Page pattern

Root-Cause Analysis

Take a stated problem apart until the underlying records explain it.

AnalysisAdvancedArchetype: Driver / Root-Cause Analysis
Typical user questions
  • Why did this happen?
  • Which level of the hierarchy carries the problem?
  • Which records are responsible?

Root-Cause Analysis — clickable example

Shared retail dataset. Every control works; the log shows what Power BI would change.

Simulation of native Power BI behaviour
Filter contextDepartment:All
Problem statementcontext
OverviewAll departmentsWeeks:1–13
KPI deviationkpi
Actual€8.4M
Target€8.5M
Difference€-89kvs Budget€8.5M -101%Attention

Gap €-89k (-1%) against target.

Driver decompositiondriver
TargetFreshBeveragesGroceryNon-foodHouseholdActual
Hierarchybreakdown
Level: department

Bars: Revenue · vertical marker: Budget

Selected driver trendtrend
W1W2W3W4W5W6W7W8W9W10W11W12W13
Underlying recordsdetail
vs Budget
Kids socks 3pk€404k€407k€100k€5k -0.6%
Cotton towel€396k€402k€100k€5k -1.7%
Salad mix€391k€392k€98k€5k -0.2%
Gouda 48+ 250g€387k€391k€97k€5k -0.9%
Croissant 4pk€368k€368k€92k€4k -0.1%
Bananas 1kg€342k€345k€85k€4k -1.0%
Chopped tomatoes€336k€342k€84k€4k -1.8%
Tomatoes 500g€331k€338k€82k€4k -2.1%
BBQ charcoal 3kg€330k€338k€83k€4k -2.3%
Semi-skimmed milk 1L€316k€319k€78k€4k -1.0%
Sourdough loaf€312k€316k€77k€4k -1.4%
Toilet tissue 8pk€306k€310k€76k€4k -1.6%
Filter coffee 500g€302k€302k€75k€4k 0.1%
Kitchen roll 4pk€300k€306k€75k€4k -1.8%
Cola 1.5L€296k€300k€74k€4k -1.3%
Mixed nuts 250g€295k€298k€73k€3k -1.2%
Dish soap 500ml€289k€294k€72k€4k -1.6%
Salted crisps 200g€286k€288k€71k€3k -0.6%
Green tea 20pk€285k€287k€72k€3k -0.7%
Sparkling water 6pk€284k€285k€70k€3k -0.5%
Chickpeas 400g€284k€282k€74k€4k 0.6%
Pilsner 6pk€272k€273k€70k€3k -0.5%
All-purpose cleaner€270k€275k€68k€3k -1.9%
Rioja 0.75L€267k€270k€66k€3k -1.2%
Basmati rice 1kg€264k€265k€66k€3k -0.3%
Garden candle€262k€265k€63k€3k -1.0%
Penne 500g€231k€236k€58k€3k -1.8%
Total€8.4M€8.5M€2.1M€101k-1.0%
What Power BI would do
  • Interact with a slicer, a bar or a navigation button to see the native behaviour described here.

Driver / Root-Cause Analysis — archetype wireframe

[ Problem / KPI ] [ Key drivers ] [ Contribution analysis ] [ Supporting evidence ] [ Detail ]

Simulation of native Power BI behaviour
Zone 1
Problem / KPI
Zone 2
Key drivers
Zone 3
Contribution analysis
Zone 4
Supporting evidence
Zone 5
Detail

Reading order follows the zones above, top-left to bottom-right.

Designer

Components: Decomposition tree, Waterfall, Bar charts, Matrix

Hierarchy: Context/control → status/primary answer → explanation/breakdown → detail → next step.

Developer

Interaction: Use only interactions that support the page's next analytical step; typical next level: **Contributor drillthrough**.

Navigation: Contributor drillthrough

Implementation: Compose from the listed native visuals/controls and the standard interaction patterns in this guide; custom visuals are exceptions.

Common mistakes
Treating the archetype as a rigid screen; adding unrelated analytical tasks; duplicating controls already handled globally.
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