diff --git a/backend/Property.py b/backend/Property.py
index d1858abe..414d0831 100644
--- a/backend/Property.py
+++ b/backend/Property.py
@@ -376,72 +376,51 @@ class Property:
                 )
                 self.recommendations_scoring_data.append(scoring_dict)
 
-            # We also use the representative recommendations to produce transformed EPCs
-            represenative_recs_to_this_phase = [
-                r for r in property_representative_recommendations
-                if r["phase"] <= phase
-            ]
+                simulation_epc = self.epc_record.prepared_epc.copy()
+                # Insert static values
+                simulation_epc["lodgement_date"] = simulation_lodgment_date
+                simulation_epc = {k.replace("_", "-"): v for k, v in simulation_epc.items()}
 
-            # TODO: This is placeholder, but it's to handle the case of having both internal and external wall
-            #       insulation as options. This will cause the process below to fall over, so we take just
-            #       external wall insulation in epc_transformations, if we have both
-            types = [
-                x["type"] for x in represenative_recs_to_this_phase
-            ]
-            if "external_wall_insulation" in types and "internal_wall_insulation" in types:
+                types = [x["type"] for x in previous_phase_representatives]
+                if "external_wall_insulation" in types and "internal_wall_insulation" in types:
+                    raise Exception("We shouldn't have this in the representative recommendations")
                 epc_transformations = [
-                    x["description_simulation"] for x in represenative_recs_to_this_phase if
-                    x["type"] != "internal_wall_insulation"
-                ]
-            else:
-                epc_transformations = [
-                    x["description_simulation"] for x in represenative_recs_to_this_phase
+                    x["description_simulation"] for x in previous_phase_representatives
                 ]
 
-            # It is possible that we could have two simulations applied to the same descriptions
-            # We extract these out
-            phase_epc_transformation = {}
-            for config in epc_transformations:
-                for k, v in config.items():
-                    if k in phase_epc_transformation:
-                        if "-energy-eff" in k:
-                            # We take the highest value
-                            if phase_epc_transformation[k] == "Very Good":
+                # It is possible that we could have two simulations applied to the same descriptions
+                # We extract these out
+                phase_epc_transformation = {}
+                for config in epc_transformations:
+                    for k, v in config.items():
+                        if k in phase_epc_transformation:
+                            if "-energy-eff" in k:
+                                # We take the highest value
+                                if phase_epc_transformation[k] == "Very Good":
+                                    continue
+                                elif phase_epc_transformation[k] == "Good":
+                                    if v == "Very Good":
+                                        phase_epc_transformation[k] = v
+                                elif phase_epc_transformation[k] == "Average":
+                                    if v in ["Good", "Very Good"]:
+                                        phase_epc_transformation[k] = v
+                                elif phase_epc_transformation[k] == "Poor":
+                                    if v in ["Average", "Good", "Very Good"]:
+                                        phase_epc_transformation[k] = v
+                                else:
+                                    phase_epc_transformation[k] = v
+
                                 continue
-                            elif phase_epc_transformation[k] == "Good":
-                                if v == "Very Good":
-                                    phase_epc_transformation[k] = v
-                            elif phase_epc_transformation[k] == "Average":
-                                if v in ["Good", "Very Good"]:
-                                    phase_epc_transformation[k] = v
-                            elif phase_epc_transformation[k] == "Poor":
-                                if v in ["Average", "Good", "Very Good"]:
-                                    phase_epc_transformation[k] = v
-                            else:
-                                phase_epc_transformation[k] = v
 
-                            continue
+                            if phase_epc_transformation[k] == v:
+                                continue
 
-                        if phase_epc_transformation[k] == v:
-                            continue
-
-                        raise NotImplementedError(
-                            "Already have this key in the phase_epc_transformation - implement me"
-                        )
-                    phase_epc_transformation[k] = v
-
-            simulation_epc = self.epc_record.prepared_epc.copy()
-            # Insert static values
-            simulation_epc["lodgement_date"] = simulation_lodgment_date
-
-            # Replace the understores with hyphens
-            simulation_epc = {k.replace("_", "-"): v for k, v in simulation_epc.items()}
-            # Add in today's costs (unadjusted
-            simulation_epc["heating-cost-current"] = int(self.energy_cost_estimates["unadjusted"]["heating"])
-            simulation_epc["hot-water-cost-current"] = int(self.energy_cost_estimates["unadjusted"]["hot_water"])
-            simulation_epc["lighting-cost-current"] = int(self.energy_cost_estimates["unadjusted"]["lighting"])
-            simulation_epc.update(phase_epc_transformation)
-            self.simulation_epcs[phase] = simulation_epc
+                            raise NotImplementedError(
+                                "Already have this key in the phase_epc_transformation - implement me"
+                            )
+                        phase_epc_transformation[k] = v
+                simulation_epc.update(phase_epc_transformation)
+                self.simulation_epcs[rec["recommendation_id"]] = simulation_epc
 
     def update_simulation_epcs(self, impact_summary):
         """