Glide lets you turn a simple Google Sheet into a professional mobile app in just a few clicks. This promise appeals to SMEs and project stakeholders seeking speed and agility to digitize an internal process or test an MVP without a dedicated development team.

Yet behind this simplicity lie structural choices and inherent limitations of no-code architecture. This comprehensive guide walks IT and operational decision-makers through each stage of the cycle: from defining the use case to structuring the Google Sheet, from visual customization to testing, up until the point where it becomes strategic to move to a custom solution to meet performance, security and scalability requirements.

Understanding Glide’s Foundations

Glide converts Google Sheets into a database and pairs it with a ready-to-use, mobile-first interface. Hosting, updates and multi-screen compatibility are managed automatically, without deploying to an app store.

Basic Principle and Simplified Architecture

At the core of Glide, each row in a Google Sheet becomes a structured record and each column a property available in the app. This approach shifts the backend into Google Sheets, ensuring rapid setup and almost instant onboarding.

Unlike traditional architecture, there’s no dedicated server, relational database or container to manage. Users focus exclusively on the spreadsheet’s structure while Glide handles the presentation layers, near-real-time synchronization and production of a Progressive Web App (PWA) installable from a browser.

This simplification reduces time-to-market and lowers initial costs. However, reliability and performance remain tied to Google Sheets’ capabilities, especially regarding data volume and advanced business logic.

Key Strengths of the Solution

Prototyping speed is undeniable: a functional interface can appear in under ten minutes after connecting to the Google Sheet. Glide offers a range of visual components (lists, cards, detail views, forms) that automatically adapt to mobile mode.

Role and permission management is built in via visibility conditions, providing granular control over data access. Computed columns enable simple operations (concatenations, sums, conditions) without writing any scripts.

Finally, publishing as a PWA occurs without external approval, avoiding the delays and constraints of app stores. Users share a link, the app opens in the browser or installs on the home screen like a native app.

Illustration in Switzerland

A Swiss logistics SME without a dedicated IT team used Glide to replace a manual booking process with a customer portal. In less than two hours, they structured a Google Sheet into “Clients,” “Services” and “Bookings” tables and set up an interface for appointment scheduling and real-time tracking.

This implementation demonstrated Glide’s ability to digitize a simple business flow quickly. Managers could focus their efforts on optimizing data rather than development, validating the concept with end users before considering a more robust evolution.

The example shows that with under 200 daily records and moderate changes, the no-code approach delivers agility without compromising service reliability.

Getting Started with Glide: Structuring Your Project

The success of a Glide app depends on clearly defining the use case and the quality of the data model in Google Sheets. A coherent structure ensures stability and scalability, regardless of processed volumes.

Defining the Use Case

Before opening Glide, it’s essential to delineate the app’s functional scope. Identify the specific business problem to solve, the target users and the primary workflow to avoid overloading the prototype and creating a confusing interface.

A service booking system, a customer portal or an internal dashboard each require specific data models and screens. Focusing on a single flow initially enables rapid iteration on delivered value.

Decide early whether the app will remain internal or open to external users to guide permission settings and the publication mode (private authenticated or public).

Structuring Your Google Sheet Intelligently

Each table should correspond to a separate tab: main entities (Clients, Products, Projects) and junction tables for complex relationships. A column should contain only one uniform data type to facilitate Glide’s automatic filtering and sorting generation.

Using consistent formats for dates, amounts and identifiers ensures reliable interpretation. Explicit column names simplify view and action creation while easing maintenance.

Anticipating relationships (for example, a “Booking Details” tab linking Clients and Services) reduces the proliferation of computed columns and improves model clarity.

Customizing the Interface and Logic

Once the structure is in place, Glide automatically generates a mobile-first interface. Simply adjust the components: dynamic lists, illustrated cards or forms, based on the business context. Styles (colors, typography) can be set in just a few clicks.

Custom actions (adding rows, sending emails, conditional navigation) address simple flows without code. Computed columns enable dynamic statuses or generate contextual text directly within the app.

This rapid customization enables a rich prototype ready for internal stakeholder testing before any broader deployment.

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Testing, Publishing and Evolving Your PWA

A poorly tested Glide prototype can be as fragile as a hastily coded solution. Rigorous testing ensures a smooth experience and rapid user adoption.

Testing Strategies

Plan scenarios covering normal usage, edge cases and input errors to verify app robustness. Test handling of empty fields, incorrect values or unauthorized access attempts to reveal breakage risks.

Involve end users in validation sessions to highlight navigation friction and unmet expectations. Their feedback guides adjustments to menu structure, button placement and error messages.

Simulating slow connection conditions and verifying HTTP latency handling confirm PWA stability, especially for mobile teams or sites with limited coverage.

PWA Deployment and Sharing Modes

Glide publishes the app as a web link installable on a smartphone’s home screen, bypassing app stores. This mode simplifies both internal and external distribution, ensuring instant updates with each Google Sheet change.

The choice between public or private access is configured via authentication: restrict to a specific domain, limit by email or open with no barrier. Administrators can adjust these settings at any time from the Glide console.

This flexibility adapts to SMEs’ real needs: rapid rollout to a small team or launching customer portals without regulatory store constraints.

Maintenance and Evolutions

Extending the app to new use cases often requires adding tables or columns in the Google Sheet. Glide syncs these additions without manual redeployment, reducing production lead times.

For frequent updates, maintain concise documentation of the structure and internal processes to ease onboarding of new contributors or external vendors.

Finally, monitoring performance (row counts, load times, sync errors) helps anticipate when to transition to a dedicated solution as volumes or complexity exceed no-code capabilities.

Glide’s Limits and Custom Solution Path

Beyond a certain data volume, business logic or security requirement, no-code architectures become restrictive. A custom, modular and scalable solution then guarantees performance, control and deep integration with existing systems.

Technical Limits and Data Volume

Google Sheets isn’t designed for more than a few tens of thousands of rows per tab. Response times degrade, filters throttle and the PWA may freeze under heavy synchronization.

Complex queries, aggregations or multi-step workflows can’t be handled in Glide without constant back-and-forth with the spreadsheet. Real-time calculations or advanced reporting then demand an API and an optimized database.

When the app serves hundreds of simultaneous users, monthly quota limits or plan-based user caps hinder growth and balloon the no-code budget.

Security, Compliance and Integration

Compliance requirements (GDPR, industry standards) sometimes mandate strict data controls, audit trails and encryption-at-rest policies. Glide, via Google Sheets, doesn’t always offer the required level of governance.

Integrating existing business systems (ERP, CRM, single sign-on) requires dedicated connectors or middleware. A custom architecture supports secure APIs, granular encryption and real-time event orchestration.

For mission-critical services, on-premises or private-cloud hosting better addresses sovereignty and certification needs—something a standard no-code PWA cannot provide.

Case Study: Transitioning to a Dedicated Architecture

An event management organization started with Glide to centralize registrations and schedules. With over 5,000 annual participants and integrated billing modules, limitations quickly appeared around PDF generation, advanced segmentation and asynchronous workflows.

They decided to migrate to a custom solution built on microservices, a PostgreSQL database and a React front end. The open-source approach preserved flexibility, avoided vendor lock-in and guaranteed scalable growth at a reasonable cost.

This case shows that Glide accelerates concept validation while custom engineering takes over to industrialize the service and fully integrate it with existing systems.

Glide: A Springboard to a Custom Mobile Solution

Glide offers unparalleled prototyping speed and ease of use to quickly digitize an internal process or launch an MVP. Its Google Sheets configuration, automatically generated mobile interfaces and code-free actions make it a powerful tool for simple use cases.

However, growing needs in data volume, complex business logic, security and integration soon reveal no-code limits. That’s when you call in engineers to design a modular, scalable and secure architecture combining open source and custom services.

Our Edana experts guide organizations through this transition: from auditing your existing Glide setup to implementing a hybrid or bespoke solution focused on ROI, performance and long-term business value. They can assess your situation, define a roadmap and steer the industrialization of your mobile application.

Discuss your challenges with an Edana expert

Many dashboards look like unreadable puzzles: too many numbers, no clear objectives, and no practical guidance when a metric deviates. These tools eventually lose all relevance and become mere statistical showcases.

An effective dashboard, by contrast, should be understood within seconds, trigger a precise action, and accurately reflect your business strategy. For a growing SME, it’s a performance lever and a true decision-support system—a scalable data infrastructure that informs every strategic discussion. Let’s review the principles for creating a KPI dashboard that is genuinely useful and action-oriented.

What Makes a Good KPI?

A good KPI must be SMART and aligned with the overall strategy. It guides your teams toward clear, measurable objectives.

SMART Principle

The SMART model requires that a metric be Specific, Measurable, Achievable, Relevant, and Time-bound. A vague KPI like “increase sales” isn’t enough: you need to specify by how much, in what timeframe, in which geographic area or customer segment.

The Specific dimension prevents any divergent interpretation among your teams. Measurability ensures the metric relies on reliable, quantifiable data.

Finally, the Time-bound criterion sets a motivating deadline for each actor, creating a beneficial sense of urgency.

Strategic Objectives and Responsibilities

Each KPI must be tied to a clear strategic objective, whether it’s accelerating growth, optimizing cash flow, or boosting customer satisfaction. This alignment ensures coherence between your ambitions and your metrics.

It is essential to assign an owner to each KPI. Ownership prevents action from being diluted: everyone knows what to monitor and how to respond in case of deviation.

The owner should also have a clear action plan outlining the steps to take if the metric strays from its target.

Associated Action Plan

A KPI is useless without the “so what?” that accompanies it. If a metric drops, your action plan defines the corrective measures to implement immediately, whether it’s a budget adjustment, a sales campaign, or a process audit.

