STEP 1: Gather data
...from secondary sources that can support assumption building and identify the limitations of the data
Gather both qualitative and quantitative data. Assumptions should be informed by data available, including population census data, survey data (Demographic and Health Surveys [DHS] and Reproductive Health Surveys [RHS]), research studies, program data about the number of providers trained and number of facilities equipped to offer the method(s), and any information about the experience of the same or like-products (including earlier generations of a product) in similar markets/countries. Complement this data with information about how the NUM will be introduced/scaled up in programs for the time for which you are forecasting—e.g., what are the plans for training, demand generation, rate of geographic expansion, etc.?
Additionally, speak to program managers, implementing partners, and technical experts who have experience introducing or scaling up the NUM in another context. Probe for information that could support assumption building (see Step #2 for tips on questions to ask). If time and funding permit, gather anecdotal data (or better still, survey data) all the way down the supply chain—it is important to understand how contraceptives move in the country, including at the facility and community levels.
Note any inaccuracies and/or discrepancies that may be present in the data sets. For example, the DHS data may be from five years ago and should be adjusted to the current situation. Refer to Table 2 to help you think through the types of data that can be collected to support assumption building and what apparent challenges may exist in the quality of that data.