10 Technology Resolutions That Will Transform Your Business in 2026
Bryon Spahn
1/6/202622 min read
Every January, business leaders make resolutions. Most fail by February. The difference between those that succeed and those that don't? Strategic implementation over aspirational thinking.
As we enter 2026, the technology landscape has shifted dramatically. Artificial Intelligence is no longer emerging—it's table stakes. Cloud infrastructure isn't a differentiator—it's expected. And the businesses thriving aren't necessarily the ones with the biggest IT budgets, but those making strategic technology decisions aligned with business outcomes.
At Axial ARC, we've spent over three decades helping small and medium-sized businesses translate complex technology challenges into tangible business value. We've seen what works, what doesn't, and most importantly, what separates companies that grow from those that stagnate.
This isn't another listicle of trendy tech buzzwords. These are ten strategic technology resolutions that address real business challenges we see every day—with practical frameworks for implementation, specific ROI expectations, and honest assessments of what it takes to succeed.
Why Traditional New Year's Tech Resolutions Fail
Before we dive into what to do, let's address why most technology resolutions fail:
Lack of Strategic Alignment: Companies adopt technology because it's trendy, not because it solves a business problem. When a $50,000 AI implementation doesn't move the revenue needle, leadership loses faith in technology investments entirely.
Absence of Clear Metrics: "We'll improve our cybersecurity" sounds great. But what does improvement look like? Reduced incident response time? Fewer successful phishing attempts? Lower insurance premiums? Without measurable outcomes, there's no way to know if you've succeeded.
Vendor Dependency Trap: Many businesses implement technology through vendors who create dependency rather than capability. When the vendor relationship ends, so does the value—leaving companies with technical debt and no internal expertise.
Resource Misalignment: Technology initiatives require more than just budget. They demand time, attention, and often behavioral change across the organization. Companies that succeed plan for the full resource investment, not just the software license cost.
The resolutions that follow address these failure points head-on. Each includes specific business outcomes, realistic resource requirements, and frameworks for measuring success.
Resolution #1: Transform Your Infrastructure from Cost Center to Strategic Asset
The Challenge: Most SMBs view infrastructure as a necessary evil—something to maintain, not optimize. This mindset costs businesses an average of 30-40% in wasted infrastructure spending annually.
The Opportunity: Infrastructure that's resilient by design and strategic by nature becomes a competitive advantage. Companies with optimized infrastructure respond faster to market opportunities, scale more efficiently, and experience fewer costly disruptions.
What Success Looks Like
Cost Optimization: Reduce infrastructure costs by 25-40% while improving performance and reliability
Operational Efficiency: Decrease unplanned downtime from industry average of 7-8 hours annually to under 2 hours
Business Agility: Scale resources up or down in response to demand without multi-month procurement cycles
Risk Mitigation: Implement automated failover capabilities that maintain operations during disruptions
Implementation Framework
Month 1-2: Assessment Phase Start with infrastructure visibility. You can't optimize what you don't measure. Conduct a comprehensive infrastructure audit that maps current spending, identifies underutilized resources, and documents true business requirements—not vendor assumptions.
For a typical mid-sized business, this audit reveals $75,000-$150,000 in annual optimization opportunities. Common findings include oversized database instances running at 15% utilization, redundant storage systems, and development environments consuming production-level resources.
Month 3-4: Strategic Design Design infrastructure architecture around business requirements, not vendor packages. This means right-sizing compute resources, implementing autoscaling where appropriate, and building in redundancy for critical systems while accepting calculated risk for non-critical workloads.
Key principle: Match infrastructure investment to business criticality. Your e-commerce platform needs five-nines availability. Your internal knowledge base can tolerate scheduled downtime.
Month 5-6: Phased Implementation Execute migrations during low-impact windows. Prioritize quick wins that demonstrate value early—typically starting with development and staging environments before moving to production systems.
A manufacturing client reduced their annual infrastructure costs from $280,000 to $165,000 through this approach—a $115,000 annual savings that funded their subsequent AI automation initiatives.
Resource Requirements
Budget: $25,000-$75,000 for assessment and migration support (typically recovers in 8-12 months through cost optimization)
Time: 20-30 hours of internal stakeholder time over 6 months
Expertise: Infrastructure architecture expertise to design resilient, scalable solutions aligned with business requirements
Success Metrics
Infrastructure Cost Efficiency: Dollar spent per user, per application, per transaction
System Reliability: Percentage uptime, mean time between failures, mean time to recovery
Scaling Responsiveness: Time required to provision new resources, ability to handle traffic spikes
Technical Debt Reduction: Elimination of end-of-life systems, reduced dependency on legacy platforms
Resolution #2: Implement AI Where It Actually Drives Business Value
The Challenge: The AI hype cycle has created a dangerous dynamic. Companies feel pressure to "do AI" without clear understanding of where artificial intelligence actually solves business problems versus where it creates expensive complexity.
