Overview
A national precast concrete manufacturer partnered with Analytic Vizion to stabilize executive reporting during a business transition, when leaders needed clear views of sales, customers, backlog, and production.
The Challenge
A national precast concrete manufacturer was transitioning into a new parent company and needed reliable executive reporting on sales, customers, backlog, and production.
While:
- Year‑to‑date and trailing‑12‑month figures did not always reconcile.
- Fiscal‑year and calendar‑year definitions were implemented differently across dashboards.
- Acquisition cutoffs were applied unevenly across reports.
- Product classification and backlog logic excluded or miscategorized parts of the business.
- Core reporting depended on hardcoded rules and manual changes in source systems.
- Legacy dashboards and scheduled exports still carried much of the reporting load.
- Reports often required manual cleanup and rework in Excel.
- Internal Sigma expertise was limited, so even basic updates were slow.
- Executive meetings frequently began with “Is this report right?” instead of “What should we do with this information?”
Without change, the manufacturer risked decisions based on inconsistent reporting, ongoing manual reconciliation work, and rising technical debt in a stack that needed to support a new ownership structure.
Our Approach
Analytic Vizion partnered with the manufacturer on a combined visual analytics, data engineering, and reporting stabilization engagement.
On the people side, the team created a simple weekly rhythm: one alignment session to confirm priorities and one working session to make changes. Stakeholders worked directly on data validation and reporting needs, including customer and geographic analysis, and approvers actively checked that updates matched leadership expectations. When stop‑work was requested, the team documented unfinished work and clear restart paths so the organization could resume without losing momentum or context.
On the process side, the team shifted reporting from ad‑hoc fixes to a structured backlog. First, they captured and prioritized requests so work could move in a clear order. Next, they moved classification logic away from hardcoded business rules toward governed seed files. Finally, they separated sales and production reporting to make future changes safer and easier to understand.
Technically, We focused on the mechanics of trust:
- Corrected reporting logic for fiscal year, calendar year, acquisition date, and trailing periods.
- Stabilized and released a new Sales Dashboard (V2) and retired the legacy dashboard.
- Built and refined analytics for customer growth and decline, geographic performance, prospects, backlog, and production.
- Developed Snowflake and dbt data models for production hours, backlog snapshots, and a Sigma‑ready summary layer.
- Corrected product‑category, backlog, prospect, and premium reporting logic.
- Restored production data flow by resolving a Fivetran synchronization issue.
- Began work on a Production Dashboard and supporting data model.
Tools and technology in play included Sigma for dashboards, Snowflake for warehousing, dbt for transformations, Fivetran for data movement, Jira for prioritization, and Excel and ADP data as sources.
Tools & Technology
The Results
By the end of the engagement window, period and acquisition logic issues in executive dashboards were corrected, so leaders could compare fiscal, calendar, and post‑acquisition views with more confidence. In addition, Sales Dashboard V2 replaced the legacy version, interactive customer and geographic analytics were in place, and backlog and production reporting had a tested foundation for future efficiency work.
As the work progressed, the outstanding reporting issue list was reduced to three items, each with a defined resolution path. At the same time, manual reporting work decreased as more executive views ran through Sigma dashboards instead of spreadsheets. As a result, the team had more trust and clarity with the numbers they work with every day.
Key Takeaways
Fix period and acquisition logic first.
Consistent fiscal, calendar, and acquisition‑date rules immediately improve executive confidence in sales and backlog reporting.
Use dashboards to reduce manual reporting.
Moving recurring executive views into Sigma, backed by Snowflake and dbt, cuts time spent rebuilding reports in Excel and lowers error risk.
Treat classification and backlog rules as governed assets.
Pulling product and backlog logic out of hardcoded model assumptions and into governed structures creates a safer foundation for future analytics work.
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