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Key KPIs During System Implementation: How to Measure Project Success?
On the myERP portal, we often analyze digital transformation cases. Some end in spectacular success, while others lead to frustration and exceeded budgets. The difference usually comes down to one word: metrics. System implementation is not just an IT project, but a profound business change. And business, as we know, is based on numbers. When planning an implementation, you should rely on both hard historical data and Key Performance Indicators (KPIs). These are important not only for the organization but also for its implementation partner. Which KPIs are worth tracking, what exactly do they measure, and when should they prove that the investment was right? No Measurable Goal = No Success Before we dive into specifics, we must address a topic that is often taboo in many projects: the company’s starting point. Clients are often afraid to reveal real data to technology partners. Meanwhile, without a reliable analysis, a proper project execution is practically impossible. If an organization does not share data, it is difficult to define any KPIs. Consequently, the implementation partner has the right to refuse the project. Why? Because the project then becomes merely an “expensive software installation” that may bring no real value. A perfect example is ROI (Return on Investment) – without calculating it, a project has no defined business goal. ROI – Return on Investment According to both clients and implementers, this is one of the most important KPIs. ROI determines the ratio of generated savings and additional profits to the Total Cost of Ownership (TCO). By “total cost,” we mean not only licenses and programming services but also infrastructure, system maintenance, and time spent on user training. When can you realistically expect a return? There is a myth that ERP pays for itself over years. Meanwhile, there are cases where the system pays for itself after just one month. A great example is Warehouse Management Systems (WMS). Rapid elimination of picking errors can instantly zero out heavy contractual penalties imposed by retail chains for delivery mistakes. In full-scale projects, achieving a positive ROI within 3-6 months is doable, provided project discipline is maintained. The key is to implement only what is critical first. Instead of expanding the system with add-ons from day one, it is better to launch core operations so the software starts earning for itself. Subsequent functionalities can then be financed from the savings already generated. Production Processes – Key KPIs If the goal is to improve production and logistics, the system must drastically improve daily operations. We focus here on efficiency and time. Process Efficiency This metric determines the amount of resources (time and costs) needed to complete processes such as month-end closing or production planning. It allows for identifying “bottlenecks” in the organization. If a process that previously involved three people for two days takes one person a few hours after ERP implementation, the company’s scalability grows rapidly. Time per Task This is a micro-scale version of efficiency. It measures the amount of time spent on a repetitive task in minutes. Based on this, you can precisely assume how much the system should shorten routine operations. Lead Time (Production Process Duration) This is the total time from the moment a customer order is received, through production planning and execution, to delivery. In today’s reality, an efficient supply chain is a powerful competitive advantage. Shortening lead time means less capital frozen in work-in-progress and faster turnover. Number of Orders per Employee A metric of pure scalability, providing information on how many documents or invoices one full-time equivalent (FTE) can handle. Why does this matter during implementation? Suppose a company’s sales grow by 30% annually. A well-implemented system will allow the same back-office team to handle this volume. No increase in back-office headcount despite growing sales is pure profit. Warehouse KPIs How to recover cash frozen on the warehouse floor? Relevant indicators in this area include inventory level and turnover. Inventory Turnover Measures how quickly goods appear on the shelves and turn into generated sales. Low turnover means cash is frozen in the warehouse. A properly implemented system should speed up the turnover of the most profitable items—and naturally increase this indicator. Inventory Level This is the volume and value of goods or raw materials held in the warehouse. A modern system ensures that inventory is kept at a minimum but 100% safe level. This protects the company from both dead stock and downtime due to material shortages. Data Quality Over Quantity This is one of the most important issues for pre-implementation analysis. Before starting a project, data should be checked for its timeliness and consistency. Data Consistency Between Departments The goal is for the salesperson, the warehouse worker, and the accountant to have access to the same data in real-time. An implemented system should ensure that every department relies on a “single version of the truth.” Data Error Rate Measures the frequency of the “human factor.” This involves wrong prices entered in an order, mistakes in item codes, or typos in delivery addresses. An implemented system should enforce validation from the first second. For example, it can block the release of goods without proper approval or prices below the minimum margin. Summary System implementation is not a luxury expense but a strategic investment. If you are preparing for talks with a technology partner – do not be afraid to show your weak points. Process openness and reliable data are the only foundation on which success can be built. If the project is already underway – keep your finger on the pulse. Manage the implementation through numbers and KPIs. By implementing the system in stages, you will quickly see that digitalization pays off many times over—and often much faster than originally anticipated.
KajaGrabowiecka
CRM System – What Is It and Why Does Your Business Need One?
