diff --git a/etl/month_end_automation_wave_3_layout.py b/etl/month_end_automation_wave_3_layout.py
index 4db67a5..e698961 100644
--- a/etl/month_end_automation_wave_3_layout.py
+++ b/etl/month_end_automation_wave_3_layout.py
@@ -21,6 +21,7 @@ class BoardID(Enum):
     _9660895490 = "NORTHUMBERLAND_COUNTY_SHDF_WAVE3"
     _9641491000 = "WATFORD_WARM_HOMES"
     _9671463094 = "SEDDON"
+    _9929454382 =  "NCHA SHDF Wave 3 Main Operation Board"
 
 
 board_ids = [
@@ -30,6 +31,7 @@ board_ids = [
     "9660895490", # Northumberland County SHDF Wave 3
     "9641491000", # Watford Warm Homes
     "9671463094", # Seddon
+    "9929454382", # NCHA SHDF Wave 3 Main Operation Board
 ]
 
 empty = "Rate card info missing"
@@ -53,6 +55,22 @@ rate_card_data_watford_warm_homes = {
 }
 rate_cards.update({"9641491000": pd.DataFrame(rate_card_data_watford_warm_homes)})
 
+rate_card_data_ncha_wave_3 = {
+    "job_type": [
+        "RA", "ATT", "Coordination Stage 1 v1", "Coordination Stage 1 v2 remodel", "Coordination Stage 1 v3 remodel",
+        "Design Archetype Complex", "Design Archetype Simple", "Design Repetitive Simple", "Coordination Stage 2", "Lodgement phase 1", "Full lodgement phase 2",
+        "Post EPR", "Post EPC", "Post ATT", "retrofit evaluation",
+        "RA no show", "ATT no show", "post EPC no show", "Full cost MTP", "measure modelling", "design type not specified"
+    ],
+    "rate": [
+        empty, empty, empty, empty, empty,
+        empty, empty, empty, empty, empty,
+        empty, empty, empty, empty, empty,
+        empty, empty, empty, empty, empty, check_with_andres
+    ]
+}
+rate_cards.update({"9929454382": pd.DataFrame(rate_card_data_ncha_wave_3)})
+
 
 
 rate_card_data_l_and_q_london = {
diff --git a/etl/month_end_automation_wave_accent_housing.py b/etl/month_end_automation_wave_accent_housing.py
index 6541a9b..9e8819f 100644
--- a/etl/month_end_automation_wave_accent_housing.py
+++ b/etl/month_end_automation_wave_accent_housing.py
@@ -172,27 +172,26 @@ final_df = None
 
 if filtered_dfs:
     final_df = pd.concat(filtered_dfs).reset_index(drop=True)
+    if final_df:
+        final_df["job_type"] = final_df["job_type"].str.lower()
+        rate_card_df["job_type"] = rate_card_df["job_type"].str.lower()
 
-if final_df:
-    final_df["job_type"] = final_df["job_type"].str.lower()
-    rate_card_df["job_type"] = rate_card_df["job_type"].str.lower()
+        # Now perform the merge
+        combined_with_rates = final_df.merge(rate_card_df, on="job_type", how="left")
+        import datetime
+        timestamp = datetime.datetime.now().strftime('%Y-%m-%d_%H-%M')
 
-    # Now perform the merge
-    combined_with_rates = final_df.merge(rate_card_df, on="job_type", how="left")
-    import datetime
-    timestamp = datetime.datetime.now().strftime('%Y-%m-%d_%H-%M')
+        # Upload to sharepoint
+        attribute = ['address', 'client', 'job_type', 'rate']
+        master_folder_name = "2501 Accent housing"
+        file_name = f"{master_folder_name}_{timestamp}.xlsx"
+        combined_with_rates[attribute].to_excel(file_name, index=False)
 
-    # Upload to sharepoint
-    attribute = ['address', 'client', 'job_type', 'rate']
-    master_folder_name = "2501 Accent housing"
-    file_name = f"{master_folder_name}_{timestamp}.xlsx"
-    combined_with_rates[attribute].to_excel(file_name, index=False)
+        file_path = os.path.abspath(file_name)
 
-    file_path = os.path.abspath(file_name)
+        upload_to_month_end_folder(file_name, file_path, master_folder_name)
 
-    upload_to_month_end_folder(file_name, file_path, master_folder_name)
-
-    invoice_name = "rate_card.xlsx"
-    file_path = os.path.abspath(invoice_name)
-    rate_card_df.to_excel(invoice_name, index=False)
-    upload_to_month_end_folder(invoice_name, file_path, master_folder_name)
+        invoice_name = "rate_card.xlsx"
+        file_path = os.path.abspath(invoice_name)
+        rate_card_df.to_excel(invoice_name, index=False)
+        upload_to_month_end_folder(invoice_name, file_path, master_folder_name)