This plan must be simple, documented, and tested in advance. That way, if you cross a threshold, you can move to execution quickly without wasting time in interpretation meetings.

Example: A Swiss SME in the trading sector set a SMART KPI of “reduce average customer payment period by 20% by the end of Q2.” Automating the follow-up workflows and daily monitoring brought DSO down from 75 to 60 days in three months, with a dedicated finance manager overseeing each step.

Golden Rules for a High-Performing Dashboard

Stick to the essentials to avoid cognitive overload. Ensure technical and organizational alignment for each metric.

5 to 7 KPIs Maximum

Beyond seven metrics, readability wanes: each owner loses sight of the priorities and decision-making stalls. Group your metrics by function (sales, finance, operations, HR) and create multiple targeted dashboards.

A sales dashboard should not include your HR ratios, and a finance tool shouldn’t display customer satisfaction KPIs. This segmentation preserves clarity for each audience.

By limiting the number of KPIs, you focus attention on what truly creates value.

Actionable KPIs

Each metric must answer this question: “What will I do if this KPI drops?” If no clear answer exists or it feels vague, the metric is poorly chosen. A good KPI should lead directly to an operational or strategic action.

If the conversion rate falls, you launch a UX audit or a retargeting campaign; if gross margin shrinks, you immediately examine production or sourcing costs. Without this direct link, the dashboard becomes decorative.

The actionability of a KPI strengthens your organization’s responsiveness and sustains trust in your management tool.

Automation and Governance

A dashboard that doesn’t update automatically loses all credibility. Ideally, data updates should occur at least daily via direct connectors to source systems (ERP, CRM, marketing automation tools…).

Governance defines who can modify the dashboard structure, add or remove metrics. This formal framework prevents drift and ensures the integrity of sensitive data.

Example: At a Swiss IT services company, daily automation of six critical KPIs eliminated manual reporting tasks, saving 12 hours of work per week and reducing data discrepancies between teams by 30%.

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Selecting Essential KPIs

Each KPI must illuminate a specific decision. Choose the metrics that reflect your most pressing business challenges.

Sales KPIs

Revenue remains the flagship metric for tracking business momentum. Monitored daily or monthly, it reveals trends and seasonality.

The conversion rate measures the efficiency of your customer journeys, whether it’s an e-commerce site, a SaaS platform, or lead generation. A low rate immediately directs you to a UX audit or offer optimization.

The Customer Acquisition Cost (CAC) should remain below the Customer Lifetime Value (CLV). Your marketing profitability depends on this ratio. Example: A Swiss e-learning SME cut its CAC by 25% in three months by improving source attribution and fine-tuning its ad budget.

Financial KPIs

Gross margin provides insight into the health of your business model. Without sufficient margin, any growth becomes fragile and risks creating a squeeze between fixed costs and revenue.

Net cash, with a minimum rule of three months of fixed costs, secures operations and covers unforeseen events. Exceeding this reserve immediately alerts the CFO.

DSO (Days Sales Outstanding) directly impacts your working capital needs. High DSO can become critical, especially in B2B sectors with long billing cycles.

Operational and HR KPIs

Delivery or service completion time influences customer satisfaction and your company’s reputation.

Inventory turnover and quality performance metrics are supply chain and quality performance metrics. Managing them optimizes both tied-up capital and product reliability.

On the HR side, turnover and absenteeism require a cautious approach. Display only aggregated data, in compliance with regulations, to protect employees and maintain trust.

Visualizations, Common Pitfalls, and Scalability

Good visualization makes a KPI readable in 5 seconds. Anticipate data evolution to ensure your dashboard’s longevity.

Choosing Visualizations

The line chart remains the best way to track changes over time. Highlighting a single KPI draws immediate attention to the current priority.

Bar charts facilitate comparisons between categories or periods. Gauges show progress toward a goal but should remain understated to avoid a gimmicky effect.

For operational details, a filterable table offers flexibility and granularity without overcrowding the visual space.

Common Pitfalls to Avoid

Too many KPIs scatter attention and create decision paralysis. Without an associated numerical target, you can’t tell if a result is satisfactory or not.

Non-automated data leads to lags, undermines trust, and turns your dashboard into a decorative toy. Restrict access to sensitive dashboards with fine-grained role management.

Complex visualizations overloaded with effects and colors make for laborious reading and discourage daily use.

Scalable Architecture

A good dashboard relies from the start on a solid data structure, with historical tracking and source quality. Open-source solutions like Metabase or Superset offer modularity that prevents vendor lock-in.

Connect your BI tool directly to your databases or through a data warehouse for automated, scalable reporting. Avoid Excel hacks—they become unmanageable and unreliable quickly.

Plan for growing volumes, diversified metrics, and increasing query loads to maintain performance and availability.

Turn Your Dashboard into a Strategic Lever

A well-designed dashboard simplifies decision-making, aligns teams, and safeguards your SME’s performance. By limiting each dashboard to 5–7 actionable, automated, and protected KPIs, you create a shared, reliable source of truth.

Favor clarity over complexity, anticipate data evolution, and secure access based on metric sensitivity. The goal isn’t perfection but operational efficiency and responsiveness.

Our experts are available to help you implement a tailor-made, modular, and scalable dashboard aligned with your business objectives.

Discuss your challenges with an Edana expert

The adoption of artificial intelligence is accelerating among Swiss companies, driven by the promise of efficiency and innovation. Yet without a clear framework, AI becomes a black box with multiple dependencies: model providers, cloud platforms, and restrictive licenses.

Each external API can become a strategic lock, weighing on data sovereignty and security. IT and executive leadership must understand that AI is not merely a tool but an asset whose governance determines technological autonomy. This article outlines the legal, technical, and organizational levers to control intellectual property rights, reduce vendor dependency, and preserve your resilience against regulatory and geopolitical changes.

Understanding and Securing the Intellectual Property of AI Models

Model licenses dictate your room for maneuver. Mastering modification rights and reversibility is crucial.

Licensing Types and Associated Risks

Language models may be distributed under permissive licenses (Apache, MIT), copyleft licenses such as GPL, or strict commercial agreements. Open-source licenses offer flexibility for fine-tuning but sometimes impose obligations to share modified code. Proprietary licenses often guarantee support but limit customization and derivative distribution.

It is essential to audit each license to identify unilateral withdrawal clauses, redistribution restrictions, and end-of-support timelines. Auditing each license helps prevent blockages due to unexpected contractual changes.

A model initially provided for free can become problematic if the publisher decides to charge for API access or restrict key features. Such changes can directly affect your budgets and deployment plans.

Modification Rights and Reversibility

Modifying an open-source model can generally be done freely, but licensing terms may require publishing your enhancements. Conversely, commercial models typically prohibit any alteration. This difference impacts your ability to train a locally adapted version for your specific business needs.

Reversibility means being able to extract your data, model weights, and training configurations without constraint. If an API service shuts down or its terms evolve, access to your in-house developments must remain guaranteed.

A reversibility plan involves retaining snapshots of your fine-tuned models and documenting training processes. These precautions prevent having to start from scratch if you switch providers.

Preserving Ownership of Data and Derivatives

Your prompts, training datasets, and enriched models represent strategic capital. It is vital to secure clear rights for their future reuse, whether internally or with a third-party provider. Ensure your contract explicitly provides for the return of all your AI assets.

A mid-sized Swiss company specializing in document analysis integrated a commercial large language model to classify its archives. Confronted with a unilateral price revision, it requested a full export of its embeddings and prompts. Thanks to a pre-negotiated clause, it migrated losslessly to an internally hosted open-source model, demonstrating the importance of anticipating derivative ownership.

Without this clause, the company would have had to retrain weeks’ worth of work, delaying its project and increasing costs.

Assessing and Mitigating Vendor Dependency

The ability to migrate to another service is a key indicator of autonomy. Tightly coupled architectures generate hidden costs and risks.

Portability and Multi-LLM

To limit vendor lock-in, it is recommended to design an abstraction layer between your applications and language model providers. This layer orchestrates API calls and normalizes results, easing the substitution of one model for another. Abstraction layer

Portability should be tested from the prototyping phase. Simulate failovers to multiple providers to identify necessary interface adjustments and quota management requirements.

A Swiss logistics SME implemented an orchestration component enabling seamless switching among three LLM APIs. When one provider’s rates spiked dramatically, it redirected 60% of its traffic to an alternative model without service interruption, illustrating the robustness of a multi-LLM approach.

Analysis of Restrictive Contractual Clauses

External API contracts often include liability caps and the right to modify service terms at any time. Verify notification periods for suspension or pricing changes. External APIs lie at the heart of your technological sovereignty.

A deceptive clause may allow the provider to block your access without recourse in case of dispute. Service level agreements (SLAs) and associated penalties must be explicit and commensurate with the stakes.

A prior audit enables you to negotiate availability guarantees, advance-notice windows, and the right to distribute load across multiple data centers or regions.

Economic Model and Hidden Costs

Beyond list prices, factor into your forecasts the costs of log storage, data egress fees, and premium support tickets. These ancillary expenses can account for up to 30% of your AI budget.

Also assess pay-as-you-go pricing versus monthly subscriptions. Heavy usage may make a flat-rate subscription more cost-effective, while sporadic use favors per-request billing. CapEx vs. OpEx

These financial analyses must be continuously reassessed to ensure the competitiveness of your AI strategy.

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Modular Architecture and Protection of Sensitive Data

Component granularity ensures flexibility and protection. Underestimating data governance exposes you to legal and reputational risks.

Compliance and Risk Assessment

Processing personal data through external APIs requires a Data Protection Impact Assessment (DPIA). This analysis maps data flows, involved third parties, and security measures.

