How a logistics company moved critical reporting from a costly, legacy QlikView environment to a governed Power BI platform on Microsoft Cloud — reducing BI run-rate, simplifying the data model, and keeping operational reporting under control.
This anonymized case story illustrates a common challenge for logistics companies locked into expensive legacy BI platforms. The dashboard metrics are representative of the business case logic used to evaluate migration ROI. Need to reduce BI TCO without losing reporting control? Let’s assess your migration path →
A mid-sized logistics company had built years of operational reporting around QlikView. Dispatch performance, fleet utilization, route profitability, customer SLA reporting, and finance dashboards all depended on a small set of legacy applications.
The system was familiar, but it was no longer economical. License renewal costs kept increasing, infrastructure was aging, and only a handful of specialists still understood the original QlikView logic. For the IT Director, this created a dangerous trade-off: cut BI costs and risk breaking reporting, or keep paying for a platform the company no longer wanted to grow.
Business users were also frustrated. Every new KPI request required IT intervention. Similar metrics had different definitions across departments. Exporting to Excel became the workaround whenever the legacy dashboard could not answer a new question.
The board asked IT to reduce the total cost of ownership before the next QlikView renewal — without lowering the quality, accuracy, or availability of reporting used by operations and finance.
The first internal estimate showed a problem: simply recreating every QlikView dashboard in Power BI would move the cost somewhere else. The real work had to start with rationalization, KPI governance, and data model simplification — not with a one-to-one visual rebuild.
Multishoring designed the migration around cost reduction, governance, and continuity of business-critical reporting.
We mapped dashboard usage, data sources, KPI ownership, refresh schedules, and dependencies. Low-value reports were retired, duplicated KPIs were merged, and critical dashboards were prioritized for controlled migration.
Instead of copying legacy logic screen by screen, we rebuilt the analytical layer around reusable datasets, certified KPI definitions, and Microsoft Cloud data pipelines using Azure Data Factory, Azure Data Lake, and Power BI.
Critical dashboards were validated side by side with QlikView before cutover. Power BI workspaces, permissions, RLS, audit logs, and ownership rules were configured to give IT control after go-live.
“Every cost discussion became a risk discussion. We knew the platform was expensive, but we could not simply switch it off without disrupting operations.”
“We reduced the run-rate without losing control. The biggest win was not just Power BI — it was finally having an analytics layer that IT and business both understand.”
Representative outcomes from the anonymized migration scenario.
We migrate critical reports into Power BI while rationalizing dashboards, rebuilding the semantic model, and protecting reporting continuity.
Explore Power BI Services
We build governed analytics environments on Microsoft Cloud, connecting operational, financial, and logistics data into one trusted reporting layer.
Explore BI SolutionsWe review your QlikView apps, license exposure, report usage, data sources, KPI ownership, and renewal deadlines to define the migration business case.
We migrate one high-value reporting domain into Power BI, validate outputs against QlikView, and prove the approach before scaling.
We expand the platform, document ownership, implement governance, train users, and retire legacy apps in a controlled sequence.
“A BI migration should not be treated as a visual redesign exercise. The real value comes from reducing platform cost, clarifying ownership, and rebuilding the reporting layer so the business can trust it after go-live. That is how you move from legacy lock-in to controlled freedom.”
