Why Warehouse IT and Operations Teams See Mobile Device Problems Differently (And Miss the Real Solution)
When a mobile scanner freezes in the middle of a pick, two very different conversations happen in most warehouses. IT sees a network connectivity issue that needs troubleshooting. Operations sees a labor productivity problem that’s costing money every minute it persists. Both departments are looking at the same incident, but they’re seeing completely different problems. This disconnect isn’t just frustrating — it’s expensive, and it’s preventing most organizations from solving their real problems when warehouse IT and Operations see mobile device problems differently.
According to Manhattan Associates’ 2024 State of Warehouse Operations survey of 2,000 supply chain professionals, almost all organizations report experiencing challenges in their warehouse operations, with the top three being out-of-date IT hardware/software, dealing with operational complexity, and issues managing orders from different channels. Yet despite this universal acknowledgment of technology problems, most warehouses continue to struggle with the same issues year after year because IT and Operations teams fundamentally see different mobile device problems when looking at the same incidents.
The Fundamental Disconnect: How Different Departments See Technology Problems
IT’s Technical Lens
When warehouse IT operations see different mobile device problems, they typically focus on technical metrics that can be measured and monitored through traditional network management tools. IT departments naturally gravitate toward:
- Network latency and bandwidth utilization: Measuring milliseconds of delay and data throughput
- Device error logs and system diagnostics: Analyzing technical fault codes and hardware status
- Infrastructure performance metrics: Monitoring access points, switches, and server response times
- Application uptime statistics: Tracking system availability percentages
This technical perspective makes perfect sense from an IT standpoint. According to research from VDC, IT departments take an average of 70 minutes to address each mobile device trouble ticket, and these device issues cause workers to lose 74 minutes of productivity. With this level of impact, IT teams need concrete data to identify and resolve problems efficiently.
Operations’ Business Impact Focus
Meanwhile, Operations teams see the same incidents through a completely different lens when warehouse IT operations see different mobile device problems. Their concerns center on:
- Lost productivity and labor costs: Calculating the dollar impact of delayed picks and extended cycle times
- Customer delivery commitments: Worrying about missed shipping windows and order accuracy
- Worker frustration and safety: Managing the human impact of technology failures
- Operational flow disruption: Understanding how one device problem cascades through the entire workflow
Research from Powerfleet shows that 50% of an order picker’s time is already spent on travel rather than productive tasks. When mobile devices fail or perform poorly, this inefficiency compounds dramatically. According to the 2024 Warehouse/DC Operations Survey, 86% of warehouses now use productivity metrics, up from 84% in 2023, indicating growing awareness of these operational impacts.
The Language Barrier
The disconnect deepens because each department uses different terminology to describe the same problems. IT might report “intermittent connectivity issues affecting 12% of devices in Zone C,” while Operations describes “pickers in the frozen section losing productivity due to scanner delays.” Both statements could be describing the exact same technical issue, but the framing creates entirely different problem-solving approaches.
This communication gap becomes particularly problematic during incident escalation. Samsung SDS research reveals that organizations lose 872 hours weekly dealing with mobile device lifecycle management issues, translating to $1.38 million annually in IT help desk support, IT security support, and lost productivity costs.
The Hidden Costs of Misaligned Problem-Solving
Financial Impact of Fragmented Approaches
When warehouse IT operations see different mobile device problems, the financial consequences extend far beyond the initial incident cost. Imprivata research found that enterprises spend an average of $5.45 million annually replacing mobile devices, plus an additional $1.4 million in ancillary costs including IT security and help desk support.
However, these direct costs pale in comparison to the productivity losses from misaligned problem-solving. Vanson Bourne research demonstrates that problems with mobile devices lead to roughly 900 hours of unplanned downtime each week, with 30% or more of revenue lost when mobile devices aren’t working properly.
The Trial-and-Error Troubleshooting Cycle
The fundamental disconnect creates expensive trial-and-error cycles. IT might spend hours optimizing network performance based on technical diagnostics, while the real problem is application-level inefficiency that only becomes apparent when measuring actual transaction completion times. Operations, meanwhile, might implement workarounds like device swapping or manual processes that mask the underlying technical issues without solving them.
