For biopharmaceutical companies preparing for an IPO, data governance is not something that should only be considered at the IPO filing stage.
As a company progresses from early-stage R&D into clinical development, commercialization, license-out activities, and global operations, data related to R&D projects, clinical programs, procurement, contracts, supply chains, expenses, revenue, and finance is often scattered across ERP systems, CRM platforms, project management tools, Excel spreadsheets, and other business applications.
If these data lack unified business rules, master data standards, and financial mappings, companies may face challenges during IPO audits, internal control assessments, management analysis, and subsequent financial disclosures—including limited data traceability, inconsistent data definitions, high manual reconciliation costs, and difficulties connecting operational activities with financial results.
Therefore, one of the core elements of IPO readiness for a biotech company is to establish a unified, traceable, and verifiable operational data infrastructure well in advance.
From R&D-Centric Operations to Complex Data Networks
Traditionally, the core focus of an early-stage biotech company is R&D.
When a company is still small, many business activities can be managed through:
- Excel
- Accounting software
- CRM systems
- Project management tools
- Standalone procurement systems
However, as the company enters a phase of large-scale growth, the relationships between different types of data become increasingly complex.
For example, a biopharmaceutical company may simultaneously manage:
R&D projects
→ CRO/CDMO partnerships
→ Clinical trials
→ Procurement & suppliers
→ Project expenses
→ Contracts
→ Milestones
→ License-out activities
→ Overseas entities
→ Financial accounting
→ Consolidated reporting
When this information is stored across different systems, management does not see one complete picture of the business. Instead, they see fragmented pieces of information from multiple systems.
This is a typical data silo problem.
Key Data Challenges Biotech Companies Should Address Before an IPO
Financial Data Cannot Be Easily Connected to Operational Data
This is a common challenge for growing companies.
For example, suppose an R&D project generates RMB 1 million in costs.
The finance system knows that RMB 1 million was spent, but management may not be able to quickly answer:
- Which project was the money spent on？
- Which stage of R&D was involved？
- Which CRO was involved？
- Which clinical program did it relate to？
- Which contract was associated with the expense？
- What was the budget？
- What was the actual cost？
- How much additional funding will the project require？
When financial data cannot be connected with operational data, the company’s management and analytical capabilities become significantly limited.
Therefore, during IPO preparation, companies should gradually establish clear relationships across:
Business → Project → Contract → Cost → Revenue → Financial Data
Contracts and Revenue Data Need to Be Connected
Biopharmaceutical companies often have complex contractual structures.
Examples include:
- License-out agreements
- License-in agreements
- CRO contracts
- CDMO contracts
- Technical service agreements
- R&D collaboration agreements
- Milestone-based payments
These contracts may involve a sequence such as:
Contract signing → Upfront payment → R&D progress → Milestone → Delivery → Revenue recognition
If contract information, business progress, and financial data are maintained in separate systems, revenue management and audit traceability become significantly more complicated.
Therefore, companies should establish a complete data relationship across:
Contract → Project → Milestone → Business Event → Financial Data
Global Operations Further Increase Data Governance Complexity
Once a biotech company begins expanding globally, data complexity typically increases further.
The company may have:
- Headquarters in China
- U.S. subsidiaries
- European subsidiaries
- Overseas bank accounts
- Multiple currencies
- Multiple legal entities
- Different tax regulations
- Different accounting requirements
- Intercompany transactions
At this stage, the company needs more than just a financial system. It needs a platform capable of supporting multiple entities, multiple currencies, global finance, and unified operational data.
This is one of the reasons why many companies reassess their ERP architecture as they enter a global growth phase.
What Role Does Oracle NetSuite ERP Play in IPO Data Governance？
ERP cannot replace IPO auditors, legal advisors, or financial advisors.
However, a properly designed ERP system can help companies establish a more unified foundation for operational and financial data.
With Oracle NetSuite, companies can build an integrated data framework around:
- Financial management
- Multi-entity operations
- Multi-currency management
- Procurement
- Project management
- Inventory
- Contract management
- Revenue management
- Business processes
- Management reporting
The key point is not that “implementing an ERP means the company is ready for an IPO.”
Rather, through standardized business processes, data standards, and system architecture, companies can establish a more stable and traceable foundation for managing their operations and financial data.
How Melin Helps Biopharma Companies Build a Digital Foundation
For Biotech, CRO, and CDMO companies, Melin focuses on the company’s actual operating processes rather than simply deploying ERP functionalities.
Key areas include:
Financial Management
Establish a unified financial accounting and management framework.
Project Management
Connect R&D projects, clinical programs, and CRO/CDMO projects with project-level costs.
Contract Management
Create clear connections between contracts, projects, milestones, and financial data.
Global Operations
Support multi-entity, multi-currency, and international business management.
Data Governance
Standardize master data, business processes, and financial data definitions.
Management Analytics
Help management move beyond simply seeing “financial results” to understanding the “operational drivers behind those results.”
When Should Companies Start Preparing？
One important principle is:
Do not wait until the IPO filing stage to start governing your data.
A more effective approach is to build data governance progressively:
R&D Stage
Establish foundational business data standards.
Scaling Stage
Implement ERP and core business systems.
Commercialization Stage
Unify financial, project, contract, and supply chain data.
Globalization Stage
Establish multi-entity, multi-currency, and global financial management capabilities.
IPO Preparation Stage
Conduct data governance, internal control, and audit readiness assessments.
Post-IPO
Continuously improve operational analysis and data management.
With this approach, data governance becomes part of the company’s day-to-day operating model, rather than a last-minute effort to “fill in the data” before an IPO.
Questions Biotech Companies Can Ask Before an IPO
Companies can start with the following self-assessment:
- Can financial data be connected to operational data?
- Do R&D projects have standardized project codes?
- Can CRO/CDMO projects be analyzed at the project-cost level?
- Can contracts be linked to specific projects?
- Can milestones be connected to financial data?
- Are License-out and similar transactions supported by a clear end-to-end data trail?
- Do overseas entities follow consistent management and reporting standards?
- Can multi-currency transactions be consolidated under a unified accounting framework?
- Can management quickly access consolidated group-level operational data?
- Can key operational data be traced historically and audited when necessary?
If several of these questions cannot be answered confidently, the company should reassess its current data architecture and governance framework.