It is also crucial to chart cross-border transfers. A non-local provider may fall under extra-European laws, triggering notification obligations and reinforced safeguards.

A Swiss financial services firm conducted a DPIA before sending client statements to a cloud LLM. It implemented homomorphic encryption and white-box processing, demonstrating that anticipating these constraints can be a competitive advantage.

Designing a Modular Architecture

A modular architecture decouples AI functions (pre-processing, generation, post-processing) and enables module replacement without overhauling the entire system. Each component exposes a standardized internal API.

Using containerized micro-services provides secure isolation and independent scaling. You can allocate more resources to text generation without overprovisioning other components.

Modularity also facilitates integrating business rules and compliance filters, ensuring that sensitive data never leaves your controlled perimeter.

Open-Source Alternatives and On-Premise Solutions

Not every use case requires the most powerful models. Lightweight open-source distributions can be hosted on-premise, offering full control over the processing pipeline.

These solutions reduce external API dependency and limit recurring costs. They are particularly suited for non-critical internal processes or rapid proof-of-concepts.

By adopting a hybrid approach, some Swiss companies combine an on-premise LLM for sensitive data with a cloud service for less critical tasks, striking a balance between performance, cost, and sovereignty.

Anticipating Legal, Regulatory, and Geopolitical Risks

Legislative changes and international tensions can suddenly disrupt service access. Integrating these scenarios into your strategy ensures continuity.

Monitoring Regulatory Developments

AI and data protection laws are evolving rapidly in Europe and worldwide. A monitoring system must track draft legislation, ISO standards, and regulatory guidance.

Transparency and explainability obligations for algorithms may become binding. Plan for decision-traceability mechanisms and audit logs to comply with future information requests.

An in-house AI compliance program, led by IT and legal departments, is a strategic asset for anticipating these requirements without operational roadblocks.

Strategic Contractual Clauses

Include reversibility clauses in your contracts to guarantee data export, service continuity assurances with penalties, and rights to replicate server environments.

Also require advance notifications for price or technical term changes, as well as co-development rights to secure access to model updates.

These clauses turn the contract into a true sovereignty lever, limiting the provider’s unilateral discretion.

Continuity Planning and Alternative Scenarios

Develop business continuity plans (BCPs) addressing scenarios such as foreign API access loss, regulatory changes, and cyberattacks targeting AI services. Continuity plans ensure your framework’s robustness.

Regularly test these scenarios by simulating the loss of a primary provider and failover to an alternative. Document steps, dependencies, and responsible stakeholders for each action.

This discipline guarantees operational resilience: even in the event of a sudden outage, your business processes continue with minimal impact.

Transforming AI Dependency into Strategic Autonomy

AI dependency can become an asset when supported by rigorous governance, modular architecture, and robust contracts. By securing your intellectual property rights, diversifying vendors, and proactively managing compliance risks, you build a resilient and scalable ecosystem.

Our experts guide IT, legal, and executive teams in crafting tailored strategies aligned with your business objectives and regulatory environment. Together, we define the technological, contractual, and organizational choices that preserve your digital sovereignty and maximize your AI ROI.

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Deadlines have already been extended once, and milestones keep slipping. Specification documents remain unsettled, meetings grow tense, and priorities seem to shift with every sprint. Faced with this reality, one critical question arises: what truly caused this delay?

Beyond bugs or unforeseen technical issues, it is often the clarity of requirements, decision-making, and internal coordination that lie at the heart of a digital project’s drift. Analyzing these factors not only uncovers the root cause but also provides a roadmap to regain control.

Insufficient Initial Scoping and Ignored Early Warning Signs

Delays often take root at kickoff when requirements aren’t clearly defined. Warning signs go unnoticed and turn into structural deviations.

Approving a schedule before fully understanding the scope lays a shaky foundation. Ambiguities multiply, and every unanswered question comes back to haunt you—often with high costs. It’s typically a few skipped key meetings or unchallenged assumptions that introduce this structural uncertainty. Estimation and Budget Management Guide

In the first weeks, it may feel like you’re off to a fast, efficient start. But beneath the surface, friction points form: latent needs emerge, and the backlog balloons. These micro-shifts eventually derail the schedule, rendering the original plan obsolete. Explore our agile best practices for software development firms in Switzerland.

Lack of Scope Definition

Without a firm scope, every stakeholder interprets requirements in their own way. Developers build a solution they believe matches the business vision, while business teams envisage a different target. This divergence creates endless back-and-forth.

Weekly reports become inventories of open issues rather than progress trackers. Unprioritized tickets pile up, and the backlog swells without a clear objective in sight.

Example: A financial services company launched a CRM module without documenting critical use cases. Three months later, key functions like contract management had never been addressed, revealing that essential workflows had not been mapped from the start.

Deferred Ambiguities

By habit, some questions are postponed until “Phase 2.” But that phase often never comes or gets diluted by new contexts. As a result, these ambiguities block testing and acceptance, forcing last-minute fixes.

Breaking the work into successive batches without thoroughly validating the initial requirements turns each batch into a mini project. Milestones add up and deliverables lag, while open tickets are sometimes simply abandoned.

This approach gives a false sense of progress, masking structural drift. “Provisional” deliverables become de facto final versions, at the risk of costly rework.

Ignored Weak Signals and Micro-Shifts

A single missed meeting, an unassigned ticket, or an unbudgeted role are all early warning signs. If these small delays aren’t addressed immediately, they create a soft spot in the schedule.

Team fatigue, unresolved minor incidents, or unanswered questions multiply, triggering a domino effect. Three weeks of cumulative slippage can translate into a month’s delay on key milestones.

This gradual drift is more dangerous than a major incident because it often flies under sponsors’ radar. Denial or the belief that simply “pushing harder” will fix things only worsens the delay.

A Real Complexity Often Underestimated

The initial perception of a “simple” solution rarely withstands integration with existing systems. Each dependency and edge case reveals unexpected effort levels.

A requirement deemed basic can clash with legacy ERPs, CRMs, or databases whose interfaces are undocumented or nonstandard. Discovery phases drag on, and integration testing becomes a minefield. guide on ERP deployment.

The schedule then rests on optimistic assumptions: “API connectivity will take two days” or “Data import is just a mapping task.” Once specific use cases surface, every new exception upends the original trajectory.

Underestimated Integrations

Initially, integration seems like smooth data exchange. In reality, each platform has its own formats, versions, and constraints. You must build adapters and handle schema mismatches.

Pre-production tests often fail due to incomplete test data or historical anomalies, making certification feel endless.

Example: In an ERP project for a distributor, automatically exporting inventory to the new system was underestimated. Business rules from the old ERP (adjustments, false-positive counts) were undocumented, forcing the team to rebuild the logic and causing a two-month delay.

Edge Cases and Rare Scenarios

Extraordinary cases treated as “unlikely” always surface during acceptance. Duplicate submissions, unfilled fields, or exceptional volumes reveal hidden limitations.

Each unexpected scenario generates a critical ticket and one or more development cycles. End-of-cycle fixes disrupt existing code stability.

This reactive defect management drains team availability for new development and extends the overall timeline.

External Dependencies and Hard Deadlines

A digital project never exists in a vacuum. Third-party vendors, license providers, or cloud services set their own schedules. A version change or major update out of your control can bring progress to a halt.

No buffer on these external milestones means any delay or API modification throws the entire plan off track.

Managing these dependencies requires heightened vigilance and regular checkpoints to prevent an external incident from becoming a bottleneck.

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Deferred Decisions Slow the Pace

Every unresolved decision stalls the team and creates queues. The project moves at the sponsors’ rhythm, not the developers’.

When steering committees are unavailable or strategic priorities shift, each batch remains pending. Scope evolves without formal sign-off, producing unstable versions and directional changes.

Fluid decision-making is as critical as clean code: without clear, responsive governance, developments pile up awaiting the essential “go/no-go.”

Late Arbitrations and Approvals

Unapproved mockups, shifting specifications, and technology choices lacking formal agreement signal lax governance. The team ends up implementing multiple options in parallel, waiting for the green light.

Each scope change demands a new schedule and regression tests, exhausting resources and extending delivery times. Discover our best practices for regression testing.

Example: An industrial manufacturing company delayed the data integration format decision. Three months of development were redone when the committee finally approved a different secure protocol than the initial proof of concept.

Shifting Priorities During the Project

Over the weeks, the roadmap can be redrawn under a different sponsor’s influence. Each new direction pushes back previous milestones and overloads the backlog with lower-priority tasks.

This “stop & go” effect suspends or cancels ongoing development as new topics emerge, disrupting team momentum.

Expected business value becomes diluted because the project never truly converges on a stable target.

Unavailable Sponsors and Sporadic Pushes

A sponsor engaged at the start may disappear or reduce availability, leaving the team unguided. Choices are then postponed, awaiting the hypothetical return of the decision-maker.

Conversely, the sudden intervention of a new strategic actor can spark a frenzy, abruptly altering the project’s course.

This organizational instability results in activity spikes followed by long waits—a rhythm that’s unsustainable over time.

Broken Communication and Over-Optimistic Planning

Clear communication is the project’s fuel, and lack of buffer is its breaking point. As soon as one falters, delays set in.

Poorly described tickets, meetings without clear agendas, and unreachable key stakeholders lead to persistent misunderstandings. Add a schedule without any slack, and every minor incident shifts the entire chain. Learn why rushing digital transformation often ends in failure.

Implicit Expectations and Meeting Silences

When participants leave assumptions unspoken, everyone fills in the blanks differently, creating gaps in understanding. “Implicit” decisions aren’t recorded and vanish with the next context change.

In meetings, the lack of clear minutes causes participants to lose track, leading to redundancies and backtracking during implementation.

