Neomind

Author: Farley Niehues

  • ServiceNow and Enterprise Automation: A Functional, Strategic, and Cost Analysis

    ServiceNow and Enterprise Automation: A Functional, Strategic, and Cost Analysis

    ServiceNow: Does It Make Sense for Every Scenario?

    Nowadays, it is common to see the market, especially HIGH-END companies and organizations, adopting international platforms such as ServiceNow as the main, and often the only, path toward the evolution and consolidation of their internal processes and automations.

    However, this perception is not limited to ServiceNow. Other global platforms, such as Salesforce, are also often treated as universal solutions, which can be a serious mistake for several reasons.

    They are, in fact, extremely robust and powerful tools, and this article is not intended to diminish or question their strengths. On the contrary, the proposal is to present a different and alternative perspective for many of the situations and functionalities they offer, providing an approach with significantly lower costs without compromising efficiency.

    Let’s Take a Quick Comparison: ServiceNow vs. Other Alternatives

    Cost per nominal user vs. module, typically billed annually in dollars

    Work with platforms of similar robustness, capable of scaling across large organizations, but with licensing models better suited to the reality of our country.

    IT-oriented process modeling

    Evaluate platforms with a delivery-oriented approach, capable of generating solutions and automations directly within business areas, decentralizing IT and addressing bottlenecks commonly found in roadmaps.

    Extremely high consulting and labor costs

    Evaluate platforms that offer a faster adoption and learning cycle, with a more attractive cost-to-knowledge ratio, allowing business areas to scale their own solutions.

    IT Service Management (ITSM)

    Work with a focus on process automation and management, adopting the discipline according to the CBOK and guiding all of the organization’s processes not only IT services, but also business areas. This can be the starting point.

    IT Operations Management (ITOM)

    The ServiceNow solution is highly robust and technical, operating in an integrated manner with infrastructure and standing out for the strength of its functionalities. As an alternative, it is possible to evaluate process automation through an All-in-One enterprise platform, using functionalities such as CMDB either through ServiceNow itself or through alternatives available on the market.

    IT Asset Management (ITAM)

    Focus on the automation of processes for asset check-in and check-out, integrating with corporate systems, ERP, asset management systems, LDAP, among others.

    Enterprise Service Management (ESM)

    Focus on other areas of the company, such as HR, finance, legal, and other corporate services, promoting standardization, operational efficiency, and a consistent experience for internal customers.

    Low-Code Automation and Processes

    Robust process management and automation software, focused on end users and on well-established process management disciplines based on CBOK, BPMN, and market best practices, give business areas the ability to create solutions more autonomously.

    ServiceNow’s automation, on the other hand, is generally focused on IT teams or highly specialized professionals, which tends to result in significantly higher costs.

    Artificial Intelligence and Analytics

    Automate processes with the ability to integrate and embed agents into their content, providing advanced functionalities to end users in a simplified manner and with minimal adoption requirements.

    Security and Governance

    Focus on a platform oriented toward data and information as the foundation of the transformation journey, where this data can be managed through robust layers of security, compliance, and auditing, ensuring event trails and traceability for everything that is created, edited, accessed, or deleted, while putting business areas in control of decisions regarding how this information should be managed and governed.

    User Experience

    Do not be carried away by dynamics or user experiences based on the attention economy thesis. The focus should be on platforms that have real usability embedded in their DNA, rather than merely perceived usability, generating greater value for end users and respecting the level of care this experience requires. Just be mindful of placing too much emphasis on making things look “pretty.”

    Document Management (ECM)

    Work with an integrated platform for documents, processes, performance indicators, and digital and electronic signatures, with an application-oriented approach based on an All-in-One platform.

    Electronic and Digital Signatures

    Platforms with an established presence in Brazil, offering native digital and electronic signature capabilities integrated with process and document management modules. In ServiceNow, this functionality is not native, which often results in additional costs for third-party solutions and integrations.

    Risk Management, Compliance, and Governance (GRC)

    For processes and management scenarios with leaner characteristics, solutions based on BPM, ECM, and related technologies can meet these needs efficiently, at significantly lower costs. ServiceNow, in turn, offers highly robust modules, but with a higher level of complexity and investment.

    Integrations

    Focus on evaluating platforms that have robust integration layers in their portfolio, requiring as little code development as possible to enable communication between systems and, preferably, without additional costs per integrated transaction or dependence on third-party components or significant implementation efforts and investments.

    How to Evaluate Management Platforms Without Compromising Flexibility and Autonomy

    Based on this comparison, it is possible to observe that there are scenarios in which alternatives with the same level of robustness and ability to scale the business in the short, medium, and long term have significantly lower acquisition, maintenance, and ongoing development costs. In addition, these alternatives can offer a set of features and differentiators that ServiceNow does not provide, making them a highly viable option and, in many cases, the true deciding factor.

    More than just delivering astronomical cost savings, these solutions are capable of providing real value within the organization’s context, not only from a functional perspective but also in terms of culture and mindset. They promote an effective, comprehensive, and sustainable digital transformation journey, without locking the company into an expensive and excessively heavyweight platform over time.

    From Theory to Practice: When Digital Transformation Delivers Real Results

    There are relevant cases, especially in the public sector, in which Neomind has worked together with its clients while considering all these variables, achieving surprising results. Soon, a case study from Brasília, involving a government agency of national relevance, will be released, concretely demonstrating this approach.

    With the Fusion Platform as its foundation, and the organization fully aware of its digital transformation journey, it was possible to raise the standard of overall management by applying the platform to its full potential. In less than three months, the initiative enabled the automation of processes, documents, performance indicators, digital and electronic signatures, mobility, governance, compliance, auditing, risk management, and AI across business areas, fully covering the scope originally envisioned for a ServiceNow project, but at a significantly lower cost.

    Digital transformation starts with well-informed decisions. Discover the Fusion Platform.

  • Native integration, No additional cost and No-code: the power of acessible automation

    Native integration, No additional cost and No-code: the power of acessible automation

    Something common in the corporate environment, regardless of the size or industry of the business, is that time and native integration are synonymous with competitiveness.

    Connected systems and data accelerate process execution and management, driving business growth.

    Technology has become such an important factor within organizations that, according to Gartner, total technology spending is expected to reach $5.5 trillion by the end of 2025.

    However, every investment needs to be properly planned and strategic. In practice, the efficiency of technological resources should be directly linked to reducing costs and saving time. After all, there is little point in adopting new resources if the company’s financial health is negatively affected.

    With this in mind, Neomind’s Fusion Platform offers accessible automation and native integration at no additional cost

    The power of native integration with Fusion Platform

    To carry out their daily routines, companies commonly rely on access to several different corporate systems. In a sales process, for example, it is necessary to cross-reference information from the CRM with the ERP and other management platforms.

