How Vision Technologies Turned a Data Bottleneck Into a Planning Foundation
Vision Technologies is a systems integrator specializing in security, access control, audio-visual systems, and low-voltage infrastructure. Operating in a project and service-based environment, the business relies on accurate, timely data to support forecasting, resourcing, and growth. To support continued growth and increasing operational complexity, Vision Technologies partnered with TwinSix to modernize its finance operations—using TwinSix Spark to build the data foundation required to unlock planning in Pigment.
For Jon Phillips, EVP of Finance, that reality created urgency. Vision was growing quickly, but finance was stuck in survival mode, manually extracting and stitching together data just to produce basic reporting. Even when the team could access the data, it lacked structure and context.
The Challenge: Data existed, but there was no path to use it
From the outside, Visiontech had modernized its systems. Internally, however, the finance team faced a much more constrained reality.
Teams exported raw transaction data into Excel, manually reshaped datasets, and stitched together reporting packages by hand. Producing standard reports could take most of a day, while deeper analysis often stretched across multiple days.
Infor LN added another layer of complexity. Data lived across fragmented tables with limited documentation and no straightforward extraction layer. Even simple reporting required complex joins and transformations to make the data usable.
To even understand how to access the data, Vision brought in external consultants. But understanding the system didn’t solve the core issue. Extracting and transforming data remained slow, fragile, and resource-intensive.
“It was data. It wasn’t information.”
If Vision wanted to scale planning, finance needed more than a planning platform. It needed a reliable way to access, structure, and operationalize data across the business.
Why TwinSix: A partner—and a product—for the hardest problem
Vision evaluated multiple planning platforms and ultimately selected Pigment for its flexibility, scalability, and ability to be owned by finance over time.
But selecting the platform was only part of the equation. The real question was how to get usable data into it.
TwinSix stood out because of how they approached that problem. Instead of treating integration as a one-off implementation task, the team introduced TwinSix Spark—a purpose-built data integration layer designed specifically for finance and planning workflows.
“It wasn’t a sales conversation. It was a solutions conversation.”
Rather than forcing a standard implementation, the team leaned into Vision’s constraints:
- A complex ERP with no straightforward integration path
- Limited internal data resources
- A need to move quickly without compromising long-term scalability
“They were very candid about what this would take. It was collaborative from the start.”
Building the foundation: How TwinSix Spark works
TwinSix Spark became the backbone of Vision’s implementation.
Spark enabled the team to:
- Connect to complex source systems like Infor LN
- Extract data through APIs, queries, and staged pipelines
- Standardize and validate data in a centralized environment
- Transform operational data into planning-ready structures
- Deliver clean, structured datasets directly into Pigment
This replaced a fragile mix of manual workflows, middleware queries, and custom extraction processes with a centralized and scalable data foundation.
Data that had previously been difficult to access, including contract detail, labor data, project costs, and service activity, could now move directly into planning models.
“If they hadn’t taken that on, we would have never been able to implement the platform.”
What had required multiple tools, manual intervention, and fragile pipelines was now orchestrated through a single integration layer.
Spark didn’t just move data. It made the data usable.
From bottleneck to momentum: Scaling how data moves
Before Spark, Jon relied on full data reloads that were slow and difficult to scale and even small changes required reprocessing large datasets.
With Spark, the architecture shifted toward change-based processing, where only new or modified data moved through the system.
The result was a major improvement in refresh performance. What previously updated every six to eight hours began moving toward near-hourly refresh cycles.
That speed fundamentally changed how finance could work with data inside Pigment.
Faster planning, richer data, and a stronger foundation
With TwinSix Spark in place, the impact extended beyond speed.
Vision’s finance team could finally work with data that was structured, reliable, and ready for planning.
Instead of spending time assembling data, the team could focus on analysis and decision-making. Reporting became faster and more consistent, and planning models could incorporate richer datasets.
Operational data that had previously been ignored, could now be used:
- Project cost and transaction data
- Contract-level detail
- Labor forecasts and service activity
This enabled more granular and informed planning, moving beyond high-level assumptions.
“We got the machine built. Now we’re refining the machine.”
From integration to ownership
With the foundation in place, Vision Technologies is now focused on expanding internal ownership and improving usability across the business.
“At some point, we need to learn to fish.”
TwinSix Spark is designed for that transition. By giving finance teams visibility and control over how operational data flows into planning, the platform enables organizations to move from dependency toward long-term self-sufficiency.
For Vision Technologies, the next phase is about refinement:improving usability, expanding access to business users, and continuing to build on the data foundation that’s now in place.
The TwinSix Spark difference
Most planning challenges don’t start in the model but in the data, and TwinSix Spark solves that problem upstream.
By combining deep finance expertise with a purpose-built integration layer in TwinSix Spark, the team created a solution that is both technically robust and operationally practical.
“They were thoughtful, engaged, and focused on solving the problem—not just implementing software.”
TwinSix Spark helps finance teams connect, transform, and activate their data, whether they’re working with legacy systems, complex ERPs, or fragmented data environments. Now you can be data ready from day one.
See how TwinSix Spark makes complex ERP data usable for planning
