Why Go-Live is So Intense: Lessons on Data Conversions from a Real Plan

This week, I had a great conversation with a senior colleague about why go-live periods can be so chaotic, especially when it comes to data conversions. It helped me connect the dots between planning, execution, and the inevitable late nights during go-live. Here’s what I learned:

✅ Static Data vs. Dynamic Data

When planning data conversions, it’s useful to think of data in two groups:

• Static Data: This is information that doesn’t change much leading up to go-live, like customer records, employee details, or supplier lists. We usually pull this data well in advance, often weeks before the production cutoff, because it’s fairly stable.
• Dynamic Data: This involves transactions and records that keep changing right up until the system shuts down, things like purchase orders, inventory movements, or project transactions. These can only be extracted after the cutoff, once no new entries are being made.

🎨 How We see Colors in Our Cutover Flowchart

To make things easier to track, we map out these conversions on flowcharts with colors that help us instantly see what’s what:

• Green indicates static data conversions, the ones we can prep early and with some breathing room.
• Dark Green highlights static data that’s on the critical path, meaning these must finish on time because other conversions depend on them.
• Yellow shows dynamic data conversions, the time-sensitive stuff that can only happen after the cutoff.
• Dark Yellow marks dynamic data on the critical path, the truly urgent conversions that directly impact the go-live timing.

This color coding isn’t a formal standard, just a handy way for our team to visualize what’s happening, when, and how these pieces fit together.

🛤️ Why the Critical Path Matters

The critical path is the sequence of dependent conversions where any delay holds up everything that follows. For example:

• You can’t load purchase orders without first loading suppliers (dark green static data).
• You can’t load inventory without purchase order receipts (dark yellow dynamic data).

If any item on this path runs late, the whole go-live schedule gets pushed back. That’s why these critical path items get extra attention during planning and testing.

⏱️ Execution Time: Why It Matters More Than You Think

Conversions aren’t just about what to extract, they’re about how long it takes. Here’s a rough example:

• Purchase Orders: 2 days
• PO Receipts: 9 days
• Inventory: 15 days

These durations might exceed the available windows. So, instead of guessing, we rely on timing data from testing phases like SIT (System Integration Testing) and UAT (User Acceptance Testing) to build a realistic cutover plan.

Dry runs help us decide:

• When exactly to start each conversion
• How long each step takes
• Who’s responsible for each task and when

That’s why understanding execution time from testing is key to a smooth go-live.

🔁 Conversion Dependencies: It’s a Chain Reaction

Most conversions depend on others finishing first. For example:

• Projects need purchase orders
• Purchase orders need suppliers
• PO receipts need purchase orders
• Inventory needs PO receipts

These dependencies are universal in ERP projects and why the sequencing and timing must be spot-on.

Final Thought

Learning how static vs dynamic data, the critical path, and dependencies all fit together has given me a new respect for the complexity behind go-live. It’s not just about pulling data, it’s about pulling the right data, in the right order, at the right time, with no room for error.

So next time you see the team at 3 am during go-live weekend, you’ll know exactly why.