    If your company does not have automated processes, you know that the lack of interconnection between software systems can compromise the operation as a whole.

    With Fusion Platform’s native integration, all corporate systems are connected quickly, practically, and at no additional cost. The goal is to eliminate the technical and financial barriers that make innovation more difficult.

    While other solutions treat integrations as an additional service, Neomind provides ready-to-use native integration. The only action required from the user is to configure the tool according to their routine, adding the systems and data required for the activity flow.

    In addition to having no additional cost, customization can be performed by any employee without requiring programming knowledge. These practical actions ensure scalability, allowing the solution to keep pace with your business growth.

    In practice, Fusion Platform connects all systems and data sources without code and at no additional cost. This is possible because it provides an advanced native integration component.

    Since there is no need to write lines of code or rely on IT support, automation becomes a strategic element that promotes agility, productivity, and focus on the core business.

    Full compatibility and integration with systems your company already uses

    Connecting to complex corporate systems has never been this simple. The native integration component was developed to act as a true intelligent hub, capable of communicating with the main corporate systems on the market quickly and at no additional cost.

    In practice, the connection can be made to any data source, especially:

    • Mercanet;
    • Prometheus;
    • RM;
    • Consinco;
    • SAP;
    • Senior;
    • Seil;
    • Data Sul;
    • Active Directory

    Data and information moving between platforms in a systematic and integrated way ensure smooth processes without failures or interruptions.

    In addition, rework is considerably reduced because teams work with updated and accurate documents. In this scenario, there is no longer a need to resend versions, exchange emails, or manually cross-reference data.

    Furthermore, everyone involved knows they have reliable data at their disposal. Aligning processes with document management means spending less time searching for or reconciling information.

    Native integration requires no technical support or lines of code

    Neomind is not only committed to offering an excellent platform, but also to facilitating and improving the user experience through usability and accessibility. When it comes to integration, BPM, ECM, Analytics, CRM, ERP, databases, and other systems can be connected in just a few steps.

    Fusion Platform has a fully intuitive, visual, and user-friendly interface. Its configuration environment is based on drag-and-drop elements, enabling any user to design integration flows and put them into operation quickly.

    These practical actions make it possible to configure activity flows, integrate systems, define permission rules, map data, and much more.

    The reason for empowering users is the belief that only those who work with processes every day know which corporate solutions should be integrated at each step of the process—and how that connection should be made.

    Native integration is designed to minimize technical complexity by eliminating the dependency on coding. As a result, innovation is accelerated and the entire business routine becomes more agile and efficient, with governance ensured throughout the operation.

    Integrated ecosystem: Automation, Documents and Analytics

    Fusion Platform is a complete solution for legal, process, analytics, document, risk, and electronic signature management. As a result, it can unify processes, data, and information to build an integrated ecosystem.

    Each of these capabilities is available through modules that support management across different business areas. However, everything operates in an interconnected way, with standardization, traceability, and monitoring at all levels of the organization.

    Specifically for process, document, and analytics automation, the solution offers specialized modules:

    • Process Management (BPM): supports the standardization and automation of process activity flows by connecting steps to corporate systems. BPM ensures control, monitoring, and agility in the execution of business processes;
    • Electronic Document Management (ECM): integrates documents and information directly into workflows, ensuring version control, traceability, and regulatory compliance. ECM centralizes the document lifecycle and ensures information integrity and governance;
    • Analytics: consolidates data from multiple sources and enables it to be analyzed through interactive, dynamic dashboards updated in real time.

    Fusion Platform has a mobile version so that this entire management ecosystem is available at your fingertips. With access from any device, at any time and from anywhere, strategic decisions can be made based on real and structured data.

    Regarding native integration, connecting data from solutions such as SAP, Senior, Datasul, or Protheus ensures that activities are not interrupted or delayed. The result is an agile operation prepared for the challenges of digital transformation. Without requiring new investments, native integration delivers significant gains in governance, productivity, and continuous innovation.

    The power of accessible automation for business growth

    More than efficiency, Fusion Platform’s native integration can unlock new possibilities and drive business growth through native, intelligent, and flexible integrations. Companies adopting the solution highlight increased speed, reduced costs, and greater flexibility in their processes. As a low-code solution, it gives users the independence to create and build their workflows in a matter of minutes. In addition, encryption and permission layers ensure full control over data and information.

    While accessible automation gives users the power to accelerate business growth, no-cost native integration keeps everything operating in perfect harmony.

    In a highly competitive business environment, expanding operations cannot come at the expense of the company’s financial health. In this scenario, the fastest-growing companies are those that can intelligently connect people, processes, and data.

    Unlike complex and expensive solutions, Neomind delivers simplicity, efficiency, and integration in a single platform. No other solution offers this level of flexibility without additional charges.

    Stop wasting time and money switching between systems. Try Fusion Platform and transform process execution and the way your entire company works.

  • Benefits of scalable platforms in the Era of Digital Transformation

    Benefits of scalable platforms in the Era of Digital Transformation

    That every business seeks growth is nothing new. The problem begins when this development is supported by technologies that cannot keep up with the pace. In other words, digitalization does not happen without the use of scalable platforms.

    Many companies decide to modernize their processes by focusing only on the urgency of the moment: solving a specific bottleneck, meeting an immediate demand, or quickly reducing costs. The result? Systems that work well today become an obstacle tomorrow.

    Monolithic systems hinder development. They make organizations dependent on rigid solutions that are difficult to integrate and require new investments for customization, growth, or the addition of new functionalities.

    It is not uncommon to see promising businesses tied to legacy systems simply because they did not consider scalability from the outset.

    Adopting scalable systems is not just a technical decision, but a strategic choice. It enables businesses to grow with greater predictability, integrate new solutions more easily, and avoid rework in the future.

    In this scenario, sustaining your business’s evolution increasingly depends on the foundation you build today.

    Why are scalable platforms so important?

    In practical terms, scalability is a technology’s ability to grow alongside the business without compromising performance or quality or causing a disproportionate increase in costs.

    Scalable solutions become strategic allies because they make it possible to:

    • handle large volumes of data and transactions;
    • integrate with different systems and technologies already in place within the company;
    • adapt to new demands and processes without the need for constant replacement or complex maintenance.

    This technical robustness ensures the long-term value of the software investment. The solution adopted today remains relevant in the future, keeping pace with the company’s growth and the increasing complexity of its processes.

    Tangible benefits of scalable platforms

    As you might expect, a tool capable of keeping pace with your business’s growth becomes a strategic asset.

    The Fusion Platform is an example of a scalable platform. It is a robust solution that stands out from competitors through its ability to manage large volumes of data and complex operations that other solutions cannot handle.

    In addition, it can be easily integrated into your existing technology ecosystem, ensuring that your investment remains valuable in the short, medium, and long term.

