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Seven pitfalls MSPs should avoid when building a resilient IT organization
Managed service providers (MSPs) are always on high alert to avoid system outages. The CrowdStrike outage in July 2024 amped up that anxiety, testing many MSPs to the hilt. Successful channel players were the ones that could quickly identify failed systems, assess repercussions, and move fast to the recovery stage.
Backups and business continuity plans were activated on an unprecedented scale, emphasizing the critical importance of IT resilience to sustain operations amid failed updates, network outages, or cyber attacks.
Clearly, MSPs need to be more ready than ever to support resilient IT infrastructures. Merely recovering from outages is no longer sufficient; a forward-thinking, proactive IT approach is essential to prevent disruptions and ensure uninterrupted business operations. Against this backdrop, here are seven key mistakes to avoid when building a resilient IT strategy.
1. Waiting for things to happen instead of shifting your mindset to proactivity
Traditionally, IT monitoring and support has been a reactive process, addressing incidents post failure. But, in the face of complex digital transformation efforts and the surge of cyber threats, a reactive approach is no longer sufficient.
By moving away from a ‘break-fix’ model, particularly when it takes the form of ticket-by-ticket problem resolution, and embracing proactive monitoring, MSPs can identify and address potential issues before they escalate.
Many MSPs have recognized the value of a proactive approach and are partnering with digital experience monitoring and management vendors that gather data from a wide range of endpoints to arm them with the visibility they need to see around the corner.
According to Lakeside Software’s recent IT Resilience white paper, a proactive model helps MSPs cut costs, reduce downtime, and boost productivity by resolving potential issues before they impact end-users. For example, a proactive IT approach enabled a U.S.-based healthcare organisation to avoid nearly 270,000 service tickets, resulting in a significant cost saving of £6.84 million. MSPs can adopt this same approach for their clients to identify issues before they escalate.
2. Lacking anticipation and not using predictive IT to detect issues early
It’s worth repeating that traditional, reactive approaches simply do not work for IT environments on the verge of a widespread problem – one that could take down the entire IT estate and disrupt business continuity.
Fortunately, with the rise of machine learning (ML) and data-driven decision-making, proactive IT can mature to the point of being predictive. Rather than relying on predefined thresholds, anomaly detection identifies deviations in system performance, enabling IT teams to address problems before they impact the broader infrastructure.
This predictive IT approach gives tech teams the early-stage visibility they need to detect estate-wide trends and, in turn, contain a pending outbreak before an IT outage occurs. Using machine learning algorithms on robust data sets, AI can detect patterns that human analysts might miss, especially when faced with vast data environments.
For example, a gradual degradation in system performance could point to an impending hardware failure, or specific user behaviours might signal potential security threats. With real-time anomaly detection, AI provides IT teams with timely insights to take preventive measures before minor issues escalate into major disruptions.
One UK-based global law firm used this approach successfully. Thanks to ML-based anomaly detection, its IT team identified three sensors that impacted 800 machines – nearly 10% of the firm’s devices. The root cause was traced to a common video driver, which the team resolved before it affected the entire organization. This proactive intervention not only minimised disruptions but also exemplifies how predictive insights can protect business continuity.
3. Under using automation to streamline IT support
Automations can help MSPs build resilient systems that are less vulnerable to human error, minimizing response times and allowing faster recovery. Equipping lower-level support teams with automation tools and AI-powered diagnostics allows MSPs to streamline support processes and enhance efficiency.
AI-driven data management solutions help to detect deviations in device usage, application performance and network health, providing deeper insights into IT infrastructure and enabling IT support teams to resolve common issues, accelerating incident resolution, and reducing operational costs.
MSPs are still cautious about using AI, however, and should be even more so if they are not checking data quality. Poor-quality data can lead to inaccuracies, damaging trust in the reliability and utility of AI systems, and compromising outputs, which rely on meaningful patterns to provide relevant and explainable insights.
Tools that can automate remediation tasks, trigger alerts, and provide AI-driven insights assist MSPs in their management of complex IT environments without overextending their resources. In one notable case, an insurance provider achieved a £780,000 return on investment by enabling 45 automation scripts, reducing service tickets by 29% and mean time to repair by 40%. Automation scripts also minimize the human effort required for routine tasks, allowing MSPs to optimize their service delivery models while reducing operational costs.
But automation isn’t just about technology; it requires investment in training and upskilling IT staff. Level 1 engineers should be trained on how to manage these automations effectively, troubleshoot when needed, and understand the underlying systems well enough to recognize when a manual intervention is required. This level of empowerment will be critical for IT teams to succeed in a proactive operating environment.
