7 Questions to Ask Before Buying Manufacturing Software
Every manufacturing software demo looks impressive. Clean dashboards. Smooth workflows. Smiling operators in stock photos.
Then you buy it. Six months later, you're back to spreadsheets because the software doesn't actually match how you run your shop.
Here's the uncomfortable statistic: 75% of ERP implementations fail. Not "underwhelm." Fail. Budget overruns averaging three to four times the original estimate. Systems that never get adopted. Projects that get quietly abandoned.
The problem isn't that choosing software is hard. It's that most buyers ask polite questions that get polished answers. They check feature boxes instead of testing whether the software fits their operation.
These seven questions aren't polite. They're designed to cut through vendor sales pitches and reveal what actually matters. The answers will save you money. Or they'll save you from making an expensive mistake.
Question 1: Was This Built for Manufacturing, or Adapted from Something Else?
Most enterprise resource planning (ERP) systems started as accounting software. Invoices, general ledger, accounts payable. Manufacturing features got bolted on later when vendors realized factories had money to spend.
You can spot the difference in how the software thinks about your business.
Accounting-first software treats production as a cost center. The chart of accounts is elegant. The bill of materials (BOM) structure is awkward. Work orders feel like an afterthought because they were.
Manufacturing-first software treats production as the center. BOMs handle multiple levels naturally. Routings capture how work actually flows. Shop floor data capture isn't a module you add. It's built in.
What to listen for: Ask the vendor to walk you through creating a multi-level BOM with an engineering revision. Watch whether this feels natural or clunky. Ask how work orders connect to inventory transactions. Observe whether they reach for workarounds.
Red flag: If the answer to basic manufacturing questions is "we can customize that," you're looking at software that wasn't designed for your needs.
Question 2: What Happens When Something Changes Mid-Shift?
Manufacturing plans are fiction by 10 AM. A machine goes down. A rush order arrives. Your best welder calls in sick. The schedule that looked perfect at 7 AM is already obsolete.
This is where legacy systems fail. They assume the plan will work. When reality doesn't cooperate, someone has to manually fix everything.
The question reveals whether the software processes data in real time or in batches.
Real-time systems update instantly. Complete an operation and inventory adjusts. Move a job and downstream schedules recalculate. You see problems as they happen, not the next morning.
Batch systems wait. Maybe hourly. Maybe overnight. By the time you see the problem in a report, it's already cost you money.
What to listen for: Ask to drag a job on the scheduling Gantt chart during the demo. Watch what happens to downstream jobs. Does inventory update? Do resource conflicts appear? If nothing changes until you "run MRP," that's batch processing in disguise.
Red flag: "Run the schedule overnight" or "recalculate weekly" means you're always working with stale data.
Question 3: Will My Operators Actually Use This?
Shop floor adoption is where implementations go to die.
The system goes live. Training happens. Operators nod along. Within a month, everyone's back to clipboards and spreadsheets because the software is too slow or too complicated to use while actually making parts.
The demo usually shows what managers see. Dashboards. Reports. Analytics. But operators aren't sitting at desks analyzing data. They're standing at machines with gloves on.
Ask to see what operators actually interact with.
What to listen for: Touch-friendly interfaces designed for shop floor terminals. Kiosk modes that don't require logging in for every transaction. Barcode scanning for fast data capture. Workflows that take seconds, not minutes.
Red flag: If the "operator view" looks like a complex desktop application with tiny buttons and dropdown menus, adoption will struggle.
The real test: Ask for adoption metrics from reference customers. What percentage of shop floor transactions go through the system? How long did it take to reach that level? If the vendor doesn't track this, they haven't prioritized it.
Shop floor visibility depends on operators entering data. No adoption means no visibility.
Question 4: What Does Implementation Really Cost?
Licensing is the number vendors put in big font. It's also the smallest number you'll actually pay.
The real cost of manufacturing software includes several categories vendors hope you won't add up:
Implementation consulting typically runs two to five times the annual license cost. Complex implementations go higher. If the vendor quotes a range, assume the high end.
Your team's time is the cost nobody includes in the quote. Successful implementations require your best people to spend 50% or more of their working hours on the project. For months. Calculate what that costs in their salary. Then calculate what happens to the work they're not doing.
Training isn't a one-time cost. New hires need training. Software updates need retraining. Someone needs to own this process permanently.
Customization compounds over time. Every modification increases switching costs. Eventually, you can't upgrade because it would break your custom code.
What to listen for: Ask for specific estimates on consulting days, training hours, and expected internal time commitment. Ask how they calculated those numbers.
Red flag: "It depends" without any attempt to estimate means they either don't know or don't want to tell you.