    The benefits provided by scalable technologies include:

    Reduced total cost

    Maintaining legacy systems or adopting tools that cannot scale can result in high costs related to maintenance, rework, data conversion, frequent migrations, and even operational downtime.

    In contrast, a solution with an adaptive architecture eliminates the need to constantly replace tools.

    By investing in the Fusion Platform, businesses gain access to a comprehensive solution whose benefits can be leveraged for many years.

    As processes become more efficient and operating costs decrease, the return on investment is achieved much faster.

    Seamless integration and the elimination of data silos

    When a company’s systems do not communicate with one another, the impact becomes apparent quickly. Information gets duplicated and data becomes inconsistent. In addition to compromising efficiency, this scenario increases operational risks and makes strategic decision-making more difficult.

    With a well-structured, scalable platform, integration is no longer a problem. Systems, new applications, databases, and different information flows can be connected in a simple and organized way.

    With data centralized, it becomes more reliable and easier to access. As a result, the business gains a holistic view, and every decision can be based on real data.

    Agility, Adaptability and Support for growth

    Digital transformation continues to advance and is already part of the reality of a significant number of companies of all sizes. However, the issue is not simply about modernizing routines. The real question is how to make this growth efficient in the long term

    As automation, artificial intelligence, and data analytics become part of everyday operations, technology needs to support this evolution. When it fails to do so, companies end up facing more problems than solutions.

    Because the Fusion Platform is a low-code solution, it allows users, even those without programming experience, to configure rules and workflows, perform integrations, build forms, and make all the customizations needed to meet their day-to-day demands. By adapting to the specific requirements of each business, the solution can support the organization’s internal and external growth.

    Investment longevity

    Switching tools with every new stage of growth represents high costs, operational risks, migration time, and the constant need to train teams.

    Scalable platforms reduce this cycle by providing a solid technological foundation from the outset.

    With sufficient resources to build a robust data infrastructure, the company is prepared to grow continuously, without technical limitations or disruptions. In addition to avoiding the need to invest in additional resources, the company can generate more revenue through greater process efficiency.

    Choosing the right platform is a strategic decision

    The mindset of adopting software solely as a tool to solve a specific problem can lead to inconsistencies in the future.

    Failing to consider business maturity, new data, integrations, adaptations, and process expansion represents a significant risk.

    Choosing a scalable platform from the outset means adopting a long-term perspective. It means understanding that technology is not an isolated cost, but a strategic investment that supports the company’s operations and expansion.

    In the era of Digital Transformation, systems capable of handling large volumes of data, integrating with the technology ecosystem, growing alongside the business, and ensuring governance and robustness can reduce costs, accelerate operations, and prepare organizations for the future.

    The Fusion Platform enables companies to centralize processes, data, documents, performance indicators, legal management, risk management, and electronic signatures in a single environment.

    All configurations can be performed in a simplified way using drag-and-drop functionality. In addition, the platform offers native integration, with everything supported by compliance and governance layers.

    In summary, Neomind’s solution was developed to support your business’s growth journey. Try the Fusion Platform, schedule a demo and bring all the benefits of scalable platforms to your business.

  • Continuous, Connected, and Contextual Decision-Making: The Differentiator for Agile Companies

    Continuous, Connected, and Contextual Decision-Making: The Differentiator for Agile Companies

    In a scenario where business moves at an accelerated pace, and opportunities emerge and disappear within minutes, fast and intelligent decision-making has become the greatest competitive differentiator.

    More than speed, what defines an agile company is the ability to decide well, based on reliable, up-to-date, and contextualized data. And this is only possible when there is structure behind the technology.

    That’s why you should discover how to keep the decision-making process efficient and how to build the foundation for using Artificial Intelligence applied to decision-making.

    First: why does your company invest in technology?

    If you are a public or private manager, an entrepreneur, or a decision-maker, stop and think: why do you invest in management systems, Artificial Intelligence, automation and other technological solutions?

    The answer, most of the time, is simple: you want reliable information, available in real time, to make well-founded decisions with confidence and agility.

    This is the core of modern management. However, many organizations still face the same obstacles as in the past:

    • Slowness in consolidating data;
    • Decisions based on manual spreadsheets;
    • Information silos between departments;
    • Difficulty seeing the big picture.

    Despite access to modern tools, the lack of a solid foundation keeps the decision-making process inefficient. And that is where the difference lies between adopting technology and structuring the company to use it intelligently. 

    The problem of decision-making with fragmented data

    Even in organizations already undergoing digital transformation, it is still common to see manual processes, data spread across multiple systems, and a lack of structured data governance. This scenario generates serious consequences:

    • Delays in critical decisions;
    • Difficulty identifying risks and opportunities;
    • Lack of trust in the available information;
    • Conflicts between departments and rework.

    The information does exist, but it is disorganized, incomplete, or inaccessible. This compromises strategic decisions and hinders the efficient use of Artificial Intelligence applied to decision-making.

    According to Harvard Business Review, data-driven companies are 5 to 6 times more likely to make effective decisions. Meanwhile, Gartner projects that, by 2028, 15% of daily work decisions will be made autonomously by autonomous AI. However, by the end of 2027, it is estimated that 40% of projects will be canceled, mainly due to excessive expectations and inadequate application of the solutions.

    The path: from doing the basics well to intelligent decision-making

    Truly agile companies build their edge on three interdependent pillars:

    1. Process automation
    2. System and data integration
    3. Information governance

    These three elements are the foundations of continuous decision-making. They allow technology, especially AI, to operate efficiently and generate real value.

    1. Automation is agility with control

    Fast, reliable decision-making starts with eliminating improvisation and manual task execution.

    Process automation ensures standardization, traceability, and efficient execution. With tools like BPMS, it is possible to map, execute, and monitor workflows with clear rules.

    Document management systems (ECM), in turn, ensure that documents are organized, available, and compliant.

    With this, the company gains:

    • Operational agility: decisions executed in minutes;
    • Standardization: clear, replicable processes;
    • Traceability: essential for governance and auditing.

    By automating routines, the team gains time for analysis and strategic thinking. These elements are crucial for impactful business decisions.

    2. Integration provides a big-picture view of the business

    Automating is essential, but if each process operates in isolation, managers will still be left with a fragmented view.

    System integration ensures a continuous flow of information across departments, connecting data and enabling broad, contextualized analysis.

    Imagine a company that has automated its sales process, but customer service isn’t integrated with the CRM, and the finance department still relies on spreadsheets. The result will be decision-making based on fragments of reality, not the whole picture.

    Integration enables:

    • Consolidating data from different sources;
    • Seeing the complete customer or product journey;
    • Cross-referencing indicators across departments and identifying hidden opportunities.

    According to Forrester, organizations with integrated data are 2.3 times more likely to make effective decisions aligned with strategic goals.

