{"id":42768,"date":"2026-05-04T21:44:37","date_gmt":"2026-05-04T16:14:37","guid":{"rendered":"https:\/\/www.verdantis.com\/?p=42768"},"modified":"2026-05-04T21:44:39","modified_gmt":"2026-05-04T16:14:39","slug":"asset-management-oil-gas-mro360","status":"publish","type":"post","link":"https:\/\/www.verdantis.com\/es\/asset-management-oil-gas-mro360\/","title":{"rendered":"Retos de la gesti\u00f3n de activos en el sector del petr\u00f3leo y el gas y c\u00f3mo los resuelve MRO360"},"content":{"rendered":"
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Asset Management in Oil & Gas: The Challenges No One Talks About Enough<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Oil & Gas is one of the most capital-intensive industries on the planet.<\/p>\n

Fixed assets — compressors, pumps, heat exchangers, turbines, pipelines — run continuously, often in the harshest environments imaginable. Offshore platforms. Desert refineries. Arctic pipelines. The pressure to keep them running is unrelenting.<\/p>\n

Yet despite decades of investment in maintenance systems, asset management in Oil & Gas remains deeply inefficient<\/strong> for most operators.<\/p>\n

Unplanned downtime costs the industry an estimated $38 million per day<\/strong> across offshore operations alone, according to a report by Siemens. Meanwhile, Aberdeen Research found that 80% of maintenance organizations<\/strong> still rely heavily on reactive or time-based maintenance strategies — approaches that were already considered outdated twenty years ago.<\/p>\n

The problem is rarely a lack of effort. It's a lack of the right data, in the right hands, at the right time.<\/strong><\/p>\n

This article breaks down the most pressing asset management challenges facing Oil & Gas operators today — and how MRO360 by Verdantis<\/a> is purpose-built to address each one of them.<\/p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Why Asset Management in Oil & Gas Is Uniquely Complex<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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No two industries face exactly the same asset management challenges — but Oil & Gas is in a category of its own.<\/p>\n

The combination of aging infrastructure<\/strong>, geographically dispersed operations<\/strong>, regulatory intensity<\/strong>, and the critical nature of every single asset<\/strong> creates a compounding problem that generic maintenance systems simply aren't equipped to handle.<\/p>\n

Here's what makes Oil & Gas asset management fundamentally different from other heavy industries:<\/p>\n

Scale and Complexity of Fixed Assets<\/strong><\/p>\n

A single refinery can contain tens of thousands of individual assets<\/strong> — from rotating equipment to pressure vessels to electrical systems — each with its own failure mode, maintenance schedule, and spare parts requirement.<\/p>\n

Upstream operations add further complexity, with assets distributed across dozens of wellheads, often in remote locations with limited logistics infrastructure.<\/p>\n

Continuous Operations, Zero Tolerance for Downtime<\/strong><\/p>\n

Unlike discrete manufacturing, Oil & Gas operates 24\/7\/365. Planned shutdowns are rare, expensive, and tightly scheduled. Unplanned stoppages cascade quickly — a single failed pump in a refinery can halt production for an entire processing train.<\/p>\n

The financial impact is immediate and severe. Unplanned downtime in refining can cost between $100,000 and $500,000 per hour<\/strong>, depending on the facility and the product mix being processed.<\/p>\n

Regulatory and Safety Pressure<\/strong><\/p>\n

HSE compliance isn't optional — it's existential. Maintenance failures that lead to safety incidents carry regulatory, reputational, and human costs that dwarf the direct operational loss. This creates a unique pressure: maintenance teams must balance operational efficiency with absolute safety compliance<\/strong>.<\/p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t80% of O&G maintenance orgs still use reactive or time-based strategies (Aberdeen Research)\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\n\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t$38M\/day \u2014 estimated cost of unplanned downtime across offshore operations (Siemens)\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\n\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tUp to $500K\/hour lost during unplanned refinery stoppages\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\n\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t25\u201335% of MRO inventory in most O&G facilities is dead stock or dormant\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\n\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t50%+ of machine downtime is linked to unavailability of spare parts or technician skills\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\n\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t11\u201335% of total OPEX is tied up in maintenance inventory across industrial operators\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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The 7 Biggest Asset Management Challenges in Oil & Gas<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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1. Unplanned Equipment Failures and Reactive Maintenance<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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The most visible — and costly — challenge in Oil & Gas asset management is unplanned equipment failure.<\/p>\n

Most operators still run large proportions of their asset base on reactive maintenance (run-to-failure)<\/strong> or rigid time-based preventive schedules<\/strong>. Neither approach is well-suited to the dynamic, high-stakes environment of Oil & Gas.<\/p>\n

