BCG and Conduct have formed a strategic partnership aimed at one of the most expensive and opaque parts of ERP transformation: understanding what heavily customized systems actually contain before design, fit-to-standard, and migration decisions are made.
Custom code analysis usually becomes painful when programs are already under schedule and budget pressure. The BCG-Conduct partnership is positioned around moving that intelligence earlier, so teams can understand dependencies, compare systems against ERP standard, and make fit-to-standard decisions before manual analysis slows the program.
Announced on May 5, the partnership combines BCG and BCG Platinion’s ERP transformation capabilities with Conduct’s AI platform for analyzing, operating, and transforming large-scale IT and ERP systems. The companies said the collaboration is designed to accelerate ERP programs, reduce risk, and give project teams more transparency into large custom code landscapes.
Analysis
What this means: The consulting market is formalizing around specialist ERP intelligence tools. BCG’s partnership with Conduct shows how large advisory firms are bringing specialist AI platforms into mainstream ERP transformation offerings. For systems integrators and ERP vendors, the competitive pressure will increase around who can diagnose legacy complexity fastest, convert that insight into design decisions, and prove the savings beyond pilots.
Custom Code Is a Hidden Migration Cost
ERP transformations often stall when teams cannot quickly determine what custom objects do, who still uses them, and what business logic depends on them. That problem becomes more acute in long-running ERP estates where years of local extensions, business-specific processes, and technical workarounds have accumulated without clear documentation.
Conduct’s platform is designed to address that gap through deep analysis of custom code and dependencies. According to the announcement, it supports comparisons across systems and against ERP standard, while reducing manual work across phases of a migration program.
The value is not simply faster code review. It is decision quality. If transformation teams can see which customizations support critical business differentiation, which duplicate ERP standard functionality, and which create avoidable complexity, they can make cleaner design calls earlier in the program.
Analysis
What this means: Custom code intelligence is becoming a frontline transformation capability. ERP programs with large customization footprints need earlier visibility into code, dependencies, and process fit before design decisions harden. For program owners and enterprise architects, this shifts custom code analysis from a technical cleanup activity to a core input into scope, standardization, and migration strategy.
Pilot Focuses on Fit-to-Standard
BCG and Conduct said an initial pilot focused on fit-to-standard analysis generated initial process designs up to ten times faster and achieved 50% to 80% cost savings through leaner delivery models and reduced manual effort.
Those figures are significant, but they should be read narrowly. The announcement ties them to a pilot focused on fit-to-standard analysis, not to full ERP program delivery. That still gives ERP program owners a useful benchmark for one of the most labor-intensive parts of transformation: assessing where the existing estate should conform to standard process and where custom logic needs to remain.
The partnership also gives BCG a more specific toolset for a problem many consulting-led ERP programs already face. BCG brings transformation orchestration, operating-model work, and delivery expertise through BCG Platinion. Conduct brings system intelligence that can help teams understand custom code landscapes and reduce manual analysis across migration phases.
Analysis
What this means: Fit-to-standard work is a clear target for AI-assisted delivery. The pilot results, including process designs up to ten times faster and 50% to 80% cost savings, apply to fit-to-standard analysis rather than entire transformations. That still gives CIOs, CFOs, and transformation leaders a practical place to test whether AI-enabled delivery can reduce consulting effort without weakening design rigor.
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Customer Claims Show the Target Problem
The announcement also points to existing Conduct customer outcomes. Conduct claimed global companies including Daimler Truck, Heidelberg Materials, and Fraport have cut project costs by more than 30%, saved millions on annual maintenance, and shipped features months faster using its platform for ERP transformations.
Those examples strengthen the case for Conduct’s technology, though they are not necessarily proof of the new BCG-Conduct delivery model. The named examples show the kind of ERP environments Conduct has served and the value claims attached to its platform, while the BCG alliance is meant to scale that capability into larger transformation programs.
That distinction matters for buyers evaluating the offering. The announcement provides strong evidence of the problem space and early performance claims in fit-to-standard analysis. The next proof point will be whether BCG and Conduct can reproduce those outcomes consistently inside full-scale ERP programs with complex governance, process redesign, business change, and partner coordination.
