Access to data can be limited. Confidentiality may restrict access, as mentioned earlier in this chapter. Data format may not be conducive, or may lack the desired detail. For example, when obtaining information on the number of available childcare facilities in a given area, data might reflect the total number of childcare facilities located in the area, rather than total childcare facilities with availability for new children. Data may require caveats, such as projections, rather than historic changes.
Most of the before mentioned difficulties can be addressed through careful attention to the assumptions behind the data, and care in applying the results of any analysis. Data incongruities can be addressed in several ways. One method is to report the results of any analysis in a likely range, rather than as a single number (i.e., the number of available childcare openings is estimated to be between 200 and 300). Another is to conduct sensitivity analyses (i.e., the area has an estimated 250 child care openings annually - sensitivity analysis shows this number changes as much as 20% as the estimate's assumptions change). Finally, planners may have to acknowledge that the existing data is unacceptable.