6  Limitations and risks

Data collection methods carry certain limitations and risks, which should be considered and mitigated to the extent possible during the design and implementation of DTM activities. Specific limitations and risks associated with DTM tools and methods covered in this Framework are indicated throughout the various tables in the previous section. Limitations and risks may vary depending on the tools and methods that are adapted or combined. The characteristics of a particular implementation approach and any related caveats for analysis or use of the data produced, should be indicated in the methodology section of DTM information products. Furthermore, IOM DTM co-authored the Inter-Agency Standing Committee (IASC) Operational Guidance on Data Responsibility in Humanitarian Action,1 providing tools on how to design data activities responsibility.

Given variations in approaches and operating environments, a risk assessment is recommended when designing a DTM exercise to identify areas of concern specific to the context and ensure mitigation measures are in place throughout implementation.2 This includes identification of potential risks for mobile populations when selecting components, tools and methods during the planning stages, as well as regular monitoring and adjustments to minimize risks throughout implementation. Do No Harm is to be prioritised throughout the entire process, including during analysis of results and sharing of data. Including an explanation of the approach, objectives and limitations of data collection when disseminating DTM products can mitigate the risk of inaccurate or misleading data analysis by third parties, for purposes that undermine the well-being of populations on the move.

In the early stages of a response, provision of the best information possible within the shortest time frame may be prioritized over statistical robustness of data, in order to produce an initial indication of population movements and needs to kick-start response planning. As access expands and the universe of analysis becomes known with more certainty, DTM exercises will often be adapted or expanded to incorporate additional tools and methods, generating information with greater validity, accuracy or precision. Data collection through DTM is repeated in multiple rounds to regularly refresh and refine available information and to adapt as needed to change in the operational context or information objectives. Past implementation experience has shown that different components, tools and methods may become relevant at different stages of an operation and combining elements can strengthen an approach and enrich the data and information produced.