The Opportunity: Strategic AI implementation focuses on augmenting human capabilities in high-value, repetitive, or data-intensive processes. Done right, AI implementations deliver 10-15x ROI within the first year.
What Success Looks Like
Operational Efficiency: Reduce time spent on repetitive tasks by 60-70%, allowing staff to focus on strategic work
Customer Experience: Improve response times and service quality through intelligent automation
Data-Driven Decisions: Surface insights from business data that would be impossible to identify manually
Competitive Advantage: Respond to customer needs and market changes faster than competitors
Implementation Framework
Month 1: Process Identification Start with pain points, not technology. Where do your employees spend hours on repetitive data entry? Where do customer inquiries go unanswered because of volume? Where are you making business decisions based on intuition rather than data?
Document these processes in detail. Map current workflows, identify bottlenecks, and quantify the current cost in time and resources. This becomes your ROI baseline.
Month 2-3: Proof of Concept Select one high-impact, low-complexity process for your first AI implementation. Customer service inquiries, invoice processing, and lead qualification are common starting points because they're well-defined and measurable.
Build a proof of concept with clear success criteria. For a customer service chatbot, define acceptable response accuracy (typically 85%+ for initial implementations), resolution rate (percentage of inquiries handled without human intervention), and customer satisfaction scores.
Month 4-6: Scale and Optimize Once your proof of concept demonstrates value, expand systematically. Add additional use cases, refine models based on real-world performance, and integrate AI tools into existing workflows.
A distribution company implemented AI-driven inventory optimization that reduced carrying costs by 22% while improving product availability by 15%. The system paid for itself in four months and now saves them approximately $340,000 annually.
Real-World Applications for SMBs
Customer Service: Virtual agents that handle routine inquiries 24/7, escalating complex issues to human staff with full context. Typical ROI: 200-300% in first year through reduced staffing needs and improved customer satisfaction.
Document Processing: AI that extracts data from invoices, contracts, and forms, eliminating hours of manual data entry. Companies often see 70-80% reduction in processing time.
Sales Intelligence: AI analysis of customer data to identify upsell opportunities, predict churn, and optimize pricing strategies. Mid-sized B2B companies report 15-25% revenue increase from better opportunity identification.
Predictive Maintenance: For companies with physical assets, AI analysis of sensor data to predict failures before they occur, reducing downtime and emergency repair costs by 30-40%.
Resource Requirements
Budget: $30,000-$100,000 for first implementation including process analysis, development, and training
Time: 30-40 hours of subject matter expert time to define requirements and validate results
Expertise: AI implementation expertise that focuses on business outcomes, not just technical capabilities
Success Metrics
Time Savings: Hours reclaimed per week, per employee, per process
Accuracy Improvement: Error rate reduction in automated processes
Cost Per Transaction: Reduction in cost to complete automated tasks
Employee Satisfaction: Reduction in time spent on tasks employees find tedious or low-value
Resolution #3: Build Cybersecurity That's Proportional to Your Risk
The Challenge: Cybersecurity advice typically comes in two flavors: enterprise-grade solutions that cost more than SMBs can afford, or consumer-grade tools that leave critical gaps. Neither approach addresses the actual risk profile of small and medium-sized businesses.
The Opportunity: Implement security measures that are proportional to your actual risk, focusing resources where they deliver maximum protection. Companies following this approach typically spend 30-40% less than those implementing generic security frameworks while achieving better protection of critical assets.
What Success Looks Like
Risk Reduction: Protect your most valuable business assets—customer data, intellectual property, financial systems
Compliance Confidence: Meet regulatory requirements without paying for unnecessary capabilities
Incident Preparedness: Respond to security incidents in minutes rather than days, minimizing damage and recovery costs
Insurance Savings: Reduce cyber insurance premiums by 15-25% through demonstrable security controls
Implementation Framework
Month 1: Risk Assessment Identify what actually matters. Not every business needs the same security controls. A professional services firm with 50 employees has different risks than a manufacturer with connected industrial systems.
Map your critical business assets, identify realistic threat vectors, and quantify potential impact. For most SMBs, the highest-risk scenarios involve ransomware, business email compromise, and accidental data exposure—not sophisticated nation-state attacks.
Month 2-3: Control Implementation Implement security controls that address your specific risk profile:
Foundational Controls (Must-Have for All Businesses):
Multi-factor authentication on all business-critical systems
Automated patching and update management
Encrypted backups with tested recovery procedures
Email security filtering to block phishing and malware
Basic network segmentation separating critical systems
These foundational controls typically cost $5,000-$15,000 to implement and prevent 80-90% of common attacks.