Oxford Economics research indicates that it takes one full-time IT employee to manage 250 devices at an annual investment of approximately $115,000. When this management is reactive and focused on symptoms rather than root causes, organizations essentially pay premium prices for suboptimal results.
Vendor Finger-Pointing and Accountability Gaps
The disconnect between how warehouse IT operations see mobile device problems enables vendor finger-pointing that further delays resolution. Network vendors blame device manufacturers, device manufacturers point to application issues, and application vendors suggest infrastructure problems. Without a unified view of how technical issues translate to business impact, organizations struggle to hold vendors accountable for meaningful solutions.
According to research from Tangoe, 67% of enterprises use up to five separate vendors for device management and security, creating additional complexity when trying to establish accountability for performance issues.
Lost Innovation Opportunities
Perhaps most costly of all, the disconnect prevents organizations from identifying and implementing innovative solutions. When IT focuses purely on technical metrics and Operations concentrates on immediate productivity concerns, both teams miss opportunities to leverage new technologies that could eliminate entire categories of problems.
The 2024 Manhattan Associates survey found that 75% of warehouse workers are excited about generative AI possibilities and 72% about robotics to improve their job roles. However, successfully implementing these technologies requires understanding both the technical capabilities and the operational impact — exactly the type of unified perspective that most organizations currently lack.
Why Traditional IT Metrics Miss the Operational Reality
The Measurement Gap
Traditional IT monitoring tools excel at measuring what’s happening to technology systems but struggle to quantify what’s happening to business processes. A network monitoring system might show that 99.5% of transactions complete successfully within acceptable technical parameters, while simultaneously missing that the remaining 0.5% of failed transactions are concentrated in high-value picking areas during peak productivity hours.
This measurement gap becomes particularly problematic in warehouse environments where small technical delays have amplified business impacts. Research shows that personnel costs make up 56.7% of the overall warehouse cost structure, making labor productivity the most significant operational concern for most facilities.
Context-Free Technical Data
Most IT monitoring systems provide technical data without business context. They might report that Device ID 247 experienced connectivity issues at 2:47 PM, but they don’t capture that this was the third device failure for the same picker during a critical customer order fulfillment window, or that the picker had to walk 200 yards to find a replacement device.
Without this context, IT teams optimize for technical metrics that may not correlate with actual business value. A network optimization that reduces average latency by 15% might seem successful from a technical standpoint, but could be meaningless if it doesn’t address the specific types of delays that impact picking productivity.
Reactive vs. Proactive Insights
Traditional IT metrics are inherently reactive, reporting what happened rather than predicting what will happen. Warehouse operations, however, need proactive insights to maintain consistent productivity. According to the 2024 warehouse automation statistics from G2, 89% of organizations will be using modernized Warehouse Management Systems functionality for labor planning and management, indicating the growing need for predictive rather than reactive management.
Single-Point-in-Time Analysis
Most IT monitoring tools capture single points in time rather than understanding patterns and trends that affect operational outcomes. A device might show normal performance during most IT monitoring intervals while experiencing brief but critical delays during specific operational scenarios, such as when multiple devices in the same zone simultaneously access the warehouse management system during shift changes.
Bridging the Gap: Creating a Unified View of Mobile User Performance
Integrated Monitoring Approaches
The solution to the problem of how warehouse IT operations see different mobile device problems lies in creating monitoring systems that capture both technical performance and business impact simultaneously. This requires tools that can correlate device-level data with operational outcomes, providing insights that make sense to both IT and Operations teams.
Modern warehouse intelligence platforms are beginning to address this need by combining traditional IT monitoring with operational metrics. These systems can show not just that a device experienced connectivity issues, but also that those issues resulted in a 12% decrease in picking productivity during the affected time period.
Business-Impact Translation
Effective solutions translate technical metrics into business language that Operations teams can understand and act upon. Instead of reporting “average response time of 847 milliseconds,” these systems might report “mobile delays cost 23 minutes of picker productivity in Zone B today.”
This translation enables both teams to understand the true priority of different technical issues. A network problem affecting administrative areas might have lower business impact than a device performance issue in high-volume picking zones, even if the network problem appears more severe from a purely technical standpoint.
