Sales, Make and Finance data unified; KPI reporting automated
Python
Make
Notion
Google Apps Script
scikit-learn
Sources
Pipeline
Notion AI workspace
Pricing models
KPI dashboards
Step 1 Sales, Make and Finance data.
Step 2 Python and Make (Integromat) move the data automatically.
Step 3 One centralised workspace for business insights.
Step 4 scikit-learn models compare pricing approaches and profitability.
Step 5 Apps Script and Google Finance API automate KPI reporting.
Animated overview of the steps below (an illustration, not recorded footage).
Before vs after
Before
Before
Sales, Make and Finance data apart
Financial reporting not yet automated
After
After
One Notion AI workspace for insights
Automated KPIs: net profit, gross profit, payback
Executive-only cost data restricted
From three sources to automated KPIs
01Step 1 of 5
Sources
Sales, Make and Finance data.
02Step 2 of 5, Make (Integromat)
Pipeline
Python and Make (Integromat) move the data automatically.
03Step 3 of 5, Notion
Notion AI workspace
One centralised workspace for business insights.
04Step 4 of 5, scikit-learn
Pricing models
scikit-learn models compare pricing approaches and profitability.
05Step 5 of 5, Google Apps Script
KPI dashboards
Apps Script and Google Finance API automate KPI reporting.
Tech stack in this project
PythonPipeline code integrating the three sources
Make (Integromat)Automation scenarios moving the data
NotionCentralised AI workspace for insights
scikit-learnPricing prediction models, compared
Google Apps ScriptAutomated KPI reports and dashboards
Google Finance API
Why it matters for supply chain
Data integration = logistics systems and ERP integration
Pricing models = margin-aware quoting
Access control = safe sharing of cost data
Linked to my Master of Logistics & SCM, University of Sydney
Read the full case study
Problem
Sales, Make and Finance data needed to be brought together for business insights, and financial reporting needed to be automated while keeping executive-only cost data restricted.
Approach
Built an automated data pipeline using Python and Make (Integromat) integrating Sales, Make and Finance data into a centralised Notion AI workspace for business insights.
Built and compared pricing prediction models with scikit-learn to examine pricing approaches and profitability considerations.
Automated financial reporting and dashboards with Google Apps Script and the Google Finance API, providing KPIs such as net profit, gross profit and payback period.
Restricted executive-only cost data within the reporting.
