Your CNC machines speak four protocols and Power BI speaks none of them
Custom business intelligence dashboards for a Dayton advanced-manufacturing or aerospace operation run $35,000 to $110,000 over 3 to 6 months. Tableau, Power BI, and Looker are brilliant at visualizing data you can already query. The problem on a Dayton shop floor is upstream: your CNC machines run mixed controls and protocols, your quality data lives in a separate system, and your job costs sit in the ERP (Enterprise Resource Planning). There is no clean table to point Power BI at, so the real metrics never surface.
You want true OEE, real-time job profitability, and scrap-rate trends by machine and operator. The off-the-shelf BI tools assume that data exists in a warehouse you can connect to. It does not. Your older CNCs barely emit data and your newer ones speak a different protocol; your CMM and inspection data is in a quality system; your labor and cost are in the ERP; your scrap reasons are on paper. Power BI cannot show you OEE because nothing has stitched machine uptime, cycle counts, quality, and cost into one queryable model.
So leadership flies on gut feel and month-end reports, and the dashboards that exist show finance after the fact, not the floor in real time. The hard, expensive part of BI for a Dayton manufacturer is not the chart. It is the data plumbing under it, and that is exactly what the BI tools assume someone else already did.
Budgeting a business intelligence dashboards build in Dayton
| Project scope | Typical cost | Timeline |
|---|---|---|
| Data pipeline + core OEE dashboards | $35k to $60k | 3 to 4 months |
| Add machine connectivity + scrap/downtime capture | $60k to $85k | 4 to 5 months |
| Full unified model + real-time profitability + alerts | $85k to $110k | 5 to 6 months |
The case for owning your business intelligence dashboards
Custom BI starts where the off-the-shelf tools stop: building the data plumbing. It connects mixed CNC controls, pulls quality and ERP data, captures scrap and downtime causes, and stitches them into one model. Only then do dashboards show real OEE, live job profitability, and scrap trends by machine and operator. For a Dayton shop, the value is not prettier charts; it is finally having data worth charting, surfaced while it can still change a decision.
- Your machine, quality, and ERP data live in silos with no unified model
- You need real OEE and live job profitability, not month-end finance
- Mixed CNC controls make off-the-shelf BI connectivity impossible
- Scrap and downtime causes never reach a dashboard today
- Your data is already clean, unified, and queryable
- Power BI or Tableau can connect to your sources directly
- You need standard financial dashboards, not floor-level OEE
- You lack the machine-data complexity that requires custom pipelines
What your build should include
Business Intelligence Dashboards services we deliver in Dayton
Digital Heroes builds the full business intelligence dashboards stack for Dayton teams. Typical engagements cover Looker, real-time analytics, KPI dashboards, data warehouse and embedded analytics.
Delivery, week by week
Exactly what you get
Dashboards backed by data that actually exists. The hard part, connecting your mixed CNC controls and pulling quality, ERP, and labor data into one model, is built first. Then you see true OEE per machine, real-time job profitability as work happens, and scrap-rate trends by operator and cause, with alerts when a machine goes down or scrap spikes. Leadership stops flying on month-end finance and gut feel and starts deciding on the live floor.
How to choose a developer in Dayton
Choose a team that treats data engineering as the real work and visualization as the easy last step. Ask how they would pull data from a 1990s CNC and a modern control into one model, and how they would capture scrap causes at the source. The best partners connect BI to your ERP, your inventory-management-software, and your custom-software-development so the dashboards reflect one source of truth. A vendor who only knows Power BI and assumes clean data will stall at the first machine.
- Machine connectivity across mixed CNC controls feeding one data model
- True OEE computed from real uptime, cycle counts, and quality data
- Real-time job profitability instead of after-the-fact month-end finance
- Scrap-rate and downtime-cause trends by machine and operator
- Decisions on live floor data rather than gut feel and lagging reports
- The data plumbing is the hard, expensive part, not the visuals
- Older machines may need retrofit hardware to emit usable data
- You own the pipelines and their maintenance over time
- If your data is already clean and unified, off-the-shelf BI may suffice
- !They quote dashboards without addressing how the data gets there
- !They assume your machine data is already queryable
- !They have no plan for mixed CNC controls and protocols
- !They ignore scrap and downtime capture at the source
- !They sell BI licenses but can't build data pipelines
Teams investing in business intelligence dashboards in Dayton usually scope it next to helpdesk & ticketing, erp, custom software, since these systems share data and budgets.
Rohan advises mid-market and enterprise teams on ERP, CRM and custom software, and has led delivery on dozens of business-software builds.
Writes for Digital Heroes, shipping business software for 2,000+ brands across 55+ countries since 2017.
Frequently asked questions
Why can't we just use Power BI for shop-floor metrics?
Power BI is excellent at visualizing data you can already query, but a Dayton shop floor has no clean table to point it at. Mixed CNC controls emit incompatible data, quality lives in one system, and cost in another. Without building the data plumbing first, Power BI cannot compute true OEE or live job profitability, which is why custom BI begins with integration, not charts.
What does it take to get real OEE?
Real OEE needs machine uptime, cycle counts, and quality data joined together in real time. On a Dayton floor with mixed CNC controls, that means connecting machines that speak different protocols, capturing downtime and scrap causes at the source, and stitching it with ERP labor data. The dashboard is trivial once that model exists; building the model is the work.
How much do custom BI dashboards cost in Dayton?
Between $35,000 and $110,000 depending on how much machine connectivity, data integration, and real-time computation you need. A data pipeline with core OEE dashboards lands at the low end; a full unified model with real-time profitability and alerts reaches the top. Most of the cost is the plumbing, not the visuals.
Can older CNC machines feed a dashboard?
Often yes, sometimes with a retrofit. Newer controls emit data over standard protocols, while older machines may need a small hardware adapter to report uptime and cycle counts. A good custom BI partner assesses your specific machines and builds connectors or retrofits so even mixed-age equipment feeds one model.
Should BI connect to our ERP and inventory?
Yes. True job profitability and scrap costing require joining floor data with ERP cost and labor and with inventory-management-software material data. Connecting BI to those systems gives one source of truth, so a scrap spike on a machine shows its real cost impact instead of just a count, and leadership sees the full picture.