Ballooning Backlog and No Buffer

The backlog becomes a catch-all when there’s no time to prioritize or break down tasks. Tickets multiply, accumulate, and remain unestimated, obscuring real urgencies.

An over-optimistic schedule with zero buffer turns each fix into structural slippage. Even minor patches push back successive releases and extend the drift.

Planning, meant to be a living tool, becomes a static document—obsolete from the moment it’s published.

Re-work and Cascading Delays

Poor communication and tight planning fuel frequent re-work. Each rewrite consumes resources and desynchronizes teams.

Instead of focusing on speeding up deliveries, time is spent correcting and harmonizing code, feeding a cycle of cascading delays.

Team morale suffers, stakeholder confidence erodes, and the project’s original trajectory becomes unreadable.

Turn Your Delay into a Strategic Advantage

Delays aren’t failures but signals: they reveal a lack of shared vision, unstable governance, shifting priorities, and underestimated risks. By coldly analyzing these symptoms, you can refocus scoping, clarify decisions, strengthen communication, and introduce the necessary buffers.

No matter your organization’s size or the complexity of your ERP, CRM, or SaaS project, our project strategists and dedicated managers are here to support you. We tailor our recommendations to your context, prioritizing open source, modularity, security, and scalability to turn these delays into value accelerators.

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When faced with technical uncertainties, some organizations choose purely reactive maintenance, intervening only after a failure is detected. While this approach minimizes planning and upfront costs, it often proves unsuitable for critical assets whose failure can paralyze business operations.

The key question is not to choose systematically between reactive and preventive, but to determine for each component the acceptable risk level and recovery objectives. In this article, we present a structured decision framework—integrating RTO/RPO, business criticality, and observability mechanisms—to guide IT governance choices.

Understanding Reactive IT Maintenance

Reactive maintenance occurs only after a failure has occurred, with no predefined schedule for operations. It differs from preventive and predictive approaches by the absence of regular checks and continuous monitoring.

Definition and Characteristics of Reactive Maintenance

Reactive maintenance, sometimes called corrective maintenance, is triggered as soon as an incident is reported by users or support systems. It relies on no verification schedule or leading indicators, reducing initial setup. In practice, the IT team switches to emergency mode upon ticket receipt, must diagnose the failure, and intervene in real time to restore service, often using a Computerized Maintenance Management System (CMMS) for tracking and coordination.

This model may seem attractive for non-critical or easily replaceable resources, as it involves no planned downtime or significant investment in CMMS software. However, the lack of proactive alerts generates a risk of unexpected—and sometimes prolonged—downtime, with an impact that is hard to gauge in advance. Business operations may then suffer sudden interruptions, disrupting the value chain.

At the strategic level, reactive maintenance aligns with a run-to-failure logic: an asset is used until it fails, then repaired or replaced. This method can be documented and validated through clear governance. The success of this strategy depends on precisely defining the permissible scopes and replacement resources.

Types of Reactive Interventions

In the field, three forms of reactive maintenance coexist. First, emergency interventions are triggered for critical incidents that threaten operational continuity or data security. The IT team drops all other tasks to restore service.

Next are “breakdown” treatments, where the failure is unanticipated and requires a standard ticket. Resolution may take time, involve external experts, and incur higher hourly rates due to time pressure.

Finally, run-to-failure applies to assets whose failure is planned and considered part of normal operation. A prearranged replacement or workaround is in place to limit downtime, provided criticality criteria remain low.

Positioning Within the Maintenance Ecosystem

Reactive maintenance occupies a specific place in a holistic strategy where preventive maintenance schedules patches, tests, and checks, while predictive maintenance uses signals (metrics, logs, trends) to anticipate issues. Combining these approaches lets you adjust monitoring levels according to service criticality.

In an asset lifecycle, the choice of intervention mode depends on total cost of ownership, business criticality, and risk tolerance. Secondary equipment or test environments can be managed in run-to-failure, whereas critical APIs, production databases, and payment services demand a more rigorous strategy.

Example: A logistics provider decided to treat its staging server in run-to-failure mode, replacing it in a “hot swap” slot as soon as a failure was detected. This approach reduced operational complexity in that environment by 75% while maintaining a recovery time under 12 hours, showing that a leaner plan can remain controlled when backed by clear procedures.

Limitations and Hidden Costs of Reactive Maintenance

Unpredictable interruptions create major business impacts and costs that are difficult to budget. Corrective maintenance often leads to cost spikes without visibility into the annual total.

Unpredictable Downtime and Business Impacts

An unplanned outage exposes a company to immediate productivity loss and a degraded user experience. Operational teams cannot perform their tasks, billing or production processes stall, and the supply chain can be affected.

In sensitive sectors (finance, healthcare, e-commerce), even a minor incident can lead to contractual penalties or regulatory sanctions. Without internal SLAs on RTO/RPO, impact forecasting is difficult, weakening the organization’s stance with clients and partners.

The domino effect can ultimately cost several times more than an annual preventive maintenance budget that once seemed minimal. This cost variability complicates financial management and may jeopardize the IT roadmap.

Operational Overruns and Penalty Risks

During a serious incident, engaging experts on short notice incurs premium rates and expedited response fees. Billable hours can be 30% to 50% higher than standard services, inflating the final invoice.

Without spare parts inventory or support contracts with SLAs, replenishment lead times can be lengthy, extending downtime. Every extra hour weighs on operational results, often without a clear forecast of daily labor costs.

Example: An SME experienced a failure of its internal API, handled reactively. Bringing in external specialists required an urgent site visit, generating an unplanned CHF 40,000 cost for less than 24 hours of downtime. This expense highlighted the importance of agile support mechanisms rather than relying solely on ticket-based interventions.

Security, Technical Debt, and Silent Degradation

In reactive mode, security patches are often applied only after a vulnerability is exploited. This approach increases technical debt and exposes the system to undetected “gray” incidents in regular operations.

Silent degradation appears as a gradual performance decline, increased latency, or resource overconsumption. Without proactive monitoring, these drifts go unnoticed until they trigger a major incident.

Energy costs can also rise, since a stressed component runs less efficiently. At the scale of a data center or cloud cluster, these inefficiencies impact both the operating budget and carbon footprint.

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Strategic Framework: Applying Run-to-Failure Wisely

Choosing run-to-failure is a governance decision that must be based on a rigorous assessment of criticality and recovery objectives. It requires clearly defined RTO/RPO and support resources aligned with the tolerated risk level.

Assessing Criticality and Business Impact

The first step is to map services and evaluate their contribution to revenue, production, or customer experience. This mapping distinguishes critical processes from secondary services.

Essential components (authentication, payment, ERP deployment, billing data flows) are assigned a high criticality level, requiring preventive or predictive coverage. Low-impact components may be run-to-failure candidates, provided there is a rapid replacement plan.

A scoring model based on financial impact and usage frequency gives a factual basis for decision-making. This score should be validated by an IT governance committee to secure stakeholder buy-in.

Defining RTO/RPO and Acceptable Risk Levels

Recovery Time Objectives (RTO) and Recovery Point Objectives (RPO) determine the maintenance strategy. An RTO of a few hours or an RPO near zero demands strong preventive mechanisms and often automated redundancy.

Conversely, an RTO of 24 hours and an RPO of 12 hours can be managed reactively, provided there are validated restore procedures and backups. The choice hinges on a cost-benefit analysis: strict RTO/RPO increase monitoring and testing expenses.

This definition must be approved by executive management, the CIO, and business leaders to reach consensus on acceptable risk levels and governance.

Criteria for Run-to-Failure Services

Several criteria help identify run-to-failure candidates: low business impact services, non-sensitive or regenerable data, and easily replaceable assets with simple workarounds.

Run-to-failure still requires a documented fallback plan: rollback procedures, automation scripts for rapid redeployment, and clearly assigned responsibilities in case of failure. This plan ensures the reactive strategy remains controlled.

Example: A training institution uses a non-critical in-house reporting tool. The team implemented a documented run-to-failure setup, with a backup environment activatable within 4 hours. This arrangement cut supervision costs while meeting an acceptable RTO for educational activities.

Progressing to Preventive and Predictive Strategies

Gradually integrating preventive and predictive maintenance mechanisms reduces risks without blowing the budget. This relies on the minimal implementation of observability tools, regular testing, and post-mortem procedures.

Implementing Observability and Alerting

Observability combines collecting metrics, structured logs, and distributed traces to provide a holistic view of service health. It feeds dashboards and alarms configured on critical thresholds.

Appropriate monitoring detects emerging anomalies (errors, latency, consumption spikes) before they trigger incidents. Alerts linked to runbooks guide teams through initial diagnostics and, if needed, escalation to emergency procedures.

Implementation can start with basic indicators (CPU, memory, error codes) and evolve toward incident-pattern and trend-based alerts.

Developing Preventive Maintenance Plans

Preventive maintenance relies on a schedule of patching, security audits, restore tests, and inventory reviews. It reduces technical debt and limits the frequency of major incidents.

A capacity planning process anticipates load growth and adjusts resources before saturation. Regular failover and recovery tests validate procedures and backup integrity.

This recurring investment pays off through fewer emergency interventions and stabilization of maintenance costs.

Fostering a Culture of Continuous Improvement and Post-Mortems

Every incident, even minor, undergoes a documented post-mortem to identify root causes and define corrective actions. This process turns every failure into a learning opportunity.

Lessons learned feed a backlog of prioritized enhancements, ranging from code refactoring to adding a specific threshold alert. The goal is to move from a “putting out fires” mindset to continuous optimization.

Cross-functional collaboration is crucial: the IT department, business project managers, and external providers participate in reviews, ensuring shared vision and collective commitment to risk reduction.

