Scanner Lineage Explorer

Making a complex scanner ecosystem easier to understand

Role: Product Manager

Product: Scanner Lineage Explorer

Focus: Product intelligence · Data lineage · Compatibility · Internal tooling

The problem

Our scanner ecosystem had become increasingly complex.

We supported a broad portfolio of scanners across different products, software versions, integrations, and metadata capabilities. While the information needed to answer customer and internal queries existed, it was spread across different sources and systems.

This made relatively simple questions surprisingly difficult to answer:

• Which scanners do we currently support?

• What is the latest version of the software?

• Which systems or products does a scanner connect to?

• What is the lineage between different components?

• What metadata can we collect from a particular scanner?

For customer-facing teams, answering these questions often meant navigating multiple sources or relying on people with specific product knowledge.

The opportunity

Rather than treating this as a documentation problem, I saw an opportunity to create a single product experience for exploring the scanner ecosystem.

The goal was simple:

Give teams one place to understand what we support, how everything connects, and what information is available.

Designing the experience

I designed the Scanner Lineage Explorer around the questions teams were actually trying to answer, rather than around how the underlying information was stored.

The experience brings four key pieces of information together.

01 — Scanner portfolio

A central view of the scanners and products within our supported portfolio.

This gives teams an immediate understanding of the breadth of the ecosystem and allows them to start their exploration from a specific scanner or product.

02 — Product lineage

The tool surfaces the relationships between scanners, software, products, and connected systems.

Instead of viewing each component in isolation, users can understand how one component connects to another and trace the wider lineage.

03 — Version intelligence

The experience surfaces the latest scanner and software versions alongside the versions that we support.

This makes version and compatibility questions easier to answer without having to search through multiple sources.

04 — Metadata visibility

The tool also shows the type of metadata we collect from each scanner.

This gives customer-facing teams another important dimension of product capability when evaluating or discussing a particular integration.

The product thinking

The key product decision was to make the experience explorable rather than informational.

A traditional documentation page could tell someone what scanners we support.

But it wouldn't necessarily help them answer:

“What does this scanner connect to?”

“What version are we supporting?”

“What information can we collect?”

“How does this fit into the wider product ecosystem?”

The Explorer brings these relationships together so that users can start with one piece of information and move through the ecosystem from there.

This shifted the experience from a static catalogue into a living map of the products and technologies we support.

Making technical complexity usable

One of the biggest challenges was not the amount of information itself, but the number of relationships between different pieces of information.

The product therefore had to balance depth with usability.

Instead of exposing every technical detail upfront, the experience provides a high-level view first, while allowing users to progressively explore the information relevant to their question.

This made the tool useful to customer-facing teams without requiring them to understand the underlying technical architecture.

Impact

The Scanner Lineage Explorer created a centralised view of our scanner ecosystem and reduced the dependency on fragmented sources of information.

It helped customer-facing teams:

• Find scanner and software compatibility information faster

• Understand lineage and system connections

• Identify the latest supported versions

• Understand available metadata

• Resolve technical product questions with less dependency on subject-matter experts

The initiative ultimately reduced query resolution time by 30%, while creating a more scalable way for teams to discover and use product intelligence.

What I learned

The project reinforced an important product principle for me:

Sometimes the problem isn't a lack of information — it's that the information is difficult to navigate.

By understanding the questions users were trying to answer and restructuring existing technical information around those questions, I was able to turn a fragmented knowledge problem into a usable product experience.

The result wasn't just better documentation. It was a product layer over a complex technical ecosystem, helping teams understand not only what we support, but how everything fits together.