Enhanced Controls (For Companies Handling Sensitive Data):
Endpoint detection and response monitoring
Data loss prevention for sensitive information
Privileged access management for administrator accounts
Security awareness training with simulated phishing
Regular vulnerability assessments
Enhanced controls add $15,000-$30,000 annually but become necessary when handling healthcare data, financial information, or intellectual property.
Month 4-6: Testing and Refinement Security controls only work if they're properly implemented and maintained. Conduct tabletop exercises where leadership responds to simulated incidents. Test backup recovery procedures. Run phishing simulations to identify training gaps.
A healthcare services company discovered through tabletop exercises that their incident response plan had outdated contact information and unclear escalation procedures. Fixing these issues took minimal investment but would have saved hours of confusion during a real incident.
Resource Requirements
Budget: $20,000-$60,000 for initial implementation depending on complexity and existing controls
Time: 15-20 hours of internal time for risk assessment and procedure documentation
Expertise: Cybersecurity expertise to design controls proportional to risk, not vendor checklists
Success Metrics
Incident Response Time: Time from detection to containment for security events
Security Awareness: Employee performance on phishing simulations (target 90%+ correct identification)
System Vulnerability: Number of critical and high-severity vulnerabilities in production systems
Insurance Impact: Changes in cyber insurance premiums and coverage terms
Resolution #4: Master Your SaaS Sprawl Before It Masters Your Budget
The Challenge: The average company now uses 130+ SaaS applications. Many departments purchase subscriptions without IT involvement, creating redundant capabilities, security gaps, and spiraling costs. Finance teams discover they're paying for hundreds of unused licenses only when it's too late.
The Opportunity: Companies that actively manage SaaS portfolios typically reduce costs by 20-35% while improving security and user experience. This isn't about cutting tools employees need—it's about eliminating waste and optimizing what remains.
What Success Looks Like
Cost Optimization: Reduce SaaS spending by 20-35% through license right-sizing and eliminating redundancy
Security Improvement: Gain visibility into all applications accessing company data
User Experience: Consolidate overlapping tools, reducing complexity and improving productivity
Contract Leverage: Negotiate better terms through usage data and competitive alternatives
Implementation Framework
Month 1: Discovery Discover everything running in your environment. This requires more than reviewing finance department subscriptions. Many SaaS purchases happen through expense reports or department credit cards.
Tools like single sign-on (SSO) providers and expense management systems reveal the true scope of SaaS usage. One professional services firm discovered 94 SaaS applications when they thought they had 35.
Common findings:
Multiple project management tools (Asana, Monday, Trello, Basecamp) with overlapping functionality
Redundant video conferencing licenses (Zoom, Teams, Google Meet all with paid plans)
Communication tools (Slack, Teams, Discord) fragmenting internal collaboration
Design applications with enterprise licenses while only 2-3 employees use advanced features
Month 2-3: Rationalization Analyze usage data to identify consolidation opportunities. Sort applications into four categories:
Essential: Business-critical tools with high utilization and no suitable alternatives Consolidate: Multiple tools serving similar functions where one would suffice Downgrade: Applications where most users need basic features but you're paying for enterprise tiers Eliminate: Subscriptions with minimal usage or abandoned completely
For each tool in the Consolidate category, assess migration effort versus annual savings. Consolidating three project management tools might save $15,000 annually but require 40 hours of migration work—typically worthwhile. Forcing sales and engineering onto the same CRM might save $8,000 but create workflow disruption that costs more in lost productivity.
Month 4-6: Optimization and Governance Implement right-sized licensing and create governance processes to prevent future sprawl.
Right-sizing typically means:
Converting power users to paid licenses while moving occasional users to free tiers
Implementing license recycling for departing employees
Negotiating usage-based pricing where possible instead of seat-based models
A financial services company reduced Adobe Creative Cloud costs by $24,000 annually by limiting full licenses to 8 design team members while providing Acrobat Pro to 40 employees who only needed PDF capabilities.
Governance doesn't mean blocking innovation. It means requiring business justification before purchasing new tools and conducting quarterly reviews of all subscriptions.
Resource Requirements
Budget: $10,000-$25,000 for assessment tools and migration support
Time: 20-30 hours of internal time for discovery and decision-making
Expertise: SaaS optimization expertise to identify consolidation opportunities and negotiate better terms
Success Metrics
SaaS Spending Per Employee: Total SaaS costs divided by employee count (benchmark against industry averages)
License Utilization Rate: Percentage of purchased licenses actively used (target 80%+ utilization)
Application Overlap: Number of tools serving duplicate functions
Time to Provision: Speed of providing access to new employees (should improve with consolidation)
Resolution #5: Transform Disaster Recovery from Insurance Policy to Business Capability
The Challenge: Most businesses treat disaster recovery as insurance—something they hope never to use. Plans sit in SharePoint folders, untested and outdated. When disruption occurs, teams scramble to piece together responses while business operations suffer.