How do you maintain a high-quality relationship with your customers? The answer to this, as well as many other challenges related to sales and marketing, is a CRM system. it combines IT tools with an appropriate business strategy. Consequently, this allows for the collection of data about contractors and the building of a lasting competitive advantage through excellent customer service. What does CRM mean and why is it important? The acronym CRM (Customer Relationship Management) refers to managing relationships with customers – both current and potential. In today’s market reality, competitive advantage is no longer built solely on price. Quality of service and speed of response have become key. These factors shape the customer experience and determine their loyalty. A modern CRM system enables: Centralizing all customer data in one secure place, Remote access to contact lists, tasks, and calendars from a single device, Detailed insight into contact history, purchases, and customer preferences, Integration of email, calendar, and mobile phone, Automation of repetitive marketing and sales activities, Managing sales opportunities and precisely estimating future revenues, Monitoring the achievement of sales goals and KPIs, Improving external and internal communication within the company. Many CRM systems also allow for the creation of sales offers. They enable the instant generation of personalized commercial proposals, which is a strong selling point in B2B and B2C discussions. How does a CRM system work? CRM serves as a central knowledge base about customers. Every interaction – from a phone call and email to a service request – is recorded in the system. How does this look in practice? Sales representatives can check the full cooperation history before a call and better prepare for negotiations. The marketing department can precisely segment the database and run campaigns (e.g., mailings). The customer service department immediately sees requests and issues, shortening the time needed to resolve them. Modern CRM systems are increasingly supported by Artificial Intelligence. AI solutions can remind users about follow-ups, suggest next sales steps, or analyze the chances of closing a given transaction. What are the types of CRM software? The choice of implementation model depends on the organization’s specifics and technological needs. Three variants are most common: Cloud-based CRM – a solution available in a SaaS subscription model, accessed via the Internet. Popular due to easy scalability and the ability to use the system from any place and device. On-premise CRM – a system installed locally on the company’s servers. It guarantees full control over data but involves higher maintenance and administration costs. CRM as an ERP module – many providers offer a Sales module that has functionalities similar to CRM. This is an ideal solution for companies that want to manage sales, finances, and production within a single, integrated environment. CRM Implementation – How to do it effectively? Implementing a system is not just about installing software, but primarily about changing the work culture. The tool will not bring the expected return on investment (ROI) if the team does not change its habits. The most important stages of CRM implementation are: Defining business goals – does the company want to increase sales? Or perhaps shorten order fulfillment time? Process audit – analyzing the current way of working and user needs. Selection of the appropriate CRM system. Integration – configuring and connecting CRM with other systems, e.g., ERP or e-commerce platforms. Team training – preferably in a workshop format to translate theory into practice. Post-implementation support – regular system optimization with the support of an implementation partner. How much does CRM cost? The cost of implementation is an individual matter. It depends on the size of the industry, the number of users, and the scope of functionality. Subscription models (monthly fee per user) as well as one-time license purchases are available on the market. It should be remembered that the budget should cover not only the software itself but also training and configuration. FAQ – Frequently Asked Questions Who is a CRM specialist and what do they do? A CRM specialist is an expert combining analytical, marketing, and technical competencies. They are responsible for process optimization, database management, and ensuring the system effectively supports sales. Their tasks include: Customer database management, Data analysis and reporting, Automation of marketing campaigns, Supporting the sales team. Is CRM the same as ERP? No. CRM and ERP are two different systems, although they often complement each other. CRM focuses on managing customer relationships. On the other hand, ERP covers all business processes, such as accounting, warehouse management, or production. In practice, many companies integrate both systems to have a full picture of their operations. Is CRM only for large companies? Absolutely not. CRM works for any organization that wants to organize customer information and plans to scale its business. Even foundations use them to manage relationships with donors. How to learn CRM? The best way to learn any system is to use it in practice. You can start by: Using a CRM demo version, Online courses in sales and marketing, Working with real data in a company. At the same time, it’s worth remembering that every system implementation process includes training future users. The goal of such learning is not only to understand how to operate the tool but also the business processes themselves. Can ChatGPT create a CRM? ChatGPT, like other LLM models in conversational form, can support the creation of simple CRM solutions. Currently, AI can generate logic or database structures needed for a system. However, OpenAI’s tool cannot replace a full-fledged CRM system in a company, especially in larger organizations where software scalability and data security are crucial. How to make a CRM in Excel? At the beginning of a business, Excel can perform basic CRM tasks. You can create a customer database, contact history, or sales pipeline in it. However, as the company scales, Excel quickly becomes insufficient. Spreadsheets primarily lack automation, and maintaining data control during team collaboration eventually becomes impossible. Is SAP a CRM system? SAP itself is not a CRM, but a provider of a broad business ecosystem. However, among its solutions, it offers a CRM solution – SAP Customer Experience.
