Tag: data

Posted on

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

Posted on

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

Posted on

Unlock KPIs and Improve Reporting with QuickBooks

It is surprising how many businesses still keep boxes of 3×5 ledger cards with customer and vendor information on them. More likely than the card box, the business may be storing its essential customer billing and vendor product information in the accounting system because that is the system they have.

These growing businesses need a better system to capture more information that delivers greater detail for accounting and reporting purposes. Just as likely, the business has other information it should and possibly could be capturing but isn’t sure about what steps to take next.

When details that inform a process are not part of an integrated system, it creates greater potential for lost or inaccurate data. The larger the volume, the more difficult and error-prone managing the information becomes.  

Business needs more detailed information about… everything.

Businesses may need to track time for payroll or jobs or both, job tracking may be a requirement, inventory tracking or more detailed inventory management may all be areas for greater attention. Mendelson Consulting can help develop these capabilities by making sure the business is using the right software, and then enabling the functionality needed to support the workflow and capture more and better data.

No data means no KPIs.

More and better data means more information to fuel KPI reporting. Key performance indicators can reflect operational performance in a variety of areas and may help identify where improvements are required.

Using data from the accounting and operational systems, businesses of all sizes measure their effectiveness using KPIs to evaluate the successes – or failures – of their processes and activities.

Mendelson Consulting’s team of QuickBooks Enterprise Experts and ERP consultants provide guidance, implementation and training, and report development to get beyond bookkeeping to proper processes that result in good accounting data. Mendelson’s cloud services team – Noobeh – sets it all up on Microsoft Azure, where data connectors, data warehouses and Microsoft Fabric weave it all together.

Whether just starting out or an enterprise or franchise expanding at a national or global level, we help businesses do more with their systems and software. We understand each stage of business and how to help our clients reach their next best level.

jm bunny feetMake sense?

J

Posted on

Mo Bigger Data

Losing valuable business data is a terrible thing. It is worse when it’s done on purpose. Every business faces changes in accounting or operational systems over the lifetime of the company and these changes more frequently than not include losing data of some type. And that means losing business intelligence.

The frustrations of changing business systems are compounded the further into the business life cycle the change comes. Much of the historic intelligence of the business is derived from the earlier days of operation. This is data which reflects the stages and activities of the business over time. When a business reaches a point where data volume or list sizes force a systems change, much of that early historic data is ultimately abandoned. There is so much data to load into a new system that the task often proves too daunting for the company, so valuable historic detail information is lost and summary information is loaded into the new system.

As a business matures, and for the business to mature in a healthy manner, specific and detailed information must be captured and analyzed. Software addressing a broad view of the business, offering only generalized functionality and basic process support, will not provide a growing business with the operational support and resultant business intelligence needed at this level.

For example, a manufacturing business needs to fully understand and manage the manufacturing processes and materials supply chain to ensure profitability and consistent product quality. A retailer needs to know which products sell in which markets to ensure product stock and availability to key customers. And all this information is time-critical if the business is to make necessary adjustments in time to benefit from them.

In the end, it is the demonstration of well-defined processes, deep insight into the business operational metrics and financial performance, and the ability to effectively and accurately report on this information that creates a basis for provable business value.

Mendelson Consulting understands how important it is to not just collect the right data to support various processes, but to use that data to better understand operational and financial performance. As operations grow, so does the need to collect data from a variety of possible sources, from phone systems to time clocks and more. Even getting data out of the accounting system can be a challenge, but there is tremendous value in having transparency of business data.

From data warehouses to data lakes, Power BI and data visualization, we help businesses access their information and develop reporting that not only informs but helps deliver greater insight which leads to improvements in performance and profitability.

When information is power, we help owners and stakeholders gain mo power by being mo better informed.

jm bunny feetMake sense?

J

Posted on

Data at Work: Intelligent Automation is Your Business Robot

Imagine having a business where connected systems are free-flowing conduits for data to move intelligently into and out of with ease. 

Software and systems connecting to one another isn’t new at all. For many years, businesses have recognized the value of having information entered in one system available in another.  Entire ERP frameworks have been created based on this concept of entering data once and using it in many ways.

A single technology stack or framework may offer such a capability, but even the most robust system may need to rely on expert systems or add-ons to address aspects of the operation.

