more feasible to use when several labs/groups use the same questionnaire or whatever. For this reason, the NIH sponsored the creation and dissemination of the NIH toolbox of cognitive measures, and the PhenX toolkit https://www.phenxtoolkit.org/ for downloadable questionnaires. This is not to say that these instruments should be the crucial dependent variables or tasks central to a study, but are handy if the item content reasonably captures what you're looking for.
As far as I know, we can use the original instrument from the author, or we can make an adaptation of it. Depending on the purpose of your study, and the condition of your sample. You can make the questionnaire more specific by adjusting it to the real work place activities / environment.
As others have noted, for research that will be published or compared to other studies, it's usually best to utilize preexisting methods of assessment that have been empirically examined for validity and reliability. Importantly, existing scales should not be altered if they are to retain their capability to be readily compared across different authors' studies. If an existing scale is adjusted, then it should be examined again for reliability and validity which could require a pilot study.
Now, if the goal from the research is to inform a client or business and is not intended to result in publications, then it may be acceptable to create an all new scale. But again, from a scientific stance the reliability and validity should be established up front to ensure the measures are successful.
I think that the good solution is at first made a review of existing methods (both published in national language and in English) and check if they allow for testing research hypotheses/allow for assessment of interesting traits/phenomena. If not, then you could think about construction of own method. If you would like not just to collect data but also propose your scale to others, then you could use existing, well-established scales along with your own method. Then it is possible that your method will occur to be better than existing ones to assessment and your future research. If not - you always have useful data, as you have chosed some method, what was validated and published before. And you could compare your results to former findings.
I think it depends on the variable you are going to capture and its conceptualization. If (i) the variable you want to measure has commonly agreed definition and you intend to use this definition and (ii) an already validated scale based on this conceptualization is available, it is better to use this scale. On the other hand, if a commonly agree definition and or scale is not found and you have operationalized the variable, then you should develop your own scale.