KajaGrabowiecka
From Go Live to a Mature ERP: How to Build Lasting Value in the First 90 Days, the First Year, and Through Continuous Improvement
Implementing an ERP system is a moment that often grows into a myth within organizations. For months – sometimes years – the company lives inside the project, wrestling with data migration, testing, integrations, and configuration. Eventually, the go‑live day arrives. The project team holds its breath. Leadership watches the screens as if they were observing a Mars rover landing. Users pray the system won’t explode. And when the first order successfully flows through the system, someone says the magic words: “We did it.” Except… that’s not true. Go live is not a success. Go live is a test. And the real success begins only afterwards. What happens after go live determines everything. The first 90 days, the first year, and the way the organization builds a continuous improvement model ultimately decide whether the ERP becomes a growth platform – or just another system people work around. This article is a guide through these three stages, built on real implementations, real mistakes, and real successes. It is a whitepaper for organizations that want their ERP to generate value – not just transactions. Go Live: The Moment of Truth That Only Opens the Real Journey Go live is the moment when the system meets reality for the first time. And as usual, reality rarely behaves according to the process documentation. This is when you discover whether the data is truly clean, the integrations truly stable, and the users truly trained. It is also the moment when you learn whether the organization is ready for change – or merely ready for an implementation. Go live is not a success. Go live is only the beginning. Many companies declare success because: orders are being processed, invoices are posting, the warehouse hasn’t stopped, production hasn’t blown up. But that is a very low bar. It’s like buying a car and calling it a success simply because the engine started. The real question is: Is the organization working better than before the implementation? In most cases, the answer is: not yet. And that’s normal – as long as the company has a plan for what happens next. The First 90 Days: The Period That Determines User Adoption and Whether ERP Becomes a Foundation or a Problem The first 90 days are the most critical stage in the life of an ERP system. This is when user habits form, processes stabilize, data and integration issues surface, and the organization decides whether it will work in the system or around it. Stabilization Is a Process, Not a Reaction The biggest mistake after go live is switching into firefighting mode. The implementation team responds to user tickets but does not manage stabilization as a structured process. As a result, changes are introduced chaotically, processes lose coherence, and users lose trust in the system. Stabilization must be managed like a project – not like a helpdesk. You need: a working rhythm, clear priorities, defined responsibilities, decision‑making mechanisms, clear rules for what gets fixed immediately and what goes into the backlog. Without this, even the best configuration will start to fall apart. Training in Context, Not in Theory Before go live, users learn the system in laboratory conditions. After go live, they learn it for real. This is when they begin to understand why inventory reservations behave the way they do, how production scheduling reacts to changes, what a posting error means, and how to handle warehouse exceptions. Training must be delivered in the live system, in real processes, with real data. Otherwise, users will return to Excel faster than you can say “workflow.” Monitoring System Health Before Symptoms Appear In the first 90 days, the organization must actively monitor system health: integration errors, batch performance, master data quality, posting accuracy, and trends in user tickets. This is the period when small issues can have massive consequences. ERP doesn’t break suddenly. ERP breaks quietly. The Biggest Risk: Normalizing Workarounds If users return to Excel in the first weeks, they will stay there for years. If they start bypassing processes, those workarounds will become the norm. If they start entering data “the quick way,” the system will lose credibility. The first 90 days require absolute discipline. If a process is meant to run in ERP – it must run in ERP. What Must Be Ready Before Go Live You must enter go live with: a support model, change governance, an optimization backlog, a training plan, system monitoring mechanisms. Equally important: assigning process owners and defining RACI (Responsible, Accountable, Consulted, Informed). Without this, go live becomes a leap into the unknown. The First Year of ERP: The Period That Determines Business Value The first year is when the organization should move from stabilization to optimization, and then to development. This is when ERP begins to deliver real value – provided the company has a plan. Why Companies Don’t Have a First‑Year Plan Most often for three reasons: implementation fatigue, no ERP owner, confusing stabilization with optimization. As a result, the organization is left alone with a system that is only beginning to live its own life. What Should Happen in the First Year Stabilization – the system must become predictable. This is the foundation. Optimization – this is when you streamline processes, automate workflows,improve data and integrations. This is when ERP starts generating value. Development – time for advanced modules, financial automation, SCM/CRM integrations, predictive analytics, and preparing for AI. The Role of the D365 F&SCM Architect The architect is the guardian of process consistency, data quality, and alignment with the roadmap. Without an architect, the system begins to drift. With an architect, the system begins to grow. The Biggest Risks in the First Year Returning to Excel. Master data degradation. Lack of change control. No process owners. No measurement of value. How to Build a First‑Year Plan You must build a 12‑month roadmap – it is the only way to move from stabilization to real value. Without it, the organization drifts and change decisions become random. Define process KPIs – they are the only way to assess whether ERP performs better than the previous system. Without KPIs, it’s easy to fall into the illusion of “the system works, so everything is fine.” Assign process owners – only they can be accountable for data quality, decisions, and development. Without owners, every department pulls the system in a different direction. Establish governance – without it, changes will be introduced ad hoc, often without impact analysis. And finally – involve the architect in every change. The architect safeguards architectural coherence and protects the organization from configuration chaos. The Continuous Improvement Model: The Stage That Separates Average Companies from Leaders The best organizations treat ERP not as a project but as a platform for continuous improvement. This is where the greatest value emerges. Why Optimization Matters More