Five Master Data Questions to Bring to Any Data Conference This Fall

Fall is conference season for data teams. Between keynotes, customer panels and hallway conversations, it’s easy to come home with a full notebook and no clearer idea of what to do next. Stibo Systems Connect and plenty of other industry events fill the calendar through November.

The best way to get value from any of them is to walk in with the right questions. For manufacturers, semiconductor companies and industrial distributors, the five below are a good place to start. Ask them of speakers, vendors and peers alike. Each answer tells you something useful about where your own data program stands.

1. Who owns our product data, and what happens when it’s wrong?

Most manufacturers can name a system of record for product data. Fewer can name the person accountable when a spec sheet lists the wrong operating temperature or a part number appears twice with different dimensions.

Ownership usually splits along system lines. Engineering owns specifications in the product lifecycle management (PLM) system. Operations owns the ERP. Marketing owns descriptions and imagery. Nobody owns the gaps between them, and that’s where most errors live.

Listen for how other companies assign data stewards, whether by domain, product line or attribute group. Ask how change requests move through their process, and whether governance rules are built into system workflows or kept in a shared drive. If the answer sounds like “we have a spreadsheet for that,” you’re hearing a common starting point, not a failure.

The question to ask: “When your product data is wrong, how long does it take to find out, and who fixes it?”

2. Is our data ready for AI, or just available to it?

Nearly every event this year has an AI session on the agenda. Stibo Systems lists AI and machine learning among the top master data management trends for 2026, and manufacturers are testing AI for customer support, part search, cross-referencing and quoting.

The more useful question isn’t whether to use AI. It’s whether your data can support it. For engineered products, AI tools depend on consistent units, complete attributes and clean relationships between parts. A tool that reads “5V,” “5 V” and “5 volts” as three different values will give three different answers to the same customer.

When presenters share an AI success story, ask what data cleanup came first, how long it took, and how they check accuracy after launch. The honest answers usually include a lot of unglamorous work on attributes and classification. Industry standards help here. Classification systems like ETIM give technical products a shared structure that both people and machines can read.

The question to ask: “What did you have to fix in your data before the AI project worked?”

3. Could we answer a compliance request from one place?

Regulators and customers are asking for more product-level detail, and the requests keep coming from new directions.

In the EU, the Digital Product Passport becomes mandatory for several battery categories on February 18, 2027, with more product groups to follow. In the US, a growing list of state right-to-repair laws, including Texas as of September 1, 2026, require manufacturers to make parts, tools and technical documentation available. The EPA’s PFAS reporting rule asks manufacturers and importers to report on substances going back more than a decade.

Each of these asks for data that already exists somewhere in the business: materials, substances, country of origin, supplier details, repair instructions. The difference between an easy response and a painful one is whether that data sits in a governed record or has to be pieced together from email threads and spreadsheets every time.

The question to ask: “When a new compliance requirement lands, do you start a project, or do you run a report?”

4. Should we be managing more than product data?

Many manufacturers start with product information and discover that product data depends on everything around it. A single semiconductor device might be sold under several part numbers, packaged at different facilities and built with materials from multiple suppliers. Answering a basic customer question about that part can mean touching product, supplier and location data at once.

This is the case for multi-domain master data management, which Stibo Systems also names as a leading trend in its 2026 outlook linked above. Managing several data domains on one platform makes it easier to keep those relationships accurate.

That doesn’t mean every company needs to do everything at once. Starting with product data is a sensible first step. The important part is designing the data model so supplier and location records can connect to it later without a rebuild.

The question to ask: “Which data domain did you start with, what made you expand, and what would you do differently?”

5. How will we know it’s working?

Sooner or later, leadership will ask what the investment returned. Companies that can answer clearly tend to be the ones that measured their starting point before the project began.

Useful metrics for manufacturers include:

• Time to launch a new product or part number across all channels
• Number of duplicate or conflicting records
• Returns, credits or quote errors traced back to data problems
• Hours spent answering customer and distributor data requests
• Rejection rates when sending data to distributors or marketplaces

None of these require a perfect dashboard to get started. A rough baseline is far better than none.

The question to ask: “Which metrics did you capture before you started, and which ones did leadership care about most?”

Bring the answers home

Good conference conversations are only useful if they change something back at the office. After the event, compare what you heard against your own situation and pick the one question where your gap feels widest. That’s usually the right place to start, whether it’s naming data owners, cleaning up attributes for an AI pilot or mapping the data your next compliance request will need.

Ready to turn your conference notes into a practical master data plan? Contact us to talk with Sitation’s master data management team about governance, data modeling and implementation on Stibo Systems.