Tag: information technology

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The Key to SMB Success: Cloud Adoption for Resilience

Business resilience used to mean backup supplies and emergency plans. Today, it means being able to adapt quickly when supply chains stall, customer expectations shift, staffing needs change, or cyber threats escalate.

For small and midsized businesses, that kind of adaptability can feel out of reach. Resources are limited, and every technology decision has to prove its value.

The good news: resilience does not require enterprise-sized budgets. It starts with creating the flexibility to pivot when circumstances demand it.

Flexibility Is No Longer Optional

SMBs are used to doing more with less, but many still rely on technology built for predictability. Legacy systems, fixed infrastructure, and disconnected applications can turn small changes into major projects.

Cloud services change that equation by helping businesses enable users, migrate workloads, optimize operations, and scale capabilities as needs evolve.

Whether supporting remote work, scaling collaboration tools, or strengthening security, the cloud helps SMBs respond faster without rebuilding their technology foundation each time something changes.

Resilience Starts with Options

Resilience is about preserving the ability to respond. The more options a business has, the easier it becomes to make thoughtful decisions under pressure instead of scrambling for temporary fixes.

  • Scale resources up during busy seasons and back down when demand stabilizes.
  • Enable employees to securely access systems and applications from virtually anywhere.
  • Deploy new tools, applications, and services faster.
  • Strengthen backup, recovery, and continuity strategies.

In practical terms, flexibility creates breathing room. When you are running a business, breathing room matters.

The Human Side of Cloud Adoption

Cloud flexibility isn’t just about infrastructure. It helps employees stay productive, teams continue serving customers, and business owners spend less time reacting to technology constraints.

No one starts their small business with a plan to troubleshoot a server problem at 10 p.m. Technology should support the work that moves the business forward—not compete with it for attention.

Cloud Adoption Doesn’t Have to Happen All at Once

Cloud adoption can happen in phases. The best place to start is where the value is most immediate – maybe in the area of collaboration, security, backup, remote access, or application modernization.

This approach turns cloud adoption from a one-time project into a practical business strategy aligned with real priorities, measurable outcomes, and a realistic pace of change.

A More Resilient Future Starts with the Right Foundation

Cloud flexibility won’t remove uncertainty, but it can change how the business faces it… from reacting under pressure to responding with confidence, agility, and control.

For SMBs, resilience is no longer just about surviving disruption. It’s about building the flexibility to keep serving customers, protecting momentum, and growing stronger no matter what comes next.

Don’t Wait Until Disruption Forces the Decision

If your technology environment is slowing your ability to adapt, act before the next disruption exposes the gap. Identify where flexibility would make the biggest difference first, whether it be for remote access, security, application modernization, backup, or business continuity and recovery.

Do not wait until outdated systems limit your options. Connect with Noobeh’s team today to explore cloud solutions that fit your business goals, budget, and pace of change. Let’s make your business a resilient one, capable of handling whatever comes next.

bunny feetMake Sense?

J

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Stay, Upgrade, or Move On? Choosing Your Next Business System

If you’re a business owner using QuickBooks accounting software and thinking it is time for a change, you aren’t alone. While QuickBooks Enterprise works really well and has for a long time, there always comes a point where a growing business simply needs more. Change for the sake of change makes no sense, but if the systems or software are holding the business back, change becomes a business imperative.

Choosing the next business accounting system can feel a little like standing at a fork in the road with three signs: keep QuickBooks and try to improve reporting, upgrade to something like Intuit Enterprise Suite, or close your eyes and jump into a full ERP with both feet. The wrong choice can create years of frustration; the right one can give the business room to grow without adding unnecessary complexity.

Surprise! There is no universal answer for the “right” accounting system.

The right choice depends on what is actually causing the pain: reporting gaps, finance process issues, or deeper operational complexity.

Option 1: Stay on QuickBooks and add Fabric

This is usually the best path when accounting is still working, but the company needs much better reporting. Maybe the business has ServiceTitan, Jobber, Cin7, HubSpot, spreadsheets, and QuickBooks all telling part of the story. Noobeh team helps businesses use Microsoft Azure and Fabric to pull that data together so Power BI can show the bigger picture.

Possible Option 2: Move to Intuit Enterprise Suite

This may make sense when the finance function itself is starting to feel stretched. The company may need multi-entity financials, stronger approvals, better controls, consolidated reporting, more AP/AR automation, or budgeting and forecasting that go beyond the basics. The team at Mendelson Consulting are among the few who can really help make this evaluation with you (years of financial system and QuickBooks experience and backed by actual CPAs).