Steer IT Maintenance Aligned with Your Strategic Objectives

The choice between reactive, preventive, or predictive maintenance must fit within a clear governance framework, defining service criticality, RTO/RPO objectives, and required monitoring levels. A mixed strategy optimizes total cost of ownership while minimizing interruption risks.

To transition from reactive to a more controlled model, it is essential to adopt observability incrementally, establish runbooks, and systematize post-mortems. This pragmatic approach ensures a balance between foresight and flexibility.

Our experts are available to help you assess your assets, set priorities, and implement mechanisms tailored to your context. Benefit from customized support to align your IT maintenance with your performance and resilience goals.

Discuss your challenges with an Edana expert

In digital transformation efforts, pushing ahead with an IT project despite repeated red flags often reflects an emotional rather than rational choice. Conversely, knowing when to stop it at the right time demonstrates solid governance, much like a Formula 1 driver lifting off the throttle before mechanical breakdown. Such rigorous decision-making safeguards resources, limits sunk costs, and preserves capacity to invest in higher-value initiatives.

In this article, we explore four critical warning signs that justify halting an IT project, illustrated with examples in a context where reliability and risk control are cardinal requirements.

Identifying the Technical Deadlock in an IT Project

When major obstacles keep mounting with no clear solution in sight, risk accumulates without any prospect of return on investment. Spotting this deadlock early enhances your ability to redirect efforts toward more viable projects.

Accumulation of Blocking Bugs

An IT project can quickly reach a deadlock when each iteration delivers more critical malfunctions. Teams then spend more time fixing errors than developing new features. This accumulation creates a technical debt that weighs on productivity and erodes stakeholder confidence.

Over the weeks, the backlog fills up with high-priority tickets, and releases follow one another without reducing the number of bugs. End users eventually lose confidence in the project’s ability to meet their needs. The cost of corrective maintenance often exceeds that of the initial development.

Halting a project at this stage allows you to freeze technical debt and reallocate resources to either revamp or build a more robust architecture, thereby minimizing the impact on the overall IT project portfolio.

Lack of a Clear Resolution Path

Beyond bugs, certain structural issues offer no clear solution: outdated technology choices, unstable or incompatible frameworks, lack of precise documentation. Each workaround attempt spawns a new, complex subproject.

In such conditions, continuing simply defers the risk, multiplying sunk costs. Proceeding without a valid refactoring model or technical migration roadmap dilutes the project’s value and jeopardizes ongoing operations.

Stopping or resizing the project at this point offers a salutary choice: abandoning unsuitable technologies and starting anew on a healthier foundation with a valid technical migration roadmap, avoiding further entanglement in unstable terrain.

Concrete Example of a Technical Deadlock

Example: A financial services company had initiated development of an internal platform on an outdated monolithic base. Each week, teams encountered several blockages related to an unstable custom layer, making integration of essential APIs impossible.

Service interruptions piled up, causing critical delays in closing the monthly accounts. No resource could produce a viable short-term refactoring plan, and the adaptation budget had already been blown.

This case demonstrates that a project without a clear technical resolution path generates a major operational risk. Halting this initiative made it possible to freeze the debt, open a recalibration phase, and immediately launch a new effort on a more scalable microservices architecture.

Managing an IT Project’s Organizational Constraints

A project cannot progress without the necessary collective skills and commitment. Ignoring resource or governance tensions is to accept a slow but certain drift.

Shortage of Key Skills

In major IT projects, certain expertise is indispensable: cloud architect, security engineer, lead developer. When one or more of these roles remain unfilled for too long, delivery pace mechanically slows and dependencies get blocked. For example, an IT solutions architect role often proves critical.

Adjacent teams wait for these key resources to validate sensitive components. This bottleneck creates additional delays and overloads the present actors, reducing quality and motivation.

Pausing the project at this stage allows redeployment of scarce profiles to other ongoing initiatives, or restructuring the project portfolio to incorporate targeted new hires or partnerships.

Gaps in Cross-functional Coordination

A digital project often involves several departments: IT, business units, marketing, security, and compliance. If cross-functional governance fails to make swift decisions, approvals stall, milestones slip, and workshops become unproductive.

This lack of synchronization creates conflicting pull effects: one team advances on a solution that no longer meets business requirements, another produces deliverables that IT rejects for non-compliance. The project ossifies in inefficient back-and-forth. Organizations should ensure proper compliance.

Choosing to halt the effort at this level allows a governance review, clear role redefinition, and establishment of an agile, collaborative steering model before any resumption.

Example of Organizational Blockage

Example: An industrial group had launched a custom ERP, mobilizing both the IT team and external consultants. Six months later, the business lead was transferred, and their successor lacked commitment to the project. This situation highlighted shortcomings in ERP deployment.

The steering committees could no longer decide on functional priorities, and validation workshops had dwindled to review meetings with no concrete actions. The ramp-up stalled.

This case demonstrates that without clear cross-functional leadership, a project grinds to a halt. Pausing it allowed reworking the organization, appointing a new sponsor, and resuming the project on a stronger collaborative footing.

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Maintaining Sponsor Engagement in an IT Project

An IT project without an active sponsor is like a ship without a captain: it drifts aimlessly. Preserving executive engagement is a prerequisite for any IT initiative.

Gradual Undermining of Governance Authority

When the initial sponsor reduces their involvement, withdraws from committees, or delegates excessively, the project loses legitimacy. Decisions are delayed—sometimes too late—and budgetary choices are postponed.

Teams perceive the disengagement and become demotivated, slowing down and losing creativity. The project’s strategic priorities blur, leaving room for internal actors to push partial interests.

Halting the project on this warning allows for governance reevaluation, placement of a sponsor capable of championing the vision and ensuring oversight, supported by clear project milestones.

Risk of Silent Drift

Without a sponsor on board, issues accumulate behind the scenes: budget overruns, resource shortages, questionable technical decisions. These drifts remain invisible as long as no one has the authority to demand accountability.

When the fiasco erupts, it is often too late to recover the situation without costly external reinforcement. The alignment of conflicting interests creates paralyzing inertia. Early detection can avoid budget overruns.

Interrupting the project before this serious drift limits losses and sends a strong message: every IT initiative must be backed by a clearly identified, continuously involved sponsor.

Example of Absence of a Sponsor

Example: A non-profit organization had undertaken a revamp of its member management platform. The chairman of the board, the initial sponsor, left the organization mid-project.

Lacking a successor, key change approvals were postponed multiple times, resulting in five delivery delays. Internal user frustration peaked during the first pilot, which was completely sidelined from the new solution.

This case illustrates that an absent sponsor dooms a project. The pause served to reestablish an appropriate steering committee, with a new operational sponsor, before any resumption.

Reevaluating an IT Project’s Initial Objectives

Changing contexts or priorities can render initial objectives obsolete. Continuing without adaptation is like navigating without a chart.

Shift in Corporate Strategy

Strategic orientations evolve: mergers, new markets, regulatory constraints, or leadership changes directly affect the relevance of ongoing projects. Objectives set a year ago may no longer align with current challenges.

Continuing the project without realigning deliverables to business priorities increases the risk of delivering a solution disconnected from real needs. Time and resources are wasted on now-secondary features.

Halting the project then allows for roadmap recalibration, KPI updates, and adoption of an action plan synchronized with present strategy.

Change in Regulatory or Market Scope

New regulations can impose stricter security or traceability requirements, profoundly altering a project’s costing and complexity. A contracting market or one opening to new entrants reassesses the expected value proposition.

In the absence of a fresh impact analysis, the project risks becoming financially or technically unrealistic. It may also lose its competitive edge if needs shift toward a more agile or modular platform.

Pausing the effort to conduct a new contextual study avoids obsolete developments and refocuses investments on truly priority modules.

Example of Obsolete Objectives

Example: An SME in logistics had launched a fleet management system with a local deployment goal. Midway through, the company acquired a German partner with multilingual management and different compliance requirements.

The initial solution neither planned for localization nor adaptation to European standards. Continuing would have meant rewriting the entire business layer, doubling the budget and timeline.

This case demonstrates that a change in context can make a project obsolete. Halting it enabled a full scope redefinition, saving time and investment and resulting in a more agile, adapted MVP.

Turning Project Termination into a Strategic Steering Lever

Stopping an IT project is not an admission of failure but an act of responsibility that protects the overall roadmap. The four signals – technical deadlock, organizational limits, sponsor loss, and objective obsolescence – are opportunities to recalibrate or redirect efforts.

In a context where risk management is imperative, this stance ensures investment longevity and stakeholder confidence. Our experts support organizations during these crucial moments, whether diagnosing a stalled project or redefining governance to optimize the IT portfolio.

Discuss your challenges with an Edana expert

While launching your ERP in production marks a major milestone, the real challenge lies in daily adoption by teams and ongoing value creation. Beyond the technical infrastructure, post–go-live success depends on a continuous‐improvement program that includes targeted training, on‐the‐ground support, feedback collection, and rapid adjustments.

Effective adoption stems from role‐tailored digital onboarding journeys, detailed usage monitoring, and agile governance of updates. Finally, to avoid a rigid system, the ERP must fit into an open, modular, and scalable ecosystem via APIs and customized workflows.

Embed Adoption through Training and Digital Onboarding

A progressive skills‐building approach ensures user autonomy and confidence from day one. Digital learning paths tailored to each role facilitate adoption and minimize resistance.

Progressive Training Path

To reinforce the fundamentals, a phased training plan ensures smooth transitions. It starts with hands-on workshops on key functions, then extends to advanced modules based on responsibilities and business use cases, leveraging change management principles. Each session is built around real company scenarios, with access to a comprehensive online Learning Management System (LMS). This phased approach maintains motivation and prevents cognitive overload while aligning skills with updated processes.

