Your Power BI dashboard is beautiful and wrong because on-time delivery means three different things in three systems
A dashboard is only as good as the definitions under it, and in most Wichita shops 'on-time delivery' is calculated three different ways in three systems, so leadership argues about whose number is right instead of acting. Custom BI with a governed data layer and agreed metrics runs $40k to $100k and 3 to 6 months. Power BI and Tableau draw whatever you feed them, including conflicting numbers nobody trusts.
Buying Power BI or Tableau does not give you trustworthy dashboards, it gives you a fast way to visualize whatever your data says, contradictions included. The real problem in a Wichita manufacturer is upstream: on-time delivery is defined one way in the ERP (Enterprise Resource Planning), another in the shipping spreadsheet, and a third in the customer scorecard. First-pass yield, scrap rate, and quote-win rate have the same disease. So you build a gorgeous dashboard, and the first executive meeting derails into an argument about whose number is correct.
The off-the-shelf BI tools assume you have a clean, governed data source. Most aviation and oilfield shops do not, they have an ERP, a couple of spreadsheets, a quality system, and a shipping log, none of which agree on definitions. Without a governed layer that reconciles them, Tableau and Looker just make the disagreement prettier and faster. The dashboard becomes a thing people distrust rather than a thing people act on.
- Core metrics are defined differently across systems
- Leadership distrusts current dashboards
- Data is scattered with no governed layer
- You need metrics aligned to OEM scorecards
- Your data already lives in one clean, governed system
- Power BI on that single source meets your needs
- Metric definitions are already agreed and stable
- You lack the will to govern definitions across teams
- One governed definition per metric (on-time delivery, first-pass yield, win rate) everyone agrees on
- Reconciled data from ERP, quality, and shipping so the numbers match across the business
- Dashboards leadership trusts and acts on instead of debating
- Metrics that match what OEM customers grade you on, so you see what they see
- A data layer that future tools and reports can all build on
- Most of the work is unglamorous data governance, not pretty charts
- Getting people to agree on definitions is organizational, not just technical
- A governed layer needs ongoing maintenance as systems change
- If your data already lives in one clean system, off-the-shelf BI may be enough
Business Intelligence Dashboards pricing in Wichita: the real numbers
| Project scope | Typical cost | Timeline |
|---|---|---|
| Governed data layer plus core dashboards | $40k to $65k | 3 to 4 months |
| Full BI with reconciliation and drill-down | $65k to $100k | 4 to 6 months |
| Enterprise BI across multiple divisions | $100k to $170k | 6 to 10 months |
The features that matter for Wichita
What we build under business intelligence dashboards in Wichita
Digital Heroes builds the full business intelligence dashboards stack for Wichita teams. Typical engagements cover Power BI, Looker, real-time analytics, KPI dashboards, data warehouse and embedded analytics.
Exactly what you get
Dashboards people trust because the governed data layer underneath them is the real deliverable: one agreed definition per metric, reconciled across your ERP, quality system, and shipping data. Leadership stops arguing about whose number is right and starts acting. It draws from the same sources your ERP, accounting, and project management systems use, so the whole business reads from one set of numbers.
How to choose a developer in Wichita
Hire a team that spends the first conversation on metric definitions, not chart styles. A serious Wichita partner knows the value is in reconciling on-time delivery across three systems, not in the visualization. If they are eager to show you slick Power BI visuals before asking how you define your numbers, they will hand you a prettier argument.
From kickoff to launch: the schedule
- !They sell the dashboard and skip the data governance
- !No plan to reconcile conflicting metric definitions
- !They assume your data is already clean and governed
- !No drill-down from summary to source
- !They cannot align metrics to OEM scorecards
Most Wichita teams pricing business intelligence dashboards end up comparing notes on helpdesk & ticketing, erp, custom software too; the systems share one data spine.
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 don't we just buy Power BI?
Power BI visualizes whatever you feed it, including conflicting numbers. The hard part in a Wichita shop is reconciling metrics like on-time delivery that are defined differently across the ERP, shipping, and customer scorecards. Without that governed layer, the dashboard is a faster argument.
What is a governed data layer?
It is a reconciled, agreed definition of each metric, drawn from your source systems, that everyone in the business uses. It is what turns a dashboard from a debate starter into a decision tool.
Can it match what our OEM customers measure?
Yes. Aligning your metrics to the OEM scorecard definitions means you see your performance the way your customers grade it, with no surprises at a business review.
Can we drill from a summary to the source?
Yes. Good custom BI lets you click from a summary number down to the underlying records, so a surprising metric can be investigated rather than disputed.