From 50% to 85% Engineer Utilization: Workflow Rules That Actually Work for MSPs

Discover practical workflow automation rules, overcome team resistance, and measure ROI to boost MSP engineer utilization from 50% to 85%. Essential strategies for IT leaders.

From 50% to 85% Engineer Utilization: Workflow Rules That Actually Work

In the competitive landscape of Managed Service Providers (MSPs), engineer utilization stands as a critical barometer of operational efficiency and profitability. Many MSPs grapple with utilization rates hovering around 50-60%, a figure that often signals significant untapped potential and, more critically, lost revenue. This article delves into actionable strategies and workflow rules designed to elevate engineer utilization to an optimal 80-85%, transforming your operational model and proving a tangible return on investment (ROI).

We will explore the common pitfalls leading to low utilization, present practical automation frameworks, discuss how to navigate and overcome team resistance, and highlight the key metrics that demonstrate success. Furthermore, we will examine essential tools and frameworks that empower MSPs to achieve these ambitious targets, ensuring your team is focused on high-value, impactful work rather than being bogged down by repetitive tasks. This journey from inefficiency to peak performance is not merely about working harder; it’s about working smarter, leveraging intelligent automation and strategic workflow optimization.

The Utilization Conundrum: Why 50% Isn’t Enough (and 85% is Just Right)

Engineer utilization, often defined as the percentage of an engineer’s time spent on billable or directly productive tasks, is a cornerstone metric for MSPs. A rate of 50% or lower is a red flag, indicative of systemic inefficiencies. This often stems from what can be termed as “administrative drag” – excessive time spent on manual ticket entry, inadequate documentation, constant context switching between disparate systems, and a general lack of streamlined processes. These non-billable activities, while necessary, consume valuable engineering hours that could otherwise be dedicated to client projects, proactive maintenance, or strategic initiatives.

Conversely, aiming for 100% utilization is not only unrealistic but also detrimental. Engineers need time for professional development, training, internal projects, and, crucially, a healthy work-life balance to prevent burnout. Industry benchmarks suggest that an optimal utilization rate typically falls between 80% and 85% [1]. This “Goldilocks Zone” strikes a balance: it maximizes productivity and profitability while allowing for essential non-billable activities like skill enhancement, strategic planning, and necessary downtime. Exceeding 85% often leads to reduced quality of work, decreased employee satisfaction, and high turnover rates, ultimately undermining long-term success [2]. Below 75%, MSPs risk significant profitability losses, struggling to cover overheads and invest in growth [3].

Key Challenges Impeding High Utilization

Several factors contribute to suboptimal engineer utilization within MSP environments:

• Manual, Repetitive Tasks: A significant portion of an engineer’s day can be consumed by routine tasks such as password resets, user provisioning, basic troubleshooting, and report generation that could easily be automated.
• Lack of Standardization: Inconsistent processes for common requests lead to engineers reinventing the wheel, increasing resolution times and reducing efficiency.
• Poor Documentation: The absence of comprehensive, easily accessible documentation forces engineers to spend time researching solutions or consulting colleagues, rather than resolving issues directly.
• Context Switching: Juggling multiple client environments, tools, and urgent requests without proper prioritization or automation leads to mental fatigue and reduced productivity.
• Reactive vs. Proactive: A predominantly reactive service model means engineers are constantly fighting fires, leaving little room for proactive maintenance or strategic improvements that could prevent future issues.
• Tool Sprawl and Integration Gaps: Using numerous disconnected tools for PSA, RMM, and other functions creates data silos and manual data transfer, wasting time and increasing errors.

Addressing these challenges systematically through well-defined workflow rules and automation is paramount to elevating engineer utilization and, by extension, the MSP’s overall profitability and service quality.

The Automation Imperative: Workflow Rules That Deliver

Achieving an 80-85% utilization rate requires a fundamental shift from manual, reactive operations to a proactive, automation-first mindset. This involves implementing specific workflow rules that systematically eliminate administrative drag and empower engineers to focus on higher-value tasks. Here are practical strategies and implementation steps:

1. The “50% Automation Rule” (Inspired by SRE Principles)

Drawing inspiration from Site Reliability Engineering (SRE) principles, a powerful workflow rule is to dedicate a significant portion of engineering time—say, 50% of non-billable hours—to automating away the largest ticket-causing issues [4]. This isn’t about reducing billable time but optimizing the non-billable segment. Instead of merely resolving recurring problems, engineers are tasked with building automated solutions to prevent them. This rule fosters a culture of continuous improvement and proactive problem-solving.