The Opportunity: Companies with mature business continuity capabilities maintain operations during disruptions that cripple competitors. While others lose revenue, customer trust, and market position, resilient organizations adapt quickly and emerge stronger.
What Success Looks Like
Revenue Protection: Maintain critical business operations during disruptions, minimizing revenue impact
Recovery Speed: Reduce recovery time from days or weeks to hours for critical systems
Stakeholder Confidence: Demonstrate preparedness to customers, partners, investors, and insurance providers
Competitive Advantage: Win business from companies that can't guarantee service continuity
Implementation Framework
Month 1-2: Business Impact Analysis Identify which business functions are truly critical and how quickly they need to recover. Not everything needs the same recovery objective.
Map your business functions by recovery time objective (RTO) and recovery point objective (RPO):
Tier 1 - Critical (RTO: 1-4 hours, RPO: 15 minutes): E-commerce platform, customer-facing applications, core transaction processing. Business cannot function without these systems.
Tier 2 - Important (RTO: 8-24 hours, RPO: 4 hours): Financial systems, inventory management, internal collaboration tools. Business can operate with temporary workarounds but not indefinitely.
Tier 3 - Standard (RTO: 48-72 hours, RPO: 24 hours): Reporting systems, document repositories, training platforms. Business operates normally without these but wants them restored soon.
Tier 4 - Deferrable (RTO: 1 week+, RPO: 1 week): Archived data, legacy systems maintained for reference, development environments. Can be restored at lower priority.
This tiering drives investment decisions. Over-engineering recovery for Tier 4 systems wastes resources. Under-investing in Tier 1 systems creates business risk.
Month 3-4: Recovery Strategy Development Design recovery strategies appropriate to each tier:
For critical systems, implement active-active or active-passive configurations with automated failover. This typically adds 20-30% to infrastructure costs but maintains operations during primary site failures.
For important systems, implement backup sites with documented recovery procedures. Manual intervention is acceptable but the path to recovery must be clear and tested.
For standard systems, ensure backups exist in geographically separate locations with recovery procedures documented.
Month 5-6: Testing and Refinement Business continuity plans that aren't tested don't work. Period.
Conduct tabletop exercises where leadership responds to disruption scenarios:
Ransomware encrypts your primary file storage
Your data center loses power for 48 hours
Your primary SaaS provider experiences a multi-day outage
A key employee departs suddenly with critical system knowledge
These exercises consistently reveal gaps: outdated contact information, unclear decision authority, missing documentation, untested recovery procedures, and unrealistic recovery time assumptions.
Follow tabletop exercises with technical recovery testing. Actually restore systems from backups. Actually fail over to secondary infrastructure. Measure recovery time against objectives.
A distribution company discovered through testing that their documented "4-hour RTO" was actually 18 hours because their restoration procedure required downloading 2TB of backup data over an internet connection with insufficient bandwidth. Identifying this gap during testing rather than an actual disaster enabled them to implement a better solution.
Resource Requirements
Budget: $25,000-$75,000 for business impact analysis, strategy development, and testing depending on environment complexity
Time: 30-40 hours of leadership and technical staff time across the engagement
Expertise: Business continuity expertise to design resilient solutions proportional to business risk
Success Metrics
Recovery Time Objectives: Measured ability to restore systems within target timeframes
Recovery Success Rate: Percentage of tested recovery procedures that work as documented
Exercise Participation: Leadership engagement in tabletop scenarios
Insurance Impact: Changes in business interruption insurance premiums and terms
Resolution #6: Build Data Strategy That Drives Decisions, Not Just Reports
The Challenge: Most companies have plenty of data but struggle to extract business value. Data lives in disconnected systems. Reports show what happened but not why it matters or what to do about it. Leadership makes decisions based on intuition supported by selective data rather than comprehensive analysis.
The Opportunity: Companies with mature data strategies consistently outperform competitors. They identify opportunities earlier, optimize operations more effectively, and make decisions faster because they have the right information at the right time.
What Success Looks Like
Decision Velocity: Reduce time required to access relevant business information from days to minutes
Operational Insights: Identify optimization opportunities worth 5-10% of annual revenue
Predictive Capability: Forecast customer behavior, demand patterns, and market trends with increasing accuracy
Competitive Intelligence: Understand market dynamics and competitive positioning through data analysis
Implementation Framework
Month 1-2: Data Audit and Use Case Definition Start with business questions, not technical capabilities. What decisions would you make differently if you had better information?