Than Implementation Implementation gives you tools. Optimization gives you outcomes. Without it, ERP remains a transactional system. With it, ERP becomes a growth platform. What a Continuous Improvement Model Looks Like You must build governance – it is the only way to manage changes predictably and in a controlled manner. Without governance, the system begins to live its own life. You must maintain an optimization backlog – it collects ideas, issues, and improvements. Without a backlog, the organization reacts instead of planning. You must work in quarterly cycles – only regularity sustains development momentum. And you must have an architect – without one, the system becomes a patchwork. Areas with the Highest Potential The greatest returns come from: warehouse & logistics, production, finance, planning. These areas benefit most from automation, data improvement, and process optimization. The Most Common Mistakes The most frequent mistakes are: no process owners, no backlog, ad hoc changes, no architect, no measurement of outcomes. How to Start – Building a Foundation That Actually Works ERP Optimization Committee – the only structure that ensures strategic, not reactive, development. Without it, ERP drifts and changes are driven by short‑term pressure rather than strategy. Process KPIs – your shield against the illusion of “the system works, so everything is fine.” KPIs reveal whether processes are stable, data is reliable, and users follow the target operating model. Optimization backlog – your safety buffer. It prevents chaos, enables prioritization, and ensures visibility of all improvement needs. Process owners – the only people who can be accountable for data, decisions, and process evolution. Without them, ERP becomes a patchwork of local variants. Architect involvement – essential for protecting architectural integrity. Without an architect, every change becomes a structural risk. Summary: The Three Stages That Determine ERP Success Go live determines whether the system starts. The first 90 days determine user adoption. The first year determines business value. Continuous improvement determines competitive advantage. Organizations that consciously manage these stages build ERP as a platform for growth. Those that don’t end up with a system that works – but changes nothing. If you aim to develop your ERP consciously and turn it into a true growth platform, our xalution practitioners are ready to support you. Let’s start the conversation.
SzymonJankowski
MRP vs. MRP 2 System – What Is It and What Are the Differences?
Manufacturing Resource Planning (MRP 2) is a direct development of the MRP concept (MRP I, MRP 1). It is an essential element of the IT infrastructure for manufacturing companies. In this article, we analyze the functionality of the MRP system and what is worth knowing when choosing a solution to support production processes. What is MRP and how does it work? MRP (Material Requirements Planning) is a method used to precisely calculate the materials and components needed to manufacture a product. The MRP method functions both as a theoretical planning concept and as advanced software. In a systemic approach, it is most commonly found in three forms: As an element of integrated ERP systems, As part of Capacity Requirements Planning (CRP) systems, As a standalone, dedicated MRP system. Production Management Systems and Resource Planning In the classic approach, the MRP 1 method is based on the “push” model. This means that the demand for raw materials is determined in advance based on sales forecasts. Goods are then produced or purchased according to the “make or buy” principle to meet the predicted demand. Modern production management systems also include modules such as: Financial and sales planning, Strategic management, Shop Floor Control (SFC) – enabling the exchange of priority information between the planner and workstations. In contrast, concepts like Lean Production operate on a “pull” model, where the production impulse comes from an actual order rather than a forecast. What is MRP 2? History and Evolution MRP 2 (or MRP II) stands for Manufacturing Resource Planning. Its history began in the 1980s when it was developed as an extension of the MRP 1 method. At that time, it was intended to provide companies with planning for all resources, not just materials. In addition to inventory, the MRP II system considers: Availability of machines and equipment, Human capital (labor force), Production capacities and schedules, Financial flows. Functions of the MRP 2 System The MRP II system allows for the creation of production plans that take available resources into account. It determines: What resources are needed, In what quantity, And at what time. MRP II also allows for identifying efficiency problems, detecting discrepancies between the plan and reality, and analyzing resource utilization. MRP Example: A furniture manufacturer receives an order for 50 tables. The MRP system analyzes the Bill of Materials (BOM) and calculates that 200 legs and 50 tops are needed. The software checks inventory: there are 100 legs in stock. It then automatically generates a purchase order for the missing pieces and schedules the assembly start date so that raw materials arrive on time. MRP 1 and MRP 2 – Common Features Used in manufacturing enterprises. Can be part of an ERP system. Support production process control. Utilize production plans, BOMs, and inventory levels. Used to calculate material requirements. IT systems supporting management. Differences Between MRP and MRP II The most important difference lies in the functional scope: MRP (MRP I): Focuses on materials, plans material requirements, and does not cover full resource management. MRP II: Covers all production resources, integrates various departments (purchasing, finance, quality), enables process simulation, and supports capacity planning while considering market realities and demand. Is MRP the Same as ERP? No, but they are closely related. MRP focuses almost exclusively on production and material logistics. ERP software covers all areas of an enterprise through modular architecture (accounting, logistics, sales, HR, etc.). Today, MRP is simply a key module within broader ERP systems. MRP 2 or APS Systems? APS (Advanced Planning and Scheduling) systems are advanced tools for planning and scheduling. Unlike MRP II, they cover the entire supply chain and allow for more precise planning. APS helps coordinate actions between suppliers and production to avoid the “bullwhip effect.” MRP II – Advantages and Disadvantages Advantages: Optimization of inventory, reduction of storage costs, elimination of downtime, and better order timeliness. Disadvantages: Sensitivity to data quality (inaccurate inventory leads to wrong plans) and the human factor (potential employee resistance). Conclusion: From MRP to APS MRP 2 is an evolution of MRP 1. These systems can be standalone or part of an ERP to ensure that materials are available for every stage of production. Modern firms typically use ERP systems with MRP/MRP II modules, often extended by APS for increased efficiency and control.
