diff --git a/etl/month_end_automation_wave_2_no_16.py b/etl/month_end_automation_wave_2_no_16.py
new file mode 100644
index 0000000..0c6d3c1
--- /dev/null
+++ b/etl/month_end_automation_wave_2_no_16.py
@@ -0,0 +1,169 @@
+# Wave 2's month end automation
+from tqdm import tqdm
+from monday import MondayClient
+from etl.osmosis_complaince_address_to_files import get_all_items, extract_asset_ids
+from pprint import pprint
+import pandas as pd
+import json
+
+monday_key = "eyJhbGciOiJIUzI1NiJ9.eyJ0aWQiOjQ5ODc2ODQxOCwiYWFpIjoxMSwidWlkIjozNjE3ODAzNCwiaWFkIjoiMjAyNS0wNC0xMVQxMToyMzoxNy40NjdaIiwicGVyIjoibWU6d3JpdGUiLCJhY3RpZCI6MTM5OTc4MjMsInJnbiI6InVzZTEifQ.-2Lit4s46ZF6AXuMW9t0TxIaFLkHqD4Yo-PyM9i2XZY"
+monday = MondayClient(monday_key)
+# NCHA SHDF Wave 3 On Hold
+board_ids = ["6946967610"]
+
+for board in tqdm(board_ids):
+    board_data = monday.boards.fetch_boards_by_id(board)
+    columns = board_data["data"]["boards"][0]["columns"]
+    col_id_map = {col["title"].lower(): col["id"] for col in columns}
+    reversed_col_id_map = {v: k for k, v in col_id_map.items()}
+    
+    
+    items = get_all_items(board, monday)
+
+    all_records = []
+    for row in tqdm(items):
+        data = {}
+        data.update({"address": row['name']})
+        data.update({"client": row['group']['title']})
+        for col in row.get("column_values", []):
+            if col.get("id") in reversed_col_id_map:
+                if col.get("type") == "file":
+                    value = col.get("value")
+                    no_of_files = 0
+
+                    if value:
+                        value = json.loads(col["value"])
+                        no_of_files = len(value.get('files', []))
+                    data.update({reversed_col_id_map[col.get("id")]: no_of_files})
+                elif "no show" in reversed_col_id_map[col.get("id")]:
+                    def extract_number_from_text(text):
+                        number_str = ''
+                        
+                        for char in text:
+                            if char.isnumeric():
+                                number_str += char
+                            elif number_str:
+                                break  # stop once a number sequence ends
+
+                        return int(number_str) if number_str else None
+                    text = col.get("text")
+                    if text is None:
+                        data.update({
+                            reversed_col_id_map[col.get("id")]: col.get("text")
+                        })    
+                    else:
+                        data.update({
+                            reversed_col_id_map[col.get("id")]: extract_number_from_text(text)
+                        })    
+                else:
+                    data.update({
+                        reversed_col_id_map[col.get("id")]: col.get("text")
+                    })
+        all_records.append(data)
+
+# Convert to DataFrame
+df = pd.DataFrame(all_records)
+
+filtered_dfs = []
+
+def get_df(df, column_name, success_critera, job_name):
