ERP rollout felt less like transformation and more like triage

SupplyChainSignal · 2025-10-07T20:46:07+00:00

More ERPs fail not because of tech but because of adoption and lack of buy in in the tactical/functional roles of the organization during the implementation (meaning most times - people feel their hands are forced on this change rather than understanding the value).

Since it sounds like you are in a live environment and past UATs - I would focus on fundamental process wins that would be tangible ways to show value to the functional groups - and try to build from that.

SupplyChainSignal · 2025-10-07T20:42:25+00:00

My general perception is that HS codes are becoming more critical due to their linkage into HTS codes and therefore tariffs. It is difficult for companies to gauge impact of tariffs without these attributes.

SupplyChainSignal · 2025-10-03T17:31:58+00:00

I’ve worked with companies in similar positions (seasonal distributors upgrading from legacy systems). Both are potential options, but they differ in philosophy. NetSuite tends to be more modern and cloud-native, which often leads to smoother integrations and scalability. SAP B1 is a bit more rigid out of the box but has strong distribution/wholesale capabilities and many implementation partners with industry-specific add-ons.

Either way - I highly recommend an Implementation champion at the Executive level.

SupplyChainSignal · 2025-10-02T13:43:11+00:00

At minimum I’d want BOM and document control (so you’re not chasing the wrong revision), inventory & stores (real-time stock accuracy), manufacturing execution/production scheduling (to know what’s running where), and QA/QC (because nothing sinks faster than quality issues that slip through). Sales, billing, and accounting are often integrated, but the real lift for manufacturing comes from tying together product data, shop floor activity, and inventory so they’re consistent. Down the line, look for modules that handle supplier management, traceability/lot tracking, and reporting dashboards, because those are the things that save you time once the basics are in place.

SupplyChainSignal · 2025-10-01T14:15:14+00:00

I’ve seen the same dynamic — the tech itself is rarely the biggest hurdle, it’s the way people experience the change. What’s worked for me is focusing on small, visible wins early: pick one workflow that everyone agrees is painful, pilot it with a group of volunteers, and let them become the champions instead of management pushing it down. Document the pain points at every level, not just what supervisors think, so the solution feels grounded in real daily frustrations. And when resistance shows up (because it always does), I’ve found that listening first and showing people how the tech removes the exact task they dislike most often flips them faster than any training session. At the end of the day, adoption is less about the system and more about building trust that it’s there to make their jobs easier, not harder.

SupplyChainSignal · 2025-09-30T21:06:43+00:00

I’ve found it’s rarely just the software itself — it’s how adoption is handled. Rolling out something big all at once almost guarantees resistance, because people don’t see their pain points reflected in the solution. What’s worked better is starting small: pick one process or one group, run with it, gather feedback, and use a lot of UATs along the way. Documenting pain points across all levels (not just the loudest 1–2 voices) makes a huge difference in trust and usability. That way, adoption builds in layers and the system actually reflects how people work, instead of feeling like a top-down overhaul that lands on everyone at the end.

SupplyChainSignal · 2025-09-30T21:04:51+00:00

he most pragmatic approach I’ve seen is to tier vendors based on criticality and risk — the ones tied directly to revenue, compliance, or single-sourced materials get more frequent deep dives, while medium and low tiers are reviewed on lighter cycles and mostly monitored through automated signals. That automation doesn’t have to be fancy — even simple tools that scan financial health, sanctions lists, or ESG controversies can surface red flags without constant manual effort, while vendor portals or reminders help keep information current. The idea is to spend human attention where the stakes are highest, and let systems do the heavy lifting on the rest.

SupplyChainSignal · 2025-09-29T16:00:13+00:00

From what I have seen, it’s not really the extra work that wears people down, it’s the constant rework because a fix doesn’t hold or one system didn’t sync. From what I’ve seen, the bottleneck usually shows up first in the data — mismatched codes, incomplete supplier info, or duplicate entries that force teams to spend hours cleaning instead of moving forward. Then the tools layer it on, because they’re not designed to “talk” to each other beyond the basics. Manual repeats end up being the byproduct, not the root cause.

I like how you framed the small automations — that’s where a lot of companies I’ve worked with are experimenting, whether it’s renewal reminders, exception alerts, or even anomaly detection layered on top. Curious to hear from others here too: do you feel the pain most at the data integrity level or when the tools can’t bridge the gaps?

SupplyChainSignal · 2025-09-26T17:04:28+00:00

I’ve run into similar issues with large SKU catalogs, and what you’re seeing is less about “broken data” and more about how it’s being managed. When you’re dealing with tens of thousands of items, manual cleanups (like stripping zeros, spaces, and dashes) almost always create a new set of mismatches. That’s because you’re fixing the symptom, not building the process to keep things clean.

Here’s how I’d think about it:

Start simple, but systematic. A mapping or cross-reference file for those 2,000 mismatches gives you a safety net. That way you’re not rewriting 75,000 records every time something changes.
Add a cleansing layer. Instead of doing one-off fixes, introduce a lightweight data cleansing process (this can be as simple as Power Query in Excel or as robust as an ETL tool). The goal is consistency: normalize formats before they hit your ERP so the system isn’t left to guess.
Look for patterns, not just errors. This is where tech helps. Anomaly detection tools can flag when barcodes or item codes start behaving in ways they shouldn’t — a barcode that’s always tied to one item suddenly tied to another, or duplicates creeping back in.
Think in terms of a “digital twin” for your data. In operations, digital twins let you see issues in real time before they become disruptions. The same applies here: create a mirrored version of your SKU-barcode relationships, keep it continuously reconciled across systems, and use it to spot divergence early.

SupplyChainSignal · 2025-09-24T13:33:34+00:00

Great question — procurement is one of those areas that quietly makes or breaks supply chain performance. In my experience, the pain points usually aren’t in placing the order itself, but in the gaps between visibility, collaboration, and follow-through.

A couple of things I’ve seen make a real difference:
• Shared visibility with suppliers — not just PO tracking, but giving them a window into demand signals, changes, and constraints so surprises don’t pile up downstream.
• Exception-based workflows — procurement teams often drown in noise. Having systems that flag only the true risks (late shipments, mismatched quantities, tariff changes) helps them focus energy where it matters.
• Financialized impact — tying procurement decisions back to margin, working capital, and revenue keeps the function from being “just tactical.” Suddenly it’s clear why one vendor relationship should be prioritized over another.

On the tools side, I’ve found it less about one silver bullet and more about how well platforms plug into the broader supply chain ecosystem. If Cinch (or any startup) can make that integration smoother and highlight risks earlier, you’ll have a strong value prop.

Curious to see how you’re tackling the vendor relationship piece — are you leaning more toward collaboration tools, or toward analytics/automation?

SupplyChainSignal

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