    Without integration and a continuous flow of information, any attempt at analysis, whether human or AI-driven, will be limited and prone to errors.

    3. Governance is trust, ethics, and consistency

    Lastly, governance provides a set of policies, controls, roles, and responsibilities that ensure the quality, security, traceability, and legal compliance of data.

    Without governance, a company may operate with outdated or inconsistent data and face legal risks, such as failing to comply with LGPD regulations. Even more serious: decisions become vulnerable to errors and biases.

    However, when governance is in place:  

    • Data gains an internal quality certification.
    • Analyses become more accurate and reliable.
    • The company operates with accountability and transparency.

    This pillar closes the cycle. Automation generates agility and centralizes information, integration provides a complete view, and governance ensures reliability.

    How do these pillars pave the way for AI?

    Artificial Intelligence is the element that amplifies everything that was already well structured.

    With organized, integrated, and governed data, AI can:

    • Identify patterns;
    • Predict behaviors;
    • Generate actionable insights;
    • Support decisions in real time and with context.

    In other words, it is AI that connects and contextualizes data to support decision-making. 

    Want a practical example?

    Previously, the risk department of a large company spent days manually consolidating data to detect fraud. Today, with automated processes and integrated data, AI identifies anomalies in real time, alerting the team to possible compliance failures or unusual transactions.

    This change was only possible because the pillars were already in place. Without automation, reliable data, integration, and governance, AI would be nothing more than a sophisticated tool, incapable of generating real value or serving as a basis for fast, evidence-based decisions.

    Digital transformation doesn’t start with AI 

    It’s common to see companies waiting for the revolutionary solution that will solve every problem. But true business innovation is about solving old problems in a new, better, and more efficient way. 

    The major transformations we have seen in public and private companies don’t come from miraculous solutions, but from strategic alignment, a digital mindset, and the intelligent use of available technologies. 

    Although it may sound very simple, few companies can honestly say they have reached this level of innovation.

    Many organizations remain stuck in mediocrity because they focus only on the short term. They put out fires, live in reactive mode, and wait for a big disruptive idea that will save everything.

    But what really transforms a business is doing the basics with excellence, every day. Looking closely at processes. Working on bottlenecks. Automating routines. Trusting the data. Building a culture of continuous improvement. And applying Artificial Intelligence on the right foundations.

    AI is the icing on the cake, but automation and governance are the foundation

    Finally, we arrive at the big truth: AI is powerful, but it doesn’t work miracles. Agile companies aren’t the ones that simply adopt cutting-edge technology, but rather those that structure their processes for real-time decisions: continuous, connected, and contextual.

    This requires more than just AI. It requires building a solid foundation of automation, integration, and information governance. In other words, without well-structured processes, AI will deliver few benefits.

    If your organization is looking for a platform that brings together automation, integration, and governance, get to know Fusion Platform. With a user-friendly, intuitive interface, it centralizes process, document, indicator, and risk management, along with native electronic signature, in a connected and reliable way.

    Start your business’s corporate innovation. Book a demo and turn information into action, with agile, connected, and context-based business decisions.

  • How to Prepare Your Data Architecture to Support Hyperautomation and Enterprise AI

    How to Prepare Your Data Architecture to Support Hyperautomation and Enterprise AI

    In recent years, hyperautomation has evolved from a simple technology trend into a strategic imperative. To make it work, organizations need a robust, well-structured, and easy-to-manage data architecture.

    The integration of process automation, Artificial Intelligence, and advanced analytics is transforming how organizations operate, make decisions, and create experiences.

    Unfortunately, data architecture is still frequently overlooked. It often remains invisible until it fails.

    However, without a solid, integrated, and governed data foundation, there is no sustainable hyperautomation, only automated silos and inconsistent decision-making.

    That is why preparing your data architecture is essential to support an AI-driven digital transformation.

    The Strategic Role of Data Architecture

    Enterprise hyperautomation goes far beyond simply replacing manual tasks. Its goal is to orchestrate complex processes by connecting systems, people, and algorithms through intelligent, automated workflows.

    To achieve this, data must flow continuously, securely, and within the proper context. It fuels both internal automation technologies, such as RPA and BPM, and AI models that forecast demand, analyze risks, or recommend actions.

    When the data layer is fragmented or unreliable, the consequences multiply. Models lose compliance, processes become slower, and executive confidence deteriorates. In other words, operational inefficiencies become amplified.

    Therefore, data architecture should be treated as a strategic pillar. It is responsible for ensuring data quality, governance, and secure information exchange across every automation layer.

    Pillars of a Data Architecture Ready for AI and Hyperautomation

    A modern data architecture must balance scalability, governance, and flexibility. Solutions such as Fusion Platform support this framework by integrating secure data, automated pipelines, and continuous data quality monitoring.

    The key pillars that provide the foundation for AI and hyperautomation are:

    Scalable and Secure Infrastructure

    Data-driven organizations require an infrastructure that grows alongside the business and keeps pace with the computational demands of Artificial Intelligence. Hybrid and multi-cloud environments help balance performance, cost efficiency, and regulatory compliance.

    It is essential for raw and unstructured data repositories (data warehouses), clean and structured data repositories (data lakes), and vector databases to coexist, creating a complete lifecycle from raw data storage to analytics and AI inference.

    Security must be built in by design through encryption, role-based access control, data masking, and continuous auditing.

    In addition, the data architecture must ensure environment isolation and compliance with regulations such as Brazil’s General Data Protection Law (LGPD), without compromising agility.

    Intelligent and Observable Data Pipelines

    Data pipelines must be intelligent and observable. They should ingest data from multiple sources, automatically detect anomalies, version data transformations, and incorporate feedback loops that identify production regressions.

    By integrating Machine Learning Operations (MLOps) and Data Operations (DataOps) practices, organizations can manage data, code, and model versions in a coordinated manner, ensuring continuous, reliable, and secure delivery.

    Integrated Governance and Reliability

    Without governance, data loses its value and becomes a risk asset. In hyperautomation environments, governance must be automated and policy-driven, with access, quality, and retention rules enforced through executable policies integrated across the entire data lifecycle.

    Data lineage is another essential pillar. Knowing where each piece of data originated, how it was transformed, and which decisions it supports is critical for audits, model explainability, and regulatory compliance.

    Organizations must also establish clear roles, such as data owners and data stewards, while promoting data literacy across teams. Trust in AI is built on transparency and shared accountability.

    Integration with Enterprise Architecture

    Automation and Artificial Intelligence only deliver meaningful results when the data layer operates in harmony with enterprise systems, applications, and business functions. Modular and flexible systems make it possible to introduce new tools and AI models without redesigning the entire data architecture.

    Following well-established enterprise architecture frameworks helps maintain consistency between strategic planning and execution. This prevents rework, duplicate data, and disconnected systems.