Calculate total cost of ownership for three years. Then add 30% because something unexpected will happen.
Question 5: How Does This Handle My Production Type?
Job shops schedule differently than make-to-stock factories. High-mix low-volume operations have different needs than high-volume production lines. Process manufacturing thinks in formulas. Discrete manufacturing thinks in assemblies.
The terminology matters here. A job shop running one-off custom parts needs flexible scheduling that handles unique routings for every job. A repetitive manufacturer running the same products needs demand forecasting and kanban-style replenishment. The features that help one can actually hurt the other.
Generic software tries to handle everything. It usually handles nothing well.
What to listen for: Specific language about your production type. References to customers with similar operations. Features designed for your scheduling complexity.
If you run a job shop handling hundreds of unique parts, ask: "Show me how you handle make-to-order with no standard routings." Watch whether the demo flows naturally or requires workarounds.
If you run configured products, ask: "Show me how you handle a product with 50 configurable options." See whether the BOM structure supports this or forces you into separate SKUs.
Red flag: Generic answers that could apply to any manufacturer. "Our flexible platform handles all production types" often means it handles none of them particularly well.
The real test: Ask for a reference customer in your industry with your production style. Talk to them about fit.
Question 6: What AI and Automation is Built In?
Modern manufacturing software should reduce manual work, not create more of it.
But "AI" has become a checkbox feature. Every vendor claims it. Few can explain what their AI actually does.
The difference is between AI-native and AI-bolted-on.
AI-native systems were designed with machine learning at the core. The algorithms learn from your data. Scheduling improves based on actual cycle times, not estimates. Demand forecasting uses your order patterns. Anomaly detection flags problems before they cause downtime.
AI-bolted-on systems added a chatbot to an existing architecture. Maybe some reports use "predictive analytics." The core workflows remain manual.
What to listen for: Specific AI capabilities with specific outcomes. "Our scheduling algorithm reduced late deliveries by 30% for [customer]" beats "we have AI-powered scheduling."
Ask: "What does your AI learn from my data over time? What gets better automatically versus what I have to configure?"
Red flag: AI mentioned in marketing but absent from the demo. Or AI features that require expensive add-on modules nobody actually buys.
Question 7: What Happens When I Need Help?
You'll need support. During implementation, something will break. After go-live, users will have questions. Two years in, you'll want to use a feature you've never touched.
The support model varies wildly between vendors.
Enterprise software often means "submit a ticket and wait." Maybe days. Maybe weeks. Your problem sits in a queue behind larger customers.
Modern SaaS vendors often provide faster response through chat and phone. But quality varies. Talking to someone quickly doesn't help if that someone can't solve your problem.
What to listen for: Specific response time commitments. Whether support is included or costs extra. Who answers: in-house experts or outsourced call centers. Whether you get a dedicated customer success contact or a ticket number.
Ask: "What's your average response time for critical issues? Non-critical? Can I talk to a human who understands manufacturing?"
Red flag: Vague answers about support. No defined SLAs. Extra cost for "premium support" that should be standard.
Bonus: The Question That Reveals Everything
Ask every vendor: "Can I talk to a customer who struggled with your software?"
Every vendor has happy references. They're pre-screened. They agreed to take calls because their implementation went well.
The interesting stories come from customers who had problems. How did the vendor respond? What got fixed? What didn't? Why did they stay instead of switching?
If the vendor can provide this reference, ask that customer:
- What surprised you about implementation?
- What would you do differently?
- What almost made you quit?
Their answers tell you more than a dozen success stories.
What the response reveals: Vendors who can't or won't provide a struggled-and-stayed reference either don't have any (unlikely) or don't stay connected to unhappy customers (a red flag for when you become one).
How to Use These Questions
Print this list. Bring it to vendor calls. Score each answer on a scale of one to five.
Create a simple scorecard. Weight the questions based on what matters most to your operation. If shop floor adoption is your biggest concern, weight Question 3 heavily. If you've been burned by implementation costs before, weight Question 4.
After each vendor meeting, compare scores. The patterns tell you more than any individual answer.
Some vendors will answer confidently. Others will deflect, change the subject, or promise to "get back to you." Those deflections are data points. A vendor who can't answer basic questions about implementation costs or support models either doesn't know or doesn't want you to know.
The goal isn't finding the software with the most features or the lowest price. It's finding software that solves your actual problems without creating new ones.
The vendors who answer these questions well understand manufacturing. The ones who deflect are selling general business software with a different label.
Ready to see how Workcell answers these questions?
We built Workcell for manufacturing operations, not adapted it from accounting software. Real-time updates. AI-native architecture. Shop floor interfaces designed for operators.
Book a demo and ask us anything. We'll show you with your data, not a pre-built sample.