Common high-value use cases for SMBs:
Customer segmentation identifying most profitable customer profiles
Product profitability analysis revealing which offerings drive margins
Sales pipeline health predicting monthly/quarterly revenue accuracy
Operational efficiency identifying process bottlenecks and waste
Inventory optimization balancing carrying costs against stockout risk
Document current data sources and identify gaps. Most companies discover they collect data but don't integrate it effectively. Sales data lives in CRM, financial data in accounting systems, operational data in spreadsheets, and customer interaction data in support platforms.
Month 3-4: Data Infrastructure Development Build data infrastructure that consolidates relevant information and makes it accessible to decision-makers. This doesn't necessarily mean building data warehouses—modern tools enable analysis without massive integration projects.
Key principles:
Start Small: Integrate data sources for one use case rather than attempting to consolidate everything
Prioritize Access: Focus on making data accessible to people who make decisions, not just analysts
Emphasize Actionability: Design reports and dashboards that highlight what to do, not just what happened
A professional services firm built customer profitability analysis integrating CRM, project management, and financial data. The integration revealed that 40% of customer engagements operated at negative margins when fully costed. This insight drove pricing changes and customer mix optimization that improved overall margins by 8%.
Month 5-6: Analytics Capability Building Deploy analytics tools and train teams to use them effectively. Most companies fail at analytics not because of technology limitations but because insights never translate into action.
Address three layers:
Descriptive Analytics: What happened? (Reports showing historical performance)
Diagnostic Analytics: Why did it happen? (Analysis revealing drivers of performance)
Predictive Analytics: What will happen? (Forecasts enabling proactive decisions)
Train both technical users who build reports and business users who consume insights. The goal is self-service analytics where business leaders access relevant data without depending on IT or analyst intermediaries.
Resource Requirements
Budget: $40,000-$100,000 for initial integration, analytics platform, and training
Time: 40-50 hours of stakeholder time defining requirements and validating outputs
Expertise: Data strategy expertise to design solutions that drive business outcomes, not just technical capabilities
Success Metrics
Decision Time: Time required to access information needed for business decisions
Insight Adoption: Percentage of insights that lead to business action
Data Quality: Accuracy and completeness of business-critical data
User Engagement: Active usage of analytics tools by business decision-makers
Resolution #7: Implement Cloud Strategy That Matches Your Business Reality
The Challenge: Cloud adoption often follows one of two problematic patterns. Companies either "lift and shift" on-premises infrastructure to cloud providers without optimization (maintaining high costs and complexity), or they over-engineer cloud-native architectures that introduce unnecessary complexity for their actual requirements.
The Opportunity: Strategic cloud implementation reduces costs, increases agility, and enables capabilities impossible with on-premises infrastructure. But success requires matching cloud architecture to business requirements rather than following prescriptive best practices designed for different use cases.
What Success Looks Like
Cost Efficiency: Reduce total cost of ownership by 30-50% compared to on-premises infrastructure
Operational Agility: Provision new environments in minutes rather than weeks
Geographic Reach: Serve customers in multiple regions without physical infrastructure investment
Innovation Enablement: Experiment with new capabilities without capital expenditure
Implementation Framework
Month 1: Workload Assessment Evaluate each application and system for cloud suitability. Not everything belongs in the cloud, and not everything cloud-ready should migrate immediately.
Assessment criteria:
Business Criticality: How essential is this system to business operations?
Usage Pattern: Is demand consistent or variable? (Variable demand benefits more from cloud elasticity)
Data Sensitivity: Are there regulatory or contractual requirements affecting deployment location?
Interdependencies: Does this system have tight integration with other systems?
Technical Debt: Is this system approaching end-of-life and ready for replacement?
Typical SMB findings:
Core business applications with variable demand (e-commerce, customer portals) benefit most from cloud migration
Legacy systems tightly integrated with on-premises infrastructure often cost more to migrate than continue hosting
Development and testing environments migrate easily and deliver quick wins
Disaster recovery and backup systems become dramatically more cost-effective in cloud
Month 2-4: Strategic Migration Planning Design migration strategy that sequences workloads for maximum value with minimum disruption:
Phase 1: Non-production environments (development, testing, training). These migrations build team experience with minimal business risk.
Phase 2: New applications and greenfield projects. Build cloud-native from the start rather than migrating later.
Phase 3: Business applications with clear cloud benefits. Focus on systems with variable demand, geographic requirements, or disaster recovery needs.
Phase 4: Remaining workloads where business justification is clear.