    Practical Strategies for Building a Data Architecture for AI and Hyperautomation

    Designing a data architecture for AI and hyperautomation is an evolutionary journey rather than a one-time project. The following practical recommendations help organizations build a sustainable foundation.

    1. Start with High-Impact, Quick-Win Initiatives

    Before pursuing complex projects, prioritize initiatives that deliver visible value and measurable impact in a short period. These early successes generate organizational learning, build team confidence, and help guide future investments more effectively.

    2. Build an Artificial Intelligence Factory

    Think of AI implementation as an industrial process. Every initiative should follow a structured workflow for data collection, testing, experimentation, and performance monitoring.

    When these steps are standardized, it becomes much easier to replicate successful outcomes across new use cases while avoiding unnecessary rework.

    3. Embed Governance into Every Process

    Well-configured tools and policies automatically enforce security and compliance rules. This ensures that data is used ethically and securely, preventing errors and reducing legal and regulatory risks.

    4. Organize and Manage the Lifecycle of Data and AI Models

    To ensure AI initiatives remain reliable, organizations must maintain control over the history, versions, and performance of both models and datasets. This provides greater transparency, simplifies audits, and enables teams to quickly identify and resolve issues that arise in production.

    5. Prepare the Teams Involved

    Digital transformation is not just about technology and algorithms. It depends on people who understand the value of data, know how to interpret it, and share responsibility for its quality and proper use.

    When technology, data, and business teams work toward the same vision, Artificial Intelligence evolves from an isolated experiment into a fundamental part of the organization’s culture.

    Throughout this journey, strong alignment between business strategy, enterprise architecture, and technical teams is essential.

    Building a mature data architecture requires lifecycle management, automated governance, and continuous monitoring. Fusion Platform supports this process by providing integrated dashboards, complete data traceability, and automated anomaly alerts.

    Hyperautomation and Enterprise AI for the Long Term

    Data architecture is the invisible foundation of intelligent digital transformation. It ensures that every automation initiative and every strategic decision is supported by reliable, traceable, and well-governed data.

    When data is treated as critical infrastructure rather than an operational byproduct, organizations gain the precision, agility, and security needed to transform isolated automation initiatives into continuous enterprise intelligence.

    Data maturity is not a destination but an ongoing journey of improvement. Every learning cycle, every enhanced pipeline, and every governance policy strengthens the foundation on which Artificial Intelligence can thrive.

    Investing in data architecture today ensures that tomorrow’s AI will do more than automate processes, it will evolve alongside the business.

    Neomind’s Fusion Platform was designed to accelerate this journey with security, traceability, and confidence. Now is the time to build the foundation your organization’s future depends on. Experience Fusion Platform.

  • Process Governance: The Essential Framework for AI

    Process Governance: The Essential Framework for AI

    Process governance is the backbone of Artificial Intelligence in organizations.

    In a scenario where algorithms automate decisions, interact with customers, and optimize operations in real time, applying AI without well-defined processes, reliable data, and traceable workflows can result in operational chaos, legal failures, and misguided decisions.

    To avoid this, it is essential to implement robust governance with clear roles, version control, compliance, and traceability. Understand how these actions will transform your digital transformation journey.

    What is process governance?

    Process governance is the practice of planning, structuring, monitoring, and controlling an organization’s business processes. Its goal is to ensure efficiency, consistency, and alignment with corporate strategies.

    It goes far beyond automating tasks or mapping workflows, it is an approach that ensures clarity about who does what, how, and why.

    In other words, it involves defining roles and responsibilities, applying clear operational rules and policies, and adopting mechanisms for auditing, traceability, and compliance with standards and regulations.

    The challenge is not adopting AI, many companies have already done that. The real challenge is scaling with control. Currently, 78% of organizations already use AI in at least one function, and 71% use generative AI in processes such as marketing, IT, and customer service.

    In an increasingly automation- and AI-driven landscape, governance becomes even more critical, ensuring that the data used by automated systems or AI models is reliable, structured, and documented.

    8 pillars of effective process governance

    1. Process modeling (BPM): formal and standardized representation of business processes, with well-defined flows, steps, rules, and events;
    2. Process lifecycle: a structure that encompasses modeling, automation, execution, monitoring, and continuous optimization;
    3. Roles and responsibilities: clarity about who is responsible for modeling, approving, executing, monitoring, and reviewing each process;
    4. Operational rules and policies: a set of internal standards, guidelines, and criteria that guide decisions and behaviors;
    5. Metrics and indicators (KPIs): performance and compliance measures used for monitoring, control, and continuous improvement;
    6. Audit and traceability: mechanisms to record and track actions, decisions, versions, and executions over time;
    7. Regulatory compliance: ensuring adherence to laws, standards, and frameworks;
    8. Supporting tools: technology platforms that enable the centralization of governance within a single environment.

    Real risks of applying AI without governance

    Without solid governance, organizations risk losing control over their operational flows, compromising information quality, and exposing themselves to legal, ethical, and technical failures.

    Furthermore, it can lead to financial losses, particularly regarding data handling.

    A study by IBM found that the average global cost of a data breach is $4.88 million. The same research also found that companies that effectively adopt AI and automation in their security practices save approximately $2.2 million per incident.

    Laws such as Brazil’s LGPD (General Data Protection Law) and risk management standards like ISO 31000 require companies to document their operations, maintain traceability of decisions, and mitigate risks associated with the use of technology. In other words, this is not only about efficiency it is a regulatory requirement.

    In detail, implementing AI without process governance can generate risks such as:

    1. Unstructured and unreliable data: AI learns from historical data. If that data is inconsistent or fragmented, models become inaccurate and biased;
    2. Undocumented processes: without clear and formalized workflows, AI operates in an environment of uncertainty, making standardization and scalability more difficult;
    3. Lack of traceability and accountability: automated decisions without auditable trails compromise compliance and make it harder to investigate failures or prove adherence to legal requirements;
    4. Automation without control: AI does not fix broken processes, it scales them. Without governance, operational errors and bottlenecks multiply rapidly.

    All of these risks demonstrate that investing in technology alone is not enough: a solid governance foundation is essential to ensure security, efficiency, and compliance. This is where Fusion Platform stands out.

    Fusion Platform: Governance and AI in the same ecosystem

    Fusion Platform is a complete, low-code solution that offers process, document, indicator, and risk management. By combining numerous functionalities, it centralizes process governance by integrating information from multiple sources with security, traceability, and scalability.

    To ensure security, Neomind’s solution offers features such as encryption, authentication, and an audit trail, reducing the risk of data leaks and unauthorized access.

    All activities carried out through Fusion Platform are governed by clear accountability rules, allowing verification of who did what, when, and at which stage.

