If you have spent any time inside Infor VISUAL ERP, you already know the system has a lot of capability. What you may also know, or suspect, is that getting the most out of VISUAL depends heavily on something that does not get nearly enough attention: your data.
This post is based on a webinar our team put together on data strategy and data integrity inside Infor VISUAL. Whether you are a long-time VISUAL user or are mid-implementation, these concepts apply directly to how well your system performs and how much you can trust what it tells you.
Here is a simple way to think about data strategy: data is the answer to a question. Did that order ship? What did that job actually cost? How much inventory do we have on hand? Your ERP should be able to answer all of those questions accurately and quickly. When it cannot, the workarounds are obvious: spreadsheets, manual tracking, and people making decisions based on information they are not entirely sure they can trust.
This is where ongoing guidance and a clear data strategy make all the difference. Without that north star, companies quietly start adding Access databases, Excel trackers, and workarounds on the side. It happens with every major ERP on the market, not just VISUAL. The software is rarely the problem. The strategy is.
The goal should always be a single source of truth. In VISUAL, that means your ERP is the system of record for parts, orders, jobs, costs, and everything in between.
During our webinar, we walked through a four-step framework for building and maintaining a data strategy inside VISUAL. It is the same framework our ERP consulting team uses when working with manufacturers who need to recover from years of accumulated clutter or get ahead of problems before they start.
Before you can fix your data, you need to know what decisions that data is supposed to support. What are the metrics that matter most to your operation? On-time delivery, job cost accuracy, inventory turns? Start there. When your data strategy is anchored to real business outcomes, it is much easier to prioritize what to clean up and what to enforce going forward.
This means establishing ownership, defining standards, and putting governance in place. Every major data domain, the part master, customer records, vendor records, BOM/routing, needs a clearly assigned owner who is responsible for accuracy and completeness. Without ownership, nobody feels accountable and data quality degrades by default.
Take inventory of where your data currently lives and what condition it is in. Classify your data types, identify gaps, and align what you have with your actual business processes. This is often where companies discover how much has drifted since their original implementation. Our ERP data migration guide covers this evaluation process in detail if you want to go deeper.
Once you know what you have and what you need, the next question is how to get there. In some cases, the data can be cleaned and restructured within the VISUAL environment. In others, a more formal data migration process is required. Either way, this step is about closing the gap between where your data is and where it needs to be.
If VISUAL is a living system, the part master is the brain. Nearly everything flows through it. How your items are set up determines how the system plans, costs, schedules, and reports. Getting this right during ERP implementation is critical, but maintaining it afterward is equally important.
When part master data is incomplete or inconsistently structured, the ripple effects show up everywhere: inaccurate MRP signals, unreliable job costing, scheduling errors, and inventory counts that do not reconcile. Getting this foundation right is the prerequisite for everything else.
Some of the key data elements that need to be carefully defined at the item level include:
One best practice we recommend: treat item creation like an ECN (engineering change notice) process. Require sign-off from all affected departments, including purchasing, engineering, accounting, and operations, before a new part is active in the system. This one step prevents a significant amount of downstream data integrity problems.
If the part master is the brain, the bill of materials (BOM) combined with the operations routing is the heart. This is where cost, planning, and scheduling information come together.
A well-structured BOM/routing drives your work orders, your schedule, and your job costing. Get it right and those three things work together. Get it wrong and none of them can be trusted.
A very common challenge is designing the BOM/routing to be theoretically complete but practically unusable. If reporting labor or issuing materials is too complex or time-consuming for the shop floor, people stop doing it accurately and the data degrades.
The right balance is designing your BOM/routing to capture what you genuinely need while keeping the transactional process manageable for the people actually doing the work.
Our webinar covered two categories of data issues that affect VISUAL users: master data problems and transactional data problems. Both are common. Both have real operational consequences.
Master data issues tend to be structural. They include outdated, obsolete, or duplicated part data; inconsistent naming conventions or formatting; incorrect or outdated vendor and customer information; incomplete master records with missing key fields; and incorrect or incomplete BOMs and routings. These problems often go unnoticed for a long time because the system keeps running, just not accurately.
Transactional data issues are more visible because they show up in day-to-day operations. Unreconciled work in process, improperly closed work orders, open purchase orders or customer orders that should have been closed, and a chart of accounts full of outdated or inactive entries are all common examples. The downstream effect is almost always the same: inaccurate reporting, KPIs based on bad data, and manual reconciliation required just to close the books each month.
Even companies that start with clean data can watch it deteriorate over time. Here are the most common culprits we see.
Every field in VISUAL exists for a reason. When users start putting information into fields that were not designed for it, the logic the system relies on breaks down. Reports pull incorrect data. MRP behaves unexpectedly. It is a small habit and a common workaround, but the consequences are surprisingly large.
When someone new comes in and does not receive proper training, they default to what they know, usually Excel. They start maintaining their own version of the truth outside the system. Over time, you end up with silos of information that are manually updated, nobody knows which version is current, and the data diverges further from reality.
Hope is not a data strategy. VISUAL allows you to configure required fields, custom validations, and other controls that enforce data standards at the point of entry. Use them. Relying on process documentation alone is rarely enough.
Every workaround starts innocently. A quick spreadsheet to track something VISUAL does not handle well. An Access database for a special project. The problem is that workarounds tend to grow roots. What starts as a temporary fix becomes someone's full-time job to maintain. Meanwhile, the ERP is no longer the system of record for that data, and you have quietly re-created the exact problem you bought VISUAL to solve.
The downstream consequences of data problems go well beyond a reporting headache. Here is what we consistently see at manufacturers whose data has drifted:
It is worth being equally specific about what you gain when your data is structured well and maintained consistently. The connection between clean data and real operational performance is something we have written about in depth, including how to make manufacturing data matter and what to look for in manufacturing data analysis.
One topic we touched on in the webinar that is increasingly relevant: quality data is the engine behind effective AI. As more manufacturers explore AI-powered tools for forecasting, scheduling, and decision support, the state of your underlying data becomes even more important. AI does not fix bad data. It amplifies it. The manufacturers who will get the most out of AI are the ones who have done the work to make their data clean, consistent, and trustworthy.
Infor VISUAL is a powerful ERP for discrete manufacturers. But the power is latent. It only materializes if the data behind the system is structured, accurate, and maintained. A solid data strategy is not a one-time implementation task. It is an ongoing discipline that determines whether your ERP delivers on its promise.
Not sure where your data stands today? An Application Process Review can help you identify where things have drifted and what it would take to get your system back on track. And if you need ongoing support to keep it there, our team at Visual South is built for exactly that.
Reach out to learn more about our Infor ERP support services, or contact us directly to start the conversation.