MarekMac
Companial Connect CEE: a Microsoft Dynamics Partner Event Worth Knowing About
Every year, Companial brings together Microsoft Dynamics partners from across Central & Eastern Europe for a day of real conversations, practical sessions, and peer exchange. No vendor theatre – just partners, talking about what’s actually working. The 2026 edition takes place on April 23 in Bucharest, Romania. This year’s agenda covers what matters most to CEE partners right now: Microsoft BizApps priorities, AI adoption in practice, building a CRM practice, and go-to-market strategies that fit the region. Sessions include a CEE-focused Microsoft BizApps update, the Road to AI panel, partner case stories on AI and agents and a GoToMarket roundtable on what’s moving the needle in the CEE Dynamics ecosystem. The event is complimentary for Microsoft Business Applications partners, with limited seats and registration required. Interested in joining this year? Check if spots are still available at companial.com/connect-cee/ Can’t make it this time? Follow the CEE Microsoft Dynamics Partners page on LinkedIn – that’s where we’ll announce the 2027 edition when the time comes.
RadosławDudziak
SAP Business One vs. Comarch ERP XL: Which System To Choose?
Choosing an ERP system is a decision that defines how a company operates for years to come. It is not just a tool for finance or warehouse management. It is an operational foundation that impacts production, sales, and organizational growth — both locally and internationally. In this context, SAP Business One and Comarch ERP XL are two popular directions. SAP Business One is associated with global standards and scalability. Meanwhile Comarch ERP XL is deeply rooted in Polish business realities. Furthermore, Comarch offers extensive modularity for production and trading companies, along with a vast network of implementation partners. The starting point for a fair comparison is simple. Both systems possess what should be the heart of any ERP — a modular architecture combining finance, trade, and logistics. However, they differ in their development philosophy and target business scenarios. ERP System Selection Criteria The most common mistake when choosing an ERP is comparing feature lists without understanding where the system will need to carry the complexity of the business. In practice, the choice between SAP Business One and Comarch ERP XL is determined by four key areas: Production Complexity The key question is: are we dealing with simple or advanced production (process-based, multi-stage, with strict quality requirements)? Relevant elements in the manufacturing industry include: Recipes and technologies, Batch traceability, Quality control, Scheduling, Complaint management. In more demanding production environments, a standard ERP often proves insufficient. Therefore, the ability to extend the system with an additional functional layer is crucial.System Development Model Comarch ERP XL is perceived as a flexible system with high potential for personalization and module customization. Beyond core functions, the manufacturer offers integration with dedicated applications for specific company processes. SAP Business One, on the other hand, prioritizes the stability of the standard, though it can be successfully expanded through dedicated integrations and external add-ons. Implementation and Time-to-Value For some companies, the most critical factor is how quickly the system can go live. The Comarch ERP XL ecosystem features approaches aimed at shortening implementation time through predefined models. This methodology is a response to long-term implementations that tend to drag on for months or even years. For organizations in early growth stages or accounting firms, Comarch ERP Optima is the dedicated starting point. A large portion of XL implementations are smooth migrations from Optima, ensuring data continuity. Conversely, an SAP Business One implementation usually places greater emphasis on in-depth process analysis before the production launch. While this requires more time upfront, it provides higher predictability of the final result. Geographic Horizon If a company is considering foreign branches, multiple languages, and local accounting regulations, built-in support for various countries becomes a business necessity rather than a marketing point. SAP Business One – Characteristics Business One is a solution dedicated to the SME sector and mid-sized companies. It is particularly valued by organizations that want to grow in a controlled manner without entering the “heavy” enterprise solution segment. This system does more than organize finances. It provides real support in planning international expansion. The SAP solution stands out for its maturity and scalability. The system is present in numerous countries and supported by a global network of partners. This not only increases investment security but also ensures greater freedom of development in the long term. Consequently, Business One — thanks to its global nature — prevails among international organizations or those collaborating with clients across different regions. In response to new market realities, SAP has expanded the system with solutions based on Machine Learning, Big Data, and AI. Built-in generative features enable “Intelligent Forecasting.” Artificial Intelligence helps predict seasonality and emerging trends within the organization. Furthermore, the system can generate intelligent sales recommendations based on purchase history analysis. The list of such innovations continues to grow. However, it is worth noting that SAP Business One is not the ideal solution for every organization. Large corporations with highly complex processes or extensive asset management may find the standard system limiting. It may also not be the best option for companies expecting a cloud-first model in the sense of the latest specialized ERP platforms. Nonetheless, SAP Business One can be enhanced with certified extensions. In manufacturing companies where the ERP standard