diff --git a/src/ert/analysis/_es_update.py b/src/ert/analysis/_es_update.py
index f83cad05c90..98be1e27749 100644
--- a/src/ert/analysis/_es_update.py
+++ b/src/ert/analysis/_es_update.py
@@ -5,7 +5,6 @@
 from collections import UserDict
 from dataclasses import dataclass, field
 from datetime import datetime
-from math import sqrt
 from pathlib import Path
 from typing import (
     TYPE_CHECKING,
@@ -348,7 +347,14 @@ def _load_observations_and_responses(
     iens_ative_index: npt.NDArray[np.int_],
     selected_observations: List[Tuple[str, Optional[List[int]]]],
     misfit_process: bool,
-) -> Any:
+) -> Tuple[
+    npt.NDArray[np.float_],
+    Tuple[
+        npt.NDArray[np.float_],
+        npt.NDArray[np.float_],
+        List[ObservationAndResponseSnapshot],
+    ],
+]:
     S, observations, errors, obs_keys = _get_obs_and_measure_data(
         source_fs,
         selected_observations,
@@ -359,19 +365,19 @@ def _load_observations_and_responses(
     # in for example evensen2018 - Analysis of iterative ensemble smoothers for
     # solving inverse problems.
     # `global_std_scaling` is 1.0 for ES.
-    scaling = np.ones(len(errors))
-    scaling *= sqrt(global_std_scaling)
+    scaling = np.sqrt(global_std_scaling) * np.ones_like(errors)
+    scaled_errors = errors * scaling
 
+    # Identifies non-outlier observations based on responses.
     ens_mean = S.mean(axis=1)
     ens_std = S.std(ddof=0, axis=1)
-
     ens_std_mask = ens_std > std_cutoff
-    ens_mean_mask = abs(observations - ens_mean) <= alpha * (ens_std + errors * scaling)
+    ens_mean_mask = abs(observations - ens_mean) <= alpha * (ens_std + scaled_errors)
     obs_mask = np.logical_and(ens_mean_mask, ens_std_mask)
 
     if misfit_process:
         scaling[obs_mask] *= misfit_preprocessor.main(
-            S[obs_mask], (errors * scaling)[obs_mask]
+            S[obs_mask], scaled_errors[obs_mask]
         )
 
     update_snapshot = []
@@ -409,10 +415,10 @@ def _load_observations_and_responses(
 
     for missing_obs in obs_keys[~obs_mask]:
         _logger.warning(f"Deactivating observation: {missing_obs}")
-    errors *= scaling
+
     return S[obs_mask], (
         observations[obs_mask],
-        errors[obs_mask],
+        scaled_errors[obs_mask],
         update_snapshot,
     )
 
@@ -512,25 +518,23 @@ def analysis_ES(
         progress_callback(
             AnalysisStatusEvent(msg="Loading observations and responses..")
         )
-        try:
+        (
+            S,
             (
-                S,
-                (
-                    observation_values,
-                    observation_errors,
-                    update_snapshot,
-                ),
-            ) = _load_observations_and_responses(
-                source_fs,
-                alpha,
-                std_cutoff,
-                global_scaling,
-                iens_active_index,
-                update_step.observation_config(),
-                misfit_process,
-            )
-        except IndexError as e:
-            raise ErtAnalysisError(e) from e
+                observation_values,
+                observation_errors,
+                update_snapshot,
+            ),
+        ) = _load_observations_and_responses(
+            source_fs,
+            alpha,
+            std_cutoff,
+            global_scaling,
+            iens_active_index,
+            update_step.observation_config(),
+            misfit_process,
+        )
+
         smoother_snapshot.update_step_snapshots[update_step.name] = update_snapshot
 
         num_obs = len(observation_values)
@@ -747,26 +751,23 @@ def analysis_IES(
             AnalysisStatusEvent(msg="Loading observations and responses..")
         )
 
-        # Load responses, and observations
-        try:
+        (
+            S,
             (
-                S,
-                (
-                    observation_values,
-                    observation_errors,
-                    update_snapshot,
-                ),
-            ) = _load_observations_and_responses(
-                source_fs,
-                alpha,
-                std_cutoff,
-                global_scaling,
-                iens_active_index,
-                update_step.observation_config(),
-                misfit_preprocessor,
-            )
-        except IndexError as e:
-            raise ErtAnalysisError(str(e)) from e
+                observation_values,
+                observation_errors,
+                update_snapshot,
+            ),
+        ) = _load_observations_and_responses(
+            source_fs,
+            alpha,
+            std_cutoff,
+            global_scaling,
+            iens_active_index,
+            update_step.observation_config(),
+            misfit_preprocessor,
+        )
+
         smoother_snapshot.update_step_snapshots[update_step.name] = update_snapshot
         if len(observation_values) == 0:
             raise ErtAnalysisError(