Shared Accountability Frameworks
Successfully bridging the gap requires establishing shared accountability frameworks where both IT and Operations teams are measured on common outcomes. This might include metrics like “total cost per picked item” that factor in both technical performance and operational efficiency, or “order fulfillment accuracy” that reflects both system reliability and process effectiveness.
Research from the logistics industry shows that organizations with aligned IT and Operations teams achieve significantly better outcomes in both technology adoption and operational performance, suggesting that the investment in bridging this gap delivers measurable returns.
Predictive Intelligence and Proactive Management
The most advanced solutions provide predictive intelligence that helps both teams address problems before they impact operations. By analyzing patterns in both technical data and operational outcomes, these systems can identify scenarios likely to cause productivity disruptions and enable proactive interventions.
For example, a system might detect that certain device performance patterns correlate with increased picking errors during peak hours, enabling teams to proactively address device issues or adjust operational procedures to minimize impact.
The Path Forward: Mobile Performance Assessment
The disconnect between how warehouse IT operations see different mobile device problems won’t resolve itself through better communication or goodwill alone. It requires systematic assessment of current technology performance from both technical and operational perspectives, followed by implementation of integrated monitoring and management approaches.
Organizations serious about addressing this challenge need to start with a comprehensive Mobile Performance Assessment that evaluates their current state from both IT and Operations viewpoints. This assessment should identify where technical issues are causing operational problems, quantify the business impact of different types of device issues, and establish baseline measurements for improvement initiatives.
The goal isn’t to eliminate all technical problems — that’s neither realistic nor necessary. Instead, the objective is to ensure that IT and Operations teams are solving the same problems and measuring success using metrics that matter to the business. When both teams can see that improving mobile transaction response times by 200 milliseconds translates to 15% better picking productivity during peak hours, they’re much more likely to collaborate effectively on solutions.
Only by creating this unified view can organizations move beyond the expensive cycle of reactive troubleshooting and vendor finger-pointing that characterizes most current approaches to warehouse technology management. The technology exists to bridge this gap — what’s needed is the organizational commitment to implement integrated approaches that serve both technical and operational requirements.
Ready to discover what your warehouse IT operations see different mobile device problems are really costing your organization? Take our Free Mobile Performance Assessment to identify the gaps between your technical performance and operational outcomes, and develop a roadmap for creating the unified visibility both your IT and Operations teams need to succeed.
Sources
- Manhattan Associates. “State of Warehouse Operations 2024.” June 20, 2024. https://www.manh.com/our-insights/resources/research-reports/state-of-warehouse-operations-2024
- Honeywell. “What Industrial Organizations Need From Mobile Computing Platforms.” 2024. https://www.honeywell.com/us/en/news/featured-stories/2024/04/what-industrial-organizations-need-from-mobile-computing-platforms
- Samsung SDS. “Hidden Costs of Poor Enterprise Device Management.” December 11, 2024. https://www.samsungsds.com/us/blog/hidden-costs-poor-enterprise-mobile-device-management.html
- Imprivata. Referenced in Samsung SDS research on enterprise mobile device costs. 2024.
- Logistics Management. “2024 Warehouse/DC Operations Survey: Technology adoption on the rise.” 2024. https://www.logisticsmgmt.com/article/2024_warehouse_dc_operations_survey_technology_adoption_on_the_rise
- Powerfleet. “How to Increase Warehouse Productivity and Efficiency in 2025.” https://blog.fleetcomplete.com/how-to-increase-warehouse-productivity-and-efficiency-in-2025/
- Transloads.co. “100 Warehouse Management & Automation Statistics to Guide Your Operations in 2024.” October 22, 2024. https://transloads.co/warehouse-management-statistics/
- Contimod. “20+ Warehouse Industry Statistics: A Must Know in 2024.” October 22, 2024. https://www.contimod.com/warehouse-industry-statistics/
- G2. “50+ Warehouse Automation Statistics to Streamline Operations.” March 6, 2024. https://www.g2.com/articles/warehouse-automation-statistics
- Oxford Economics. “Maximizing Mobile Value study.” 2022. Referenced in Samsung research.
- Vanson Bourne. Referenced in Tangoe research on enterprise mobility management costs.
- Tangoe. “What is Enterprise Mobility Management?” January 16, 2025. https://www.tangoe.com/guides/what-is-enterprise-mobility-management/
