Transparency.

How easily all the participants can see what is going on, in a system of standards and monitoring for compliance with those standards, is a very significant indicator for the system's integrity. But current practice offers only a few units of measurement for transparency, such as whether workers can see their own files ^[2] and whether policies and code standards are accessible to all. ^[3] Transparency of the monitoring process is somewhat better covered (see Monitoring), with openness to government inspection, ^[4] independent monitoring, ^[5] and non-confidential monitoring ^[6] among the factors being checked.  

Two key criteria for transparency, both of which could easily be measured, are (a) whether workers are provided with the findings of any monitors who come to the factory, either directly or through their representatives; ^[7] and (b) whether findings are made public. The recent public disclosure of audit results for 50 factories, provided by the Fair Labor Association for seven of its participating companies, is an example of the latter. ^[8] Routinely checking these two criteria would be a significant advance by itself in measurement practice. 

Having workers see monitors' findings not only reduces the chance of major mistakes and omissions; it also acts as an incentive for monitors to be thorough and accurate in the first place.Having the public see the findings also makes it likelier that errors and omissions will be identified, either immediately or later as other relevant information accumulates. It also creates similar incentives for monitors, at least among monitors who expect to continue in the business and who expect to be competing with other monitors for clients and credibility in the future.A system with transparency mechanisms is therefore significantly more likely to be reliable than one without them. 

Feedback and Revision.

A system that learns from its own experience is also inherently likely to be more reliable than one that does not. Current measurement practice focuses on whether or not there are built-in procedures for review and adjustment, ^[9] including accountability mechanisms ^[10] that create incentives for continuous improvement. Securing the name of the individual manager who is responsible for compliance failures, and explicitly identifying the consequences of failure (including "no consequence" if that is the case), should be a routine part of any compliance monitoring system. 

The closest to a model unit of measurement in this area, combining the themes of feedback and transparency, looks at whether workers are aware of corrective actions that the factory has taken in response to a monitor's findings. ^[11] When a system that is supposedly protecting workers asks those workers if its efforts are succeeding, it is much likelier to be operating in good faith than one that does not. Hence, whether it makes the effort to ask is, itself, a valuable indicator.

Applicable Standards.

Clarity about what the applicable standards are should be taken for granted, and any sign of secrecy is an obvious negative signal. The existence of written policies covering all relevant areas of workers' rights, ^[12] available to all ^[13] in workers' own languages ^[14] and meeting all requirements of local law, ^[15] is easy to measure. 

More difficult to measure are ambiguities in the words of the policies as written, which may indicate a lack of enforceability.Ambiguities vary by topic and are dealt with in the sections covering specific topics that appear above. 

Turnover.

The broadest measure of worker satisfaction is the turnover rate in the factory.This can be measured, for each relevant work category, either in terms of percentage turnover of the workforce in a fixed time period (such as every year), or in terms of the average tenure of workers. ^[16] Turnover is a basic statistic that should be collected routinely. It can be compared with other factories in the same country or region in similar industries. It can also be studied for possible correlation with other statistical measurements (see the discussion of statistical measurement units in Health and Safety and Non-Discrimination above), again across a number of factories for which the same types of data are available.If correlations are identified, then turnover rate can become an extremely useful signal for specific problems in the areas of correlation.