As it turns out, being the only man in the room wasn’t the embarrassing part. The real problem was discovering that somewhere over the last couple of decades, I seem to have lost all sense of rhythm.

That’s what happens when you finally get off the couch. You discover the real problem isn’t what you expected.

The same thing is happening with AI right now.

Leaders are making resolutions to “figure out AI,” but most are approaching it the same way people approach the gym in January: without a framework. They dabble, feel overwhelmed, try random things without a plan, and eventually conclude they’ll revisit it later when the technology is “more mature.”

After 24 weeks documenting my own AI journey, I’ve realized the biggest shifts aren’t about tools or technology. They’re about mindset.

The two types of leaders I keep meeting

Over the last few months, I’ve noticed two distinct groups of leaders struggling with AI adoption.

The first group has been experimenting personally for a while. They summarize documents, draft emails, maybe brainstorm ideas occasionally. They understand AI can improve personal productivity, but they can’t connect those experiences to business strategy. When leadership asks about AI direction, they default to vague language like “we’re evaluating opportunities.”

The second group is already organizationally committed. They’ve approved pilots, purchased licenses, and declared AI a strategic priority. But they’re overwhelmed by competing ideas, vendor pitches, webinars, and LinkedIn hot takes. They have activity without clarity.

What both groups have in common is this: they’re trying to skip the part that matters most.

The first group is waiting for organizational clarity before building personal mastery. The second group is trying to drive organizational transformation before experiencing personal transformation. Both approaches fail for the same reason:

You cannot lead what you haven’t experienced yourself.

The principle that changes everything

The single most important thing I’ve learned over the last 24 weeks is this: personal transformation before organizational transformation.

You don’t need to become a technical expert. But you do need enough firsthand experience to distinguish real capability from hype. You need your own stories of what worked, what failed, and where AI genuinely changes how work happens.

The leaders who will separate themselves this year won’t necessarily have the biggest budgets or the most aggressive strategies. They’ll be the ones who put in the reps personally.

Everything else builds from there.

Shift 1: From search engine to thinking partner

Most people still use AI like Google with better grammar. They ask a question, get an answer, decide whether it’s good enough, and move on. When the response disappoints them, they conclude AI isn’t ready for serious work.

That’s like walking into a gym, failing to bench press 200 pounds on day one, and deciding weightlifting doesn’t work.

The real breakthrough happens when you stop treating AI like an answer machine and start treating it like a thinking partner.

AI works best through dialogue. Context matters. Iteration matters. Pushback matters. The shift happens when you stop asking isolated questions and start having conversations: explaining your goals and constraints, refining responses collaboratively, challenging shallow answers, and letting the interaction evolve.

You know you’ve made this shift when you stop judging AI by its first response and start building on it instead.

Shift 2: From waiting to exploring

Once you know how to think with AI, the next shift is learning what to explore.

Most leaders are waiting for the obvious use case — the one so compelling and risk-free that adoption becomes automatic. I don’t think that moment is coming.

The best opportunities are usually hidden behind frustrations you’ve normalized: broken processes, recurring annoyances, inefficiencies everyone has learned to tolerate because “that’s just how it works.”

The shift happens when you stop waiting for AI to prove itself and start bringing your frustrations to AI as diagnostic conversations.

Not: “How do I automate this?”

But: “What’s actually broken here?”

One of the most valuable techniques I’ve discovered came from adapting a medical diagnostic framework: start with the chief complaint, let AI ask systematic questions, and look for the unlocking moment where your understanding of the problem changes.

That’s when real progress starts. You know you’ve made this shift when you stop accepting friction as normal and start investigating it instead.

Shift 3: From consumer to creator

This was the most profound shift for me personally.

For years, I searched for better tools, better apps, better integrations. When I couldn’t find exactly what I wanted, I assumed building it myself would be too expensive, too technical, or too time-consuming.

Then I used AI to solve a 20-year frustration with my personal task management system in less than a week. Not by finding the perfect software. By creating exactly what I needed.

That changed how I think about capability entirely.

You no longer have to wait for someone else to build the exact solution you want. AI dramatically lowers the barrier between identifying a problem and prototyping a solution.

That doesn’t mean everyone needs to become a developer. It means leaders can now describe what they want in plain language, iterate rapidly, and test ideas before making formal investments.

You know you’ve made this shift when the question changes from “Does this exist?” to “How could I build this?”

The sequence matters

These shifts build on each other.

You can’t create solutions until you’re exploring meaningful problems. You can’t explore meaningful problems until you know how to think with AI collaboratively.

Most organizations try to skip straight to enterprise transformation without building leadership literacy first. That’s why so many AI initiatives produce activity without meaningful change.

The sequence matters because the mindset matters. And the mindset has to become personal before it becomes organizational.

Your Week 25 challenge

This week, identify one frustration you’ve been living with for a long time. Something small, personal, and fully within your control.

Then spend 30 minutes talking to AI about it. Not asking for solutions. Diagnosing the problem.

Let AI ask questions. Push back on shallow answers. Explore the issue until your understanding changes.

Because that’s the real goal at this stage. Not mastering AI. Learning how to think differently with it.

The year ahead

Twelve months from now, there will be two kinds of leaders.

The first group will spend the year waiting for clearer use cases, better tools, more mature technology, or someone else to figure it out first.

The second group will spend the year experimenting, learning, building literacy, and discovering opportunities hidden inside frustrations they’d stopped noticing.

The difference between those groups won’t be technical skill. It will be whether they were willing to get off the couch and start learning before they felt ready.

This post is part of my “AI Over 40” series. It first appeared on LinkedIn: AI for the Over 40 [Week 25]: The Three Shifts That Actually Matter

Read more AI and Copilot blogs.

The post AI for the Over 40 – Week 25: 3 Shifts for AI Leadership Transformation appeared first on ArcherPoint.

Why dealership management systems and equipment rental management software matter more than ever

As operations grow more complex, disconnected tools create inefficiencies that are hard to detect but expensive to ignore. Revenue leakage, poor visibility, underutilized assets, and inconsistent processes often stem from systems that were never designed to work together.

This is especially true for multi-branch organizations managing high-value equipment across rental, sales, and service lines. What worked at a smaller scale begins to break down as operational complexity increases.

The complexity challenge in dealer and rental operations

Equipment dealer and rental, sales, and service businesses rarely fit neatly into a single operational box. An organization might sell new equipment, rent short- and long-term assets, provide field service and maintenance, manage large parts inventories, and operate across multiple branches or regions. Each of those activities introduces its own workflows, data requirements, and financial implications.

Historically, many companies have addressed this complexity by layering systems on top of one another. A legacy ERP handled accounting. A rental module or third-party tool tracked contracts. Service teams relied on separate systems or spreadsheets. Inventory lived somewhere else entirely. Over time, these disconnected systems became “good enough” simply because they were familiar.

The problem is that what once worked at a smaller scale breaks down as volume, asset count, and customer expectations increase. Too often, leadership teams realize this breakdown is occurring only after it has started affecting profitability.

The visibility gap in disconnected dealership management systems

One of the most common frustrations among dealer and rental executives is the inability to see what is actually happening across the business in real time. Leaders know revenue is coming in and costs are going out, but understanding why performance looks the way it does is far more difficult.

Questions that should be simple to answer often require manual effort, reconciliation, or delayed reporting. Executives want to know which assets are underutilized, which branches are driving margin, where service backlogs are forming, and how rental performance compares across regions. Instead, they are handed reports that are already outdated by the time they are reviewed.

