Poor network investment and operations decisions from lack of accurate schedule‑based analytics
Definition
Vendors emphasize that integrated scheduling suites enable better operational and financial evaluation of new or modified assets, indicating that prior to such tools, companies struggle to accurately assess capacity, bottlenecks, and cost impacts of changes.[3] Academic models similarly show that detailed scheduling is needed to understand true pumping, inventory, and interface costs across a pipeline network.[4][6]
Key Findings
- Financial Impact: Misjudging true bottlenecks can lead to misallocated capital—e.g., a $50–200M pipeline looping or tank project built in the wrong place, or under‑investment where it is truly needed—and to ongoing operating costs from failing to address real constraints; even one such misinvestment can create tens of millions of dollars in value destruction over its life.
- Frequency: Annually
- Root Cause: Incomplete or poor‑quality scheduling data and limited scenario modeling capabilities cause management to rely on averages and heuristics rather than detailed network simulations when deciding on expansions, debottlenecking projects, or contract structures.[3][4][6]
Why This Matters
This pain point represents a significant opportunity for B2B solutions targeting Oil and Coal Product Manufacturing.
Affected Stakeholders
Midstream asset planners, Capital projects and strategy teams, Pipeline and terminal optimization groups, Executive leadership and board members
Deep Analysis (Premium)
Financial Impact
$10-30M in contract penalties for service failures; $5-20M in lost new business due to inability to demonstrate reliable capacity • $10-30M in lost aviation fuel contracts; $5-15M in contract penalties if capacity assumptions were wrong • $10-30M in lost contract opportunities due to inability to demonstrate capacity; $5-15M in competitive bids lost to competitors with better visibility
Current Workarounds
Annual gut-feel projections; informal usage tracking; historical 'peak day' assumptions; PowerPoint presentations based on anecdotes; email back-and-forth with finance on capacity needs • Combination of terminal operator phone coordination, manual Gantt charts in Excel, WhatsApp group for last-minute changes, memory-based tracking of queue positions • Daily coordination calls with terminal; manual inventory spreadsheets; contingency plans for 'when supply gets tight'; reliance on fuel supplier relationships for advance notice
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Methodology & Sources
Data collected via OSINT from regulatory filings, industry audits, and verified case studies.
Related Business Risks
Sub‑optimal pipeline and terminal schedules causing lost throughput and revenue
Excess pumping energy, drag‑reducing agent, and operating costs from inefficient schedules
Product contamination and interface reprocessing due to poor batch sequencing
Delayed billing and revenue recognition from fragmented scheduling and accounting data
Idle pipeline and tank capacity from manual, non‑optimal scheduling
Regulatory non‑compliance exposure from inadequate scheduling visibility and reconciliation
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