is not enough, the ProcessForce add-on radically changes the system’s capabilities. It allows for precise management of recipes, batches, quality control (traceability), and advanced production planning. Comarch ERP XL – Characteristics Software from Comarch enjoys significant popularity on the Polish market — it is already used by approximately 6,000 companies. The ERP XL system is especially appreciated by medium and large enterprises focused on local operations, as it adapts perfectly to national regulations. The foundation of Comarch ERP XL’s advantage is its lightning-fast response to regulatory changes. Importantly, clients have a real influence on product development through participation in the Comarch Community and Programming Boards. From an IT perspective, the system is “open”. Full documentation of SQL structures allows administrators to independently build automations and reports. The update process has been simplified to the level of a quick installation. At the same time, the system is much less frequently implemented for international projects. Consequently, the strength of its international ecosystem is lower than that of SAP. Although Poland remains its key market, the system successfully supports capital groups operating in multiple countries, offering stability and scalability unavailable to smaller solutions. Comarch ERP XL performs particularly well in manufacturing and trade-service companies. In production, users can plan and control material requirements (MRP) while maintaining integration with the warehouse. Additionally, the system is developed according to the ERP 5.0 concept. Comarch is building an intelligent ecosystem that integrates production with omnichannel sales and full operational mobility. The system is currently undergoing a deep technological transformation. Users are already utilizing responsive web interfaces, and a full architectural rebuild—planned for next year—is already available in a demo version. The system architecture is being expanded with specialized AI agents that automate routine tasks and optimize operations. In the field of AI, Comarch is setting standards through: AI Hub – a platform for building dedicated AI agents; ChatERP – an intelligent conversational interface for easier navigation and reporting; Comarch OCR – full automation of document entry into the workflow; AI in APS – advanced algorithms optimizing production planning in real-time. Summary There is no single “best” ERP system. Instead, there is a program tailored to a specific business scenario. Therefore, before choosing, one must ask the key question: where will the company be in 3–5 years, and what is its primary goal? If an organization thinks globally, prioritizes standards, and wants to build a scalable operational model, it should lean toward SAP Business One. Conversely, Comarch ERP XL will be the better choice if the company operates locally, requires high flexibility, and places production as its top priority.
KajaGrabowiecka
Business Intelligence (BI) System. Who Is It For And Which Tool to Choose?
Business Intelligence (BI) is a modern solution that enables comprehensive data analytics. This system can significantly improve decision-making processes and help gain a competitive advantage in the market. In the following article, we explain when it is worth deciding to implement this tool. Business Intelligence – For Whom? A BI system (short for Business Intelligence) is an environment and set of tools used for advanced business analysis. It is a very broad field that focuses on finding savings, optimizing production, creating “what-if” analyses, or generating complete financial balance sheets. The decision-making process in many enterprises requires a parallel combination of advanced digital solutions with vast amounts of data. Many companies still use multiple systems or sources that are not integrated with each other. In the long run, this leads to significant delays and complications in key processes, over which control may eventually be lost. Business Intelligence tools are the answer to these problems, enabling effective management of a company’s most important operational areas. BI solutions allow for efficient data integration, which in the short term enables: Quick aggregation and retrieval of data. Finding relationships and correlations between individual events. Understanding these events and reaching accurate business conclusions. Current BI systems are so advanced that they can independently recognize data and then generate tables or entire spreadsheets. Naturally, all datasets can also be cleaned or processed in many ways. BI tools enable data analysis and organization using various functions, such as drag-and-drop, which significantly simplifies operation for users within a company. As it turns out, when implementing a BI system, employees do not need to have specialized programming knowledge. Examples of using these tools in daily work include: Analyzing the correlation between salary increases and staff inefficiency. Studying the relationship between demand and the price of a given product or service. Analyzing economic cycles. The ultimate goal of business analysis tools is to find dependencies between phenomena and make significant business decisions based on them. Most Popular BI Tools Knowing how analytical technology works, the next question is about specific solutions. When choosing the right BI system, it is worth paying attention to integration capabilities and market leaders. The most popular tools include: Power BI – One of the most popular systems on the market. It integrates perfectly with the Microsoft ecosystem (including Excel and Azure) and allows for the creation of highly interactive dashboards. Tableau – A powerful tool famous for its extremely advanced and aesthetic data visualizations. It is ideal for huge datasets and deep analytical explorations. Qlik – A modern BI system distinguished by its associative engine. It allows users to freely explore data in all directions instead of