This lack of visibility is rarely caused by a lack of data. Dealer and rental organizations generate enormous amounts of operational information every day. The issue is that the data is scattered across systems that do not speak the same language. When sales, rental, service, parts, and finance each operate in silos, leadership loses the ability to make fast, confident decisions.

A modern dealership management system addresses this by creating a single operational and financial foundation. Instead of relying on after-the-fact reporting, leaders gain access to live, role-specific performance views. The goal is not more dashboards for the sake of dashboards, but to have a shared understanding of what is happening across the organization and where attention is needed most.

How equipment rental management software reduces revenue leakage

Rental revenue leakage is one of the most damaging issues in the industry. It emerges through dozens of small inconsistencies that feel manageable in isolation:

• Equipment might be returned late without triggering additional charges.
• Damage might be noted but never billed.
• Contract terms might be interpreted differently across branches.
• Discounts might be applied manually without clear approval rules.

Over time, these small gaps add up to significant lost revenue.

What makes revenue leakage especially dangerous is that many organizations underestimate its impact. Without a clear way to quantify what is being missed, leaders assume the losses are minimal or unavoidable. In reality, even modest leakage percentages can translate into substantial annual losses for organizations with large fleets.

Modern equipment rental management software reduces leakage by being consistent. Automated contract enforcement, standardized pricing logic, precise time-based billing, and integrated inspection workflows ensure that what should be billed actually is. The result is improved margin protection without sacrificing customer relationships.

Moving from reactive to proactive maintenance with modern systems

Few issues frustrate rental customers more than equipment that is unavailable or unreliable. Downtime directly affects customer trust and repeat business, yet many dealer and rental organizations still operate in a largely reactive maintenance model.

In these environments, service teams are often stretched thin, maintenance schedules are tracked manually, and asset history is fragmented across systems. Equipment is serviced when it fails rather than when data suggests it should be. This approach may feel manageable in the short term, but it inevitably leads to higher repair costs, reduced asset lifespan, and lost rental opportunities.

The most effective dealer management platforms help organizations move along a maintenance maturity curve. Planned maintenance becomes systematic rather than discretionary. Service teams gain visibility into asset usage, service history, and upcoming needs. This shift from reactive to planned maintenance not only improves fleet availability but also fundamentally changes how organizations think about asset value and lifecycle management.

How a dealership management system improves equipment utilization

Equipment utilization sits at the center of rental profitability, yet it is often misunderstood or inconsistently measured. Many organizations track utilization at a high level but struggle to connect it to financial outcomes or operational decisions.

Without clear utilization insight, leaders may hold onto underperforming assets too long, invest in equipment that does not align with demand, or overuse assets without sufficient maintenance planning. Utilization data that lives in isolation rarely drives meaningful action.

When utilization is integrated into a broader dealer management platform, it becomes far more powerful. Leaders can see utilization trends by asset type, branch, customer segment, or contract type. They can connect usage patterns to maintenance costs, downtime risk, and margin performance. This enables more informed decisions about fleet composition, asset redeployment, and capital investment. Utilization stops being a static report and becomes a strategic planning tool.

Parts inventory optimization with integrated dealer management systems

Parts management is another area where operational friction quietly erodes performance. Parts departments constantly navigate trade-offs between availability and carrying costs. Overstocking ties up capital and increases the risk of obsolescence, while understocking leads to service delays and emergency purchases.

In many organizations, parts inventory decisions are based on historical habits rather than real usage data. Service teams might not have clear visibility into inventory levels, and inventory planners might not fully understand upcoming maintenance demand.

Integrated dealer management solutions that include parts management connect inventory directly to equipment data and service operations. This alignment allows organizations to forecast demand more accurately based on actual asset usage and maintenance patterns, reduce excess stock, and ensure critical parts are available when needed. Over time, this improves both service efficiency and financial performance.

Scaling multi-branch operations with standardized systems

Growth is often a sign of success, but for dealer and rental organizations, it introduces new challenges. As branches multiply, processes naturally diverge. Local teams develop their own pricing, service, and customer management strategies. While this flexibility can be valuable, it often leads to inconsistency, data quality issues, and governance challenges.

Leadership teams struggle to compare performance across branches or roll out improvements consistently. Training new employees becomes more difficult, and best practices remain isolated rather than shared.

Modern platforms address this by standardizing core processes while still allowing for controlled local variation. Pricing rules, workflows, and data structures are consistent across the organization, making performance easier to measure and improve. At the same time, branch-level nuances can be accommodated without undermining governance. This balance is essential for organizations that want to scale without sacrificing control.

Improving customer experience with connected rental and dealer platforms

Customer expectations in the rental and dealer space have evolved. Customers want fast, accurate quotes, clear availability information, transparent billing, and reliable service timelines. When internal systems are fragmented, delivering a consistent experience becomes difficult.

Delays, errors, and miscommunication are often symptoms of internal complexity rather than poor customer service intent. When sales, rental, service, and billing are not tightly integrated, customers feel the friction immediately.

Dealer management and rental process platforms that unify these functions enable smoother customer journeys. Quotes convert to contracts more quickly. Availability is accurate. Service updates are reliable. Billing aligns with expectations. Over time, this operational excellence becomes a differentiator that drives loyalty and repeat business.

Technology readiness assessments: Know when to upgrade your dealership management system or rental software

Many modernization journeys begin not with a software search but with a realization: Existing systems no longer support the business. Leaders notice that reporting takes too long, manual workarounds are multiplying, and scaling is harder than it should be.

Technology readiness assessments often surface these issues clearly. They reveal where systems are fragmented, where processes are overly manual, and where growth is being constrained. Just as importantly, they help organizations understand what to fix first. For dealer management and rental process companies, these assessments are powerful tools because they align technology conversations with real operational pain rather than a list of features.

From disconnected tools to unified platforms

The most successful dealer and rental organizations are no longer thinking in terms of individual tools. They are investing in platforms that unify operations, finance, assets, and analytics on a shared foundation.

This platform approach enables faster improvements, stronger governance, and better long-term scalability. Instead of constantly integrating new point solutions, organizations build on a core system that evolves with the business. For dealer management and rental process providers, this shift represents both a challenge and an opportunity to move beyond transactional software delivery and become strategic partners in operational transformation.

Choosing the right dealership management system and equipment rental management software

The pressures facing dealer and rental organizations are not going away. Asset costs will continue to rise. Customers will continue to expect more. Competition will continue to increase. What is changing is the ability to address these pressures proactively. Modern dealer management and rental process platforms give organizations the tools to reduce friction, protect margin, and scale with confidence, with features that include:

Unified financials and operations ➜ Brings all core business functions into a single system, eliminating data silos and enabling faster, more accurate decision-making.

Real-time asset tracking ➜ Provides instant visibility into asset location and status, improving utilization, availability, and customer responsiveness.

Automated billing and contract enforcement ➜ Ensures accurate, consistent invoicing by automatically applying contract terms, reducing revenue leakage and manual errors.

Maintenance scheduling and service history ➜ Enables proactive service management by tracking maintenance needs and asset history, reducing downtime and extending equipment life.

Multi-branch support ➜ Standardizes processes across locations while maintaining centralized control, making it easier to scale operations without losing consistency.

Reporting and analytics ➜ Transforms operational data into actionable insights, helping leaders identify trends, optimize performance, and drive profitability.