    Fusion Platform’s features form the foundational structure for AI implementation:

    Traceability

    Every document and form is precisely monitored regarding who accessed it, when, and what changes were made. Access control is managed with configurable permissions by user, group, role, folder, and document.

    All changes are recorded with date, time, author, and modified content, ensuring everyone works with the same updated versions.

    Task Center

    Brings together all activities assigned to users, with task redistribution, delay alerts, and color-coded status monitoring, reducing the occurrence of process bottlenecks.

    Reports and indicators

    Processes and activities can be tracked in real time through customized dashboards. Access control ensures that strategic information is available only to specific profiles.

    Audit center

    Compiles complete usage trails, from user logins to changes in documents, processes, forms, and settings. Information can be filtered by time period, sampling, IP address, author, or action type. This makes it possible to investigate suspicious activity, trace failures, identify data leaks, and reinforce compliance with standards and regulations such as the LGPD.

    Collaborative modeling

    The creation, analysis, and improvement of business processes is carried out jointly by different teams. Documentation and workflow design can involve the participation of all stakeholders.

    Fusion Platform success story

    In the partnership between Avalara and Neomind, the platform serves as the process governance foundation that enables end-to-end tax automation.

    While Avalara provides specialized solutions for tax calculation and fiscal compliance, Fusion Platform organizes and standardizes internal operational workflows, ensuring traceability, version control, and adherence to regulations.

    This creates an ideal environment for applying Artificial Intelligence, with reliable data, formalized processes, and comprehensive audit capabilities.

    As a result, companies not only automate their tax obligations safely and efficiently, but are also prepared to apply AI in a strategic, scalable, and fully compliant manner.

    Roles in AI-driven governance

    For governance to function as the foundation of digital transformation with AI, roles and responsibilities must be clearly established:

    • Process manager: responsible for mapping, modeling, and optimizing workflows. Acts as a bridge between operations and strategy.
    • Data analyst: collects, structures, and prepares the data used by AI models.
    • AI and machine learning specialist: creates, trains, and monitors algorithms, ensuring alignment with process objectives.
    • Compliance and legal team: verifies that automated processes comply with current legislation.
    • Business managers: use the generated insights for decision-making and operational realignment.

    Fusion Platform facilitates this integration by enabling everyone to work within the same ecosystem, with defined permissions, controlled access, and full visibility over all actions.

    It is important to remember that AI is not a project with a beginning, middle, and end. It is a continuous process of learning and evolution.

    Only through ongoing process governance work can AI evolve with control, security, and real strategic value.

    AI and governance walk the same path

    Governance and Artificial Intelligence are not parallel paths, they are integrated tracks. Success in the digital era depends on the combination of intelligent automation, data-driven decisions, and well-structured processes.

    With Fusion Platform, your company can turn this vision into reality. Ready to structure your governance and apply AI with true security, traceability, and scalability?

    Try Fusion Platform and gain competitive advantages and continuous growth with governance and Artificial Intelligence.

  • How Legal Automation Can Reduce Operational Risks in the Legal Sector

    How Legal Automation Can Reduce Operational Risks in the Legal Sector

    In a sector where deadlines are non-negotiable and the margin for error is minimal, legal automation has moved beyond a trend — it has become essential.

    By implementing task digitization, standardizing workflows, and integrating technologies, it is possible to transform legal operations into a more efficient, secure, and traceable environment.

    However, managing countless simultaneous cases, each with distinct rules, deadlines, and requirements, without proper standardization or tools, makes operational risk inevitable.

    What about your organization? Does your legal operation still rely on endless access to government websites, spreadsheets, and manual controls? Discover how to make your routine more productive and efficient with legal automation.

    The Challenges of Operating Without Legal Automation

    The complexity of legal routines and the high volume of data demand precision at every step. In a scenario marked by strict deadlines, detailed procedural rules, and heavy documentation, any mistake carries financial and reputational risk.

    Furthermore, the lack of uniformity across court systems undermines control and raises the cost of legal operations.

    In general, the main problems faced are:

    • Manual errors in petitions, contracts, or registrations;
    • Missed procedural deadlines;
    • Lack of standardization in workflows;
    • Difficulty tracking actions and decisions;
    • Duplicate documents or inconsistent versions.

    Faced with this scenario, the automation of legal processes is consolidating itself as a strategic ally for mitigating operational risks and increasing efficiency.

    How to Reduce Operational Risks in the Legal Sector?

    Automation transforms the way legal departments and law firms manage their activities. It can replace manual, error-prone tasks with automated, configurable, and auditable workflows.

    The main risk mitigation mechanisms in legal management are:

    • Reduction of human error: activities such as filling out documents, tracking deadlines, and submitting petitions become automated, minimizing mistakes caused by distraction or oversight;
    • Action traceability: each step of the legal process is recorded in an auditable way, allowing managers to track who did what, when, and how, promoting transparency and compliance;
    • Automatic alerts and notifications: ensure compliance with deadlines and commitments through reminders and automated workflows, preventing delays and procedural losses;
    • Process standardization: with ready-made templates and defined workflows, legal operations become more efficient, reducing variability and errors arising from different interpretations among professionals;
    • Integration with legal systems: by centralizing information from different courts — such as TRT, PJE, EPROC, TJRJ, and STF — in a single environment, data loss and rework are avoided, and access to information is streamlined.

    In practice, legal automation does not just optimize tasks. It creates a safer, more reliable, and sustainable environment for lawyers, public prosecutors, and legal departments.

    Now imagine having a technology solution capable of unifying automation, traceability, and practicality in a single environment. That is the value proposition of the legal module of the Fusion Platform.

    Fusion Platform Legal Module: Complete Automation for the Legal Sector

    The Fusion Platform legal module is a legal technology solution developed to unify and automate legal operations, standardize access to courts, and optimize legal routines — especially in the management of tax enforcement proceedings.

    Check out the main features of the Fusion Platform legal module:

    Process Automation and Operational Workflows

    • Complete automation of legal processes;
    • Creation and management of legal document templates;
    • Smart filing (immediate, scheduled, or deferred);
    • Bulk and centralized petition submission;
    • Automatic validations ensuring compliance between stages;
    • Portfolio dashboard with deadline tracking.

    Deadline and Commitment Management

    • Intelligent deadline control and monitoring system;
    • Automatic alerts for upcoming expirations and pending actions;
    • Protocol scheduling via the National Interoperability Model (MNI).

    Document, Contract, and Signature Management

    • Batch document creation, versioning, and review;
    • Draft and contract review in just a few clicks;
    • Integrated electronic signature (including WhatsApp);
    • Batch signing for high productivity;
    • Secure digital environment with full audit trail.

    Integration with Legal Systems and External Databases

    • Direct connection to courts including TRT, PJE, EPROC, TJRJ, and STF;
    • Integration with tax debt systems and public databases;
    • Direct case file viewing and advanced case search.