Intentionally Not Migrated: Legacy systems approaching replacement, applications with prohibitive licensing costs in cloud, or systems with requirements better served by on-premises infrastructure.
Month 5-6: Pilot Migration and Optimization Execute pilot migration with comprehensive optimization. Many companies waste cloud spending by replicating on-premises architecture rather than adopting cloud-native capabilities.
Key optimization opportunities:
Right-size compute resources based on actual utilization (most on-premises systems are significantly over-provisioned)
Implement auto-scaling for variable demand workloads
Use object storage for archives rather than expensive block storage
Leverage managed services to reduce operational overhead
Implement automated shutdown for non-production environments (typically saves 60%+ on development costs)
A manufacturing company reduced their total infrastructure costs from $240,000 annually to $140,000 through strategic cloud migration—but only after optimizing their architecture. Their initial cloud estimate was $280,000, higher than on-premises costs, because they planned to replicate existing architecture without optimization.
Resource Requirements
Budget: $50,000-$150,000 for assessment, migration, and optimization depending on environment complexity
Time: 30-40 hours of internal stakeholder time
Expertise: Cloud architecture expertise to design optimized solutions, not direct replicas of on-premises infrastructure
Success Metrics
Total Cost of Ownership: All-in costs including infrastructure, labor, and overhead
Provisioning Time: Time required to deploy new environments or resources
System Availability: Uptime for critical business systems
Scaling Responsiveness: Ability to handle demand spikes without degraded performance
Resolution #8: Develop Internal Technology Capabilities Instead of Dependency
The Challenge: Many businesses outsource technology completely, creating vendor dependency that limits agility and increases long-term costs. When vendors control critical knowledge and infrastructure, companies lose the ability to make independent technology decisions.
The Opportunity: Building internal technology capability—even in companies without dedicated IT staff—enables strategic decision-making, reduces vendor dependency, and creates organizational knowledge that compounds over time.
What Success Looks Like
Strategic Independence: Make technology decisions based on business requirements, not vendor recommendations
Cost Management: Negotiate better vendor terms through credible alternative options
Organizational Knowledge: Build technology understanding that persists beyond individual vendor relationships
Decision Quality: Evaluate technology investments based on business value rather than sales presentations
Implementation Framework
Month 1-2: Capability Gap Assessment Identify where vendor dependency creates business risk or limits strategic options. Common areas include:
Infrastructure Knowledge: Understanding your actual architecture, dependencies, and costs rather than relying on vendor descriptions
Application Expertise: Capability to configure, customize, and troubleshoot business applications without vendor support for every change
Data Access: Ability to extract, analyze, and use your own business data without vendor intermediaries
Strategic Planning: Understanding technology options and trade-offs to evaluate vendor proposals critically
Most SMBs discover they lack visibility into their own technology environment. One distribution company realized they couldn't answer basic questions about their infrastructure configuration, making it impossible to evaluate alternative vendor proposals credibly.
Month 3-4: Targeted Knowledge Transfer Build internal capability strategically. This doesn't mean hiring IT staff to replace every vendor relationship. It means developing sufficient knowledge to make informed decisions and maintain reasonable oversight.
Approaches vary by company size and sophistication:
Small Companies (10-50 employees): Designate technically-capable employee (doesn't need to be full-time IT) for oversight. Provide training on core systems, infrastructure basics, and vendor management. This person becomes the internal technology advocate who translates business needs and evaluates vendor recommendations.
Mid-Sized Companies (50-250 employees): Hire part-time or fractional technology leadership for strategic guidance. Develop documentation of critical systems, dependencies, and procedures. Build relationships with multiple vendors to maintain competitive options.
Growing Companies (250+ employees): Consider full-time technology leadership for strategy and vendor management. Develop internal expertise for tier-1 support and routine operations while outsourcing specialized functions.
Month 5-6: Documentation and Process Development Create organizational knowledge assets that persist beyond individual employees or vendor relationships:
System architecture diagrams showing how applications and infrastructure connect
Procedure documentation for common operations and troubleshooting
Vendor relationship records including contracts, support contacts, and service history
Technology decision framework guiding investment evaluation
Business continuity procedures reducing dependency on specific individuals
This documentation transforms institutional knowledge from "Bob knows how this works" to documented capabilities that survive employee transitions and vendor changes.
Resource Requirements
Budget: $20,000-$60,000 for training, fractional expertise, and documentation development
Time: 40-50 hours of internal time for knowledge transfer and documentation
Expertise: Technology advisory services to identify capability gaps and develop strategic roadmaps
Success Metrics
Vendor Switching Cost: Effort and cost required to change technology vendors
Internal Resolution Rate: Percentage of technology issues resolved without external support
Decision Confidence: Leadership confidence in technology investment decisions
Knowledge Distribution: Number of employees who understand critical systems (reducing key person risk)
Resolution #9: Embrace Automation Where It Multiplies Human Capability
The Challenge: Automation conversations often focus on replacement—using technology to eliminate human roles. This framing creates resistance, limits implementation scope, and misses the greatest opportunities. The real value of automation isn't replacing people but enabling them to do higher-value work.
