diff --git a/R/final_models.R b/R/final_models.R
index cc97ab98..6823599f 100644
--- a/R/final_models.R
+++ b/R/final_models.R
@@ -619,6 +619,15 @@ final_models <- function(run_info,
 
   # clean up any parallel run process
   par_end(cl)
+  
+  # condense outputs into less files for larger runs
+  if(length(combo_list) > 100) {
+    cli::cli_progress_step("Condensing Forecasts")
+    
+    condense_data(run_info, 
+                  parallel_processing,
+                  num_cores)
+  }
 
   # reconcile hierarchical forecasts
   if (forecast_approach != "bottoms_up") {
@@ -633,13 +642,6 @@ final_models <- function(run_info,
     )
   }
   
-  # condense outputs into less files for larger runs
-  if(length(combo_list) > 1000) {
-    condense_data(run_info, 
-                  parallel_processing,
-                  num_cores)
-  }
-  
   # calculate weighted mape
   weighted_mape <- get_forecast_data(run_info = run_info) %>%
     dplyr::filter(Run_Type == "Back_Test", 
diff --git a/R/hierarchy.R b/R/hierarchy.R
index da0ab062..72d87255 100644
--- a/R/hierarchy.R
+++ b/R/hierarchy.R
@@ -420,6 +420,20 @@ reconcile_hierarchical_data <- function(run_info,
   hts_nodes <- hts_list$nodes
   original_combo_list <- hts_list$original_combos
   hts_combo_list <- hts_list$hts_combos
+  
+  # check if data has been condensed
+  cond_path <- paste0(
+    run_info$path, "/forecasts/*", hash_data(run_info$experiment_name), "-",
+    hash_data(run_info$run_name), "*condensed", ".", run_info$data_output
+  )
+  
+  condensed_files <- list_files(run_info$storage_object, fs::path(cond_path))
+  
+  if (length(condensed_files) > 0) {
+    condensed <- TRUE
+  } else {
+    condensed <- FALSE
+  }
 
   # get unreconciled forecast data
   if (is.null(parallel_processing)) {
@@ -430,10 +444,17 @@ reconcile_hierarchical_data <- function(run_info,
     return_type <- "df"
   }
 
-  fcst_path <- paste0(
-    "/forecasts/*", hash_data(run_info$experiment_name), "-",
-    hash_data(run_info$run_name), "*models", ".", run_info$data_output
-  )
+  if(condensed) {
+    fcst_path <- paste0(
+      "/forecasts/*", hash_data(run_info$experiment_name), "-",
+      hash_data(run_info$run_name), "*condensed", ".", run_info$data_output
+    )
+  } else {
+    fcst_path <- paste0(
+      "/forecasts/*", hash_data(run_info$experiment_name), "-",
+      hash_data(run_info$run_name), "*models", ".", run_info$data_output
+    ) 
+  }
 
   unreconciled_tbl <- read_file(run_info,
     path = fcst_path,
@@ -677,11 +698,6 @@ reconcile_hierarchical_data <- function(run_info,
             ) %>%
               dplyr::select(Combo, Date, Target)
 
-            fcst_path <- paste0(
-              "/forecasts/*", hash_data(run_info$experiment_name), "-",
-              hash_data(run_info$run_name), "*models", ".", run_info$data_output
-            )
-
             schema <- arrow::schema(
               arrow::field("Combo_ID", arrow::string()),
               arrow::field("Model_ID", arrow::string()),
diff --git a/R/read_write_data.R b/R/read_write_data.R
index a2999023..5ee304b0 100644
--- a/R/read_write_data.R
+++ b/R/read_write_data.R
@@ -86,21 +86,20 @@ get_forecast_data <- function(run_info,
   }
   
   # get forecast data
-  if(condensed) {
-    print("reading condensed files")
+  if(forecast_approach != "bottoms_up") {
     fcst_path <- paste0(
       "/forecasts/*", hash_data(run_info$experiment_name), "-",
-      hash_data(run_info$run_name), "*condensed", ".", run_info$data_output
+      hash_data(run_info$run_name), "*reconciled", ".", run_info$data_output
     )
-  } else if (forecast_approach == "bottoms_up") {
+  } else if (condensed) {
     fcst_path <- paste0(
       "/forecasts/*", hash_data(run_info$experiment_name), "-",
-      hash_data(run_info$run_name), "*models", ".", run_info$data_output
+      hash_data(run_info$run_name), "*condensed", ".", run_info$data_output
     )
   } else {
     fcst_path <- paste0(
       "/forecasts/*", hash_data(run_info$experiment_name), "-",
-      hash_data(run_info$run_name), "*reconciled", ".", run_info$data_output
+      hash_data(run_info$run_name), "*models", ".", run_info$data_output
     )
   }
 
@@ -716,7 +715,7 @@ condense_data <- function(run_info,
   list_of_batches <- list()
   
   # Define the batch size
-  batch_size <- 10000
+  batch_size <- 100
   
   # Calculate the number of batches needed
   num_batches <- ceiling(length(initial_file_list) / batch_size)