Phase 1: Data Inventory & Consent Audit
Build a detailed, system-level personal data inventory and audit all existing consent mechanisms. This phase creates the foundational data map that everything else depends on. You cannot manage what you do not know you have.
🎯 Objectives
- ✓ Create a comprehensive Record of Processing Activities (ROPA) for all personal data
- ✓ Audit all existing consent collection mechanisms for DPDP compliance
- ✓ Map all data flows — internal and external — involving personal data
- ✓ Identify all instances of children's data processing
- ✓ Assess cross-border data transfer activities
Detailed Record of Processing Activities (ROPA)
🎓 Beginner's Note
ROPA is essentially a big table that says: For Process X, we collect Data Y, for Purpose Z, stored in System A, shared with Vendor B, kept for N months. If you have done data modelling, think of ROPA as an entity-relationship diagram but for privacy.
💡 Consultant Tips
- ● Use a structured spreadsheet or GRC tool — do not try to maintain ROPA in Word documents
- ● Interview process owners for each business function: HR, Finance, Sales, Marketing, Customer Support, IT
- ● Include automated processing: analytics pipelines, ML models, automated marketing, chatbots
- ● Map both structured data (databases) and unstructured data (documents, emails, chat logs)
Consent Mechanism Audit
🎓 Beginner's Note
Go through your client's website and app as if you were a customer. Sign up, create an account, make a purchase. At every step, note: Did they ask for my consent? Was the notice clear? Did I understand what I was consenting to? If you as a professional cannot answer yes, ordinary consumers certainly cannot.
💡 Consultant Tips
- ● Screenshot every consent interface for your audit file
- ● Check for dark patterns: pre-ticked boxes, confusing language, consent buried in T&Cs
- ● Verify that each consent is linked to a specific purpose, not a blanket consent
- ● Test the withdrawal process — try to actually withdraw consent and see how hard it is
Data Flow Mapping
🎓 Beginner's Note
Imagine you are tracking a single customer record from the moment it enters the organisation. Where does it go? Who touches it? Where does it end up? Draw that journey for each major data category. This is your data flow map.
💡 Consultant Tips
- ● Use tools like Visio, Lucidchart, or even simple diagrams — the format matters less than completeness
- ● Distinguish between data flows that cross organisational boundaries and internal flows
- ● Highlight cross-border transfers with a different colour — these need special attention
- ● Include shadow IT and informal channels (WhatsApp, personal email) — they are often the biggest risk
Children's Data Identification
🎓 Beginner's Note
Under 18 means even 17-year-olds are children under DPDP. If your client has any users who might be under 18 — and for consumer-facing businesses, they almost certainly do — you need a plan for children's data compliance.
💡 Consultant Tips
- ● Check if your client's services are used by anyone under 18 — education, gaming, social media, and entertainment companies are high risk
- ● Review age verification mechanisms (or lack thereof)
- ● If the client cannot confirm users are adults, assume children's data is present and plan accordingly
- ● India has a very young population — the under-18 demographic is massive, making this a critical area
Retention Schedule Development
🎓 Beginner's Note
Retention schedule = a table that says 'Delete this type of data after X months/years.' It prevents data hoarding (keeping data forever 'just in case') which is both a privacy risk and a DPDP violation.
💡 Consultant Tips
- ● Start with legal requirements: Income Tax Act (8 years), Companies Act (8 years), GST (6 years), employment records (varies by state)
- ● For data retained only on consent, define purpose-based retention: 'data retained until order is delivered plus 30-day return window'
- ● Do not forget backup tapes and archives — these also contain personal data that must eventually be purged
- ● Create a retention schedule matrix: Data Category / Purpose / Legal Basis / Retention Period / Deletion Method