Implementation Steps:

• Identify Top Pain Points: Analyze ticket data to pinpoint the most frequent, time-consuming, and repetitive issues. These are prime candidates for automation.
• Allocate Dedicated Time: Explicitly schedule time for automation development. This ensures it doesn’t get sidelined by urgent client requests.
• Empower Engineers: Provide training and tools (e.g., scripting languages like PowerShell or Python, low-code automation platforms) to enable engineers to build their own automations.
• Measure Impact: Track the reduction in ticket volume or resolution time for automated tasks to demonstrate the ROI of this effort.

2. Standardized and Automated Onboarding/Offboarding

User lifecycle management—onboarding new employees and offboarding departing ones—is notoriously time-consuming and prone to errors when handled manually. Automating these processes can free up significant engineering hours.

Implementation Steps:

• Define Clear Workflows: Map out every step involved in onboarding (e.g., account creation, software provisioning, access rights, email setup) and offboarding (e.g., account deactivation, data archiving, license revocation).
• Leverage Identity and Access Management (IAM) Tools: Integrate with Microsoft 365, Azure AD, or other IAM solutions to automate user creation, group assignments, and license allocation.
• Script Common Tasks: Use PowerShell scripts or automation platforms to provision software, set up VPN access, and configure security settings automatically.
• Create Self-Service Options: For simple tasks like initial password setup, empower new users with guided self-service portals.

3. Intelligent Ticket Categorization and Routing

Manual triage of incoming support tickets is a major time sink and a source of delays. Implementing intelligent categorization and routing ensures tickets reach the right engineer with the necessary context, faster.

Implementation Steps:

• Utilize PSA Automation Rules: Configure your Professional Services Automation (PSA) system (e.g., HaloPSA, ConnectWise) with rules to automatically categorize tickets based on keywords, sender, or subject line.
• Implement AI-Powered Triage: Explore AI-driven solutions like Pia that can analyze ticket content, assign priority, and route to the appropriate team or individual, often with pre-filled diagnostic information.
• Standardize Ticket Templates: Encourage clients and internal teams to use structured forms for submitting requests, making it easier for automation engines to interpret and process.

4. Empowering Self-Service with Automated Solutions

Many common support requests (e.g., password resets, software installation requests, access to shared drives) can be resolved by end-users themselves if provided with the right tools. This significantly reduces the L1 support burden.

Implementation Steps:

• Develop a Knowledge Base: Create a comprehensive, easy-to-search knowledge base with step-by-step guides for common issues.
• Implement Self-Service Portals: Deploy portals where users can initiate password resets, request software from an approved catalog, or troubleshoot basic connectivity issues.
• Automate Backend Fulfillment: Ensure that requests made through self-service portals trigger automated workflows on the backend (e.g., a software request automatically deploys the application via RMM).
• Measure Reduction in L1 Tickets: Track the number of tickets deflected by self-service options to quantify the time savings for engineers.

5. Proactive Infrastructure Governance and Auditing

Manual audits of cloud environments, license usage, and security configurations are time-consuming and often reactive. Automating these governance tasks ensures continuous compliance and cost optimization, preventing issues before they escalate.

Implementation Steps:

• Automated Cloud Spend Monitoring: Implement tools that continuously monitor Azure, AWS, or Google Cloud spend, flagging anomalies and identifying underutilized resources.
• License Management Automation: Use scripts or dedicated tools to track software license usage, ensuring compliance and optimizing costs by reallocating unused licenses.
• Security Configuration Audits: Automate checks against security baselines and compliance frameworks, identifying misconfigurations or vulnerabilities in real-time.
• Leverage Specialized Services: For complex infrastructure governance, consider partnering with specialists like 13th Octet (https://13thoctet.com/). Their expertise in independent infrastructure governance, cloud architecture, and disciplined managed services can help identify gaps and “stop the rot” before it costs you, ensuring your IT assets are robust and secure.

Overcoming Team Resistance: A Human-Centric Approach to Automation

Implementing automation is not just a technological challenge; it’s a cultural one. Engineers, like any professionals, can be resistant to change, especially when it involves altering established routines or perceived threats to their roles. Overcoming this resistance is crucial for successful adoption and requires a human-centric approach.