Reactive maintenance means you're always behind the curve — scrambling for parts, skills, and contractors after a failure has already occurred. Time-based maintenance, while more predictable, often results in over-maintenance of healthy assets<\/strong> o under-maintenance of assets that are degrading faster than scheduled intervals anticipate<\/strong>.<\/p>\n

The result: maintenance teams spend most of their time fighting fires rather than preventing them.<\/p>\n

The real problem<\/strong> is that maintenance decisions are being made without adequate data. Failure patterns, asset history, spare part availability, work order backlogs — these exist in siloed systems that don't talk to each other. Planners make critical decisions based on incomplete pictures.<\/p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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2. Spare Parts Inventory: Too Much or Never Enough<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Spare parts management is one of the most misunderstood — and underinvested — aspects of Oil & Gas asset management.<\/p>\n

The typical approach is conservative hoarding: stock everything you might possibly need, because the cost of being without a critical part during a breakdown far outweighs the cost of holding inventory.<\/p>\n

The problem? This logic doesn't scale.<\/strong> A major refinery or upstream operation can have anywhere from 50,000 to 200,000 unique material line items<\/strong> in its MRO inventory. Applying a blanket stocking philosophy to that volume doesn't just strain working capital — it actively obscures the inventory picture.<\/p>\n

Aberdeen Research has noted that 25% of maintenance inventories in industrial operations are dead stock<\/strong> — parts that haven't moved in years, are now obsolete, or are stocked far beyond any plausible consumption scenario. Across an O&G enterprise, this can represent tens of millions of dollars<\/strong> in working capital tied up unproductively.<\/p>\n

At the same time, stockouts of genuinely critical parts remain a leading cause of extended downtime. Operators simultaneously over-stock non-critical items and under-stock the parts that actually matter.<\/p>\n

This isn't a supply chain failure. It's an intelligence failure<\/strong> — rooted in the absence of accurate criticality data and demand forecasting at the part level.<\/p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tThe Over-Stocking Problem\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/h4>\n\t\t\t\t\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Dead stock and excess MRO inventory silently drain working capital. Parts sit in storerooms for years — many obsolete, many duplicated across plant locations. The carrying costs compound annually, and the clutter actively makes it harder to find the parts you actually need.<\/p>\n

Key consequences:<\/p>\n

– Working capital locked in dormant inventory<\/p>\n

– Warehouse space consumed by obsolete parts<\/p>\n

– Duplicate procurement across plants<\/p>\n

– Inaccurate stock counts masking real availability<\/p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tThe Under-Stocking Problem\t\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/h4>\n\t\t\t\t\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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For critical assets, a missing spare part doesn't just delay a work order — it halts production. When a pump impeller or a control valve fails unexpectedly, every hour spent waiting for a part is an hour of lost throughput.<\/p>\n

Key consequences:<\/p>\n

– Extended downtime while parts are expedited<\/p>\n

– Emergency procurement at premium prices<\/p>\n

– Cascading production losses<\/p>\n

– Safety exposure from deferred maintenance<\/p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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3. Criticality Assessment Done Manually \u2014 and Inconsistently<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Ask most Oil & Gas operators how they determine which assets and spare parts are "critical" — and you'll hear a variation of the same answer: a periodic, multi-team workshop exercise using FMECA, VED, or ABC analysis models, producing a spreadsheet that someone will update… eventually.<\/p>\n

Criticality assessment is foundational to every downstream maintenance and inventory decision. And yet it remains one of the most manually intensive, inconsistently executed processes in the industry<\/strong>.<\/p>\n

The problems are significant:<\/p>\n

It assumes all parts linked to critical assets are also critical.<\/strong> In practice, this is false. A critical asset may have hundreds of associated spare parts — many of which are low-cost, fast-replenishable items that carry minimal downtime risk. Treating all of them as critical inflates stocking requirements dramatically.<\/p>\n

It's a snapshot in time, not a live view.<\/strong> A criticality assessment completed in 2021 doesn't account for changes in production volumes, supplier lead times, new failure patterns, or asset retirement. Outdated assessments make outdated stocking decisions.<\/p>\n

It's people-dependent, not data-dependent.<\/strong> The quality of a criticality assessment depends heavily on the knowledge and availability of the right subject matter experts — people whose time is perpetually scarce in Oil & Gas operations.<\/p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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4. Poor Master Data Quality Across Asset and Material Records<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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You cannot manage what you cannot accurately describe.<\/p>\n

Master data quality is the silent killer of asset management performance in Oil & Gas. Incorrect, incomplete, or duplicated records across asset masters, material masters, and supplier databases create cascading problems across every downstream function.<\/p>\n