Take the next step

For companies serving the equipment dealership and rental market, operational excellence becomes a competitive advantage. ArcherPoint specializes in helping equipment dealers and rental companies modernize with Microsoft Dynamics 365 Business Central, unifying rental, sales, service, parts, assets, and financials into one scalable platform. The result is clearer visibility, stronger margin protection, and a foundation built for multi-branch growth.

Let’s evaluate where your current systems stand and identify practical next steps toward operational excellence. Take the Dealer Technology Readiness Assessment or contact ArcherPoint by Cherry Bekaert to learn more.

And be sure to download our white paper, RPM: A Recipe for Success For Dealerships that Rent, Sell, & Service Equipment.

The post Equipment Dealer and Rental Process Management: How Modern Platforms Can Help Remove the Friction That Erodes Profitability appeared first on ArcherPoint.

Why old-school tax compliance is now a business liability

For decades, tax compliance operated on a simple model — sell a product, calculate the taxes owed, and file a return with the appropriate agency after the fact. This “file and remit later” approach is rapidly becoming obsolete. Governments worldwide are aggressively digitizing their tax administrations, moving to a model that provides real-time visibility into business transactions.  

The global shift to real-time reporting and e-invoicing

The new global standard adheres to Continuous Transaction Controls and mandatory electronic invoicing (e-invoicing). Instead of waiting for a quarterly or annual filing, tax authorities now require the submission of transaction data for clearance as it occurs. 

More than 60 countries have already adopted some form of e-invoicing, with more announcing their own unique mandates every year. Even the U.S. government has a mandated e-invoicing framework for its own intra-governmental transactions, signaling the inevitable direction of domestic policy.

The importance of getting it right

In this new environment, a compliance failure is no longer a simple billing error that your company can correct later. If your invoice doesn’t meet a country’s specific e-invoicing format, the government can reject the platform, which could mean your shipment can’t leave the warehouse, the customer doesn’t receive their goods, and your company doesn’t get paid. 

Because a failed audit can lead to frozen shipments, damaged customer relationships, and a significant distraction for the entire executive team, tax compliance ERP selection is a critical factor in mitigating operational risk.

Native ERP tools vs. specialized tax engines

This regulatory shift creates a core dilemma for any company implementing a new ERP. You must decide which architectural path to take. Should you rely on the tax modules included with your ERP, or integrate a specialized, third-party tax engine? The answer depends entirely on your business’s specific circumstances.

Assessing the capabilities of native ERP tax modules

A modern ERP is a comprehensive, connected, and integrated tool that includes native tax capabilities. These modules are excellent for managing tax schedules, applying rates for a limited number of jurisdictions, and running basic reports.

For a business that operates in a single location with a simple product or service offering, this functionality is often sufficient. However, these native tools generally rely on ZIP codes for rate calculations, which can be inaccurate, and they typically require manual updates to keep pace with changing rules.

Identifying the tipping point for a third-party solution

A specialized third-party tax engine, often called ERP tax software, offers a more complex alternative. These solutions plug into your ERP and take over the entire tax calculation and compliance process. They maintain a constantly updated database of thousands of tax jurisdictions, handle complex product taxability rules, automatically manage exemption certificates, and can even automate the filing and remittance process. 

The tipping point for needing such a solution arrives when the complexity of your business operations outpaces what your internal team can reasonably manage with native tools.

A framework for choosing your path

To determine the right path for your business, you don’t need to be a tax expert. You need to answer four strategic questions about your operations and risk tolerance.

1. How complex is your sales and use tax nexus?

For businesses operating in the United States, “nexus,” the connection between your business and a state that obligates you to collect and pay sales tax, is complex. With thousands of sales and use tax jurisdictions, each with its own rates and rules, manual management poses a significant risk. If your business sells into multiple states and municipalities, a specialized engine that provides rooftop-accurate calculations is a powerful risk management tool.

2. Are you selling internationally?

If your growth plan includes international sales, the compliance burden becomes more complex. If you plan to operate globally, you must have a strategy for handling the unique, nonnegotiable compliance formats in each country.

3. What is your internal team’s capacity and expertise?

Be realistic about your team’s bandwidth. Your finance and IT professionals are likely already stretched thin managing the core ERP implementation. A third-party solution offloads this burden, freeing your team to focus on high-value strategic activities.

4. What is your actual tolerance for compliance risk?

Ultimately, this decision comes down to risk. Can your business tolerate a scenario in which shipments are held up at a border due to an incorrect invoice format? Do you have the resources to manage a lengthy audit from a foreign tax authority? 

Viewing compliance as a vital element of your business continuity plan helps clarify the decision. For many organizations, the cost of a specialized tax engine is a small insurance premium to pay to protect against major operational and financial disruptions.

Your ERP is a platform, not a total solution

Choosing and implementing a new ERP is one of the most important strategic decisions a company can make. A modern system like Microsoft Dynamics 365 Business Central provides the essential, unified platform for your entire operation. 

However, for a growing business in today’s complex regulatory world, the ERP is only the foundation. The right ERP tax compliance strategy depends on your unique nexus footprint, global ambitions, internal capacity, and risk tolerance.

Build a tax strategy that fits your business

Making the right choice between native ERP tools and a specialized, integrated tax engine requires a clear-eyed assessment of your specific needs. One of the most critical success factors in any ERP implementation is selecting the right ERP partner who can provide guidance on these strategic decisions.

If you are navigating these questions as part of your move to Business Central, ArcherPoint can help. We will collaborate with you to analyze your operational profile and build an ERP tax software and compliance strategy that ensures your new system is a platform for growth and a shield against risk.

Contact us to talk to an expert today.

The post How Tax and Compliance Planning Ties to Your ERP Choice appeared first on ArcherPoint.

The Dynamics 365 Business Central community, comprising developers, project managers, and consultants, collaborates across platforms to share valuable insights. At ArcherPoint, we greatly value their dedication and expertise. To ensure widespread access to this technical knowledge, we created Developer Digest.

Building development teams focused on quality

After facilitating a panel session at Directions North America in April, Matt Traxinger decided to launch a new series focused on the question, “How do you build a team that writes good software consistently, in an industry where almost everything rewards shipping and almost nothing rewards structure?”

The problem with many software projects, especially those that center on a niche product and development environment like Business Central, is that developers, including those at Microsoft, have made technical decisions based on reasonable information at the time that have led to development constraints further down the line. Every developer makes these types of decisions, and they are not always wrong.

As Traxinger puts it, “The question is whether those decisions, rational when they were made, still make sense now that the constraints have shifted. Sometimes the answer is yes. Sometimes it’s more uncomfortable than that.”

The series will attempt to go beyond the technical questions and best practices and instead focus on “how do you build a team that writes good software consistently; how do you create conditions where quality is the default; and hold open the possibility that some of what looks like a problem is actually a reasonable adaptation to circumstances that haven’t changed as much as they appear to have.”

Check out Matt’s first installment, We Know What the Problems Are, on LinkedIn.

An LLM is NOT all there is to AI

In a recent blog post, Stefano Demiliani takes a hard look at bringing AI into the real world. Demiliani quotes these disturbing statistics:

• Around 60/70% of enterprise AI projects fail.
• Only around 5% of AI pilot programs achieve rapid revenue acceleration.
• The average organization scrapped around 40% of AI proofs of concept before they reached production.