The Opportunity: Strategic automation that augments human capability delivers 5-10x ROI by eliminating tedious manual work while freeing employees to focus on activities that require judgment, creativity, and relationship-building.
What Success Looks Like
Productivity Gains: Reduce time spent on routine tasks by 50-70%
Employee Satisfaction: Improve engagement by eliminating tedious work employees find unsatisfying
Quality Improvement: Reduce errors in repetitive processes by 80-90%
Business Growth: Scale operations without proportional headcount increases
Implementation Framework
Month 1-2: Process Identification and Prioritization Identify high-impact automation opportunities by talking to employees about their daily frustrations. The best automation candidates share these characteristics:
High Volume: Tasks performed frequently enough that automation delivers meaningful time savings Rules-Based: Processes that follow predictable logic rather than requiring judgment Low Complexity: Workflows that are well-defined and stable rather than constantly changing High Tedium: Tasks employees find mind-numbing and error-prone due to repetition
Common high-value automation opportunities:
Invoice Processing: Extract data from invoices, match to purchase orders, route for approval, and post to accounting systems. Typical result: 70% reduction in processing time and 90% reduction in data entry errors.
Customer Onboarding: Collect information, create accounts, provision access, and generate welcome communications. Typical result: Reduce onboarding time from 2-3 days to 2-3 hours.
Report Generation: Extract data from multiple systems, perform calculations, format presentations, and distribute to stakeholders. Typical result: Reduce weekly reporting burden from 8-10 hours to 30 minutes of review time.
Lead Qualification: Score incoming leads based on criteria, route to appropriate salespeople, and trigger follow-up sequences. Typical result: 40% increase in qualified leads contacted within 1 hour.
Expense Approval: Route expense reports based on amount and category, verify policy compliance, escalate exceptions, and process approved expenses. Typical result: Reduce approval time from 5-7 days to 24 hours.
Month 3-4: Pilot Implementation Build automation for one high-impact process. Start with something meaningful enough to demonstrate value but constrained enough to complete quickly.
Use appropriate tools for the complexity level:
Simple Automation: Zapier, Power Automate, or similar no-code tools for straightforward workflows
Complex Automation: Custom development for intricate business logic or legacy system integration
Intelligent Automation: AI-powered tools when processes require data extraction, classification, or decision support
Measure baseline performance before implementing automation. You can't demonstrate impact without understanding current state. Document time spent, error rates, and employee satisfaction with the manual process.
A professional services firm automated client onboarding, reducing time from 40 hours of scattered work over three weeks to 4 hours of concentrated effort. This freed project managers to focus on delivery rather than paperwork while improving client experience through faster, more consistent onboarding.
Month 5-6: Expansion and Refinement Expand automation based on pilot results. Add related workflows, optimize existing automations, and document lessons learned.
Key success factors:
Change Management: Involve affected employees in design to increase adoption
Exception Handling: Build clear procedures for situations automation can't handle
Continuous Improvement: Review automation performance regularly and refine as processes evolve
Knowledge Transfer: Train employees to modify and maintain automations rather than creating new technical dependencies
Resource Requirements
Budget: $30,000-$80,000 for initial automation development including process analysis and implementation
Time: 30-40 hours of subject matter expert time to document processes and validate automation
Expertise: Intelligent automation expertise to design solutions that augment rather than replace human capability
Success Metrics
Time Savings: Hours reclaimed per week, per employee, per process
Error Reduction: Decrease in process mistakes and rework
Employee Satisfaction: Feedback on work quality and engagement
Throughput Improvement: Increase in volume processed without additional resources
Resolution #10: Establish Technology Governance That Enables Rather Than Restricts
The Challenge: Technology governance often swings between two extremes. Either there's no governance (leading to chaos, security gaps, and wasted spending), or governance becomes bureaucracy that slows innovation and frustrates employees. Most SMBs struggle to find the middle ground.
The Opportunity: Effective governance provides just enough structure to prevent problems while maintaining agility. Companies with mature governance make better technology investments, respond faster to opportunities, and build capabilities that compound over time.