For example, a Swiss industrial SME first trained its production managers on scheduling screens, then, two weeks later, its quality teams on KPI tracking. This sequence halved data‐entry errors and accelerated time-to-competence by 30%.

Blended training combines e-learning, video tutorials, and in-person workshops. This hybrid format addresses diverse learning preferences and ensures rapid skills development.

Finally, post-training tests measure knowledge retention and identify further support needs, ensuring each user masters their functional area before progressing.

Role-Based Digital Onboarding

Creating customized journeys for each profile—purchasing, finance, logistics, sales—helps contextualize usage. Onboarding modules combine interactive tutorials, step-by-step guides, and in-app help bubbles. At each login, users receive contextual assistance to complete specific tasks, reducing reliance on support and helping to secure the adoption of a new digital tool.

A Swiss financial services firm deployed role-based digital onboarding: client relationship managers received workflows broken into micro-tasks, while the IT department monitored progress via a dashboard. The result was 85% adoption of contract-management features within the first month.

Thanks to open-source tools, these help modules are easily customizable and evolve with ERP updates. Project teams adjust content based on field feedback without relying on an external vendor.

Digital onboarding also integrates with existing collaboration tools (Microsoft Teams, Slack) to trigger automated notifications and reminders aligned with each user’s learning pace.

Empowerment through Super-Users

Identifying and training local super-users is essential. These ambassadors, close to daily operations, serve as references, accelerating peer learning and sharing best practices. They organize experience-sharing sessions and relay improvement needs. Their involvement establishes a local support network, reducing pressure on the IT department and speeding up issue resolution.

Super-users gain privileged access to the roadmap of upcoming updates, making them project partners. They test prototypes, validate UX tweaks, and prepare internal change cycles.

In recognition, an internal rewards system (badges, newsletter mentions) highlights their contribution, boosting engagement and the quality of daily user support.

ERP Support and Structured Feedback

A targeted support setup minimizes friction and keeps operations running smoothly. An organized collection of user feedback feeds a continuous improvement plan focused on business value.

On-the-Ground Support and Priority Tickets

Implementing an internal helpdesk with differentiated SLAs based on incident criticality ensures rapid response. Blocking tickets (invoicing, production halts) are addressed within one hour, while enhancement requests follow a dedicated cycle. A centralized back office logs requests and assigns them to super-users, the IT department, or an internal ERP optimization team.

Evolving, self-service documentation addresses frequent questions and reduces ticket volume. Dynamic FAQ solutions can link articles directly to ERP screens, guiding users to the right answer.

Finally, weekly reporting analyzes ticket trends to adjust development priorities, anticipate training needs, and stabilize the ecosystem.

Structured Feedback and Feedback Loops

Deploy quick surveys after each key phase (go-live, training, major update) to capture on-the-ground impressions. These short polls, integrated into the ERP or sent by email, amplify user voices and guide corrective plans. Each response is categorized by business impact and technical feasibility, then incorporated into the project’s agile roadmap.

Co-creation workshops bring together the IT department, business teams, and super-users to enrich development projects with real scenarios. This collaborative approach fosters buy-in and ensures relevant UX improvements.

Tracking the Customer Satisfaction Score (CSAT) on core modules allows continuous priority adjustment and demonstrates tangible experience improvements.

Usage Monitoring and Business KPIs

Setting up BI dashboards connected to the ERP provides real‐time visibility into usage metrics: transaction volumes, most-used features, average task times. Sharing these metrics with business teams helps identify under-utilized areas and plan targeted actions (training, UX tweaks, additional features).

Open‐source monitoring tools facilitate KPI integration into the existing ecosystem, whether via Grafana or Power BI, without disrupting daily operations. For deeper insight, see our article on BI ERP for precise, data-driven industrial management.

By showcasing these indicators in steering committees and business meetings, you cultivate a culture of continuous improvement and prove the ERP’s direct impact on performance.

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Optimize the ERP via UX, Automations, and Agile Micro-Developments

Refined UX and targeted automations maximize efficiency and user satisfaction. Agile micro-developments quickly address friction points and add business value.

UX Improvements and Screen Simplification

User‐journey analysis often reveals cluttered screens or overly linear processes. By refining navigation, visual hierarchy, and labels, task completion becomes easier. Workshops to validate prototypes align ergonomics with business needs before any development.

A modular approach based on reusable open‐source components speeds up UX enhancements and ensures visual consistency across the application.

Coupling regular user testing with agile cycles ensures each release improves the experience without disrupting operations.

Complementary Automations and Robotic Process Automation (RPA) Bots

In environments where processes cross multiple systems, adding automation scripts or RPA bots tackles repetitive tasks outside the ERP’s native scope. Invoicing, bank reconciliation, dashboard data feeds—these routines can be automated to free up time and reduce manual errors.

A Swiss e-commerce site implemented an RPA bot to feed daily external sales into its ERP. This automation eliminated 80% of manual work and cut inventory discrepancies by 60%.

Lightweight open-source tools ensure quick integration and simplified maintenance, while offering the flexibility to develop custom scripts for specific needs.

By governing these automations in an agile manner, each new use case is evaluated for ROI before scaling up.

Agile Micro-Developments and Rapid Adjustments

To quickly fix a friction point without waiting for a large project cycle, iterative micro-developments (spikes) are ideal. Planning 1- to 2-week sprints addresses priorities identified through support and feedback. These short initiatives deliver immediate gains and showcase the IT department’s responsiveness.

Built on a modular architecture, these micro-developments don’t disrupt overall stability or the standard release cycle. They integrate seamlessly via existing APIs and connectors.

By capitalizing on these quick wins, the IT department builds trust with business teams and encourages further suggestions to enhance the ERP.

Evolve the ERP Ecosystem with Integrations and Agile Governance

Custom Integrations via APIs and Service Bus

Opening your ERP through well-documented APIs simplifies exchanges with other systems (CRM, WMS, BI). By leveraging an open-source service bus, you ensure traceability, security, and scalability of data flows. Each new integration follows a reusable template to accelerate future projects, particularly with an API-first integration approach.

This standards-based strategy lets your ecosystem evolve without inflating costs or depending on a single vendor.

Automatically generated, centralized documentation maintains interface consistency and minimizes regression risks during updates.

BI Dashboards and Fact-Based Management

ERP operational data feeds interactive BI dashboards. Combining Power BI, Metabase, or Grafana, decision-makers access custom reports: product margins, delivery times, supplier performance. This visibility boosts responsiveness and guides strategic decisions.

Dashboards include proactive alerts on critical thresholds (low stock, overdue deadlines), shifting management from reactive to predictive.

Thanks to agile governance, each report is reviewed quarterly and adapted to evolving business objectives.

Agile Governance and Shared Roadmap

A steering structure that brings together the IT department, business teams, and service partners defines a five-year roadmap refined in quarterly sprints. Steering committees reassess priorities at each quarter’s end, measure the impact of changes, and adjust the backlog based on key metrics.

Choosing open-source, modular solutions strengthens governance flexibility, as components can be updated or replaced without creating excessive dependencies.

Transparent decision-making, ROI-based project scoring, and precise effort tracking create a virtuous cycle, continuously aligning the ERP ecosystem with strategic goals.

Transform Your ERP into an Organizational Alignment Lever

Securing adoption and optimizing post–go-live performance relies on a setup that integrates progressive training, structured support, continuous feedback, and agile micro-developments.

Your ERP should not be a rigid silo but the heart of an open ecosystem governed by agile processes and modular integrations. By combining refined UX, targeted automations, and robust APIs, it becomes a driver of performance and innovation.

Our experts are ready to support you in your continuous improvement program, transforming your ERP into a flexible automation platform and the foundation of a modern information system.

Discuss your challenges with an Edana expert

In an IT environment where availability and service quality are critical, it’s not enough that “it works”: you must be able to demonstrate reliability, manage commitments and legally secure every promise. Service Level Agreements (SLAs), Service Level Objectives (SLOs) and Service Level Indicators (SLIs) form an inseparable triptych for structuring the performance of your services, whether it’s a SaaS platform, a digital product or a mission-critical information system.

Beyond technical monitoring, these levers enable alignment of business priorities, control of investments and transformation of operational data into a genuine strategic decision-making tool.

The SLA, SLO and SLI Triptych

Service performance cannot be decreed; it must be defined. It relies on a clear contract (SLA), internal objectives (SLO) and factual measurements (SLI). Without this shared governance, technical, legal and commercial teams often speak different languages.

SLAs: A Clear Contractual Commitment

The SLA represents the formal promise made to customers, detailing availability levels, response times and resolution deadlines, as well as the penalties for non-compliance. It legally binds the company and serves as a common reference point for all stakeholders. Precision in the SLA is crucial: it defines the scope of services, exclusions, support tiers and escalation procedures.

When drafting it, precise language is essential, vague terms must be avoided, and exceptions thoroughly documented. For example, an SLA may promise 99.9% uptime per month but specify planned maintenance windows or impacts stemming from third-party dependencies. These clauses protect the company while establishing a framework of trust.

Example: A mid-sized firm initially drafted its SLA using generic metrics without clarifying the concept of “maintenance windows.” Business teams and the client interpreted availability differently, leading to disputes. This incident highlighted the importance of formalizing every criterion and transparently describing service tiers.

SLOs: Internal Operational Objectives

SLOs translate the SLA into concrete operational targets for technical teams—for example, an API request success rate, an average response time or a maximum Mean Time To Repair (MTTR). They serve as the roadmap for daily performance management and for structuring monitoring and alerting processes.

SLOs are set according to service criticality and the actual capacity of the infrastructure. They may vary by environment (production, pre-production, testing) and should follow a continuous improvement logic. An overly ambitious SLO can lead to unnecessary overinvestment, while a too-lax SLO can result in quality drift.