These statistics reveal a problem with the way AI projects are developed. Demiliani stresses that customers are running a business – they don’t want a demo or proof-of-concept, they want a reliable, auditable product.

As he puts it, “[Customers] care about ROI, not about using the latest fancy AI tools. Does this AI system make them money, save them time, or reduce risk?”

He offers a list of what customers should be able to expect from an AI project:

• Respects their data governance policies and security boundaries.
• Integrates with existing systems that predate modern cloud architecture.
• Handles edge cases, exceptions, and domain-specific logic that no prompt can address.
• Operates reliably at scale, not as a prototype that works once.
• Logs decisions, maintains audit trails, and supports compliance requirements.
• Behaves consistently even when the LLM’s behavior drifts.

Demiliani goes on to discuss how developers can build reliable AI agents for their customers.

Read more in his blog, Why Customer’s AI project fail? The gap between hype and reality.

NuGet: Get symbols without having a BC instance running

New in the AL tools in Visual Studio is NuGet, a way to get symbols without a Business Central instance running.

Using the command, AL: Download Symbols from Global Sources, developers can download symbols directly from public NuGet feeds from Microsoft or from custom feeds.

In addition, the AL.symbolsCountryRegion setting allows you to provide localization (for example, us for the U.S., ca for Canada, de for Germany, or w1 for worldwide) instead of relying on the connected tenant’s localization.

This new feature makes it easier for developers to download symbols that match your current Business Central version.

To learn more, read the blog, Download Symbols From a NuGet Feed, by Brad Prendergast, or watch Erik Hougaard’s video, Get Your Symbols via NuGet like a Pro!

Are you interested in Dynamics NAV and Business Central development? Check out our collection of NAV/BC Development Blogs.

Read “How To” blogs from ArcherPoint by Cherry Bekaert for practical advice on using Microsoft Dynamics NAV and Dynamics 365 Business Central.

The post Dynamics Business Central / NAV Developer Digest – Vol. 553 appeared first on ArcherPoint.

In this client testimonial, ONICON shares how they approached their NAV 2017 to Business Central migration and why working with an experienced partner helped them navigate the process with confidence.

Planning a Dynamics NAV to Business Central SaaS migration

ONICON, a fast-growing manufacturer of precision flow meters used globally in the HVAC industry, had been running Dynamics NAV 2017 for years.

As part of their modernization strategy, they planned a move to Business Central in the cloud to:

• Align ERP with their existing cloud-based CRM
• Improve data sharing across systems
• Leverage Power Platform tools and integrations
• Support long-term scalability

After evaluating multiple partners, ONICON selected ArcherPoint for its migration experience and structured approach.

A structured ERP migration process

From the outset, ArcherPoint guided ONICON through a detailed assessment process, including:

• Reviewing existing add-in vendors and solutions
• Evaluating compatibility with Business Central
• Identifying where replacements were needed

During the migration, the team:

• Converted NAV customizations into AL code
• Executed data migration and multiple mock go-lives
• Refined processes based on real-world testing

The process was highly collaborative, with ongoing communication between ONICON’s team, the project manager, and ArcherPoint’s lead developer.

Reducing risk during ERP migration

ERP migrations rarely go exactly as planned—and ONICON’s experience reinforced the importance of preparation and expertise.

During the final migration weekend, a configuration issue arose while connecting Business Central to CRM—something that hadn’t appeared during testing.

Rather than delay the project, ArcherPoint’s team worked alongside ONICON for several hours to troubleshoot in real time. The lead developer ultimately identified a solution outside the standard interface, enabling the migration to proceed successfully.

This level of responsiveness underscores the value of working with a partner who understands both the process and the potential risks.

A long-term ERP partnership

Beyond the migration itself, ONICON emphasized the importance of working with a partner they could rely on throughout the process

ArcherPoint was consistently:

• Responsive and easy to work with
• Collaborative throughout the project
• Invested in the success of the implementation

Over time, the relationship evolved beyond a typical vendor engagement—becoming a trusted partnership built on communication and shared goals.

Watch the client testimonial

If your organization is planning a Dynamics NAV to Business Central migration, learning from companies that have successfully navigated the process can help you avoid common pitfalls and move forward with confidence. Reach out to ArcherPoint by Cherry Bekaert to explore how an experienced migration partner can support your transition.

Video Transcript

My name is David Stevenson from ONICON Incorporated. I’m a Senior Software Developer there. We’re located in Largo, Florida.

ONICON is a manufacturing company. We make precision flow meters and other measurement tools that are used extensively in the HVAC industry. Our products are installed all over the world. We’re a fast-growing company.

I started as a consultant with ONICON for about three years, and then I went full-time almost 16 years ago.

We were looking at moving from NAV 2017 to Business Central in the cloud. We assessed that whole process, and I had heard ArcherPoint make a presentation at one of the conferences about their migration process. That was very impressive to us.

We looked around and evaluated other options, and then decided to make ArcherPoint our partner for our migration effort because of their experience in doing so many migrations.

From the very beginning of our migration project, ArcherPoint was very methodical in taking us through the steps. They had a very good assessment process at the start. They helped us review all of our add-in software vendors and the products we were using in NAV to determine how they would translate into Business Central.

We ended up having to replace a couple of vendors that didn’t have a Business Central solution, and ArcherPoint helped us through that process.

When we got into the actual migration, their migration team took all of the many customizations we had done in NAV and worked through them over a period of several months. They converted them into AL code for Business Central.

They then completed the initial data migration and our first mock go-live. Through that process, we assessed the weaknesses and things that weren’t working exactly as expected, or areas where Business Central worked a little differently from NAV.

It was a great collaborative effort back and forth between our team, the project manager, and the lead developer who was handling the migration coding work.

We had a lot of communication with the ArcherPoint lead developer, who was very responsive and provided quick turnaround on the items we needed adjusted.

We completed a second mock go-live, made a few more refinements, and then the actual go-live weekend went very smoothly.

We had already migrated our CRM to the cloud, and it seemed like the logical next step. We were still running on the original release version of NAV 2017 and had not made significant changes to it aside from a few communication updates.

We wanted to move BC onto the same online platform as CRM so we could take advantage of Power Apps, Power Platform tools, and collaborative features to transfer data between the two systems more easily than we could on-premises.

What stood out to us was the friendliness of the employees, their helpfulness, and their responsiveness to our needs—especially during the migration.

One example stands out. On migration weekend, when we were finishing configuration of our connection to CRM, the setup screen in BC got stuck in an incorrect configuration. That issue had not occurred during our mock go-lives.

They stayed up with us for several hours that night while we were close to pulling the plug. The lead developer found a way to make the necessary configuration change outside of the user interface and ultimately salvaged the project.

We were delighted to have resources who were so knowledgeable and able to solve problems on the spot to help us get through that weekend successfully.

Yes, I would definitely recommend ArcherPoint. Their knowledge of migrations in particular is unsurpassed.

They’ve completed so many migrations and have the depth of experience and understanding of what can go wrong—and what likely will go wrong if certain steps aren’t taken first.

I would highly recommend ArcherPoint for anyone looking to change partners or begin a migration project.

We’ve developed a strong working relationship with several people on the ArcherPoint staff. It’s become more than just a business relationship—it feels more like a friendship—and we value that very highly.

The post Dynamics NAV to Business Central Migration: ONICON’s Cloud Journey appeared first on ArcherPoint.

