A practical guide to smart BI planning in today’s ERP world

So you’ve decided your business is finally ready to get serious about Business Intelligence. Maybe your ERP is humming along, your spreadsheets have spiraled out of control, or your leadership team is tired of waiting a week for a report that should take an hour. Whatever pushed you here, congratulations—this is a real step forward.

But let’s be honest: BI is one of those areas where it’s surprisingly easy to spend a lot of money and end up with very little to show for it. Dashboards nobody opens. Reports that contradict each other. A shiny Power BI workspace that quietly becomes the most expensive screensaver in the company.

The difference between BI that pays off and BI that gathers dust almost always comes down to planning. Not a 90-page strategy document—just a few honest conversations before you start clicking around in tools. Here’s how we walk clients through it.

1. Start with the decisions, not the dashboards

The most common mistake we see is teams jumping straight into tool selection. Power BI or Tableau? Fabric or Snowflake? Embedded analytics in Dynamics 365 Business Central, or a standalone warehouse?

None of that matters yet. The first question is much simpler: what decisions are you trying to make better?

Should the CFO be able to see daily cash position without pinging accounting?
Does your operations manager need to spot a margin slip on a product line within the same week, not the next quarter?
Are sales leaders trying to forecast pipeline with something more reliable than gut feel?

Write the decisions down in plain English. If you can’t articulate the decision, no dashboard is going to rescue you.

2. Set goals you can actually measure

“Increase profitability” is not a BI goal. It’s a wish. BI works best when you point it at something concrete and measurable—ideally something already living in your ERP.

Better examples:

Reduce days sales outstanding (DSO) by five days over two quarters.
Cut month-end close from ten business days to five.
Improve on-time delivery rate from 88% to 95%.
Identify the bottom 10% of SKUs by margin and make a quarterly decision on each.

Specific goals give your BI project a finish line. They also make it obvious which data sources matter—and which ones you can safely ignore for now.

3. Get honest about your data before you visualize it

Here’s the uncomfortable truth: most BI projects don’t fail because of the tool. They fail because the underlying data is messier than anyone wanted to admit.

If your ERP has three versions of the same customer, inconsistent GL coding across entities, or item masters maintained by whoever happened to be free that afternoon, no amount of beautiful visualization will save you. A pretty chart built on dirty data just helps you make the wrong call faster.

Before you invest in BI, take a hard look at:

Data ownership. Who is accountable for the accuracy of customer, vendor, and item records?
Single source of truth. Is your ERP genuinely the system of record, or are critical numbers still living in someone’s spreadsheet?
Integrations. How clean is the handoff between your ERP and your CRM, e-commerce, warehouse, or payroll systems?

This is exactly why we encourage finance and operations leaders to evaluate BI and ERP strategy together rather than as separate projects. The analytics layer is only as trustworthy as the operational platforms feeding it.

4. Plan for today’s ERP reality—and tomorrow’s

BI in 2026 looks very different than it did even a few years ago. A few shifts worth planning around:

Analytics is moving into the ERP itself. Platforms like Microsoft Dynamics 365 Business Central now ship with embedded Power BI reports, role-based dashboards, and direct connections to Microsoft Fabric. For a lot of mid-market companies, the right answer isn’t “buy a separate BI suite”—it’s “use what’s already there, well.”
AI copilots are changing how people ask questions. Natural-language queries (“show me top customers by gross margin this quarter”) are no longer a novelty. But they only work if your data model is clean and well-labeled underneath.
Cloud ERP unlocks real-time reporting. If you’re still running a legacy on-prem ERP with nightly batch exports, your BI ceiling is lower than you think. Sometimes the smartest BI investment is finishing your ERP modernization first.
Governance matters more, not less. The easier it gets to build a dashboard, the easier it gets to build a wrong one. Plan now for who can publish what, how versions are managed, and how sensitive data is protected.

The goal is a BI environment that grows with you—not one you have to rip and replace every time you add an entity, open a new line of business, or change ERPs.

5. Keep it simple enough for people to actually use

This one rarely makes it into BI vendor pitches, but it’s the one that quietly determines success: can a busy human get the answer they need in under thirty seconds?

If your dashboard requires a training session, a glossary, and three filters before it shows anything useful, your team will go back to exporting to Excel. Every time. Aim for:

One screen per role that answers the three questions that person asks most often.
Plain-language metric names, not cryptic field codes from the ERP.
Clear ownership—someone whose job it is to keep that report honest.

BI should make the obvious things obvious. Save the deep, exploratory analysis for the analysts; give everyone else clarity.

The bottom line

Good BI isn’t really about software. It’s about pairing the right decisions with trustworthy data and putting it in front of people who can act on it. The tools—Power BI, Fabric, embedded analytics in your ERP, AI copilots—are wonderful, but they’re the last 20% of the project, not the first.

If you’re weighing a BI investment alongside a possible ERP move, or trying to figure out whether your current platform can support the analytics your leadership team is asking for, that’s exactly the kind of conversation we have with finance and operations leaders every week. We’d be glad to compare notes.