following predefined query paths. BI Modules in ERP systems – Many ERP systems have built-in tools that analyze company data in real-time without the need for external integrations. Does Implementing a Business Intelligence System Have to Be Expensive? Many people still believe so – however, this is not true. Currently, the market provides entrepreneurs with BI software versions that are completely free or available in flexible subscription models (SaaS). Even free demo versions, despite limited capabilities, allow for downloading sheets and basic data linking or visualization. This allows entrepreneurs and potential users to familiarize themselves with the logic of the business data analysis system before making a final investment decision. Who Is a BI System Intended For? The market for BI system users is very diverse. When focusing on an advanced implementation (which includes a pre-implementation analysis), you must ensure that your company needs such a solution. It is about economic justification—specifically, having enough data that can be turned into profit. It is difficult to set a strict limit at which a BI system becomes indispensable. However, a good evaluation method is to look at the number of employees and the company’s turnover. For smaller companies, the key criterion is the nature of the business. For example, should a company with 15 employees doing simple sales invest in a powerful analytical system? Probably not. However, there are cases where a team of only 30 people processed such vast datasets that implementing BI became a condition for their further growth. Excel and Databases Are Not Enough For Advanced Analysis Excel is well-known to employees in most companies and is very easy to implement. However, when faced with Big Data, its significant flaws appear: Static analyses instead of real-time updated models. Complicated and error-prone merging of datasets. The monotony of manual report refreshing. Limitations on the number of records that can be processed. Direct databases solve the capacity problem but create a barrier in usability – the need to know SQL. Presenting data from two tables is simple, but when there are hundreds of tables, constantly writing SQL queries becomes inefficient. This is where Business Intelligence systems come in. Data Analysis vs. ERP Systems If an enterprise already has ERP software, it is halfway there. These tools generate reports that allow for constant monitoring of company efficiency and decision-making. However, they are not built for predictive analytics but for handling current operations. ERP tools use OLTP (Online Transaction Processing) databases, designed for immediate, secure data entry. In contrast, BI systems are often based on OLAP (Online Analytical Processing) databases, which are most effective for analysis. It is worth remembering that ERP solutions are usually not the only ones collecting company information. Therefore, a tool (e.g., an integrated BI system) is needed to combine data from ERP, CRM, and other sources, visualizing it in one place. When To Implement a Business Intelligence System? If financial resources allow and analytical needs are growing – as soon as possible. By deciding on a BI system at an early stage of digitalization, you enforce order and a consistent data architecture. Later implementations, in an environment burdened by “technical debt” and information chaos, tend to be much more expensive. Equipping yourself with a data warehouse and appropriate BI tools will facilitate every subsequent step in the company’s technological development. Implementation Methods Every professional system should be implemented with the help of a team of specialists. There are two common methods used during implementation: Potential Analysis – The software provider, together with the client, looks for areas requiring improvement. Information problems and challenges at the intersection of different systems are identified. The competence of BI consultants is key here. Proof of Concept (PoC) – A test implementation on a limited sample of data. It checks whether a given BI system will meet the company’s requirements in practice. The PoC results in a final purchase decision. How to Avoid Failure During Implementation? Implementing BI tools is a significant challenge. The project involves both logistical and purely organizational obstacles. To avoid problems, pay attention to these key risks: Too much data – Integrating everything “as is” unnecessarily prolongs the process. You should focus on KPIs that have real business significance. Dirty data – Gaps and errors often lower the credibility of results. To avoid this, data should be cleaned before implementation. Resistance to change – Even the best system is useless if the staff avoids it. The keys are training and showing employees how the new system will facilitate their daily work. How to Maximize the Effects of Using BI? First and foremost, customize the dashboards. Different experts play different roles and need different data. A CEO wants to see margins from a “bird’s eye view,” while a production shift manager needs real-time machine failure rates. Views must be personalized. Use only the necessary tools. Depending on the technology and provider, some systems offer advanced reporting features and numerous data access points. However, there is a risk that these “gadgets” will eventually cause information noise. It is better to use only the tools you truly need – simplicity and utility win. Summary Implementing Business Intelligence is not just about mechanically replacing Excel sheets with pretty charts. A modern BI system allows you to look at your company from a completely new, often surprising perspective. A fresh perspective helps in continuous optimization and quick reactions to dynamic market changes. Before you decide to buy a specific solution, ask yourself: How will these analyses directly improve my company’s financial results?
MarekMac
Artificial Intelligence in ERP Systems. Which AI Solution Should Businesses Choose?