Defining SLOs structures efforts around metrics shared by DevOps, support and business teams. In case of deviation, they guide action plans and investment priorities in infrastructure or automation.

SLIs: Factual Performance Measurements

SLIs correspond to the data actually measured: API latency, percentage of successful requests, continuous availability or average restoration time. They are typically collected via monitoring and observability tools, such as availability probes or metrics from Prometheus.

SLI reliability is essential: a misconfigured or inaccurate indicator can lead to erroneous decisions, phantom alerts or lack of incident visibility. Therefore, robust pipelines for collecting, transforming and storing metrics must be implemented.

Without reliable SLIs, you can’t know if SLOs are met and thus whether the SLA is being honored. Operational data quality then becomes a governance pillar for IT steering committees.

Aligning SLAs and SLOs

An SLA must be realistic and aligned with your operational capabilities, and each SLO must be granular enough to drive continuous improvement. The articulation between these two levels ensures consistency between customer promises and internal efforts.

Aligning Business Commitments and Technical Performance

Co-developing SLAs and SLOs requires the involvement of business leaders, development teams and architects. Each brings a perspective: business stakeholders define needs and priorities, technical architects outline possibilities, and support anticipates incident scenarios.

This collaborative effort avoids unrealistic promises and establishes a common exchange platform. It clarifies functional and technical scope, evaluates dependencies and quantifies risks. Regular reviews harmonize expectations and foster a culture of shared responsibility.

By involving all stakeholders, the SLA evolves beyond a mere contractual document to reflect a pragmatic operational vision. IT executive committees then gain a transversal steering tool.

Prioritizing Investments Using SLOs

Each SLO must be linked to indicators of business criticality and risk. For example, an online payment service will have stricter SLOs than an internal information portal. This hierarchy guides budget allocation and technology choices (scaling, redundancy, caching).

SLOs pave the way for an iterative improvement roadmap. Priority investments focus first on the most critical services, then extend to lower-impact layers. This approach ensures measurable ROI and prevents resource dispersion.

By rigorously following these targets, CIOs can document resource usage, justify budgets and demonstrate the impact of each dollar invested on reliability and customer satisfaction.

Avoiding Unrealistic Promises and Managing Penalties

Offering a 99.999% SLA without an appropriate architecture exposes the company to high penalties in case of breach. It’s better to start with achievable service levels and progressively raise targets, linking each new tier to a technical upgrade plan.

Penalty clauses should remain deterrent but proportionate: they encourage performance without jeopardizing the client relationship over minor failures. Penalties can be capped or adjusted based on incident severity and business impact.

Mastering SLOs and contingency plans (escalation playbooks, recovery procedures) reduces exposure to penalties and strengthens mutual trust. IT oversight committees incorporate these indicators into their regular governance.

Example: A retailer promised 99.99% availability for its click-&-collect service without planning geographic redundancy for its APIs. During an incident, the contractual penalty equaled 20% of monthly revenue. This experience underscored the need to calibrate SLAs in line with architecture and tie SLOs to a realistic error budget.

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Transforming Observability through SLIs

SLIs form the direct link between operational reality and strategic objectives. Collecting them rigorously allows you to anticipate incidents and continuously adjust priorities. Observability thus becomes a true engine of resilience and innovation.

Collecting and Ensuring the Reliability of SLIs

The first step is to precisely identify relevant metrics (latency, error rate, uptime, MTTR) and ensure their reliability. Probes should be placed at every critical point: edge CDN, API gateway, databases, etc.

A redundant collection pipeline (e.g. agent plus external probe) guarantees measurement availability even if one monitoring component fails. Data are stored in a time-series platform or in a data lake or data warehouse to enable historical analysis and event correlation.

SLI quality also depends on regularly purging obsolete data and validating collection thresholds. A skewed indicator compromises the entire steering system.

Observability and Real-Time Alerting

Beyond collection, real-time analysis of SLIs enables detection of anomalies before they massively affect users. Configurable dashboards (Grafana, Kibana) offer tailored views to technical leads and steering committees.

Alerts must be calibrated to avoid “alert fatigue,” with phased thresholds: warning, critical, incident. Each alert triggers a predefined playbook involving engineering, support and, if needed, executive decision-makers.

Combining logs, distributed traces and metrics provides 360° visibility into service health and accelerates incident resolution.

Error Budget and Data-Driven Decision Making

The “error budget” corresponds to the tolerated margin of error per SLO. As long as it’s not exhausted, the team can perform moderate-risk deployments. Once depleted, non-essential changes are suspended until the budget is replenished, preventing gradual quality degradation.

This mechanism enforces discipline: every new feature reflects a balance between innovation and reliability. Governance committees use the budget consumption history to prioritize optimizations or redesigns.

Example: A public agency implemented an error budget on its national online declaration portal. It found most budget spikes occurred during unplanned updates. This insight led to a weekly maintenance window, reducing budget consumption by 30% and improving user experience.

Cloud-Native Architecture for SLAs, SLOs and SLIs

A cloud-native, microservices and API-driven architecture facilitates the implementation of the SLA/SLO/SLI triptych by offering modularity, redundancy and automated scalability.

Impact of Cloud and Microservices Architectures

Distributed architectures isolate critical services and enable independent scaling of each component. By assigning SLAs and SLOs per service, you delineate responsibilities and mitigate domino effects during incidents.

Cloud environments provide auto-scaling, dynamic provisioning and multiple availability zones.

Integrating Monitoring and Executive Dashboards

Consolidating SLIs into dashboards dedicated to IT and business leadership enables quick performance reviews. Aggregated KPIs (overall availability rate, incident count, error budget consumption) feed decision-making bodies.

It’s recommended to tailor these dashboards by role: an “exec” overview, an “operations” detailed view and a “compliance” version for legal. This segmentation enhances clarity and accelerates decision cycles.

Enhancing Resilience and Redundancy with Contextual SLOs

Third-party dependencies (cloud services, external APIs) should be governed by specific SLOs and resilient architectures (circuit breaker, retry, fallback). Each integration requires an ad hoc SLO to limit impact surface.

Implementing redundant zones, multi-region databases or geographically distributed Kubernetes clusters ensures service continuity in case of local failure. SLOs then include RTO (Recovery Time Objective) and RPO (Recovery Point Objective) criteria.

This contextual approach balances cost and risk and optimizes reliability according to business criticality.

Manage Your Digital Reliability as a Strategic Asset

SLAs, SLOs and SLIs are not mere documents or metrics: they form a governance framework that aligns commercial commitments with technical capacity and legal compliance. Each step—from defining the SLA to collecting SLIs, building the SLOs and designing the underlying architecture—strengthens your IT resilience and positions reliability as a performance lever.

Whether you’re planning to overhaul your service agreements or integrate advanced monitoring, our experts are at your disposal to co-construct a contextual, modular and scalable solution that aligns with your business challenges, legal requirements and IT strategy.

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Cheap web development seduces with its attractive price, but initial savings can quickly morph into budget overruns and frustration. Behind a low-cost offer often hide gaps in transparency, rigor, and expertise, resulting in delays, costly fixes, and lost business value.

Rather than blaming technology alone for overruns, it is crucial to understand how selecting the wrong provider and neglecting serious upfront scoping drain budgets and stall digital performance.

Risks of Low-Cost Web Development

Hidden risks behind a “cheap web development” offer. Low-cost services conceal structural weaknesses that undermine quality and profitability.

Opaque Proposals: Promises vs. Reality

Very low-priced offers are often based on superficial estimates. Without a thorough needs analysis, the provider underestimates the project’s functional and technical complexity, then makes up for slim margins by cutting quality. This approach leads to incomplete solutions, poorly designed interfaces, and missing features.

In such a context, every poorly defined item generates additional costs during user acceptance testing. Change requests multiply and each update becomes a high-priced ticket. Decision-makers then discover that the final bill far exceeds the initial budget.

Compared to a consultancy-oriented offer, the gap isn’t just the hourly rate but the initial investment in expertise and methodology. Serious scoping sets clear boundaries and limits unpleasant surprises, whereas a low-cost proposal often covers only minimal scope.

Example: A Swiss nonprofit entrusted the development of its membership portal to a bargain-priced agency. No UX research or business validation was performed. The result: users couldn’t follow the registration flow, maintenance costs doubled the original budget, and repeated reminders were needed to fix basic navigation issues. This case shows how the absence of upfront scoping can turn an ordinary web project into an endless ordeal.

Missing Agile Process: The Domino Effect of Delays

In low-cost projects, agile sprints and ceremonies are often sacrificed to speed up production. Without regular progress checkpoints, technical and functional issues surface too late, forcing corrections at the end of the cycle. Time saved initially is lost during validation and adjustment phases.

Lack of code reviews and automated tests increases regression risks. Each untested new feature can break existing modules, triggering repeated and expensive correction cycles. Internal teams become overwhelmed by tickets, hindering their ability to focus on priority enhancements.

By contrast, a well-orchestrated agile process includes continuous reviews and testing, ensuring steady quality improvements. Fixes happen in real time, and stakeholders stay involved throughout the project, safeguarding schedule and budget.

Unaddressed Requirements: Quality Takes a Hit

To maintain a rock-bottom price, the provider may exclude requirements not explicitly listed, such as accessibility, security, or scalability. These critical dimensions fall outside the low-cost scope and are either billed extra or simply neglected.

The outcome is a fragile platform, exposed to vulnerabilities and unable to handle increased load. Maintenance and security-hardening costs then become recurring, unforeseen expenses that drain the IT budget and obscure the project’s true cost.