Option 3: Move to a full ERP

A full ERP starts to make sense when the business has outgrown simple accounting-centric tools entirely. That usually happens when global entities, multi-currency, multi-entity consolidation, inventory, manufacturing, supply chain, or operational workflows become too complex to manage around the edges.

That is when a system like Microsoft Dynamics 365 Business Central enters the conversation. Where Intuit Enterprise Suite may provide a “next step” for finance teams, Business Central could likely be the superior (read = longer-term) solution due in part to the tight integration with applications and services the business likely already uses.

A simple decision framework

FactorQuickBooks + FabricIntuit Enterprise SuiteERP
RoleAccounting + analyticsLight operational finance platformComplete Finance and Operational Platform (Full business system)
CostLow to moderateModerateModerate to high
ImplementationFairly FastMediumMedium to long
FlexibilityVery highModerateHigh
Operational depthLimitedModerateVery deep
Reporting powerVery high (Fabric)Moderate, but higher if Fabric is addedHigh

The question to ask first

Do we mainly need better insight, better finance scale, or a new and modernized business system?

  • If the problem is visibility → Fabric
  • If the problem is finance scale → Enterprise Suite
  • If the problem is finance and/or operational complexity → ERP

The bottom line

The modern SMB stack is not always about picking one perfect system. More often, it is about building the right combination of operational tools, accounting or ERP software, a data platform like Microsoft Fabric, and dashboards in Power BI. Start with the business problem first, then choose the system path that solves it with the least unnecessary complexity. What’s truly important is to look ahead a little bit and consider what the next likely issue will be, and to address is now rather than facing another purchasing decision later.

The best choice is usually the one that solves today’s bottleneck without creating tomorrow’s burden. That may mean improving reporting, scaling finance, or moving to an ERP, but the decision should start with the business problem and not the software label.

Not sure which path makes sense?

Connect with our team at Noobeh and lets discuss your top-of-mind challenges. It may not require a formal assessment to get the improvements started. If things sound a little more complicated, the next step would be a short systems assessment by Mendelson Consulting specialists.

List the tools you use today, the reports leadership actually needs, the manual work your team repeats every month, and the workflows that are starting to break. Once we help reveal those gaps, the decision becomes less about software buzzwords and more about choosing the platform that solves the real problem.

bunny feetMake sense?

J

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Data Is the Real Competitive Advantage

AI is powerful, but it’s not magic. AI can’t compensate for fragmented systems, poor processes, or unreliable data. When a business succeeds with AI, it isn’t necessarily because they have the most advanced models. More often, AI success is found by those with the strongest data foundations.

High-Quality Data is the Foundation for Successful AI in Business

Artificial intelligence is rapidly becoming a competitive differentiator in business. From forecasting demand and optimizing pricing to automating customer service and detecting fraud, AI promises efficiency, insight, and scale. Yet many AI initiatives fail to deliver meaningful results—not because the algorithms are weak, but because the underlying data is.

In practice, AI is only as good as the data it learns from. Without high-quality, well-organized, and reliable data, even the most advanced AI tools will produce inaccurate insights, reinforce bad decisions, or fail entirely. For businesses looking to use AI responsibly and effectively, data quality is not optional – it is foundational.

Garbage In, Garbage Out: The Reality of AI

AI systems don’t “think” or “reason” in the human sense. They identify patterns based on historical data. If that data is incomplete, inconsistent, outdated, or biased, the AI will replicate and amplify those problems.

Sales forecasts built on inconsistent historical revenue data will be unreliable, customer churn models trained on incomplete customer records will miss key risk signals, and AI copilots trained on poorly documented internal processes will give incorrect guidance to employees.

In short, AI can’t fix broken data. It can only scale its flaws.

AI Strategy Should Follow Data Readiness

Many organizations pursue AI due to competitive pressure or fear of falling behind. This “AI FOMO” often leads to rushed implementations that skip essential groundwork.

A better approach is to ask these four simple questions:

  1. Do we trust our core business data today?
  2. Can we explain where key numbers come from?
  3. Are our processes documented and consistently followed?
  4. Do we have a single, reliable version of the truth?

If the answer to any of these questions is “no,” the priority should be improving data quality—not deploying more AI tools.

High-Quality Data Enables Trust and Adoption

AI systems only create value if people trust and use them. When employees see AI outputs that conflict with known realities or change unpredictably, confidence erodes quickly.

On the other hand, when AI is built on clean, well-governed data, the insights it provides align with business intuition and recommendations are explainable and defensible. This increases adoption of the tool across teams, and allows AI to become a decision-support tool rather than a black box.

