Readiness has less to do with sophistication than most vendors imply. Plenty of technically advanced operations get poor results because their data doesn’t reflect reality, while unglamorous manufacturers with clean records and clear problems do well. Here’s what actually predicts it.
Signs You’re Ready
Your transactions are captured close to when they happen. Material issues, receipts, and production completions posted the same day rather than batched weekly. This is the single strongest predictor of success, and it’s a discipline question rather than a technology one.
You have at least two years of usable history. Enough to learn seasonality and supplier behaviour. Less than that and models are guessing with extra steps.
Your BOMs approximate reality. Not perfect — approximately right, with variances you know about. If nobody can say whether they’re accurate, that’s the first project.
Your planners are running the business out of spreadsheets. This sounds like a negative and it’s a strong positive signal: it means people are already doing analysis the system can’t, which is exactly the work that transfers well.
You have complexity that exceeds manual capacity. Many SKUs, multiple sites, volatile demand, unreliable lead times. Complexity is where these tools earn their keep.
You can name your most expensive recurring problem. Excess stock, expedite costs, schedule instability, whatever it is. A specific problem gives the project a target and a way to know if it worked.
Someone senior owns supply chain performance. Not as one item among twelve — as their responsibility. Projects without an owner drift.
Your team is frustrated with current tools. Frustration is easier to work with than satisfaction. Teams who feel the pain adopt readily.
You measure something already. Even imperfectly. Organisations that measure nothing struggle to prove value and tend to abandon projects halfway.
You can start small. A product family or a site you can run a bounded pilot on, with the ability to fall back. If everything has to change at once, wait.
Signs You Should Fix Something First
Stock records that routinely disagree with physical counts by wide margins. Fix the transaction discipline before anything else — no model overcomes unreliable inventory data.
BOMs nobody trusts. Audit your top products first.
Data locked in systems nobody can extract from, or held mostly in individuals’ heads and personal spreadsheets.
An organisation in the middle of an ERP migration. Do one thing at a time.
No agreement on what the problem is. If ops, sales, and finance each name a different root cause, resolve that before buying anything, or you’ll implement a tool that solves nobody’s version.
The Honest Summary
You need decent data, a real problem, and someone accountable. Most manufacturers who think they’re not ready are closer than they assume — and most who think they’re ready haven’t checked their data.
If you’re unsure which camp you’re in, run one test. Pick a fast-moving component, take the system’s stock figure, and go and count it. Then check the last four deliveries of that item against their quoted lead times. Two hours of work will tell you more about your readiness than any assessment questionnaire.
ticktick.ai includes a data readiness assessment before implementation, so gaps surface before they become disappointments.