+    _ = df[
+        df[column_name].str.lower().isin(success_critera)
+    ].copy()
+    _["job_type"] = job_name
+    return _
+
+# RA
+ra = get_df(df, "ra", ["completed"], "RA")
+filtered_dfs.append(ra)
+
+
+# PRE- ATT
+att = get_df(df, "att", ["completed"], "ATT")
+filtered_dfs.append(att)
+
+# V1 Coordination
+v1 = get_df(df, "coordination status".lower(), [
+    "rc complete",
+], "V1 Coordination")
+filtered_dfs.append(v1)
+
+# V2 Coordination
+# v2 = get_df(df, "mtp v2 status", ["rc v2 complete"], "V2 Coordination")
+# filtered_dfs.append(v2)
+
+# # V3 Coordination
+# v3 = get_df(df, "v3 rc status", ["uploaded"], "V3 Coordination")
+# filtered_dfs.append(v3)
+
+# v3 = get_df(df, "v3 invoice status", ["to be invoice"], "V3 Coordination")
+# filtered_dfs.append(v3)
+
+# Design stage 1
+# design1 = get_df(df, "design invoice status", ["to invoice"], "Design")
+# filtered_dfs.append(design1)
+
+# Design revision
+# design2 = get_df(df, "design revision invoice", [
+#     "Rev. A to invoice".lower(),
+#     "Rev. B to invoice".lower(),
+#     "Rev. C to invoice".lower(),
+#     "Rev. D to invoice".lower(),
+# ], "Design Revision")
+# filtered_dfs.append(design2)
+
+# Lodgement Phase 1
+lodg1 = get_df(df, "lodg. phase 1 invoice status".lower(), ["to invoice"], "Lodgement Phase 1")
+filtered_dfs.append(lodg1)
+
+
+# Full Lodgement Phase
+full_lodgement = get_df(df, "full lodgement invoice status".lower(), ["to invoice"], "Full Lodgement")
+filtered_dfs.append(full_lodgement)
+
+# POST EPC
+post_epc = get_df(df, "lodged epc", ["complete", "complete & lodged",], "POST EPC")
+filtered_dfs.append(post_epc)
+
+
+# # POST EPR
+# post_epr = df[
+#     df["post-epc status"].str.lower().isin(["post epr completed"])
+# ].copy()
+# post_epr["job_type"] = "POST ATT"
+# filtered_dfs.append(post_epr)
+
+# Post ATT
+post_att = get_df(df, "post att", ["done", "post att complete"], "POST ATT")
+filtered_dfs.append(post_att)
+
+# Retrofit Evaluation
+retro = get_df(df, "retrofit evaluation", ["done"], "Retrofit Evaluation")
+filtered_dfs.append(retro)
+
+# RA NO Show
+ra_ns  = df[
+    df["ra no show evidence"].fillna(-9999) != df["ra no show invoice"].fillna(-9999)
+].copy()
+ra_ns["job_type"] = "RA NO SHOW"
+filtered_dfs.append(ra_ns)
+
+
+# ATT NO Show
+att_ns = df[
+    df["att no show evidence"].fillna(-9999) != df["att no show invoice"].fillna(-9999)
+].copy()
+att_ns["job_type"] = "ATT NO SHOW"
+filtered_dfs.append(att_ns)
+
+
+# Post visit no show
+# epc_ns = df[
+#     df["epc no show evidence"].fillna(-9999) != df["epc no show invoice"].fillna(-9999)
+# ].copy()
+# epc_ns["job_type"] = "EPC NO SHOW"
+# filtered_dfs.append(epc_ns)
+
+final_df = pd.concat(filtered_dfs).reset_index(drop=True)
+
+final_df[['address', 'client', 'job_type']]
\ No newline at end of file
diff --git a/etl/month_end_automation_wave_3_layout.py b/etl/month_end_automation_wave_3_layout.py
index 586b6da..e393890 100644
--- a/etl/month_end_automation_wave_3_layout.py
+++ b/etl/month_end_automation_wave_3_layout.py
@@ -9,11 +9,15 @@ import json
 