    Strategic Management and Performance Indicators

    • Customizable dashboards with legal KPIs;
    • Real-time management reports;
    • Operational performance monitoring.

    Artificial Intelligence and Legal Chatbots

    • Automated legal information search;
    • AI-assisted defense drafting;
    • Intelligent review of contracts and procedural documents.

    10 Real Gains from Automating the Fusion Platform Legal Module

    Unlike other platforms, the Fusion Law Platform is a solution built specifically for the legal sector.

    That means the form templates, integrations, and all document management are designed around the real needs of the industry. Moreover, Fusion’s AI capabilities provide greater productivity and speed to everyday routines.

    Among the main benefits of legal automation, the following stand out:

    • Greater agility and performance in day-to-day operational tasks;
    • Prevention of manual errors through automated, auditable workflows;
    • Standardization of operational workflows;
    • Automatic alerts;
    • Greater security with auditable records and centralized documentation;
    • Compliance with regulations and privacy policies;
    • Standardized document templates;
    • Deadline compliance through automatic alerts;
    • Management analytics and reports updated in real time;
    • Integration with legal systems, tax debt systems, and external databases.

    See Legal Automation Success in Practice

    The platform currently handles more than 500,000 active cases and over 7,000 petitions filed per month.

    The large volume of data from the Rio de Janeiro Municipal Attorney General’s Office (PGM-RJ), for example, is managed using the features of the Fusion Platform legal module.

    In 2023 alone, the PGMRJ had more than 33,000 tax enforcement proceedings filed, and over 210,000 tax debt certificates received in 2024 via DAM.

    In addition, the platform eliminated more than 50,000 tasks per month — the equivalent of over 1 million tasks throughout the year.

    More Control, Organization, and Security in Legal Operations

    In fact, it is automation in legal process management — with well-defined rules, automated activities, and procedural intelligence — that offers a new level of control.

    In general, legal automation tools ensure that operations are carried out correctly. A step only moves forward to the next when all necessary validations have been met. This prevents tasks from being completed outside the standard or in non-compliance.

    Furthermore, the centralization of documents and records in a secure digital environment reduces the risk of loss, facilitates versioning, and ensures compliance with regulations such as the LGPD (Brazil’s General Data Protection Law).

    More than a technological trend, legal automation is a concrete response to the operational vulnerabilities of the sector. By enabling standardized, traceable, and integrated workflows, the legal sector is transformed into an efficient, secure, and future-ready environment.

    Want to understand, in practice, how automation can transform your institution’s legal operations?

    Schedule a free demo of the Fusion Platform legal module and discover how to eliminate missed deadlines, rework, and risks with a solution built specifically for the legal sector.

  • PCF: Process Classification Framework and Process Automation

    PCF: Process Classification Framework and Process Automation

    To be honest, can you classify your company’s processes? Do you keep them in an organized and standardized way? If not, it’s time to meet the PCF.

    It is common for many companies to have difficulty describing and classifying the activities carried out due to the lack of terms and categories. This is a problem that the Process Classification Framework sets out to solve.

    Understanding business processes is essential to achieve efficiency and agility in today’s business landscape. And, it was precisely to facilitate its understanding and management that this classification structure model was created.

    In addition, the tool facilitates the implementation of automated solutions, which, in turn, bring countless benefits, such as increased productivity and reduced errors.

    So, if you want to transform your operations by promoting an agile and effective environment, understand the applications of PCF in process automation.

    What is PCF?

    PCF or Process Classification Framework is a methodology that aims to identify, classify, organize and standardize business processes.

    This process classification structure favors the understanding of the internal workings of an organization from a horizontal point of view.

    For easy understanding, it consists of a hierarchical list of the composition of the processes, starting from the highest level to the most basic or simple.

    In short, it is as if it were a universal language that companies of all sizes and segments can use to optimize their processes.

    In general, the PCF divides processes into broad categories such as primary, support and management processes.

    Its main components are:

    • Categories: Represent the highest levels of classification. It groups processes with similar characteristics and objectives. Examples of categories are: production processes, management processes, financial processes;
    • Process groups: This is a subdivision of the categories. It groups more specific processes, such as assembly processes or manufacturing process;
    • Processes: These are detailed units of work. It has the definition of the tasks and sequences necessary to achieve a specific goal. Here you will find specific classifications such as: “manufacturing process of product X”;
    • Activities: comprises the tasks, of different levels of complexity, that make up a process.  

    Identifying and categorizing processes offers a holistic view, providing a better understanding of how they connect and contribute to business objectives.

    It’s important to clarify that this isn’t a visual representation of the workflow. PCF is not a tool similar to BPMN, but it serves as a basis for process modeling.

    Why should companies use the process classification framework?

    By utilizing PCF, organizations gain a clear view of their workflows, identifying areas for improvement. As a highlight, it facilitates the visualization of processes whose automation should be prioritized.

    This methodology serves as a basis for organizations to develop the definitions and modeling of internal processes. In addition, it offers a consistent language for mapping the ways of working carried out today.

    The use for modeling allows you to develop and manage a variety of business models, helping employees rationalize the impact or changes in the adopted models.

    Specific reasons for adopting PCF involve:

    • holistic view of processes: observe the complete picture of all processes, whether strategic or operational;
    • understanding of interdependencies: understanding how activities are related, facilitating the discovery of bottlenecks and flaws;
    • align processes with strategy: ensures that all activities are directed towards the company’s objectives;
    • unified communication: standardization of the language to facilitate the exchange of information between sectors;
    • identification of opportunities for improvement in inefficient, redundant or rework-generating processes;
    • have a solid foundation for the use of other methodologies such as BPMN, Lean and Six Sigma;
    • it favors risk management and the creation of contingency plans to proactively mitigate threats.

    In general, the PCF is a fundamental tool for companies of different sizes and levels of complexity to increase business efficiency. This is often achieved by optimizing activities with the automation of processes.

    PCF and Process Automation with Fusion Platform

    Based on the classification provided by the PCF, the order of priority for automation is defined. Considering, mainly, those who have more very manual, bureaucratic activities, with bottlenecks or a high rate of errors.

    Fusion Platform is a complete, user-friendly, low-code, and customizable solution to meet the specific demands of your organization.

    After classification and organization with PCF, Fusion comes into action, offering capabilities to map, automate, and monitor the identified processes, facilitating end-to-end digital transformation.

    Mapping creates leaner, more intuitive, and more practical workflows. Rather than focusing on small tasks, the focus is on achieving a specific goal.

    Process optimization involves simplifying the flow as a whole, eliminating unnecessary and non-value-added activities, and must be carried out with a view to automation. The correlated and parallel activities are considered, and the integration with other systems already used by the company.

    As it is a platform for the management of processes, risks, documents, indicators, and electronic signature, using the Fusion Platform in the execution of processes, employees can focus on strategic activities directly related to the company’s reason for being.