Consider the scale: a mid-sized refinery might have 30,000–80,000 material master records<\/strong>. In most ERP systems, a significant proportion of these records will have one or more data quality issues — missing attributes, incorrect categorization, duplicate entries under slightly different descriptions, or obsolete records that were never deactivated.<\/p>\n

The downstream impact is severe:<\/p>\n

– Procurement planners can't identify whether the right part is already in stock — because duplicates and miscategorizations obscure inventory reality<\/p>\n

– Maintenance planners can't confidently link a spare part to the asset it belongs to — because Asset BOM linkages are incomplete or inaccurate<\/p>\n

– Inventory optimization models produce unreliable outputs — because the underlying data they rely on is dirty<\/p>\n

Poor material master data is directly responsible for both the over-stocking and stockout problems described above. It's the root cause, not the symptom.<\/p>\n

Verdantis' MDM Suite (https:\/\/verdantis.com\/mdm-suite) addresses this foundational layer — ensuring that asset and material records are clean, enriched, and synchronized before any downstream optimization can take place.<\/p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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5. Multi-Plant Inventory Blindspots<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Oil & Gas operators rarely run a single facility.<\/p>\n

Upstream operators manage portfolios of fields, platforms, and processing facilities. Downstream refiners may operate multiple plants across several geographies. And yet, in most organizations, inventory visibility stops at the plant boundary<\/strong>.<\/p>\n

A maintenance planner at Refinery A doesn't have easy visibility into whether the part they urgently need is sitting in the storeroom at Refinery B, 200 kilometers away. Instead, they raise an emergency purchase order — incurring premium costs, extended lead times, and unnecessary supplier dependency — for a part that already exists within their own enterprise.<\/p>\n

This isn't a logistics problem. It's a data visibility problem<\/strong>.<\/p>\n

According to McKinsey, inter-plant inventory optimization alone can reduce MRO inventory holdings by 15–25%<\/strong> in multi-site industrial operations — without impacting service levels. That's a significant working capital opportunity that most operators are leaving on the table.<\/p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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6. Inadequate Work Order Planning and Parts Readiness<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Effective maintenance execution depends on one deceptively simple prerequisite: having the right parts available when the work order is ready to execute.<\/p>\n

In practice, parts readiness is one of the most persistent bottlenecks in Oil & Gas maintenance operations<\/strong>.<\/p>\n

Planned shutdowns — turnarounds — are among the most complex logistics exercises in industrial operations. A refinery turnaround might involve thousands of work orders, tens of thousands of individual part requirements, and hundreds of contractors, all coordinated over a window of days or weeks. A single missing part can delay the restart of an entire process unit.<\/p>\n

For unplanned work orders, the problem is even more acute. When equipment fails unexpectedly, planners must rapidly identify what parts are needed, where they are, and how quickly they can be mobilized. Without accurate inventory data, BOM linkages, and supplier intelligence — all integrated into a single system — this becomes a manual, error-prone scramble.<\/p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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The Turnaround Dilemma<\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Refinery turnarounds are planned years in advance — yet parts availability failures remain one of the top causes of overruns. The average turnaround cost overrun attributable to supply chain and parts issues is estimated at 15–20% of total planned cost.<\/p>\n

The root causes are consistent: inaccurate BOMs, poor demand forecasting, fragmented inventory data across plants, and no early-warning system for stockouts on critical items.<\/p>\n

Without an integrated parts intelligence layer, turnaround planners are essentially flying blind.<\/p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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7. The Transition to Predictive Maintenance \u2014 and Why It Stalls<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Predictive Maintenance (PdM) is widely recognized as the future of Oil & Gas asset management. The promise is compelling: use real-time sensor data from SCADA and IIoT systems to predict failures before they occur, enabling maintenance to be performed at exactly the right time — not too early, not too late.<\/p>\n

The technology is increasingly mature. IIoT sensors are cheaper and more reliable than ever. Data pipelines are more accessible. And yet, PdM adoption in Oil & Gas remains lower than most operators and technology vendors would have you believe<\/strong>.<\/p>\n

The stall point is almost always the same: PdM generates predictions, but organizations aren't equipped to act on them.<\/strong><\/p>\n

A predictive model tells you that Pump P-101 is likely to fail within the next 14 days. But if your maintenance team can't quickly determine which spare parts are required, whether they're in stock, what the lead time is for the items that aren't, and how to prioritize this work order against everything else in the backlog — then the prediction doesn't prevent the failure. It just gives you slightly more warning.<\/p>\n

Predictive maintenance without integrated inventory intelligence and work order planning is an incomplete solution.<\/p><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\u00bfQu\u00e9 nos diferencia?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Ofrecemos una escalabilidad sin igual y capacidades multiling\u00fces,
probada para optimizar los procesos empresariales e impulsar mejoras en los resultados.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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