When two or more systems need to connect, the idea is to create that connection and enable the unattended and intelligent movement of data.  People shouldn’t have to get involved for the information to flow from one system to another… it should just go by itself.  Like a robot.

A simple example might be someone who owns a web store and does their bookkeeping with QuickBooks.  The webstore isn’t running QuickBooks. It is running an e-commerce solution or shopping cart system. This allows customers to buy things online.  However, the webstore does create sales orders and charge transactions and may even manage an inventory of salable items.

Business owners often take on the task of getting the information from the webstore to QuickBooks and vice versa. They either enter the information manually themselves or hire an employee to do it.  This manual re-entry of information introduces a large potential for errors in the data entered and is time-consuming and costly.

If it is problematic for a small retailer, imagine having the problem multiplied many times over. It is unimaginable for even small businesses with active and growing operations. As the volume of data grows, the time consumed and the data entry error costs stack up.

“It was just awful,” said David Clothier, treasurer of the Knoxville, Tenn., company, which operates more than 500 Pilot Flying J truck stops nationwide. “There were humans everywhere.” wsj.com/articles/the-new-bookkeeper-is-a-robot-1430776272

Rather than having a person re-type the information from one system into another, software-based integration programs are generally available to help users map the data and move it from one solution to the other.  This approach is faster and reduces the error rate, increasing the overall value and usefulness of the information.

Automation isn’t the only requirement that makes this all robot-like.  The additional requirement is intelligence.  If people still must get directly involved for something to happen, then all the happening is still based on human performance. No robots here.

Intelligent integration of information occurs when the systems at both ends can make decisions and act on them. 

For example, a business might use a solution that allows vendors to submit their invoices electronically.  Through a base of rules that match invoices to requests and approvals, the system can issue payment and record the transactions automatically and without human intervention, saving hugely on personnel and processing costs.  Robots (the automation solution) wouldn’t make up all the rules but could follow them repetitively and without question once established.

…software can help businesses operate more effectively. “If you think like a human, there are only certain things you can do. When you think like a robot, many things are possible.” wsj.com/articles/the-new-bookkeeper-is-a-robot-1430776272

It isn’t a new paradigm for improving business operations, this doing of things a bit smarter than before and leveraging technology to get more done in less time.

The difference is that the pace of change is increasing, giving businesses less time to address inefficient processes and outmoded working models. Mendelson Consulting and the Noobeh cloud services team recognize that intelligent automation and integration shouldn’t be a one-time setup. Instead, we partner with clients to find the best solution to not only address today’s needs but tomorrow’s new demands.

jm bunny feetMake Sense?

J

Posted on

For Franchise Business, Platform Agility Helps Deliver Customer Value

In every corner of the franchise world, businesses are talking about growing value. Customers are pursuing lower prices and are spending less, and the competitive marketplace often pushes businesses into a race to the bottom. With pressures coming from all sides – rising labor and supply costs, inflation and the cost of capital, changes in consumer spending habits – franchise operations are looking for ways to differentiate themselves and delight customers while supporting profitability and growth.

Value is not simply a discounted price on an item. To the buyer, value is often found in the quality of the product or service, and fast friction-free transactions made without errors. New bundles of products and offering new add-ons may also improve the customer’s value perception. The introduction of online and mobile ordering and partnering with third-party delivery services is not only an enhancement to the customer experience but can open new revenue streams by reaching new customers and serving current customers better.

Understanding where changes might be made to not only improve value to the customer, but also to the business and stakeholders, is the challenge. Only through close monitoring of operational and financial data will businesses understand what adjustments are needed to achieve the desired results. Yet the complexities of data collection, integration and reporting often pose barriers to exposing the information needed to fully inform stakeholders.

Mendelson Consulting and Noobeh Cloud Services understand that many franchise organizations are faced with challenges in identifying, collecting, combining and reporting on their operational and financial data. Working with Microsoft Azure and having team members and partners experienced in working with a wide variety of financial and operational systems, Mendelson Consulting and Noobeh help businesses create the foundations for flexible, agile and massively scalable data collection, storage and analysis.

From standardizing accounting systems and processes to establishing data lakes and foundations for data analysis and reporting, Mendelson Consulting and Noobeh have the range of services and solutions and partners to help support new, established and fast-growing franchise operations. Its about delivering more value… to our clients and to theirs.

jm bunny feetMake Sense?

J