 monday_key = "eyJhbGciOiJIUzI1NiJ9.eyJ0aWQiOjQ5ODc2ODQxOCwiYWFpIjoxMSwidWlkIjozNjE3ODAzNCwiaWFkIjoiMjAyNS0wNC0xMVQxMToyMzoxNy40NjdaIiwicGVyIjoibWU6d3JpdGUiLCJhY3RpZCI6MTM5OTc4MjMsInJnbiI6InVzZTEifQ.-2Lit4s46ZF6AXuMW9t0TxIaFLkHqD4Yo-PyM9i2XZY"
 monday = MondayClient(monday_key)
-# WCHG Walkups-Operations
-board_ids = ["9349630181"]
+board_ids = [
+    # "9349630181", # WCHG Walkups-Operations
+    "8829428746", # 2502 Accent Housing
+  
+]
 
 
 for board in tqdm(board_ids):
+    print(f"working on board {board}")
     board_data = monday.boards.fetch_boards_by_id(board)
     columns = board_data["data"]["boards"][0]["columns"]
     col_id_map = {col["title"].lower(): col["id"] for col in columns}
@@ -68,81 +72,69 @@ df = pd.DataFrame(all_records)
 
 filtered_dfs = []
 
+
+def get_df(df, column_name, success_critera, job_name):
+    if column_name in col_id_map:
+        _ = df[
+            df[column_name].str.lower().isin(success_critera)
+        ].copy()
+        _["job_type"] = job_name
+        return _
+    else:
+        print(f"failed to find {column_name}")
+
+
 # RA
-ra = df[
-    df["ra invoicing status"].str.lower().isin(["to invoice"])
-].copy()
-ra["job_type"] = "RA"
-filtered_dfs.append(ra)
+ra = get_df(df, "ra invoicing status", ["to invoice"], "RA")
+if ra is not None:
+    filtered_dfs.append(ra)
 
 
-# ATT
-att = df[
-    df["pre att invoicing status"].str.lower().isin(["to invoice"])
-].copy()
-att["job_type"] = "ATT"
-filtered_dfs.append(att)
+att = get_df(df, "post att invoicing status", ["to invoice"], "ATT")
+if att is not None:
+    filtered_dfs.append(att)
 
-# V1 Coordination
-v1 = df[
-    df["mtp invoicing status"].str.lower().isin(["(v1) ioe/mtp to invoice"])
-].copy()
+modeling = get_df(df, "mtp invoicing status", ["modelling to invoice"], "V3 Coordination")
+if modeling is not None:
+    filtered_dfs.append(modeling)
 
-v1["job_type"] = "V1 Coordination"
-filtered_dfs.append(v1)
+v1 = get_df(df, "mtp invoicing status", ["(v1) ioe/mtp to invoice"], "V1 Coordination")
+if v1 is not None:
+    filtered_dfs.append(v1)
 
-# V2 Coordination
-v2 = df[
-    df["mtp invoicing status"].str.lower().isin(["(v2) ioe/mtp to invoice"])
-].copy()
+v2 = get_df(df, "mtp invoicing status", ["(v2) ioe/mtp to invoice"], "V2 Coordination")
+if v2 is not None:
+    filtered_dfs.append(v2)
 
-v2["job_type"] = "V2 Coordination"
-filtered_dfs.append(v2)
+v3 = get_df(df, "mtp invoicing status", ["(v3) ioe/mtp to invoice"], "V3 Coordination")
+if v3 is not None:
+    filtered_dfs.append(v3)
 
-# V3 Coordination
-v3 = df[
-    df["mtp invoicing status"].str.lower().isin(["(v3) ioe/mtp to invoice"])
-].copy()
-
-v3["job_type"] = "V3 Coordination"
-filtered_dfs.append(v3)
-
-# Design stage 1
-design1 = df[
-    df["design invoicing status"].str.lower().isin(["to invoice"])
-].copy()
-design1["job_type"] = "Design"
-filtered_dfs.append(design1)
+design1 = get_df(df, "design invoicing status", ["to invoice"], "Design")
+if design1 is not None:
+    filtered_dfs.append(design1)
 
 # Design Revision
 revision_letter = ['a', 'b', 'c', 'd']
 for letter in revision_letter:
-    design2 = df[
-        df["design revision invoice"].str.lower().isin([f"rev. {letter} to invoice"])
-    ].copy()
-    design2["job_type"] = "Design Revision"
-    filtered_dfs.append(design2)
+    design = get_df(df, "design revision invoice", [f"rev. {letter} to invoice"], "Design Revision")
+    if design is not None:
+        filtered_dfs.append(design)
 
