The stack is not stupid. The handoffs are the problem.
Tally is good at accounting. Excel is good at flexible analysis. WhatsApp is extremely good at getting a person to respond. The failure appears when the same order, payment, stock movement or promise has to be re-entered across all three.
That means the first question is not “which ERP should replace everything?” It is “which repeated handoff creates the most delay, re-entry or uncertainty?” If the current tools are otherwise doing their jobs, connecting them can be cheaper and less disruptive than a full replacement.
Five handoffs worth measuring first
Walk through one normal week and count how often these happen.
- IndiaMART, website or WhatsApp lead → spreadsheet or CRM
- Sales order → production / purchase planning tracker
- Dispatch update → salesperson → customer message
- Bank / payment event → Tally → receivables follow-up
- Shift or warehouse status → WhatsApp → Excel → management MIS
When an integration layer is enough
If one system is already the accepted source of truth for each domain, a thin integration layer can remove a surprising amount of labour. The layer listens for events, validates data, applies rules, updates the right system and exposes exceptions.
This works particularly well when staff are not asking for a completely new planning model. They are asking for fewer exports, fewer calls and fewer contradictory versions of the same status.
When you actually do need ERP work
Do not use automation to preserve a fundamentally broken master-data model. If nobody agrees on item codes, BOMs, customer IDs, inventory ownership or who is allowed to change a production state, integration will simply move bad data faster.
That is the dividing line: automate stable rules and stable sources of truth; redesign the process first when the truth itself is disputed.
A sensible first build
Pick one handoff with daily volume. Capture the baseline time and exception rate for two weeks. Build only the smallest end-to-end path. Keep uncertain cases visible to a human. Then compare the new operating data with the baseline before expanding.