    The processes are executed with the help of BPMS, providing the opportunity to collect data that is presented in metrics and reports to monitor the performance of automated activities.

    These analyses create a constant cycle of continuous improvement, and with the Fusion Platform, those involved can manage and monitor them in real time, through the system or application.

    Adopt tools and methodologies to analyze, monitor, and manage your processes quickly, intuitively, and accurately.  Classify existing processes in your organization with PCF.

    Don’t waste any more time, request a demo and realize the true digital transformation of your business.

  • Apply the PDCA Cycle and ensure the continuous improvement of your processes

    Apply the PDCA Cycle and ensure the continuous improvement of your processes

    The PDCA method is a means used by companies to improve their processes, products, and services. This cycle is not only about specific problems, but about the implementation of a culture of continuous improvement.

    To better understand the concept, think about the following situation: Pedro is the sales manager of an e-commerce. In the last month, the number of requests has plummeted. Customers who usually make purchases every 15 days suddenly disappeared. When analyzing some indicators, Pedro saw that the indicator related to customer satisfaction dropped dramatically.

    So, Pedro decided to meet with the customer service team to understand what may be happening. Analyzing some data, it was noticed that the main complaint of customers is the delay in delivery. The manager begins to research the issue further and discovers that there is a flaw in the sales process, which has recently been adapted.

    There is no doubt that it will be necessary to act yesterday, because, otherwise, the company’s cash, which is already asking for help, will suffer even more.

    Thus, Pedro and the team decided to develop an action plan and implement the PDCA cycle.

    What is PDCA?

    Plan, Do, Act and Check, from the initials of each word, we have the acronym PDCA.

    Developed in the 1950s by management consultant Dr. William Edwards Deming, when we talk about PDCA, we refer to a very important quality tool.

    Known as the Shewhart Cycle, the Deming Cycle, or PDSA (Plan, Do, Study, Act), PDCA came about because Deming wanted to create a solution to help companies develop hypotheses about what needs to change and then test them in a continuous feedback loop. Hence the term “PDCA cycle”. 

    It is a four-stage iterative approach that aims to continuously improve processes, products, or services, and is an excellent tool for problem solving.

    The PDCA methodology is widely used by companies that wish to improve their management levels with the efficient control of processes and internal and external activities, standardizing information and minimizing the chances of errors in decision-making.

    Because it is a continuous feedback loop, once implemented, PDCA becomes a constant in the company, since its main objective is continuous improvement.

    Applications and advantages of the PDCA cycle

    The PDCA Cycle can improve any process or product, being applicable in numerous situations. In the field of technology, for example, the methodology of plan, do, act, and verify is used to analyze the software development lifecycle.

    In the manufacturing and services industry, the tool is used for the development of new products. Project management also enjoys its benefits.

    These are just a few examples, the method can be used in several other departments or segments to obtain advantages such as:

    • Helps in the implementation of Total or Six Sigma Quality Management initiatives;
    • Assists in the continuous improvement of processes;
    • Avoids the waste of resources;
    • It is replicable: from the moment a new technique or process method is successfully verified and analyzed, the company can expand the method already knowing the results to be expected;
    • Explores a range of solutions to problems;
    • It allows the company to test a small-scale process change before investing in a method that may not work or will require adjustments.
    • Contributes to cost reduction.

    A very important application of the PDCA Cycle is in Goal Management. Remember Pedro’s story? Well, the customer satisfaction indicators were much lower than expected, which ended up interfering with sales and profitability goals.

    By applying PDCA, an action plan is developed to correct the deviations that are hindering the achievement of goals. That is, the good relationship between planned and realized is guaranteed.

    How the PDCA Cycle works

    As we have seen, the methodology has four phases that must be followed:

    Plan

    This is where the PDCA Cycle begins. In this first phase, the objectives and goals must be defined. As it is the initial part, it is recommended to pay greater attention and consider actions such as:

    • Establish the objectives and goals of the task to be improved or developed;
    • Describe the task in detail, being clear in the specifications;
    • List the professionals who will be part of the PDCA;
    • Define deadlines, the necessary financial resources, expected cost, labor, among others.

    Do

    After thorough planning, it must be put into practice, to the letter. That is, to follow and respect what was planned. This is where you get your hands dirty, usually in three steps:

    1. Training of those involved in the project;
    2. Execution of the process;
    3. Data collection

    Don’t forget to pay attention to four points:

    • Perform all tasks as planned;
    • Keep stakeholders informed of progress;
    • Follow the schedule; e,
    • Highlight any variations observed.

    Check

    This is the part of the PDCA Cycle where flaws in the project are identified. To do this, you must measure the results achieved and check if the goals have been met. This check can be done in two ways:

    • Parallel to implementation, to ensure that the work is being done well;
    • At the end, for a more comprehensive statistical analysis. The measurement at the end will allow adjustments not made or not previously noticed.

    In this step, the root causes of the problems that have occurred are also identified.

    Act

    In the last phase, corrective actions are applied. Remember that the PDCA Cycle is used for continuous improvement? Exactly for this reason, here you should:

    • Correct the deviations found;
    • Identify preventive actions for root causes, such as implementing risk management;
    • Implement preventive actions and verify the result;
    • Repeat the first three steps (Plan, Do, Act) until all goals are achieved.

    Think of the PDCA Cycle as a ball that is always moving forward with the goal of improving.

    Fusion Platform at the PDCA cycle

    Pedro, from our story, managed to take actions to reverse the negative results. The sales process was improved by detecting gaps between activities. But Peter knows that the work has only just begun.

    Because he no longer wanted to go through the suffocation of not having real-time and centralized information, Pedro decided to implement a risk management platform, processes, documents, indicators, and electronic signature.

    Operating end-to-end, the Fusion Platform offers a suite of solutions to ensure operational excellence.

    By providing process automation, centralization of information, facilitating communication, and having indicators updated in real time, the solution optimizes routines and drives continuous improvement.

    Among the features available, it is possible to map, monitor, manage and analyze processes. Enabling, among other points, identifying bottlenecks, monitoring the performance and execution of activities in real time.

    Specifically for the PDCA Cycle, Neomind developed the Goals and Strategies Management module. In addition, there is the quality accelerator, which enables the effective control of action plans through the control of pending deadlines.

    Regarding document management, all forms and files are centralized, which ensures quick access and collection of information. In Central Analytics, there are personalized reports and analysis on the performance of all associated activities.

    Without a doubt, if Pedro already had the Fusion Platform, he would not have to face problems in his sales process.

    And if you don’t want to be like Peter and want to ensure greater efficiency, productivity, quality, and continuous improvement across your organization, try Fusion Platform.

    Combining Fusion Platform and PDCA is ensuring success and extraordinary results for your organization.

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