Common Reasons for Resistance:

• Fear of Job Displacement: The most prevalent concern is that automation will render their skills obsolete or lead to job losses.
• Loss of Control/Autonomy: Engineers may feel that automated systems reduce their control over problem-solving or decision-making.
• Increased Workload (Initial Phase): The effort required to learn new tools, build automations, and adapt to new workflows can initially feel like an added burden.
• Skepticism about Effectiveness: Past negative experiences with poorly implemented tools or processes can lead to distrust in new automation initiatives.
• Lack of Involvement: Engineers who are not consulted or involved in the automation strategy may feel disenfranchised.

Strategies to Overcome Resistance:

1. Communicate Vision and Benefits Clearly: Articulate that automation is not about replacing engineers but about “eliminating the boring stuff” [5]. Emphasize that it frees them to focus on more complex, strategic, and intellectually stimulating work—architecture, advanced troubleshooting, client advisory, and innovation. Highlight how it reduces burnout and improves job satisfaction.
2. Start with “Quick Wins” and Small Iterations: Don’t attempt a massive, disruptive overhaul. Begin by automating small, highly repetitive tasks that engineers universally dislike. Demonstrating immediate, tangible benefits builds trust and enthusiasm for larger initiatives.
3. Involve Engineers in the Process: Empower engineers to identify automation opportunities and even build the solutions themselves. This fosters ownership and leverages their intimate knowledge of existing workflows. Create an “automation champion” program.
4. Provide Comprehensive Training and Support: Invest in training on new tools and methodologies. Ensure there’s readily available support and resources for engineers as they adapt to automated workflows.
5. Incentivize and Reward Automation Efforts: Recognize and reward engineers who successfully implement automations that save the team time or improve efficiency. This can be through bonuses, public recognition, or career advancement opportunities.
6. Address Concerns Transparently: Create open channels for feedback and address fears or skepticism directly and honestly. Be prepared to adjust strategies based on engineer input.

By framing automation as an enabler for professional growth and a means to enhance job quality, MSP leaders can transform resistance into enthusiastic adoption, turning engineers into automation advocates.

Proving the ROI: Metrics That Matter

Demonstrating the return on investment (ROI) of automation initiatives is crucial for securing buy-in and continued investment. Beyond just anecdotal improvements, MSPs need concrete metrics to prove that workflow rules are effectively boosting engineer utilization and profitability. Here are key metrics and how to measure them:

1. Engineer Utilization Rate

This is the primary metric. Track the percentage of time engineers spend on billable or directly productive tasks versus total available hours. The goal is to move from 50% to 80-85%.

• Measurement: `(Billable Hours + Productive Non-Billable Hours) / Total Available Hours`
• Impact of Automation: Automation reduces the “productive non-billable” component by shifting repetitive tasks to machines, allowing more time for billable work or higher-value non-billable activities like R&D.

2. Time Savings (Hours per Week/Month)

Quantify the hours saved by automating specific tasks. This is a direct measure of efficiency gains.

• Measurement: Compare the average time taken for a task before automation versus after. Multiply by the frequency of the task.
• Example: If automated password resets save 5 minutes per incident and there are 100 such incidents per month, that’s `500 minutes (approx. 8.3 hours)` saved.

3. Cost Savings

Translate time savings into monetary value by multiplying saved hours by the average hourly cost of an engineer.

• Measurement: `Total Hours Saved * Average Hourly Engineer Cost`
• Example: If 8.3 hours are saved per month at an average engineer cost of $50/hour, that’s `$415` saved monthly from just one automation.

4. Increased Productivity

Measure the increase in the number of tasks completed or clients served per engineer without increasing headcount.

• Measurement: `(Tasks Completed After Automation – Tasks Completed Before Automation) / Tasks Completed Before Automation`
• Impact of Automation: Engineers can handle more tickets, manage more client environments, or take on more complex projects within the same timeframe.

5. Revenue Growth (Capacity Expansion)

Automation allows MSPs to scale without proportionally increasing operational costs. This means the ability to take on more clients or offer new services with existing staff.

• Measurement: Track the increase in client count or service offerings directly attributable to freed-up engineer capacity.
• Impact of Automation: By increasing utilization, MSPs can grow their client base by 10-20% without needing to hire additional engineers, directly impacting the bottom line.

6. Employee Satisfaction and Retention

While harder to quantify directly in monetary terms, reduced burnout and increased engagement from meaningful work have a significant long-term ROI.

• Measurement: Employee surveys, turnover rates, and qualitative feedback.
• Impact of Automation: Engineers are happier when they are not performing mundane tasks, leading to higher morale, better service quality, and reduced recruitment costs.

