The primary causes are people, process, and data — not the platform. Gartner finds that more than 70% of ERP initiatives will fail to fully meet their original business case by 2027. Panorama's research on discrete manufacturing is starker: 73% miss objectives, with average cost overruns of 215% (Godlan/Panorama Consulting, 2025). Both datasets point to the same root causes: underinvestment in change management, data quality problems that weren't addressed before migration, and processes that were automated before they were redesigned.

The fully loaded cost includes implementation fees, change management and organizational design, data migration and cleansing, integration development, training programs, post-go-live stabilization, and the productivity dip that occurs in the 60-90 days after go-live while teams adjust. Many organizations budget for the first category and underestimate the others. The 215% average cost overrun in discrete manufacturing reflects this gap (Godlan/Panorama Consulting, 2025).

Implementation is standing up a new or significantly upgraded system. Optimization is getting more value from a system you already have. Most organizations that aren't seeing the ROI they expected from their ERP need optimization, not a new implementation — the system is capable of more than they're using it for. The distinction matters because the fix is different: implementation is a capital project, optimization is a combination of configuration, process redesign, and adoption work. A good starting point is an honest assessment of whether your gaps are in what the system can do or in what your organization is actually using it to do.

Huron leads with advisory — the operating model, process design, and change management work that determines whether an ERP program delivers. Most firms lead with the platform. Huron's delivery model is advisory-led, which matters for industrial and energy organizations where change is local: adoption at a manufacturing plant or energy facility requires a different plan than the one approved at headquarters.

Post-go-live work includes stabilization, adoption measurement, platform optimization, and — for organizations that built AI readiness into their modernization — activating the AI capabilities the new foundation can now support. Change management doesn't end at go-live either. The organizations that sustain adoption are the ones that continue the floor-level support, role reinforcement, and performance measurement past the launch date. The honest measure of a successful ERP implementation isn't whether the system went live. It's whether the organization is actually working differently because of it.

The work that most determines whether an ERP program succeeds happens before a platform is selected or a line of configuration is written. It includes an operating model assessment — defining how the organization needs to work, not just documenting how it works today — and a clear-eyed look at data quality, process gaps, and organizational readiness for change. Platform selection should follow that assessment, not precede it.

Change management scoping also belongs in this phase: the organizations that treat change management as a pre-go-live training event consistently underdeliver. The ones that build it in from the start are significantly more likely to meet their objectives. For a closer look at what AI readiness requires from your ERP foundation before you begin, AI-ready ERP: building the foundation your AI investments require covers the data and organizational components in detail.

The three most common failure modes are scope underestimation — total cost typically runs 215% above the initial implementation quote — change management underinvestment, and timeline compression (Godlan/Panorama Consulting, 2025). Organizations that run operating model design and implementation concurrently consistently land closer to 24 months than 12. The organizations that manage these risks treat change management and data foundation work as prerequisites, not parallel workstreams.

A full-scope cloud ERP modernization typically runs 12-24 months from operating model assessment to stable post-go-live operations. Implementation scope, data complexity, number of legal entities, and integration requirements are the primary drivers of timeline variance. Programs that start with a thorough pre-implementation assessment typically run faster and encounter fewer mid-project surprises.

SAP extended support for ECC ends in December 2027. Extended maintenance is available through 2030 at a cost premium. The decision of whether to migrate — and to which platform — should be driven by an honest operating model assessment: what you need your ERP to do, where your current system falls short,