What Success Looks Like
Investment Alignment: Technology spending directly supports business objectives
Risk Management: Proactively identify and mitigate technology risks
Decision Velocity: Accelerate good decisions while preventing bad ones
Strategic Coherence: Build integrated technology capabilities rather than disconnected tools
Implementation Framework
Month 1-2: Governance Framework Design Create lightweight governance structure appropriate for company size and complexity. Most SMBs need three governance layers:
Strategic Governance: Quarterly review of technology strategy, major investments, and capability roadmap. Participants: Executive leadership and technology decision-makers. Focus: Alignment with business objectives and resource allocation.
Operational Governance: Monthly review of ongoing initiatives, risks, and operational performance. Participants: Technology leadership and functional managers. Focus: Execution quality and issue resolution.
Technical Governance: Standards and guidelines for technology selection, implementation, and operations. Participants: Technical staff and vendors. Focus: Consistency, security, and maintainability.
The key is right-sizing governance. A 50-person company doesn't need the same structure as a 5,000-person enterprise.
Month 3-4: Standards and Decision Frameworks Develop practical standards that guide decisions without creating bureaucracy:
Technology Selection Framework: Criteria for evaluating new tools and platforms (business value, integration requirements, security implications, total cost of ownership, vendor viability)
Security Standards: Baseline requirements all systems must meet (authentication, data protection, access controls, incident response)
Data Standards: Guidelines for data classification, retention, and access (what data exists, where it lives, who can access it, how long it's kept)
Architecture Principles: High-level guidance for system design (prefer integration over duplication, build for change, design for failure, document everything)
These standards should fit on a few pages and focus on principles over detailed procedures. The goal is enabling informed decisions, not creating compliance checklists.
Month 5-6: Implementation and Communication Roll out governance with emphasis on value proposition. Governance succeeds when employees understand it makes their work easier, not harder.
Effective governance:
Accelerates vendor selection by providing clear evaluation criteria
Reduces security incidents by establishing baseline protections
Prevents wasted spending by identifying redundant capabilities before purchase
Improves integration by encouraging compatible technology choices
A services company implemented lightweight governance that reduced time to approve new technology purchases from 6-8 weeks to 5-7 days by replacing ad-hoc evaluation with clear criteria and designated decision authority.
Resource Requirements
Budget: $15,000-$40,000 for governance framework design and implementation
Time: 20-30 hours of leadership time for framework development and approval
Expertise: Technology advisory expertise to design governance appropriate for company size and maturity
Success Metrics
Decision Time: Time from technology need identification to purchase approval
Investment Alignment: Percentage of technology spending directly supporting business objectives
Governance Overhead: Time spent on governance activities (target: less than 5% of technology team time)
Initiative Success Rate: Percentage of technology projects delivering expected business value
Making Your 2026 Resolutions Reality
These ten resolutions represent genuine opportunities to transform technology from cost center to strategic advantage. But implementation requires more than good intentions.
The Implementation Principle
Success comes from strategic focus, not scattered effort. Attempting all ten resolutions simultaneously guarantees failure. Instead, select 2-3 resolutions most aligned with your business priorities and execute them excellently.
Ask three questions:
Where are we losing money or opportunity due to technology limitations?
Where could we compete more effectively with better technology capabilities?
Where are we creating unnecessary risk through technology gaps?
Your answers reveal which resolutions deliver maximum business impact for your specific situation.
The Partnership Principle
Strategic technology implementation requires expertise most SMBs don't maintain in-house. That's not a weakness—it's reality. The question isn't whether to engage external expertise but how to do so strategically.
Effective partnerships build your capabilities rather than create dependency. Partners who succeed long-term:
Transfer Knowledge: Leave your team more capable than they found them
Align Incentives: Deliver business outcomes, not billable hours
Provide Flexibility: Engage when you need them, disengage when you don't
Speak Business Language: Discuss ROI and business impact, not technical specifications
The Axial ARC Difference
We've helped companies like yours translate complex technology challenges into tangible business value. We're not a vendor selling products—we're a strategic partner building your capabilities.
Our approach centers on three principles:
Resilient by Design: Technology infrastructure and solutions built to withstand disruption and adapt to change
Strategic by Nature: Every technical recommendation directly supports specific business objectives with measurable outcomes
Partner, Not Vendor: Success means leaving your organization more capable, not more dependent
Whether you're ready to optimize infrastructure, implement strategic AI, strengthen cybersecurity posture, or build technology governance, we bring the expertise to translate these resolutions into reality.
Start Your Technology Transformation
The businesses that thrive in 2026 won't be those with the biggest technology budgets. They'll be the ones making strategic technology investments aligned with business priorities.
Which of these ten resolutions would transform your business? What's holding you back from implementation?
Let's discuss how to make your 2026 technology resolutions reality.
At Axial ARC, we transform technology complexity into competitive advantage. Reach out to explore how strategic technology partnership can accelerate your business objectives.