BI Solution Planning - Designing a Power BI Solution That People Actually Use
There's a difference between having a BI strategy and planning a specific BI solution, and conflating the two is behind a lot of wasted Power BI effort. Strategy is the big-picture call about where your organisation is heading with data. Solution planning is the much more practical work of designing one particular thing: the inventory dashboard, the sales reporting model, the finance pack. Strategy sets the direction. Solution planning is where a real, working report either gets built well or gets built as the four-hundred-and-first thing nobody trusts.
Microsoft covers this in their implementation planning series under BI solution planning, and it's the layer of the planning that gets skipped most often. People love talking strategy because it's abstract and nobody has to commit to anything. Solution planning is where you have to make actual decisions, and it's the part that determines whether the build succeeds. So this is the consultant's take on doing it properly, based on a lot of solutions we've planned, some that flew and some that taught us things the hard way.
Start with the decision, not the dashboard
The first question on any solution should never be "what should this report show." It should be "what decision is this helping someone make, and who makes it." Get that wrong and everything downstream is built on sand, no matter how good the data modelling is.
I've sat in too many requirements meetings where someone reels off a list of metrics they'd like to see, and if you build exactly that, you get a dashboard that's technically correct and practically useless. The metrics are there, they're accurate, and nobody changes a single decision because of them. What was missing was the link to an actual choice someone has to make.
So the planning conversation I push for is about decisions. A retailer told us they wanted a "stock dashboard." Fine, but what decision? Turned out the real decision was a store manager deciding each morning what to reorder, and the thing that decision needed was simply which lines were running low and how fast they were selling. That's a far smaller, sharper solution than the sprawling stock dashboard they'd originally asked for, and it actually got used because it answered a question someone genuinely had at 8am every day. Most of the metrics on the original wishlist would have been glanced at once and ignored.
Get the requirements from the people who'll use it
This sounds obvious and it's astonishing how often it doesn't happen. Solutions get planned in a meeting full of managers and IT, and the people who'll actually use the thing every day are nowhere in the room. The result is a report designed for how leadership imagines the work happens rather than how it actually happens.
The frontline users know things the planning meeting doesn't. They know that the data is messy in a particular way, that there's a workaround everyone uses, that the metric leadership wants is calculated three different ways depending on who you ask. If you don't talk to them during planning, you find all this out during the build when it's expensive to fix, or worse, after launch when the report quietly gets abandoned because it doesn't match reality.
When we plan a solution we insist on talking to the actual users, not just the sponsors. It can be a slightly awkward conversation to ask for, because the sponsor sometimes feels they can speak for everyone. They can't. The gap between how the boss thinks the job is done and how it's actually done is where dead dashboards come from. This is a core part of how our Power BI consultants approach a build, and it's saved more projects than any technical decision we've made.
Scope the data before you fall in love with the design
Once you know the decision and the users, the next planning question is the unglamorous one: what data do you actually need, where does it live, and what state is it in. This is where a lot of solution plans quietly come apart, because people design a beautiful report and only later discover the data to feed it is missing, dirty, or locked in a system nobody can get into.
Plan the data honestly. For each thing the solution needs to show, trace it back to a source. Is that source reliable? Does it update often enough? Who owns it? Is the field you need actually populated, or is it technically there but empty half the time? I've seen a planned solution that depended on a "customer segment" field that turned out to be filled in for about a third of records. The whole design assumed that field was solid. It wasn't, and the assumption should have been caught in planning, not three weeks into the build.
This is also where you make the early architecture calls that are painful to undo later. How fresh does the data need to be? Real-time, daily, weekly? That answer drives whether you import the data or query it live, and getting it wrong means either a sluggish report or one that's needlessly complex. Plan it deliberately rather than defaulting. We work through these data and architecture decisions as part of our broader Microsoft Fabric and Power BI work, because they're the ones that quietly determine whether the solution performs and whether it can be maintained.
Decide what good enough looks like, and what's out of scope
Every solution plan needs a deliberate decision about scope, and specifically about what you're not going to do. Without it, scope creep is guaranteed. Someone always wants one more metric, one more filter, one more drill-through, and each addition seems small, but they pile up into a solution that takes three times as long and tries to be everything to everyone.
Good planning draws the line on purpose. This solution answers these questions for these people, and that's it. The other ideas aren't bad, they're just a different solution for a different time. Writing that down protects the build and gives you something to point at when the requests start arriving mid-project. It also forces a useful conversation about what "good enough" means, because perfect is the enemy of shipped. A solution that answers the core question well and launches beats an everything-and-the-kitchen-sink one that's still in planning six months later.
There's an honesty needed here that planning meetings often dodge. Not everything the business wants is worth building, and part of planning a solution well is being willing to say so. An outside perspective genuinely helps with this, because we're not caught in the internal politics and can say "that bit isn't worth the effort" without it being career-limiting. That candour is half of what good BI strategy work actually delivers at the solution level.
Plan for the boring stuff that decides longevity
The last thing a solution plan should cover, and the bit that gets skipped most, is what happens after launch. Who owns this solution? Who updates it when the business changes? Who do users go to when a number looks wrong? A solution with no owner is a solution with a use-by date, and an awful lot of orphaned Power BI reports started life with a great build and no plan for the day after.
Plan the ownership up front. Decide who's responsible for the data model, who handles change requests, how the thing gets documented so the next person can understand it. None of this is glamorous and all of it determines whether your solution is still trusted and used in two years or quietly dead in six months. The build is the easy, visible part. The maintenance plan is what separates a solution that earns its keep from one that becomes the next thing nobody trusts.
The order I'd actually follow
If you're planning a Power BI solution from scratch, the sequence is straightforward even though the discipline to follow it isn't. Nail down the decision the solution supports and who makes it. Talk to the real users, not just the sponsors. Trace every metric back to honest, reliable data and make your architecture calls deliberately. Draw a firm line around scope and write down what's out. Then decide who owns the thing for the long haul before you build a single visual.
That's solution planning done properly, and it's a different and more concrete job than setting strategy. Strategy tells you which solutions are worth doing. Solution planning makes sure the ones you do actually get used. Both matter, and skipping either is how reporting investments turn into expensive disappointment.
The full BI solution planning guidance from Microsoft is worth reading alongside this if you want the formal version. If you've got a solution you're about to build and you want to make sure the planning is sound before anyone touches Power BI Desktop, that's exactly the point where a second set of eyes pays for itself. Have a chat with us and we'll help you plan it so it lands.