diff --git a/pisa/analysis/analysis.py b/pisa/analysis/analysis.py
index fe9ab18fd..10a18cdea 100644
--- a/pisa/analysis/analysis.py
+++ b/pisa/analysis/analysis.py
@@ -294,28 +294,35 @@ def detailed_metric_info(self, new_info):
                 [d[self.metric[0 if not is_detectors else i]]["maps"]["total"] for
                  i, d in enumerate(self._detailed_metric_info)]
             )
+            # Set off by assuming we're unable to obtain the total prior contribution
+            metric_val_from_priors = np.nan
             if is_detectors:
                 # 1)
                 # TODO: We don't have access to the Detectors instance itself here
                 # -> no straightforward way to correctly determine the total prior
                 # contribution (cf. Detectors.init_params())
-                metric_val_from_priors = np.nan
+                pass
+            elif not "priors_penalty_total" in self._detailed_metric_info[0][self.metric[0]]:
+                # 2) Don't attempt to manually compute total prior contribution:
+                # there may be correlations!
+                pass
             else:
-                # 2)
-                # can obtain the total prior contribution from any of the list entries
-                metric_val_from_priors = np.sum(
-                    self._detailed_metric_info[0][self.metric[0]]["priors"]
-                )
-            total_metric_val_from_detailed = metric_val_from_maps + metric_val_from_priors
+                # 3) Can read out the pre-computed total prior contribution from
+                # any of the list entries
+                metric_val_from_priors = self._detailed_metric_info[0][self.metric[0]]["priors_penalty_total"]
         else:
             self._detailed_metric_info = self.deserialize_detailed_metric_info(new_info)
             if self.metric_val is None:
                 return
             # sanity check on metric value
-            total_metric_val_from_detailed = (
-                self._detailed_metric_info[self.metric[0]]["maps"]["total"] +
-                np.sum(self._detailed_metric_info[self.metric[0]]["priors"])
-            )
+            metric_val_from_priors = np.nan
+            if "priors_penalty_total" in self._detailed_metric_info[self.metric[0]]:
+                metric_val_from_priors = self._detailed_metric_info[self.metric[0]]["priors_penalty_total"]
+            metric_val_from_maps = self._detailed_metric_info[self.metric[0]]["maps"]["total"]
+
+        # Get the total and compare if possible
+        total_metric_val_from_detailed = metric_val_from_maps + metric_val_from_priors
+
         if not np.isnan(total_metric_val_from_detailed):
             if not recursiveEquality(total_metric_val_from_detailed, self.metric_val):
                 logging.warning(
@@ -455,6 +462,7 @@ def get_detailed_metric_info(data_dist, hypo_maker, hypo_asimov_dist, params,
                 if include_maps_binned:
                     name_vals_d['maps_binned'] = MapSet(maps_binned)
                 name_vals_d['priors'] = params.priors_penalties(metric=metric)
+                name_vals_d['priors_penalty_total'] = params.priors_penalty(metric=metric)
             detailed_metric_info[m] = name_vals_d
         return detailed_metric_info
 
@@ -479,6 +487,10 @@ def deserialize_detailed_metric_info(info_dict):
                     # Deserialize if necessary
                     name_vals_d["maps_binned"] = MapSet(**info_dict[m]["maps_binned"])
             name_vals_d["priors"] = info_dict[m]["priors"]
+            if "priors_penalty_total" in info_dict[m]:
+                # Don't assume that this entry exists either, so that old fit
+                # results can still be deserialized
+                name_vals_d["priors_penalty_total"] = info_dict[m]["priors_penalty_total"]
             detailed_metric_info[m] = name_vals_d
         return detailed_metric_info