7. Service Level Agreement (SLA) Compliance and Resolution Times

Automated workflows can significantly improve response and resolution times, leading to higher client satisfaction.

• Measurement: Track average response times, resolution times, and SLA adherence rates before and after automation.
• Impact of Automation: Automated triage and self-service options ensure faster initial responses and quicker resolution of common issues.

By meticulously tracking these metrics, MSPs can build a compelling case for automation, demonstrating clear financial and operational benefits that justify the initial investment and effort.

Key Tools, Vendors, and Frameworks for MSP Automation

The right toolkit is essential for successful workflow automation. The MSP ecosystem offers a variety of solutions, each with its strengths. Here’s a review of key categories and specific vendors:

1. Professional Services Automation (PSA) Platforms

PSAs are the central nervous system of an MSP, managing client relationships, ticketing, projects, and billing. Modern PSAs offer robust automation capabilities.

• HaloPSA: Increasingly popular for its modern interface, high customizability, and powerful native automation features. Many MSPs are migrating to HaloPSA for its advanced workflow capabilities and superior user experience compared to older systems [6]. It excels in service board management and ticket workflows.
• ConnectWise Manage: A long-standing industry leader, ConnectWise offers comprehensive features but can be complex to configure and less intuitive for some users. Its strength lies in its extensive ecosystem and deep integrations.
• Autotask PSA: Another established player, offering strong project management and billing functionalities, with a focus on streamlining operational processes.

Comparison Table: PSA Platforms

2. Automation and Hyperautomation Platforms

These tools go beyond basic PSA automation, enabling complex, cross-platform workflows and leveraging AI.

• Rewst: A low-code Robotic Process Automation (RPA) platform specifically designed for MSPs. Rewst allows MSPs to build sophisticated workflows without extensive coding, integrating with various PSA, RMM, and other tools. It’s praised for its ability to automate end-to-end processes like user onboarding/offboarding, automated reporting, and proactive maintenance tasks [7]. Rewst focuses on empowering MSPs to build custom automations quickly.
• Pia: An AI-powered service delivery platform that focuses on automating help desk operations. Pia offers pre-built automations and deep PSA integrations, providing fast time-to-value. It excels in intelligent ticket triage, automated responses, and resolving common issues using AI, significantly reducing the burden on L1 support [8]. Pia aims to bring hyperautomation to MSPs with its AI capabilities.

Comparison Table: Automation Platforms

3. Remote Monitoring and Management (RMM) Tools

RMMs are critical for automating device management, patching, and proactive alerts. While not directly utilization tools, their automation capabilities free up engineer time.

• ConnectWise Automate (formerly LabTech): A powerful RMM with deep scripting and automation capabilities, allowing for extensive customization.
• Datto RMM: Known for its ease of use and robust feature set, including scripting, patch management, and remote access.
• NinjaOne (formerly NinjaRMM): A cloud-native RMM praised for its intuitive interface and strong automation features, particularly for endpoint management.

4. Infrastructure Governance and Security Platforms

These tools and services ensure that IT environments are secure, compliant, and cost-optimized, often through automated auditing and policy enforcement.

• Cloud Native Tools: Azure Policy, AWS Config, Google Cloud Security Command Center for automated compliance checks and policy enforcement.
• Specialized Governance Services: For independent oversight and expert-driven architecture, services like 13th Octet provide critical value. They offer risk reviews, cloud security frameworks, and disciplined managed services, ensuring that IT infrastructure is robust and secure, preventing costly failures before they occur. Their focus on governance and architecture helps MSPs and their clients maintain a “gold standard” environment.

Case Study / Example: Automating User Onboarding for a Mid-Sized MSP

Consider a hypothetical mid-sized MSP, “TechSolutions,” struggling with a 55% engineer utilization rate. A significant portion of their engineers’ time (approximately 15 hours per week per engineer) was spent on manual user onboarding and offboarding tasks across various client environments. This included creating user accounts in Active Directory/Azure AD, provisioning Microsoft 365 licenses, setting up email, granting access to shared drives, and deploying standard software packages.

The Problem: Each new user onboarding took an average of 2 hours of an engineer’s time, and TechSolutions onboarded roughly 20 new users per month across their client base. This amounted to 40 hours per month dedicated solely to this repetitive task.

