The Customer: Who they are
A multi-brand fashion retailer whose buying teams made assortment and pricing decisions off weekly static reports.
The Challenge: Identifying the villain
By the time a QlikView report reached a buyer’s inbox, the sell-through data was already several days stale — a real cost in a business where trend cycles move in weeks. “We were making buying calls on last week’s story,” said the Head of Commercial Analytics.
The Journey: The search for a solution
The retailer considered simply upgrading QlikView licenses, but the platform’s ageing architecture couldn’t support the near-real-time refresh rates the buying team needed.
The Discovery: Finding IDS
IDS was engaged after the retailer’s IT director attended a webinar on BI platform migrations and recognized the QlikView-to-Qlik-Sense path as directly relevant.
The Solution: The hero arrives
IDS migrated the QlikView estate to Qlik Sense, rebuilding the semantic layer with a governed self-service model — buyers could explore sell-through, stock cover, and markdown impact themselves, without waiting on the BI team for every new cut.
The Implementation: The battle
Migration ran brand-by-brand to limit disruption during peak trading periods, with training embedded at each rollout wave so buyers adopted self-service rather than reverting to their old static reports. The obstacle: several legacy QlikView apps had no documented data model; IDS reconstructed logic through interviews with the original report owners.
The Results: The happy ending
- Report refresh: weekly → daily
- Buyer-led analysis requests to the BI team: down 40%
- Time to identify a markdown opportunity: days → hours
- Self-service adoption across buying teams: 80%+ within one quarter
“We’re reacting to trends in days, not weeks.” — Head of Commercial Analytics
Technologies used: Qlik Sense · QlikView (migration source)