 # Lodgement Phase 1
-lodg1 = df[
-    df["lodgement phase 1 invoicing status"].str.lower().isin(["to invoice"])
-].copy()
-lodg1["job_type"] = "Lodgement Phase 1"
-filtered_dfs.append(lodg1)
+lodg1  = get_df(df, "lodgement phase 1 invoicing status", ["to invoice"], "Lodgement Phase 1")
+if lodg1 is not None:
+    filtered_dfs(lodg1)
 
 # Full Lodgement Phase
-lodg2 = df[
-    df["full lodgement invoicing status"].str.lower().isin(["to invoice"])
-].copy()
-lodg2["job_type"] = "Full Lodgement"
-filtered_dfs.append(lodg2)
+lodg2 = get_df(df, "full lodgement invoicing status", ["to invoice"], "Full Lodgement")
+if lodg2 is not None:
+    filtered_dfs.append(lodg2)
 
 # POST EPC
-post_epc = df[
-    df["post epc & eval. invoicing status"].str.lower().isin(["to invoice"])
-].copy()
-post_epc["job_type"] = "POST EPC"
-filtered_dfs.append(post_epc)
+post_epc = get_df(df, "post epc & eval. invoicing status", ["to invoice"], "POST EPC")
+if post_epc is not None:
+    filtered_dfs.append(post_epc)
 
 
 # # POST EPR, not right now
@@ -152,45 +144,31 @@ filtered_dfs.append(post_epc)
 # post_epr["job_type"] = "POST ATT"
 # filtered_dfs.append(post_epr)
 
-
-# Post ATT
-post_att = df[
-    df["post att invoicing status"].str.lower().isin(["to invoice"])
-].copy()
-post_att["job_type"] = "POST ATT"
-filtered_dfs.append(post_att)
-
+post_att = get_df(df, "post att invoicing status", ["to invoice"], "POST ATT")
+if post_att is not None:
+    filtered_dfs.append(post_epc)
 
 # Retrofit Evaluation
-retro = df[
-    df["rc stage 2 invoicing status"].str.lower().isin(["to invoice"])
-].copy()
-retro["job_type"] = "RC stage 2"
-filtered_dfs.append(retro)
+rc = get_df(df, "rc stage 2 invoicing status", ["to invoice"], "RC stage 2")
+if rc is not None:
+    filtered_dfs.append(rc)
 
 # RA NO Show
-ra_ns  = df[
-    df["ra no show invoice"].str.lower().isin(["to invoice","to invoice (+1 previous no show)", "to invoice (+2 previous no shows)"])
-].copy()
-ra_ns["job_type"] = "RA NO SHOW"
-filtered_dfs.append(ra_ns)
+ra_ns  = get_df(df,"ra no show invoice", ["to invoice","to invoice (+1 previous no show)", "to invoice (+2 previous no shows)"], "RA NO SHOW")
+if ra_ns is not None:
+    filtered_dfs.append(ra_ns)
 
 
 # ATT NO Show
-att_ns = df[
-    df["pre att no show invoice"].str.lower().isin(["to invoice","to invoice (+1 previous no show)", "to invoice (+2 previous no shows)"])
-].copy()
-att_ns["job_type"] = "ATT NO SHOW"
-filtered_dfs.append(att_ns)
+att_ns = get_df(df, "pre att no show invoice", ["to invoice","to invoice (+1 previous no show)", "to invoice (+2 previous no shows)"], "ATT NO SHOW")
+if att_ns is not None:
+    filtered_dfs.append(att_ns)
 
 
 # Post visit no show
-#post work no show invoice
-epc_ns = df[
-    df["post works no show invoice"].str.lower().isin(["to invoice","to invoice (+1 previous no show)", "to invoice (+2 previous no shows)"])
-].copy()
-epc_ns["job_type"] = "EPC NO SHOW"
-filtered_dfs.append(epc_ns)
+epc_ns = get_df(df, "post works no show invoice", ["to invoice","to invoice (+1 previous no show)", "to invoice (+2 previous no shows)"], "EPC NO SHOW")
+if epc_ns is not None:
+    filtered_dfs.append(epc_ns)
 
 final_df = pd.concat(filtered_dfs).reset_index(drop=True)