The Solution: TechSolutions decided to implement an automated user onboarding workflow using Rewst integrated with their HaloPSA and Microsoft 365/Azure AD. The new workflow involved:

1. HaloPSA Ticket Trigger: A new client onboarding request in HaloPSA automatically triggered the Rewst workflow.
2. Data Collection: Rewst prompted for necessary user details (name, department, roles) via a standardized form.
3. Azure AD/M365 Automation: Rewst automatically created the user account in Azure AD, assigned the appropriate Microsoft 365 license, and added the user to relevant security groups.
4. Software Provisioning: Through integration with their RMM, Rewst initiated the deployment of standard software packages to the user’s workstation.
5. Communication: Automated emails were sent to the new user with login credentials and to the client manager confirming completion.

Metrics That Proved ROI:

• Time Savings: The automated process reduced onboarding time from 2 hours to approximately 15 minutes per user. For 20 users per month, this saved `(2 hours – 0.25 hours) * 20 users = 35 hours per month`.
• Cost Savings: At an average engineer cost of $60/hour, this translated to `$2,100` in direct cost savings per month from this single automation.
• Increased Utilization: The 35 hours saved were reallocated to proactive maintenance and strategic client projects, contributing to a 5% increase in overall engineer utilization within the first three months.
• Reduced Errors: Automation virtually eliminated human errors in provisioning, leading to fewer follow-up tickets and improved client satisfaction.
• Faster Client Onboarding: TechSolutions could onboard new client employees significantly faster, enhancing their service delivery reputation.

This case study exemplifies how targeted automation, even for a single workflow, can yield substantial ROI and directly contribute to higher engineer utilization, moving TechSolutions closer to the 85% target.

Future Outlook: Evolving Trends, Risks, and Opportunities

The journey towards optimized engineer utilization is continuous, shaped by evolving technological landscapes and client demands. MSPs must remain agile and forward-thinking to capitalize on emerging opportunities and mitigate risks.

Evolving Trends:

• Hyperautomation: The convergence of RPA, AI, Machine Learning (ML), and process mining will enable even more sophisticated and intelligent automation, moving beyond simple task automation to end-to-end process orchestration.
• AI-Powered Predictive Maintenance: AI will increasingly predict potential issues before they occur, allowing for automated proactive remediation and further reducing reactive support tickets.
• “Everything as Code” (EaC): Infrastructure, configurations, and even security policies will be defined and managed as code, enabling greater automation, version control, and consistency.
• Enhanced Cybersecurity Automation: Automated threat detection, incident response, and compliance reporting will become standard, freeing cybersecurity experts from manual analysis.

Risks to Consider:

• “Automation Debt”: Poorly designed or undocumented automations can become technical debt, requiring significant effort to maintain or update.
• Over-Automation: Automating processes that are too complex, rarely occur, or require significant human judgment can lead to more problems than it solves.
• Security Vulnerabilities: Automated systems, if not properly secured, can become new attack vectors. Robust security practices must be integrated into every automation.
• Skill Gap: The need for engineers with automation development skills (e.g., scripting, API integration, low-code platforms) will intensify, requiring continuous training and upskilling.

Opportunities for Growth:

• New Service Offerings: Freed-up engineer capacity allows MSPs to develop and offer advanced services like vCIO consulting, specialized cybersecurity services, or cloud architecture design.
• Competitive Differentiation: MSPs with highly efficient, automated operations can offer superior service quality and faster response times, gaining a significant competitive edge.
• Scalability: Automation provides the foundation for scalable growth, enabling MSPs to expand their client base without a linear increase in operational costs.
• Talent Attraction and Retention: A forward-thinking, automation-driven culture is attractive to top engineering talent, helping MSPs recruit and retain skilled professionals.

By embracing these trends and proactively addressing risks, MSPs can not only achieve optimal engineer utilization but also position themselves as leaders in the evolving IT services landscape.

Conclusion: The Path to a More Productive Future

The journey from 50% to 85% engineer utilization is not a distant dream but an achievable reality for MSPs willing to embrace strategic workflow automation. It demands a commitment to identifying and eliminating administrative drag, empowering engineers with the right tools, and fostering a culture that values proactive problem-solving over reactive firefighting.

By implementing workflow rules such as the “50% Automation Rule,” standardizing onboarding, leveraging intelligent ticket management, and promoting self-service, MSPs can unlock significant efficiencies. Overcoming team resistance requires clear communication, involvement, and demonstrating the tangible benefits of automation—not as a threat, but as a catalyst for more engaging and impactful work.