The result is often:

• Lots of activity, but little insight into what actually engages with students
• Frustrated students who don’t know where to go for information or which tool to use
• Staff and student leaders who spend more time managing systems than engaging students

This blog will help you visualize your engagement technology stack, understand how the pieces should work together, and identify gaps, overlaps, and missed opportunities.

Why student engagement tools often fail

Student engagement software initiatives rarely fail because of a lack of effort. They fail because of fragmentation.

Over time, many Student Unions adopt tools incrementally, adding platforms for events, email campaigns, club management, voting, surveys, and web portals as needs arise. Each system may function well on its own, but without intentional integration, they create operational silos.

This fragmentation introduces several challenges:

Disconnected platforms limit visibility

When engagement data is spread across multiple systems, leadership cannot see a unified view of student participation. Event attendance, voting activity, and communication performance are tracked separately, making it difficult to identify trends, measure representation, or justify investment decisions.

One-way communication replaces an engagement strategy

Mass email and social messaging might distribute information, but without integration with participation data, communications cannot be targeted, measured, or optimized. Engagement becomes reactive rather than data-driven.

No measurable engagement outcomes

Without a connected data foundation, Student Unions struggle to answer fundamental questions:

• Which activities build sustained involvement?
• Which student segments are underrepresented?
• Which programs generate long-term leadership participation?
• How does engagement correlate with retention or campus outcomes?

For university administrators and IT leaders, this is more than an operational inconvenience. It limits strategic planning, weakens reporting credibility, and increases reliance on manual data reconciliation.

Engagement technology must function as a system that integrates identity, participation, communication, and reporting so activity becomes measurable and insight becomes actionable.

Core components of an engagement stack

A healthy engagement stack isn’t a single tool. It’s a connected system made up of these core components:

Student data and profiles

This serves as the foundation and should include:

• Basic student identity and role information
• Participation history (events, clubs, leadership, voting, etc.)
• Status, preferences, and eligibility

This data should not live in multiple systems.

Communication channels

This includes:

• Email
• Text notifications
• App or portal announcements
• Targeted messaging

The goal is not more messages. Instead, the goal is relevant, timely, targeted communication based on real engagement data.

Event and activity management

This includes:

• Event creation and promotion
• Registration and attendance tracking
• Club meetings and activities
• Volunteer and participation tracking

This is where engagement actually happens.

Feedback and voting

This includes:

• Surveys and polls
• Elections and referendums
• Feedback forms and issue reporting

These tools close the loop between participation and voice.

Reporting and Analytics

This is where strategy is informed of:

• Participation trends
• Engagement by segment
• Retention of involved students
• Impact of events and programs

Without this layer, engagement is just activity, not strategy.

How the tools should connect

A modern engagement stack should work as a system, not a collection of apps.

Data should flow between systems

• Event attendance should update student profiles
• Voting and surveys should enrich engagement history
• Participation data should drive communications

There should be a single source of truth

Leadership should have access to one source where they can see:

• Who is involved
• How are they involved
• How engagement changes over time

Engagement insights should span activities

You should be able to answer:

• Which events engage the students most?
• Which channels actually drive turnout?
• Which groups of students are underrepresented?

Questions to ask before adding new tools

Before adopting another platform, ask:

• Will this integrate with what we already use?
• Who owns the data, and where does it live?
• Will this reduce complexity or add to it?
• Can students actually find it and use this tool?
• Does this tool improve insight or just add activity?

If a tool doesn’t strengthen the overall system, it usually weakens it.

Find out more

ArcherPoint helps student unions and associations identify gaps in their student engagement systems. If you want help integrating your engagement systems and designing a connected architecture, ArcherPoint can help you:

• Map your current engagement stack
• Identify integration gaps and risk areas
• Design aligned engagement and operations platforms
• Build phased roadmaps tied to institutional outcomes

Contact ArcherPoint by Cherry Bekaert to schedule a free assessment and start building a modern, resilient student engagement strategy.

The post Designing a Connected Student Engagement Technology Stack appeared first on ArcherPoint.

As we have started helping clients move from AI literacy to organizational transformation, I have seen the same trap appear again and again. It is easy to fall into, and we nearly fell into it ourselves. I call it the solutioning trap.

The solutioning trap

Here is how it usually works. A client identifies a process they want to automate with AI. They describe the outcome they want, and sometimes they even specify the technology they think should be used. The consultant, eager to help, starts building toward that specification.

The problem is that nobody has yet validated whether the proposed approach is the right one. Nobody has tested whether the AI can actually do what everyone assumes it can do. Nobody has uncovered the blind spots in how the challenge was originally framed.

So the team starts building, and once that happens, they are committed. Time and money get invested before the approach has been proven. If the solution turns out to be wrong, the work has to be discarded and the process starts over. That is what the failure rate looks like in practice. It is not usually incompetence. It is building too early.

The moment I pumped the brakes

A few weeks ago, a client approached us about automating their quoting process. They had done a lot of homework and had even used AI to generate a detailed requirements and solution document.

Our consultant did what many good consultants naturally do: he started testing approaches to validate the client’s vision. By the time I found out, we were already moving toward proving the client’s proposed solution before we had even signed a statement of work. That is when I stepped in and pumped the brakes.

The pushback was understandable. The client had told us what they wanted. They had handed us a spec. Why not just build what they asked for?

Because with AI projects, that frame is usually wrong. Our job is not simply to build what the client requests. Our job is to determine whether what they are asking for is actually what they need. That means validating multiple approaches, surfacing blind spots, and resisting technology lock-in before we know what works.

That conversation pushed me to formalize something I had been learning from Dr. Jules White at Vanderbilt University. He calls it Conversation First Prototyping. I have adapted it to what I think most people will understand more clearly: Chat First Prototyping.

The chat first prototyping framework

The core idea is simple: before you build anything, manually prototype the solution inside a chat interface. The consultant acts as the orchestrator, moving step by step through the workflow with AI, validating each part before anyone writes code or builds automation.

This approach breaks into three phases.

Phase 1: discovery and validation

This begins like a traditional discovery effort. You observe the current process, document how work actually happens, and understand the real workflow instead of the idealized version.

But then you add something critical: chat-based testing. The consultant manually runs the proposed steps through an AI chat interface to see what actually works. In the quoting example, that might include testing whether the LLM can extract the right information from customer service transcripts and contracts, transform that information into something usable, and match customer requests against contract terms to generate options and pricing.

Each step is validated in chat before anyone writes a line of code. That process exposes issues early—security and permission gaps, bad data formats, unrealistic expectations about model capability, or process steps that do not work the way people assumed. The deliverable from this phase is not software. It is validated knowledge: what works, what does not, and what should actually be built.

Phase 2: vibe code prototype

Only after Phase 1 do you build anything. And even then, the first build is a prototype. Using natural language and AI-assisted coding, you create a working proof of concept based on what has already been validated.

This keeps the work fast and relatively low-cost. The goal is not production readiness. The goal is to prove that the validated workflow can function when automated.

Phase 3: refinement and production

This is where traditional development begins. Features are expanded, systems are hardened, integrations are finalized, and the solution is prepared for real use.

But by the time a team reaches this phase, the biggest risks have already been removed. The idea has been tested in chat. It has been tested again in prototype form. The remaining task is not discovery. It is productionizing what already works.

Why this changes everything

This framework solves several problems at once.

Pricing becomes more realistic. Instead of trying to estimate a full solution full of unknowns, you can scope discovery and validation first. That is far easier to define and price.

