Enterprise resource planning systems promise seamless control over manufacturing operations, yet inventory records routinely diverge from physical stock, forcing factory shutdowns for reconciliation. This disconnect, known as inventory drift, stems from architectures built for batch processing in an era of continuous production. Dinesh Garg, senior IT manager at Honeywell Intelligrated, argues in a CIO.com article that ‘Your ERP isn’t broken — it’s just outdated, because inventory accuracy still depends on stopping the factory instead of reconciling reality in real time.’

Garg draws from decades in aviation, automotive, and warehouse automation, observing that ERP systems record transactions accurately only under perfect human execution. Manufacturing execution systems capture production but miss financial alignment. Work-in-process inventory remains opaque due to complex bills of materials, phantom assemblies, and dynamic consumption like backflushing. ‘Inventory accuracy was being treated as an operational event when it should have been treated as a system control function,’ Garg writes.

Cycle counting, meant to minimize disruptions, exacerbates drift by assuming a valid base model and patching discrepancies later. In a detailed scenario, a factory with 100 units split across stockroom, WIP, and QA sees a physical move of 10 units to WIP go unrecorded in the system. A WIP cycle count adds a +10 adjustment, inflating totals to 110 unless all locations sync simultaneously—a process demanding production halts.

Roots of Persistent Drift in Modern Plants

Traditional ERP thrives on periodic controls, unfit for high-mix environments with real-time changes. MES data flows fast, but without deterministic reconciliation, systems drift. WIP challenges dominate: multi-level BOMs make components uncountable without explosion logic. Patents like US20080255968A1 proposed timestamp reconciliation but ignored execution context, remaining unimplemented.

Garg’s research on ResearchGate confirms periodic mechanisms fail amid IoT and automation acceleration. ‘In live, high-mix manufacturing environments, where production runs continuously, configurations change frequently and execution data moves in real time, those assumptions no longer hold true,’ he notes. Audits rely on manual fixes, eroding trust across ERP, MES, and finance.

Recent web searches reveal industry-wide struggles. A KPC Team post on 2026 ERP trends highlights predictive modules surfacing ‘inventory drift’ alongside machine risks, with prescriptive AI rerouting work orders. Yet, most solutions remain reactive.

Patented Path to Continuous Verification

Garg’s solution, outlined in UK patents GB2521650.8 and GB2521655.7, reimagines inventory as a live control. Core: snapshot-based verification—capture a timed physical baseline, track all movements digitally, then mathematically reconcile later without freezes. A unified single-screen interface lets operators scan any item by part, quantity, location, and job; the system infers context.

BOM explosion dynamically computes expected versus actual consumption, including scrap and returns, auto-generating variances. Deterministic logic ensures auditability, augmented by AI for anomaly detection. ‘One approach detects errors after they accumulate. The other prevents them from accumulating at all,’ Garg states. Benefits include no shutdowns, aligned systems, faster closes, and inventory as a trusted digital asset.

His background at CSIR, Toyota/AISIN via ADVICS North America, informs this ERP-agnostic design, primed for robotics and IoT scale-up. ‘Manufacturing is becoming more automated, distributed and real-time. Robotics, IoT and AI increase execution speed, but they also amplify the cost of weak data foundations.’

ERP Vendors Push Real-Time Edges

2026 rankings spotlight innovations addressing drift indirectly. Top10ERP.org praises NetSuite’s real-time visibility into raw materials, WIP, and finished goods, integrating RFID for tracking. Cetec ERP offers mobile warehousing and quality assurance in a single MES-ERP platform at $40/user/month.

DELMIAWorks (ex-IQMS) unifies ERP and MES for comprehensive execution. The Retail Exec ranks ERPNext for open-source customization in inventory and sales, while Epicor ERP scales for SMBs with extensive stock controls. Fulfil’s AI-native dashboard syncs multichannel stock in real time.

Panorama Consulting’s analysis emphasizes ERP scalability for growth, AI-driven predictive analytics, and cycle count automation to cut reconciliations. ‘Using an ERP solution to simplify the process can improve inventory records and ensure successful checks and balances.’

AI and Cloud Reshape Reconciliation

Trends point to AI-embedded ERPs. BatchMaster forecasts cloud-native shifts from monolithic systems, with AI operationalizing sustainability via real-time tracking. NetSuite’s 2025.2 release adds multivariate forecasting and AI close management, per AlphaBold.

X discussions echo urgency. CIO.com posted on inventory counts halting factories, linking Garg’s piece. Source Logistics warns of drift from siloed warehouse views, advocating network-level planning in a blog. MLC CAD Systems highlighted DelmiaWorks streamlining Acme Audio’s RFQ-to-shipping with unified visibility.

DOSS Operations Cloud claims unified architecture eliminates sync delays, per their trends report. Syspro enables real-time manufacturing integration for WIP tracking and variance reporting. These align with Garg’s vision but lack full deterministic BOM reconciliation.

Implementation Hurdles Ahead

Adopting such architectures demands data stewards, automation guilds, and UX focus, as KPC Team advises. Panorama notes 72.6% of firms deployed AI per their 2025 report, yet legacy layering persists. Garg’s patents offer a blueprint: shift from event-based to continuous control.

For insiders, the stakes rise with automation. Weak foundations amplify errors in distributed ops. Early movers like Honeywell Intelligrated gain edge via AI-optimized execution. As Garg concludes, redesigned systems prevent drift, slashing enterprise risks in real-time manufacturing.