The ROI is clear: increased profitability, enhanced client satisfaction, improved employee morale, and the capacity for sustainable growth. As the IT landscape continues to evolve, MSPs that prioritize intelligent automation will not only optimize their engineer utilization but also solidify their position as indispensable partners in their clients’ success. For those seeking to fortify their IT foundations and ensure robust infrastructure governance, consider exploring the specialized services offered by 13th Octet at https://13thoctet.com/. They can help you identify and address critical gaps, ensuring your infrastructure is secure and resilient.

FAQ: Common Questions About Engineer Utilization and Automation

Q1: What is a good engineer utilization rate for an MSP?

A: An optimal engineer utilization rate for an MSP typically falls between 80% and 85%. This range balances maximizing productive work with allowing essential time for training, professional development, internal projects, and preventing burnout. Rates below 75% often indicate profitability issues, while consistently exceeding 85% can lead to employee fatigue and high turnover.

Q2: How can automation help improve engineer utilization?

A: Automation significantly improves engineer utilization by reducing the time spent on manual, repetitive, and low-value tasks. This frees up engineers to focus on more complex, strategic, and billable work. Examples include automated ticket triage, user onboarding/offboarding, patch management, and routine system checks, all of which minimize administrative overhead and context switching.

Q3: What are the biggest challenges in implementing automation in an MSP?

A: The biggest challenges often include team resistance (fear of job displacement, skepticism), the initial investment in tools and training, the complexity of integrating disparate systems, and the effort required to define and standardize workflows. Overcoming these requires clear communication, phased implementation, engineer involvement, and demonstrating tangible ROI.

Q4: How do I measure the ROI of automation for my MSP?

A: Measuring ROI involves tracking several key metrics: engineer utilization rate, time savings (hours per task/week), cost savings (monetary value of saved hours), increased productivity (more tasks/clients per engineer), revenue growth (capacity to take on more business), and improvements in employee satisfaction and SLA compliance. Quantifying these helps justify automation investments.

Q5: What tools are essential for MSP workflow automation?

A: Essential tools include a robust Professional Services Automation (PSA) platform (e.g., HaloPSA, ConnectWise) for ticketing and client management, an Automation/Hyperautomation platform (e.g., Rewst, Pia) for building complex workflows and AI-driven triage, and a Remote Monitoring and Management (RMM) tool (e.g., ConnectWise Automate, NinjaOne) for endpoint automation. Additionally, specialized services for infrastructure governance (like 13th Octet) can provide critical architectural and security automation.

Q6: How can I overcome engineer resistance to automation?

A: Overcoming resistance requires a multi-faceted approach: communicate clearly that automation enhances roles, not replaces them; involve engineers in identifying and building automations; start with small, impactful “quick wins”; provide comprehensive training and support; and incentivize automation efforts. Focus on how automation frees them for more engaging, high-value work.

References:

[1] Runn.io. (2025, October 27). Do Your Utilization Rates Compare to Industry Benchmarks? https://www.runn.io/blog/utilization-rate-benchmarks

[2] Monograph. (2026, June 10). Utilization Rate Guide for Architecture and Engineering Firms. https://monograph.com/blog/utilization-rate

[3] Harvest. (n.d.). Utilization Rate Benchmarks by Industry – Optimize with Data. https://www.getharvest.com/calculators/utilization-rate-benchmarks-by-industry

[4] Reddit. (2026, May 9). Has the “Automation first” MSP idea ever worked? https://www.reddit.com/r/sysadmin/comments/1t87v46/has_the_automation_first_msp_idea_ever_worked/

[5] LinkedIn. (2025, April 3). How to Overcome Resistance to Automation in Your Organisation. https://www.linkedin.com/pulse/how-overcome-resistance-automation-your-organisation-f4dwc

[6] Dataflow Dynamics. (2025, April 6). HaloPSA vs. ConnectWise: Which PSA Solution is Best for Your MSP? https://www.dataflowdynamics.com.au/post/halopsa-vs-connectwise-which-psa-solution-is-best-for-your-msp

[7] Rewst.io. (2023, February 26). Rewst.io Automation : r/msp. https://www.reddit.com/r/msp/comments/11c06ko/rewstio_automation/

[8] Pia.ai. (n.d.). Pia – AI Automation for IT Help Desks. https://pia.ai/

This blog post is brought to you by 13th Octet. For independent infrastructure governance, cloud architecture, and disciplined managed services that find the gaps before they cost you, visit https://13thoctet.com/.