Risk stays lower. A short validation phase and a prototype phase cost far less than diving directly into a full build that may need to be abandoned.

Technology lock-in is reduced. You do not commit to a specific model, platform, or architecture before you have seen what actually works.

Clients build literacy. When clients participate in chat-first testing, they see AI’s strengths and limitations for themselves. They become better decision-makers.

The process becomes repeatable. Different clients and different use cases can still follow the same pattern: discovery, validation, prototype, production. That is how you build a practice instead of improvising every engagement from scratch.

What would have happened otherwise

If we had followed the client’s AI-generated specification without this framework, I believe we would have spent significant time trying to force the wrong approach to work. We would have been locked into assumptions before validating them. And if the approach failed, we would have thrown away both time and effort before starting over.

That is what failure often looks like in enterprise AI. Not a lack of intelligence. Not a lack of effort. Just moving from idea to build too fast.

How this connects to the rest of the journey

This framework is not separate from the first 24 weeks of this series. It is the organizational application of the same ideas that have been showing up all along.

Week 9 was about literacy before agency. Clients cannot delegate decisions about AI if they do not understand what AI can and cannot do.

Week 15 highlighted barriers to adoption, including the tendency to assume the first idea is the right one because we have not imagined alternatives.

Week 18 was about the shift from consumer to creator—stopping the habit of accepting whatever the tool gives you and starting to architect what you actually need.

Week 20 emphasized build literacy, then buy. You cannot make good platform or vendor decisions until you understand the problem and the range of viable approaches. Chat First Prototyping helps build that understanding before major commitments are made.

Your week 24 challenge: question your next AI project

If you are considering an AI implementation—whether you are building internally or working with a consultant—start with a few hard questions.

Are you solutioning too early? Have you already locked onto a technology or architecture before validating that the approach works?

Could you test the workflow in chat first? Before automation, could you manually walk the process through an AI interface and see what happens at each step?

What assumptions are you making that you have not yet validated? About the data, the workflow, the model, or the outcome?

Who would act as the orchestrator? In a chat-first prototype, someone needs to connect the steps manually and learn from the process. What would that person discover before any code gets written?

The bottom line

Twenty-four weeks ago, I started this series to document my own AI transformation. At first, the goal was personal literacy. Over time, the challenge became larger: how do we help organizations navigate AI projects without becoming part of that 95% failure rate?

Chat First Prototyping is my current answer. Not because it is the only framework, but because it addresses the problems I keep seeing: projects that start building before validating, technology decisions made too early, consulting efforts that cannot be scoped well, and clients who never build enough literacy to make smart decisions.

The principle is simple: do not build until you have proven it works in chat. Let a human orchestrate before automation takes over. Validate first. Build second.

Start in chat. Validate everything. Then build what you know works.

This post is part of my “AI Over 40” series. It first appeared on LinkedIn: AI for the Over 40 [Week 24]: Why Your AI Project Should Start in a Chat Window

Read more AI and Copilot blogs.

The post AI for the Over 40 – Week 24: Why Your AI Project Should Start in Chat appeared first on ArcherPoint.

Industry studies from organizations like the National Retail Federation consistently show that shrinkage is a mix of external theft, internal theft, and, critically, process and administrative errors. For many retailers, these internal and operational issues quietly account for a large percentage of losses.

This shift in understanding is reshaping how leading retailers approach shrinkage. Rather than treating it solely as a loss-prevention issue, they are reframing it as a margin-management and operational-visibility challenge.

The hidden drivers of shrinkage

Today, shrinkage is increasingly tied to everyday operational inefficiencies across the store and supply chain. These include:

• Pricing and promotion errors
• Incorrect shelf placement or labeling
• Inventory inaccuracies
• Out-of-stocks and phantom inventory
• Poor backroom organization
• Understaffing and lack of process discipline

Even small mistakes—like a product being stocked in the wrong location or priced incorrectly—can cascade into lost sales, inaccurate inventory records, and ultimately margin erosion.

One of the costliest examples is phantom inventory—when systems show stock is available, but the shelf is empty. Customers walk away, sales are lost, and replenishment isn’t triggered because the system believes inventory is still on hand.

What makes this especially challenging is that these issues are often invisible at scale. A single store might absorb minor inefficiencies, but across dozens or hundreds of locations, the financial impact becomes significant.

Why traditional loss prevention falls short

Historically, loss prevention teams have focused on surveillance, theft detection, and incident response. These capabilities are still important, but they address only part of the problem.

The bigger issue is a lack of visibility into store operations. Retailers often lack real-time insight into what is actually on the shelf, whether pricing is accurate, whether promotions are executed correctly, and whether inventory counts reflect reality. Without this visibility, retail shrink becomes a symptom of broader operational blind spots rather than a standalone issue.

For example, a pricing discrepancy might be written off as shrinkage when in reality it stems from a breakdown in promotion execution or data synchronization between systems. Similarly, inventory discrepancies may result from receiving errors or process gaps, not theft.

How technology is changing the game

Leading retailers are now investing in technologies that connect store operations, inventory, and analytics, bringing shrinkage into a broader operational context.

AI-powered shelf and inventory monitoring: Computer vision, IoT devices, and robotics can scan shelves to detect misplaced items, pricing errors, and stock gaps. These tools help retailers identify and correct issues before they impact sales or inventory accuracy.

Integrated data platforms: Modern retail systems unify POS, inventory, workforce, and supply chain data into a single source of truth. This integration allows retailers to identify patterns and root causes of shrinkage across locations and time periods. Instead of reacting to isolated incidents, retailers can see systemic issues such as recurring discrepancies tied to specific stores, processes, or product categories.

Predictive analytics: Advanced analytics enables retailers to anticipate where inventory shrinkage is likely to occur. For example, patterns in inventory adjustments, staffing levels, or sales anomalies can signal emerging risks. This shifts shrinkage management from reactive to proactive, helping retailers intervene before losses occur.

Workflow automation: When issues are detected, automated workflows can trigger corrective actions, such as restocking, relabeling, or cycle counting, without relying entirely on manual processes. This reduces the lag between identifying a problem and fixing it, which is critical in fast-moving retail environments.

Breaking down silos

One of the most important shifts happening in retail is the breakdown of silos among store operations, loss prevention, the supply chain, and finance. Historically, these functions operated independently, each with its own data and priorities. Today, leading retailers are aligning them around shared metrics, especially margin and inventory accuracy.

Loss prevention is no longer just about catching bad actors; it is about protecting profitability across the entire operation.

For example, improving inventory accuracy benefits not only loss prevention but also replenishment, merchandising, and customer experience. When all teams use the same data, shrinkage is easier to diagnose and reduce.

The human factor still matters

But technology alone is not enough. Many shrink-related issues are exacerbated by understaffing, inconsistent training, or a lack of accountability. When stores lack sufficient personnel to maintain inventory discipline, errors increase and visibility decreases. Even the best systems cannot compensate for inconsistent execution at the store level.

Retailers that succeed in reducing shrinkage combine technology with:

• Better staffing models
• Standardized operating procedures
• Ongoing training and reinforcement
• Clear ownership of inventory accuracy

Frontline employees play a critical role in maintaining shelf integrity, ensuring accurate counts, and properly executing promotions. Empowering them with the right tools and processes is essential.

From loss prevention to margin optimization

The most successful retailers are no longer asking, “How do we stop theft?” They are asking, “Where are we losing margin, and why?”

