Update README.md

README.md

@@ -14,5 +14,6 @@ The live dashboard can be accessed online, here:
 ### Dashboard Workflow
 
 * **Step 1: Data Source** ("Dashboard dataset.xlsx") - the data source must be located within the same folder (or GitHub repository) as the following python scripts.
-* **Step 2: Load & Transform Data Source** ("BOE_Data.py") - this python script uses pandas library to load, clean and transform the Data Source from step 1. The final output of this python script is an object called "data_bundle.pickle", which contains several dataframes that feed in to subsequent data visualisations.
-* **Step 3: Load data_bundle and generate interactive dashboard** ("BOE_Dash.py") - this python script unpacks the "data_bundle.pickle" object produced in step 2, and uses the resulting bundle of dataframes to generate various plots. This python script makes heavy use of "Dash" and "Plotly" libraries to build the dashboard and its interactive features.
+* **Step 2: Utilities** ("BOE_Utilities.py") - this utilities file contains several functions that will be invoked in the next step. Housing these functions separately in this utilities file is intended to aid the user's comprehension of how the files, including "BOE_Data.py", work together.
+* **Step 3: Load & Transform Data Source** ("BOE_Data.py") - this python script makes heavy use of the functions defined in our "BOE_Utilities" module, to load, clean and transform the Data Source from step 1. The final output of this python script is an object called "data_bundle.pickle", which contains several dataframes that feed in to subsequent data visualisations.
+* **Step 4: Load data_bundle and generate interactive dashboard** ("BOE_Dash.py") - this python script unpacks the "data_bundle.pickle" object produced in step 3, and uses the resulting bundle of dataframes to generate various plots. This python script makes heavy use of "Dash" and "Plotly" libraries to build the dashboard and its interactive features.