4. Overlooking data quality, leading to hampered recovery efforts
As organizations progress towards proactive, predictive and one day fully autonomous IT, prioritizing high-quality data becomes essential. Without high-quality data, businesses risk flawed decisions that can hurt the bottom line, making data integrity vital for efficient operations and regulatory compliance. MSPs must prioritize data accuracy, consistency, and security, regularly auditing and cleaning data to spare customers the pitfalls of poor-quality data.
Reliable data is accurate, complete, well-organized, from trusted sources, and updated frequently to remain relevant. The stronger the data, the more effective the AI which will power self-healing systems of the future – since data quality directly influences the reliability, explainability, and trustworthiness of AI-driven insights and outputs.
5. Staying in the dark about what’s happening across the full IT estate
IT resilience is not only about preventing incidents but also about enabling swift recovery when disruptions occur, which requires comprehensive visibility across the IT estate. By gathering and interpreting insights into client systems, MSPs and IT teams can develop thorough incident response plans and prioritize data-driven recovery to minimize downtime and monitor the impact of outages and track recovery progress.
In large-scale IT disruptions, access to detailed data across an entire IT estate is essential for prioritizing recovery and swiftly restoring mission-critical services. For example, during the CrowdStrike outage, teams using digital experience platforms could assess affected devices, prioritize critical systems, and monitor remediation at scale, facilitating faster client recovery.
The effectiveness of IT recovery depends on the IT team’s ability to accurately assess events within the enterprise environment. Resilient IT requires visibility at all stages during an incident. Actionable insights help to address incidents effectively, making complete visibility across the IT estate indispensable with a granular view covering user activity, application performance, and device health. This detailed information is critical during an IT outage or cyber incident; for instance, in a network outage or ransomware attack, understanding which users and systems are affected enables the prioritization of recovery efforts and helps reduce downtime.
6. Not finding ways to simplify IT infrastructure especially in transformation projects
Resilience in IT infrastructure becomes harder to achieve as complexity increases, particularly during transformation projects. IT leaders face the challenge of maintaining performance and reliability across intricate, interdependent systems without inflating costs. A 2024 IT Leaders’ Survey found that 65% of respondents prioritized ‘doing more with less’, making efficient infrastructure management critical.
To build resilience, MSPs should focus on simplifying and streamlining both hardware and software environments. Regular audits of software licences and hardware usage help identify redundancies, extend device lifecycles, and reduce unnecessary layers of complexity. For example, a U.S.-based bank identified £3.34 million in savings by cutting unused software licences and shifting to a condition-based hardware refresh strategy, enhancing both budget efficiency and system manageability.
As the demand for high-performance computing grows, with advances such as TOPS (Trillions of Operations Per Second) enabling unprecedented levels of data processing, channel players must anticipate and address the strain that increasing complexity places on resilience. Integrating data monitoring and management across systems enables IT teams to maintain control and visibility, critical for responding to future disruptions effectively.
7. Underestimating impact of digital employee experience on IT resilience
A positive digital employee experience (DEX) is essential for supporting resilience, as it has a direct impact on productivity, retention, and employee satisfaction. DEX isn’t just about providing functional tools but ensuring they’re user-friendly, reliable, and reduce downtime. In fact, Unisys reports that 49% of employees lose one to five hours each week due to IT issues, costing employers over £3,000 per employee in lost productivity. By minimizing these disruptions, MSPs using DEX platforms can help channel customers boost productivity and reduce costly downtime.
DEX platforms offer valuable insights into how technology affects day-to-day work by monitoring application performance, device boot times, and other metrics. For MSPs, using these platforms to identify and resolve friction points enables faster recovery from disruptions and reduces downtime, directly contributing to resilience. Reducing tech-related frustrations not only boosts employee morale and engagement but also ensures a more stable and resilient IT environment for clients.
The path to long-term IT resilience
To minimize downtime and safeguard clients, MSPs are increasingly adopting proactive IT and security measures, using autonomous technologies to streamline operations, detect issues early, and respond swiftly. By embracing proactive management, automation, predictive analytics, AI insights, and (DEX) platforms, MSPs reduce friction, simplify infrastructure, and optimize resources, helping clients maintain stability and continuity amid disruptions.
They not only boost client resilience but also enhance their own reputations for reliability and strategic insight, strengthening any competitive position and delivering value in a dynamic IT landscape.