Trust starts with data.

High-quality data is the real enabler of AI—turning automation into insight, predictions into action, and experimentation into sustainable advantage. For organizations serious about using AI in business, the path forward is clear: fix the data first. That’s where the competitive advantage will come from.

bunny feetMake Sense?

J

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Fix the Data, Then Let AI Scale It

For SMB’s Using Solutions like QuickBooks Online, Service Titan or Jobber, High-Quality Data Is Critical for AI

Many small and mid-sized businesses now run on a combination of operational and financial tools. A typical stack might be QuickBooks Online (QBO) for accounting plus Service Titan or Jobber for field operations. Noobeh helps these businesses centralize their data, making it available for analysis and AI.

What we increasingly find is that various AI vendors promise AI-powered forecasting, automation and insights, but AI does not create clarity on its own. When data across these systems is inconsistent or poorly structured, AI simply automates confusion. To get real value from AI, SMBs must first ensure their data is accurate, aligned, and trustworthy.

The Reality of Disconnected SMB Systems

For these small businesses, each system serves a different purpose. QuickBooks tracks financial transactions, revenue, and expenses, where Service Titan or Jobber manages the jobs, customers, technicians and billing. There may be problems lurking in these various systems, and it is often revealed when the data is centralized and made ready for reporting and AI-enabled analytics.

These problems arise when the same business concepts—customers, jobs, revenue, costs—are represented differently in each system. Common examples of this include jobs marked as complete in Service Titan or Jobber but not fully invoiced in QBO, or customers duplicated or named differently across platforms, or any situation where manual spreadsheet adjustments are needed to make the reports work.

Imagine training your AI on this data. It isn’t going to resolve the data issues or repair them, it will repeat them at scale.

A Practical AI-Ready Data Path for SMBs

Before deploying AI features across QBO, Service Titan or Jobber, our consulting teams help our clients focus on making sure the data is ready by cleaning and standardizing QBO financial data and ensuring jobs, customers, and invoices align across systems. Our cloud services team leverages Azure platform services to create automation and eliminate manual spreadsheets and workarounds. Then we centralize the data in Microsoft Fabric, creating a single source of truth allowing reports to be validated prior to laying AI on top. This approach turns AI from a grand experiment into a dependable business tool.

Trust Is the Real Measure of AI Success

AI only delivers value when business owners, finance teams, and operators trust the outputs. That trust comes from seeing numbers that reconcile, reports that make sense, and predictions that align with reality. When this alignment occurs through high-quality data, AI forecasts become credible and insights are explainable. Decision-making improves consistently.

Fix the Data, Then Let AI Scale It

AI can help SMBs compete with much larger organizations—but only when it’s built on a strong data foundation. QuickBooks Online, Service Titan, Jobber, and Microsoft Fabric form a powerful stack, but their value depends on data quality and alignment.

For SMBs, the winning strategy is clear: fix the data first, then let AI scale what’s already working.

jm bunny feetMake Sense?

J

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AI FOMO and Your Business

“AI FOMO” (Fear of Missing Out) has become a major force behind business adoption of artificial intelligence.

Rather than pursuing AI with a clear strategy, too many organizations are investing because of competitive pressure, media buzz, and fear of falling behind. This reactive approach often leads to rushed, expensive, and poorly executed initiatives that fail to create real value—and can even spark internal friction.

Surveys show that a large share of IT leaders and executives—sometimes more than 60%—acknowledge that FOMO significantly influences their AI adoption decisions. This fear is fueled by rapid technological change, assumptions that competitors are gaining an advantage, and limited understanding of what AI can and cannot actually do.

Implementing AI without thoughtful planning or alignment to business needs often results in wasted investments in tools that don’t address real problems. Projects may stall in the early stages or fail to produce any measurable benefit or return on the investment.

Among the biggest challenges with AI centers on data and trust.

When a business puts speed of development above quality and security, it can lead to data errors, AI “hallucinations” and just plain wrong answers that diminish trust in AI systems. Workers may already feel threatened or undervalued, which creates anxiety and slows tech adoption, so care must be taken to not prematurely introduce AI that may further erode trust in the technology.

I’ve always understood that technology isn’t just a tool, it can be a strategic advantage helping businesses gain in ways not previously available. The key is to move away from fear-based adoption and toward a deliberate, value-driven approach.

Start with identifying the real business problem. With AI, figure out what problems you need the technology to solve for you rather than asking what AI can do. Just because AI can do something doesn’t mean you want it to do it for you, or that it will deliver any real value to your process or operation.

