With the growing attention to data as a critical resource, data loss and its associated consequences are of greater concern. Data loss due to different kind of system failures, physical disasters, crimes and human errors may cause costly business damages. This study proposes an analytical framework for assessing the monetary damage of data loss. The assessment is done at the data batch level, and considers factors such as the cost of restoration, monetary damages due to irrecoverable loss, and system interdependencies. A context in which such valuation framework can be applied is the replication of data to remote sites and the associated information technology tools. The configuration of replication solutions is driven today primarily by technical characteristic. This study suggests that value assessment of data batches can be embedded into replication configuration toward reducing business damages of data loss. The proposed framework is evaluated in a simulated environment with large datasets. The results highlight the feasibility of the proposed framework in terms of application and parameter estimation, as well as the potential benefits in terms of taking into consideration the high variability in the value of data between systems when configuring a replication process