Legacy BI consolidated. Monthly iteration cadence.

A global hand-tool manufacturer had accumulated three separate reporting platforms over a decade \u2014 each with its own licensing cost, filtering syntax, and skill requirement. Allari® consolidated all three onto Power BI across Sales and Manufacturing domains, validated feature parity, and established a standing monthly cadence so the dashboards evolve with the business rather than freezing at cutover.

What the Consolidation Produced

3 \u2192 1

Three legacy reporting platforms consolidated onto Power BI for Sales and Manufacturing domains.

Validated

Filtering behavior matched against the legacy reporting platforms so end users retained full capability.

Monthly

Standing monthly Changes & Issues cadence so dashboards evolve with the business rather than freezing at cutover.

Same team

BI modernization delivered by the same custodial team running JDE production support \u2014 no vendor silo.

Source: Allari ticket database, customer-cleared reporting \u00b7 Client identity withheld at customer request \u00b7 Methodology available under NDA

Three Platforms, No Single Source of Truth

A Decade of Platform Accumulation

The manufacturer had accumulated three separate reporting platforms: a desktop BI tool for general analytics, a JDE-native report writer for ERP-specific output, and a mobile reporting platform for field access. Each added its own licensing cost and operator burden.

Fragmented view: Sales reports and manufacturing dashboards were split across the three platforms. There was no single source of truth \u2014 answering a cross-domain question required pulling from at least two systems.

Skill lock-in: Each tool had its own filtering syntax, refresh cadence, and required skill profile. Knowledge could not be consolidated \u2014 a change in one platform did not propagate to the others.

DIAGNOSIS: Redundant licensing, siloed knowledge, and a mobile platform approaching deprecation \u2014 with no consolidation path in place.

Sustainment Risk Was Growing

Vendor sustainment for the three legacy platforms was becoming harder to manage in parallel. The mobile reporting platform's deprecation loomed, creating urgency \u2014 but a hasty migration without feature parity would erode user trust and force retraining.

Meanwhile, the manufacturer's relationship with Allari already covered JDE production support. The same team held institutional knowledge of the underlying JDE data model \u2014 which meant BI modernization could happen without a cold start.

Legacy Platform Types

Three-Phase Consolidation

Inventory & Consolidation Map

• \u2014 Catalogued every existing report across all three legacy platforms
• \u2014 Identified overlap, duplication, and gaps between Sales and Manufacturing views
• \u2014 Documented filtering logic and refresh dependencies per platform
• \u2014 Produced a consolidation map as the governing artifact for Phases 02 and 03

Sales Domain — Power BI Rebuild

• \u2014 Rebuilt Sales reporting on Power BI with explicit feature-parity matching
• \u2014 Filtering behavior matched against the legacy system — stated success criterion
• \u2014 End users retained every filter combination from the prior platform
• \u2014 Data validated against legacy source systems before cutover

Manufacturing Domain + Ongoing Iteration

• \u2014 Extended Power BI consolidation to Manufacturing domain
• \u2014 Established standing monthly Changes & Issues cadence
• \u2014 Dashboards evolve with the business — not frozen at cutover
• \u2014 Cross-domain Sales and Manufacturing visibility unified on a single platform

Engine Credentials — Same Team, No Silo

• \u2014 Request Classification: BI requests routed alongside JDE tickets
• \u2014 OpenBook® transparency — cost visibility across ERP and BI workstreams
• \u2014 15-Minute Work Measurement — every unit of BI work tracked
• \u2014 Embedded teams — no separate BI vendor or inter-team handoff

What the Engagement Delivered

The manufacturer did not need more reporting tools. It needed fewer \u2014 unified under a single platform that its custodial team could maintain, extend, and validate without switching contexts. Power BI provided that platform.

The feature-parity requirement was the key structural constraint: migration is only credible if users do not regress. By cataloguing legacy filtering behavior before rebuilding, Allari ensured that the consolidation was a net gain, not a trade-off.

The monthly iteration cadence transformed the engagement from a one-time project into a continuous service. Dashboards that evolve with the business are fundamentally different from dashboards frozen at go-live \u2014 they remain decision-ready as the organization changes.

Client identity withheld at customer request. Engagement details, metrics, and outcomes verified against Allari's internal ticket database and customer-cleared reporting. Methodology and supporting evidence available under NDA on request.

Three reporting platforms consolidated onto Power BI for Sales and Manufacturing.

Filtering behavior matched against legacy systems — users retained full capability.

Standing Changes & Issues cadence — dashboards evolve with the business.

No separate BI vendor — same custodial team as JDE production support.

Validation of data model against legacy source systems before cutover.

Questions About This Engagement

Why did the manufacturer consolidate three reporting platforms instead of maintaining them separately?

Each legacy platform — a desktop BI tool, a JDE-native report writer, and a mobile reporting platform — carried independent licensing costs, its own filtering syntax, a distinct refresh cadence, and a separate skill profile. Operators could not move knowledge between tools, sustainment was becoming harder, and one of the platforms was approaching deprecation. Consolidating onto a single Power BI layer eliminated the redundant cost structure and created a unified source of truth across Sales and Manufacturing.

How did Allari ensure end users did not lose capability during the migration?

Feature parity was a stated success criterion, not an afterthought. Before rebuilding any report, Allari catalogued every existing report across all three platforms. During the Sales domain build, filtering behavior was explicitly matched against the legacy system — ticket evidence documents this as a deliberate deliverable. Users retained every filter combination they had before, with the added flexibility of Power BI's native interactions.

What does the 'monthly iteration cadence' mean in practice?

After the initial consolidation, a standing monthly Changes & Issues cadence was established. Rather than freezing the dashboards at cutover and issuing tickets for every subsequent change, the engagement includes a structured monthly cycle to evolve the dashboards as the business changes — new sales regions, manufacturing line adjustments, updated KPI definitions. The dashboards stay current without requiring a new project each time.

How was this BI modernization connected to the manufacturer's existing JDE production support?

The Power BI work was delivered by the same custodial team that runs JDE production support for this manufacturer. BI requests are routed and classified alongside JDE tickets under the same Request Classification framework. There is no separate BI vendor, no inter-team handoff, and no communication gap between the ERP layer and the reporting layer — the team that understands the JDE data model is the same team building and maintaining the dashboards.

Want what Global hand-tool manufacturer has?

Three legacy reporting platforms collapsed onto Power BI. Monthly iteration cadence established. Same team. No vendor silo.

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This is the engagement summary. The monthly statement is what arrives in your Power BI workspace.