This broader perspective transforms shrinkage from a narrow loss prevention issue into a strategic opportunity. By improving operational visibility and discipline, retailers can reduce unnecessary losses, improve product availability, enhance the customer experience, and increase overall profitability.

In this context, shrinkage becomes a measurable signal of operational health. The more accurately a retailer can track and manage inventory, pricing, and execution, the less shrinkage they will experience.

How retailers can take control of shrinkage

Shrinkage will always be part of retail, but how retailers understand and manage it is evolving.

The most effective organizations are beginning to see that shrinkage is not just a loss-prevention issue but a controllable operational lever. When retailers shift their mindset in this way, they move from reacting to losses after the fact to actively managing the conditions that create them.

This starts with recognizing a simple truth: shrinkage isn’t inevitable. Many of its root causes can be identified, measured, and addressed through better visibility and execution.

In practice, retailers can begin to reduce shrinkage by focusing on a few key areas:

• Gaining real-time visibility into inventory, pricing, and shelf conditions
• Aligning store operations, loss prevention, and supply chain around shared data
• Standardizing processes to reduce variability across locations
• Equipping store teams with the tools and training needed to maintain accuracy

Ultimately, reducing retail shrinkage comes down to improving how the store operates day to day. The more consistent and transparent those operations become, the easier it is to identify where margin is being lost and correct it before it impacts the business.

The goal is to make shrinkage measurable, manageable, and predictable.

Retailers that succeed in this shift don’t just reduce losses. They improve product availability, create better customer experiences, and strengthen margins across the entire operation.

Contact ArcherPoint by Cherry Bekaert to learn more about how we can help you control shrinkage and become more competitive.

The post Store Shrinkage Is Not Just a Theft Problem, It’s an Operations Problem appeared first on ArcherPoint.

It’s 6:47 PM on the last Friday of the month. Your controller just emailed you — again — with a revised P&L. This is version seven. The file is named PL_Final_FINAL_v3_JulieFixes_REAL.xlsx. Sound familiar?

Here’s the uncomfortable truth: Most finance teams running Business Central are still exporting raw trial balance data into Excel, manually building reports, and praying that the formulas didn’t break when someone inserted a row. They do this month after month. Meanwhile, a powerful, built-in financial reporting engine sits right inside their ERP, untouched.

Financial Reports in Business Central is that engine! If you’re coming from NAV or earlier BC versions, you might know this feature as Account Schedules — it was renamed in BC 2022 Wave 2 (v21, October 2022) and enhanced. The Financial Reports feature is not new. It’s not an add-on. It’s not an extra license. And yet, it remains one of the most underutilized features in the entire platform.

This guide will change that. Whether you’re a BC beginner setting up your first report or a CFO looking to slash your reporting cycle from days to minutes, everything you need is right here — and you can follow along using the free Cronus demo company.

What are Financial Reports in Business Central?

Think of Financial Reports (Figure 1) as a reporting workbench built directly into Business Central. Unlike canned reports that give you a fixed view, Financial Reports let you design exactly the financial statement you need — an Income Statement, a Balance Sheet, a departmental P&L, a budget variance analysis, or anything else your board demands.

The magic comes from three simple building blocks:

The Three Building Blocks

The beauty of this design? You can mix and match. One Row Definition can be paired with different Column Definitions — one for “Actual vs. Budget,” another for “This Year vs. Last Year,” a third for “Monthly Trend.” Three completely different executive reports, built from the same foundation.

Walkthrough: Building your first financial report

Let’s get hands-on. We’ll build a simple Income Statement from scratch using the Cronus demo data in BC28. Even if you’ve never opened this feature before, you’ll have a working report in about 15 minutes.

Step 1: Create a Row Definition

The Row Definition is your report’s backbone. It lists the accounts and totals that will appear as line items.

1. Search for “Row Definitions” and open the list.

2. Click + New to create a blank Row Definition.

3. Give it a name: MY-IS-ROWS (Figure 2). Keep it short — the Name (code) field on Row Definitions is limited to 10 characters.

4. Important (BC28+ only): Starting with Business Central 2026 Wave 1 (v28), Row Definitions, Column Definitions, and Financial Reports have a Status field. If your environment is on BC28+, change the Status from Draft to Active so the definition isn’t blocked. On BC27 and earlier, this field doesn’t exist, so you can skip this step.

Now populate the rows. Here’s a simplified structure using Cronus G/L Account ranges:

Note: In practice, you’ll find Totaling Type is almost always set to Posting Accounts by default on new rows. To create a heading row, keep it as Posting Accounts, but leave the Totaling field empty — an empty account range means no data, just a label. Check Bold to make it stand out. For blank separators, leave both Description and Totaling empty. Important: the account ranges above are illustrative only. Always check your own Chart of Accounts (Figure 3) before copying these ranges — Cronus numbering varies across localizations, and your production COA will almost certainly differ.

Note on Row Type: Each row also has a Row Type field that, in most versions, defaults to Net Change — this is correct for Income Statement accounts (revenue and expenses). If you build a Balance Sheet report later, you’ll need to set Row Type to Balance at Date for asset, liability, and equity rows.

Step 2: Create a Column Definition

Now, let’s define how we want to view the numbers. We’ll start simple.

1. Search for “Column Definitions” and open the list.

2. Click + New and name it: MY-BASIC (Figure 4).

3. (BC28+ only) Change the Status from Draft to Active — a Draft column definition will be blocked on Financial Report.

4. Add these columns:

The date range is not set in the Column Definition — it’s controlled at runtime via the Date Filter on the Financial Report page.

Step 3: Bring it together: Create the financial report

1. Search for “Financial Reports” and click + New.

2. Name it: MY-IS (like the built-in names: IS, BS, M-INCOME).

3. Set Row Definition to MY-IS-ROWS and Column Definition to MY-BASIC.

4. (BC28+ only) Change Status from Draft to Active. All three components must be Active. If any are Draft, the report shows Blocked.

5. Click Edit Financial Report to preview. Set your Date Filter (e.g., 06/01/25) and watch the numbers populate (Figure 5).

Congratulations! You just built your first Financial Report from scratch!

Did you notice the negative revenue? Sales Revenue shows as -1,716.30 and Net Income as -2,142,879.00. That’s because revenue accounts in BC carry credit balances. Jump to Pro Tip #4: Show Opposite Sign & Row Formatting below to learn how to fix this.

Power features that will impress your board

Power feature #1: Use Dimension Filters to create a P&L in Business Central to see your business by department

Business Central’s Dimensions are metadata tags attached to every transaction. On any Financial Report, set the Department Filter (Figure 6) and your Income Statement instantly becomes a departmental P&L.

CFO Insight: This replaces 80% of the “Can you slice this by department?” requests your team gets every month.

Power feature #2: Budget vs. Actual with Variance columns

Create a new Column Definition called BUD-V-ACT (Figure 7) with four columns: Actual (Net Change, Entries), Budget (Net Change, Budget Entries), Variance (Formula: 10-20), and Variance % (Formula: 30/20*100).

Now, when you view the report, you’ll see four columns side by side — no Excel formulas needed.

Note: For the Budget column to show data, the Cronus demo must have G/L Budget entries. Search for “G/L Budgets” to verify.

Power feature #3. YoY Period Comparisons

Similarly, create a new Column Definition called YOY-COMP (Figure 8) with four columns: Current Period (Net Change, Entries), Same Period LY (Net Change, Entries, with Comparison Date Formula set to -1Y), Change (Formula: 10-20), and Change % (Formula: 30/20*100).

