Client Overview
Ordinary Folk is dedicated to reimagining the building blocks of healthcare in Asia by leveraging technology to simplify the patient experience. Through its platforms - Noah for men’s health, Zoey for women’s wellness, and Cyrus for AI-powered logistics—the company aims to provide modern, discreet, and accessible healthcare solutions for stigmatised conditions across the region.
The Challenge
Ordinary Folk faced several critical data challenges that were impacting their operational efficiency:
- Manual data assembly from multiple sources including Stripe, Facebook Ads, Google Ads, Lazada, and TikTok
- Inconsistent data formats and conflicting information across platforms
- Complex subscription model requiring sophisticated tracking
- Need for unified metrics across three geographical markets
Our Solution
We implemented a comprehensive data transformation program in two phases:
Phase 1: Infrastructure Setup
- Implemented data pipelines to BigQuery warehouse using Fivetran
- Created > 40 intermediate staging tables for visualisation and reporting
- Designed and implemented Tableau Cloud and Pulse dashboards with high-priority metrics
Phase 2: Process Optimisation
- Automated COD (Cash on Delivery) data enrichment for Hong Kong and Singapore markets
- Encoded key classification data directly in Stripe and other upstream metadata fields via API
- Enhanced subscription tracking and analytics
- Developed automated processes for order processing and tracking
Together, these foundations set the stage for scalable insights and leaner operations across teams.
The Results
Our work with Ordinary Folk has delivered significant operational and strategic benefits:
- Eliminated manual data assembly processes: Replaced spreadsheet-based workflows and ad hoc exports with automated pipelines, freeing up 2-4 hours per week for the finance and operations teams
- Automated Subscription and Order Tracking: Streamlined complex fulfilment workflows, especially for Cash on Delivery (COD) orders, ensuring accurate reconciliation and better visibility into customer activity
- Improved Data Accuracy and Trust: Created robust staging layers and embedded classification rules upstream, reducing discrepancies and enhancing the reliability of dashboards used by cross-functional teams
- Empowered Data-Driven Decision-Making: With real-time dashboards and intuitive visualisations now in place, stakeholders can proactively monitor business performance and act on insights without waiting for manual reports
"Partnering with work.flowers unlocked more than just dashboards.
We’ve automated key workflows and are now layering in AI to make decisions faster and smarter.
What stood out most was their ability to think beyond tooling -they helped us architect systems that scale, and gave our team time back to focus on what truly matters.”
Sean Low
Founder, Ordinary Folk
What’s Next
With the foundation now stable, we’re layering on AI to make insights and workflows faster, smarter, and even more proactive:
📈 Executive & Investor Reporting
We’re developing streamlined Tableau dashboards tailored for Monthly Investor Updates and Quarterly Board Decks. These will surface high-level metrics already available in BigQuery, making executive reporting faster, clearer, and less manual.
🤖 AI for Performance Marketing
We’re piloting an AI-driven tool to analyze marketing performance across channels. The system aims to surface proactive insights—such as underperforming segments or emerging trends—and generate hypotheses to guide campaign optimisation. This is an exploratory area, and we’re actively evaluating how well current models deliver actionable value.
🚚 Operational Intelligence with Tableau Pulse
We plan to leverage Tableau Pulse to deliver real-time AI-generated insights into logistics KPIs like delivery times and order fulfilment. To support this, we’ll establish new pipelines that ingest operational data not currently captured in BigQuery or Fivetran.
Let’s Build Together
Ready to move faster with cleaner data and smarter automation? Let’s explore what we can build together.
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