Today, AI is no longer just a trend but a tool from which companies expect measurable benefits. As a result, managers are no longer asking whether an ERP system includes AI features, but rather what type of AI capabilities it offers. In this article, we organize the market and highlight the differences that matter for decision-makers. Just 2–3 years ago, artificial intelligence in business systems was often treated as an “add-on” to sales presentations. Today – especially from the perspective of CFOs and IT managers – it is an area that is rigorously evaluated. This is also reflected in the findings of the “Cyfrowy Menedżer” report prepared by myERP, which clearly shows a shift toward a “prove it” mindset. AI is expected to deliver results only when a company has solid foundations in the form of high-quality data and clearly defined KPIs. How to Compare AI Solutions in ERP? The biggest trap in implementing AI within ERP systems is assuming that an LLM can compensate for disorganized data and processes. From a purchasing perspective, it is better to treat AI as a productivity layer. Artificial intelligence shortens working time, supports decision-making, and automates routine tasks – but it also requires high-quality input data. IT and finance departments should pay attention to three key aspects: Scope of process interventionSome AI solutions act only as informational assistants, providing summaries or insights from reports. Others can perform actual actions within the system – such as setting credit limits or issuing documents. Sources of generated responsesSome solutions rely exclusively on internal company data, reducing the risk of AI “hallucinations.” Others – especially generative AI tools – require users to define the sources the LLM can access. Costs and technical conditionsSome AI features are included in ERP systems at no additional cost. Others offer advanced capabilities available through paid options. AI Assistants in ERP Systems The most visible form of AI for users is conversational assistants. These solutions enable interaction with ERP systems using natural language, inspired by tools like ChatGPT or Gemini. They also help accelerate onboarding for new employees. ChatERP from Comarch ChatERP is a built-in chat assistant that allows users to interact with ERP in natural language. Ultimately, it is intended to cover both on-premise and cloud versions of all Comarch ERP systems. Currently, it is available in BETA. Its functionality includes: Access to company data available in the system Data analysis and reasoning Suggesting system features Executing tasks on user request A key aspect is the ability to perform business operations such as setting credit limits or issuing invoices. In practice, this requires strict permission and audit mechanisms. Without them, the risk of incorrect commands increases. Comarch ensures the protection of personal and sensitive data in ChatERP. Queries and responses may be processed by technology subcontractors, but the AI should not disclose business secrets. Still, companies with high security requirements should formally define data-sharing rules before implementation. Genius by Asseco Business Solutions In terms of declared functionality, Genius is closer to the concept of a digital coworker that monitors tasks, supports decisions, and suggests actions. According to Asseco BS, it notifies users about pending decisions and tasks, answers ERP-related questions, and supports processes such as orders, invoices, and warehouse documents. Additionally, based on user-provided context, the assistant can deliver actionable recommendations. This approach is enhanced by two important elements: Adaptive interface – AI analyzes user behavior and suggests changes to layout, menus, or screen elements, implemented only after user approval. Analytical layer – Genius provides intelligent insights based on real-time ERP data. MAiA in Monitor ERP System Monitor ERP includes its own AI assistant that “structures, compiles, and analyzes data.” Its main goal is to handle time-consuming tasks. MAiA is not just a chatbot – conversational mode is only one interface. It also works through automated summaries and analyses embedded directly in business processes, similar to how Gemini Pro summarizes documents in Google Drive. Importantly, Monitor’s AI relies exclusively on internal business data, ensuring data integrity and control. MAiA also supports text-related tasks – summarizing notes, translating emails, and refining communication tone. MAiA is available in two versions: Basic – included for all customers Pro – available with a monthly per-user fee The Pro version is initially offered as a free trial. Monitor ERP continues to develop AI features and actively collects user feedback via its Ideas Forum. AI Application Ecosystem Instead of a Single Feature An interesting approach comes from Proalpha, which in 2025 introduced its Industrial AI platform. This is a catalog of over 30 AI applications covering core processes – from procurement and production to service. The platform integrates AI solutions from Empolis and Nemo and is built in a SaaS architecture, enabling smooth integration with both Proalpha’s ecosystem and third-party systems. Nemo’s AI capabilities include: Identifying correlations and anomalies in processes Defining recommended actions Evaluating optimization potential in financial terms In this platform-based approach, AI becomes the “engine” of data integration and analytics. For decision-makers, two key implications stand out: Data processing approach – Industrial AI handles both structured (tables) and unstructured data (documents, notes), turning hidden knowledge into actionable insights Automated recommendations – which can be implemented based on diagnosis and trend forecasting The Microsoft Ecosystem and AI in ERP A unique position in the market is held by Microsoft Dynamics 365 – a scalable ERP/CRM platform deeply integrated with other Microsoft services. Implementations are delivered by multiple myERP partners, including companies such as Companial, Integris, MS POS Poland, xalution Group, IT.integro, and Solemis. Copilot Microsoft has embedded Microsoft Copilot in ERP systems in two ways: as a conversational assistant and as embedded functionality within system features. Key capabilities in Dynamics 365 Business Central include: Conversational guidance on system functionality Data analysis using filters and sorting Creation of sales documents (quotes, orders, invoices) Marketing content generation E-document mapping Bank reconciliation Document numbering automation Product substitution suggestions Order processing automation Power BI Many organizations want ERP data to be consumed in a self-service analytics model. In this context, Copilot in Microsoft Power BI provides significant value: Fast creation and modification of reports and visualizations Automatic report summaries Conversational interaction with data However, Copilot in Power BI is a paid feature (Fabric or Premium). Additionally, organizations must ensure high data quality for AI to function effectively. AI in ERP – What Should You Choose? There is no single “best AI” solution for all organizations. The right choice depends on the dominant challenge within the company – whether it is low user productivity, the need for stronger financial control, or real-time production optimization. Key takeaway:AI in ERP should not be treated as a standalone feature, but as a strategic layer that enhances how people work with data, processes, and decisions.
KajaGrabowiecka