Change for the sake of change makes no sense, so it is essential to understand if there is actually a problem that AI may be able to solve and that the benefits of the solution outweigh the cost to develop and the risk potentially introduced. Start small and have pilot projects in low-risk but high-impact areas of the business where the organization can learn and refine before scaling.

Among the most important aspects of AI in business is the data the AI works with. This is where many businesses fail in their initial attempts with AI development, due largely to the fact that data is siloed or segregated and completely unclassified or categorized.

For AI development to deliver effective business benefit, high-quality, organized data and solid data infrastructure are essential.

AI systems learn directly from the data they are given. If the data is incomplete, inaccurate, inconsistent, or poorly managed, the AI’s performance will reflect those flaws. AI models are only as good as their data because AI systems—especially machine learning and generative AI—identify patterns and make predictions based on training data.

Poor-quality data results in biased, unreliable, or incorrect outputs. High-quality data supports accurate, trustworthy, and consistent results. If an AI is trained on inaccurate or inconsistent information, it will learn (and repeat) those errors.

Shift from a fear of missing out to a fear of missing the advantages of AI.

The focus should be on maximizing AI’s potential to create a competitive advantage, taking strategic risks that are aligned with the business goals. Replace fear-driven decision-making with thoughtful, goal-oriented planning and turn AI into a meaningful source of long-term value and differentiation rather than an anxiety-inducing trend to chase.

Noobeh cloud services works on the Microsoft Azure platform, creating data platforms and delivering services that fuel and support AI development. Let us create the dynamic data infrastructure your business needs to develop the intelligence to propel you forward.

jm bunny feetMake Sense?

J

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Timing is Everything: Security, AI and the Tech Stack in Restaurants

Running a restaurant or chain of restaurants is no easy task. Margins are often razor thin while customer demands continue to expand. Food service, like so many other industries, is struggling to bear the weight of change as labor shortages, rising costs, increasing cybersecurity risk, and demands for an improved customer experience push the industry to do more efficient and effective business. To keep up, businesses must learn more about what’s really going on in the operation, and to turn that insight into action. Timing is everything, and now is the right time to look at technology and platforms which will deliver greater insight and intelligence.

Whether it is leveraging commercial solutions available from partners or through building the tech stack by DIY, businesses in the restaurant industry are looking for innovative solutions to drive more profitability as well as increasing revenues leveraging resources they’re already paying for. AI is playing a big role in this evolution and businesses of all sizes, from the single-location entrepreneur to the multi-location franchise, are taking steps to incorporate it into the operation. Yet AI is all but useless if it doesn’t have the data to analyze.

An example of a transformational solution for the restaurant industry might be Curbit’s products, which include digital infrastructure and real-time AI capabilities that enable the software to analyze the data around service, real-time order progress, kitchen performance and guess sentiment. Microsoft’s Azure and Azure AI platform is key to Curbit’s innovation and development, enabling them to give the information which powers timely decision-making rather than offering only after-the-fact reports or outdated dashboard data.

In the category of maximizing the resources you’re already paying for, look at new services available through DoorDash, where lunch special and happy hour promotional offerings help businesses drive demand in off-peak times. Designed to increase revenues and drive greater sustainability, the service also reflects how restaurants are increasingly faced with the need to leverage online tools and mobile ordering to replace the reduction in foot traffic at brick and mortar location.

On the other side of that coin is information security and privacy and how businesses deal with the realities of cybersecurity threats and the need for greater levels of protection. Collecting more data for analysis means there is an increased risk of exposing private data if not adequately protected.

Considering high profile incidents like what happened with Panera, adequate cybersecurity protections must be part of the essential infrastructure that supports the operation. What was initially described as a systemwide technical outage at Panera was ultimately found to have been a cybersecurity breach exposing some employee personal data and the basis for a class action lawsuit filed by Panera employees.  

Whether it belongs to employees or customers or others, personal and private data must be protected. The cost of protecting the data is likely lower than the cost of dealing with a data breach and the potential resultant backlash, which is another part of the equation which must be considered.

Mendelson Consulting and Noobeh cloud services recognize how businesses need to modernize their systems, developing greater intelligence and resilience in the operation. We also recognize the importance of redundancy and agility in systems, and how quality managed cybersecurity solutions and services help guard against attack.

From ERP and specialized business solutions to platform, hosting and managed service, Mendelson Consulting and Noobeh cloud services can help your business meet the demands of doing business now and in the future.

jm bunny feetMake Sense?

J