The Comparison Date Formula is the magic here. -1Y means “same period, one year ago.” Other useful formulas: -1M (prior month), -1Q (prior quarter). Just swap the Column Definition on your MY-IS report and the comparison appears instantly.

Power feature #4. Drill-Down – From Report to Transaction

When viewing a Financial Report, click on any number in a cell that pulls from G/L accounts. BC will immediately open the underlying G/L Entries with posting dates, document numbers, and source codes (Figure 9).

Note: Drill-down only works on cells from Posting Accounts, Total Accounts, or Account Category rows. You cannot drill down on Formula rows or columns.

Power feature #5. Export to Excel & Excel layouts

Every Financial Report can be exported to Excel (Figure 10) with a single click. Starting with BC 2025 Wave 1 (v26), you can save Excel templates in Business Central and run reports using saved templates via Open in Excel (using layout). The raw data goes to a hidden sheet; your formatted sheet references it.

Real-world scenarios every CFO cares about

Scenario #1: Departmental P&L

Standard Income Statement Row Definition + Net Change column for the current month + Department dimension filter. Each department head sees their numbers exactly.

Scenario #2: Board-ready Budget Variance report

Detailed P&L Row Definition + BUD-V-ACT column definition. Export using a saved Excel template with conditional formatting for a polished board package.

Scenario #3: Cash Flow snapshot

Use the built-in Cash Flow Statement Row Definition from Cronus. Pair with monthly trend columns (12 columns, one per period). A 12-month waterfall without external tools.

Scenario #4: Quick KPI dashboard for the CEO

Compact Row Definition with 8–10 rows: Total Revenue, Gross Margin, EBITDA, Net Income, AR/AP/Cash Balances. Column Definition with Current Month, YTD, and Same Period Last Year. One page, nine numbers, three perspectives.

Tips and tricks: The expert’s playbook

Pro Tip #1. “Set Base for Percent” Totaling Type

This step requires setup in both Row and Column Definition. Add a row with Totaling Type = Set Base for Percent (Figure 11) as the very first row in your Row Definition (before any data rows), with Show set to No. Then in the Column Definition, add a Formula column with the formula 10% (where 10 is your Current Period column number). This produces a common-size Income Statement in which every line is expressed as a percentage of revenue (Figure 12).

Pro Tip #2. Copy and reuse definitions

On the Financial Reports page, use Copy Report Definition to duplicate an entire report. For Column Definitions, use Import/Export actions to share between companies.

Pro Tip #3. Date formulas that save time

Note: these formulas return a single date (the last day of the period), not a range. To filter across a period, combine them with the range operator — e.g., -CM..CM for the full current month, or -CY..CY for the full current year.

Important: Don’t confuse Date Filter formulas with Comparison Date Formulas in the Column Definition. The Comparison Date Formula (e.g., -1Y) is a separate field that shifts the period relative to the Date Filter.

Pro Tip #4. Show opposite sign and row formatting

Revenue accounts in BC post as negative amounts (credit balances). The Show Opposite Sign checkbox on a Row Definition row flips the sign so revenue appears positive — the way your board expects. Apply it only to the posting-account row where the sign needs to flip. Using it on a formula row, such as Gross Profit, where both revenue and COGS are aggregated, produces an incorrect result because the sign is flipped after aggregation is complete. The Row Definition also offers Bold, Italic, Underline, and Double Underline toggles for each row. These carry through to printed/PDF versions. Per Microsoft Learn, some formatting doesn’t carry over to Excel exports—apply it in the Excel template instead. Figure 13 shows all these columns highlighted.

What’s new in BC 2026 Wave 1 (v28)

• Company logo on PDF outputs.
• Report Categories and Statuses (Draft, In Review, Published).
• Scheduled distribution to a distribution group with report inbox delivery.
• Combine multiple reports into a single PDF for easier sharing.
• Run reports over all values of a dimension in one action.
• Global defaults for negative format, report period, and logo placement.
• Enhanced audit log tracking who ran which report and when.
• New tile/card view on the Financial Reports list.

What’s next?

This blog covered the foundations of Financial Reports in Business Central. There’s a lot more to explore — Power BI integration, Copilot for finance analysis, multi-company consolidation, and API access. We can deep dive into any of these topics based on your needs. Contact ArcherPoint by Cherry Bekaert to find out more. And check out our collection of How-To blogs to learn more about getting the most from Business Central.

The post Master Financial Reports in Business Central (without using Excel!) appeared first on ArcherPoint.

The Dynamics 365 Business Central community, consisting of developers, project managers, and consultants, collaborates across various platforms to share valuable insights. At ArcherPoint, we greatly value their dedication and expertise. To ensure widespread access to this technical knowledge, we created Developer Digest.

Enable or disable indexes in the client

New in BC v28 is a performance enhancement that lets users enable and disable indexes in the BC client. This new feature (actually, resurrecting a feature from C-Side, but I digress) allows users to disable unused indexes to save storage and reduce costs when inserting or modifying data in SQL, especially since not all companies use all available indexes.

You can watch Microsoft demonstrate enhanced index management on their YouTube page and read more about table keys and indexes on Microsoft’s Table Keys Learn page.

Duilio Tacconi discusses this feature in more detail in his blog, Dynamics 365 Business Central 2026 Wave 1. What’s New in Performance.

Microsoft Business Central resources for partners

Now is a good time to remind everyone that Microsoft provides useful Business Central resources for Microsoft partners that are worth checking out:

• General list of Business Central resources for partners: Includes hot topics, latest release news, social posts, and partner readiness.
• Business Central Viva Engage: Social media network for partners to interact with each other and the Microsoft product team.
• Business Central office hours: Provided once or twice a month and includes discussions of new features, new releases, and upcoming events.
• Business Central YouTube channel: Place to watch Business Central videos, including: What’s new, Copilot and AI, tips and tricks, technical deep dives, and Microsoft’s Under the Hood podcast series.
• Business Central LinkedIn page: Provides Business Central news and announcements from the BC product group.
• Business Central Partner Portal: Provides partner resources, including pitch decks and compete decks.

The move to the Responses API for AI projects

The Responses API combines the best of Chat Completions and the Assistants API, representing Microsoft’s preferred approach for future AI projects. Among its advantages, the Responses API offers better performance, lower costs, and flexible input options. For example, the Responses API provides more efficient token handling than Chat Completions, resulting in significant cost savings. The Responses API also reduces much of the development complexity compared to Chat Completions.

Stefano Demiliani offers a comprehensive assessment of what the Responses API means for AI development in BC projects in his blog, From Chat Completions to Responses API: why Azure OpenAI’s new paradigm changes everything.

Read more about Responses API on Microsoft Learn.

Data positions within streams

Understanding the concept of streams in AL is hard enough. Getting your arms around which position the data has in a stream can be even more difficult.

Erik Hougaard takes a look at how to understand data positioning within InStreams and OutStreams and how they can be used.

Watch Erik’s video, What’s your position on positions in streams?, to learn more.

Are you interested in Dynamics NAV and Business Central development? Check out our collection of NAV/BC Development Blogs.

Read “How To” blogs from ArcherPoint by Cherry Bekaert for practical advice on using Microsoft Dynamics NAV and Dynamics 365 Business Central.

The post Dynamics Business Central / NAV Developer Digest – Vol. 552 appeared first on ArcherPoint.