By embracing a quality-oriented approach from the start, these requirements are built into the initial estimate. The apparent short-term premium becomes an assurance of a durable, extensible solution, curbing long-term financial drift.

Limiting Scope Creep

Absent serious scoping invites scope creep. Without clear boundaries and milestones, every additional request becomes a new line item.

Insufficient Scoping: Ill-Defined Boundaries

A bare-bones specification fuels divergent interpretations between client and provider. Listed features are vague, measurable objectives are missing, and responsibilities remain informal. As a result, each party understands requirements differently and tensions arise at the first demos.

This vagueness lets the low-cost provider bill any clarification as extra work, since it wasn’t part of the original quote. Meetings multiply without yielding concrete deliverables, and the budget inflates to address avoidable confusion.

Rigorous scoping relies on a preliminary study, cross-functional workshops, and validated documentation. By precisely defining scope, you reduce drift risk and protect your initial investment.

Scope Creep: The Snowball Effect

Scope creep occurs when an unplanned change triggers successive requests that disrupt the schedule. Every technical addition, however minor, alters the architecture and may require hours of extra development and testing.

In a low-cost setting, there’s no clear governance to arbitrate these demands. Projects become an ongoing catalog of small tweaks with no real business prioritization, eventually exhausting the budget envelope.

Conversely, disciplined project management uses a product discovery workshop, a business-value-prioritized backlog, and a regular steering committee. Each change is evaluated for ROI and technical impact, enabling refusal or rescheduling of adjustments outside the initial scope.

Budget Transparency: Unanticipated Costs

Low-cost providers often apply differentiated rates depending on task type. Design work, process setup, and technical research can be billed above the advertised rate. These hidden costs only surface at project end, when the client realizes the true amount due.

Without a monitoring dashboard, each invoice stacks on the last until the budget is shattered. Business teams lack visibility into remaining effort, and the IT department must urgently arbitrate among competing projects.

Choosing a transparent offer—with interim reports and budget-consumption metrics—gives you control and lets you adjust scope or priorities before funds are fully spent.

The Importance of Senior Oversight

Lack of expertise and guidance slows your projects. A junior-only team without senior oversight breeds errors, delays, and dissatisfaction.

Unsupervised Junior Teams

To meet ultra-low rates, a provider may rely exclusively on junior profiles. These developers often lack the experience to anticipate technical and architectural pitfalls. They apply known recipes without tailoring innovative or customized solutions.

Their limited autonomy requires frequent reviews and constant support. Without oversight, they introduce technical workarounds or one-off hacks, creating technical debt from the first versions.

A senior team, by contrast, anticipates structural choices, recommends proven patterns, and leverages mature know-how. Risks are identified early and code quality becomes integral to the project culture.

Example: A Swiss public agency experienced a 40% schedule overrun when launching a new service portal. The junior developers on the project had never implemented a complex workflow. Without senior mentorship, they made logic errors that extended acceptance testing and forced an external audit to refactor code before production. This example underscores the value of experienced oversight for schedule security.

Missing Code Reviews

In a low-cost offer, code reviews are often skipped in favor of rapid deliveries. Without these checkpoints, stylistic errors, security flaws, and code duplication go unnoticed. Anomalies accumulate and weaken the application foundation.

Each new feature adds unrefined or poorly structured code, focusing maintenance efforts on bug fixes instead of innovation. Support costs swell, despite the original goal of minimizing expenses.

Systematic code reviews ensure adherence to best practices, bolster security, and guarantee maintainability. They foster knowledge sharing within the team and drive continuous improvement.

Absence of Senior Leadership: Impact on Reliability

Without an architect or technical lead, there’s no holistic vision of the ecosystem. Technological choices are made ad hoc, often without consistency across modules. Each developer follows their own interpretation, neglecting alignment with digital and business strategies.

This lack of coordination leads to service duplication, inconsistent ergonomics, and single points of failure. In the event of an incident, investigation is laborious because no one has a complete map of the solution.

Senior leadership defines the target architecture, ensures component coherence, and guides technical choices toward robustness and scalability. It guarantees shared accountability and up-to-date documentation.

Impact of Technical Debt

Invisible technical debt weighs on your budget without you noticing. Maintenance and evolution costs quietly accumulate, eroding your ROI.

Accumulating Invisible Debt

Shortcuts taken to hit a rock-bottom price leave traces in the code. Lack of tests, incomplete documentation, undocumented technology choices… these elements form technical debt that grows with each iteration.

This debt doesn’t appear in initial budgets, but its effects emerge when a bug fix, update, or new feature first requires “clearing the backlog.” Teams then spend more time unraveling past decisions than delivering new value.

By formally declaring and quantifying technical debt, you can integrate it into your IT roadmap and address it proactively, using a digital roadmap. This prevents legacy from becoming a major barrier to your digital ambitions.

Costly Maintenance: Silent Invoices

Corrective interventions billed on a time-and-materials basis stack up without the client realizing the cost origin. Each ticket addressing a debt-related bug incurs an hourly rate often higher than the initial development cost.

Over months, maintenance fees can account for 50% or more of the annual IT budget, reducing resources available for innovation. Trade-offs become hard, and strategic initiatives are postponed.

A well-documented, modular, and tested architecture keeps maintenance costs in check. Fixes are rapid, with controlled impact on schedule and budget, preserving capacity to invest in future projects.

Lack of Scalability: The Glass Ceiling

Technical debt ultimately limits the solution’s scalability. Any request for load increase or new features bumps up against fragile code and a lack of modularity.

The result is blocked growth, sometimes forcing a partial or complete platform rewrite. This “big bang” can cost up to ten times more than a planned, incremental refactor.

By adopting a modular, open-source-based approach aligned with your business needs from day one, you ensure healthy, controlled scalability. Your application becomes an asset that adapts to growth, without a glass ceiling.

Turn Cheap Web Development into a Sustainable Investment

Choosing a low-cost provider may deliver initial savings but exposes you to structural risks, scope overruns, technical debt, and insidious maintenance costs. Serious scoping, agile governance, and senior expertise guarantee a reliable, scalable solution aligned with your business goals.

Your priorities are cost control, infrastructure longevity, and return on investment. Our Edana experts are ready to help you define the right digital strategy, secure your project, and transform your needs into lasting benefits.

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In many Swiss organizations, the accumulation of specialized tools often seems to be the answer to every operational need or management requirement. For a CIO or CTO, this typically translates into a highly technical mindset: adding a software solution for every process or metric.

Yet, on the ground, operational teams endure these heterogeneous, repetitive, and fragmented interfaces at the expense of their productivity. It’s time to adopt an approach focused on actual usage, rationalize your tools, and rethink the overall ecosystem. By simplifying without sacrificing control, you can ensure adoption, data consistency, and a sustainable return on investment—perfectly aligned with the expectations of the Swiss market.

Assessing the Impact of Software Proliferation on Your Information System

The stacking of business applications creates friction and diffuses accountability. This initial assessment is essential to measure the real impacts on productivity and costs.

Impact on Team Productivity

Each new tool demands training, additional credentials, and often a different data context. Employees spend considerable time switching between applications, duplicating data entry, or searching for where to find specific information.

This fragmentation leads to cognitive fatigue, slows decision-making processes, and sometimes results in input errors. Product or sales teams may end up concealing these dysfunctions rather than reporting them, which undermines reporting quality and reliable management.

Increased IT Department Complexity

Beyond the user experience, integrating multiple software solutions places a significant maintenance burden on the IT department. Updates, compatibility tests, and security patches multiply. For insights on securing your cloud ERP, consult our guide.

Downtime accumulates with every version upgrade, and dependency management becomes time-consuming. In the medium term, this can hinder the IT department’s ability to roll out new projects, as a large portion of the budget is absorbed by operational maintenance.

Technical debt grows without immediate visible effects—until a critical incident exposes the excessive interdependencies between systems, making recovery long and complex.

Hidden Costs and Underutilized Licenses

Cumulative licenses, SaaS subscriptions, and support fees often vary by department, obscuring the overall budget allocated to the information system. Functional redundancies go unnoticed without a periodic review process.

In some companies, up to 30% of licenses remain completely unused, while other purchased modules no longer match everyday needs. The absence of unified reporting prevents informed decisions regarding the relevance of each license.

Example: A digital services company maintained five CRM solutions across different divisions. Each was underutilized and required a dedicated maintenance contract. After a simple audit, the IT department decommissioned two redundant licenses, immediately saving 20% of the annual budget while improving the consistency of customer data.

The takeaway for the IT department is clear: every underutilized license represents a fixed cost that does not translate into on-the-ground performance gains. Without precise measurement, it remains difficult to justify either removal or consolidation of tools deemed indispensable. For improved technical debt management, consult our guide on technical debt control.

Refocusing the Information System on Business Usage

An approach centered on actual processes ensures that each tool delivers tangible value. It starts by identifying operational needs before selecting or retaining any software.

Mapping Critical Processes

The first step is to map information flows and key stages of each activity. This goes beyond listing software—it identifies bottlenecks or slow points in daily processes.

Mapping requires collaboration between the IT department, business units, and field teams. It should reveal redundancies, manual steps, and overly complex interfaces that slow execution. To learn more about workflow architecture, read our article.

This shared diagnosis forms the foundation for any rationalization effort and allows you to quantify each tool’s real impact on business performance by evaluating and selecting solutions tailored to your processes.

Prioritizing Real Needs

Once processes are documented, improvements must be ranked by their contribution to revenue, customer satisfaction, or risk reduction. This prioritization should incorporate user feedback, often overlooked in software decisions.

Advanced features are sometimes underused because they don’t align with everyday practices or are too burdensome to configure. It’s better to focus on high-value modules than to accumulate new licenses.

Iterative management of these priorities avoids monolithic projects and ensures a tangible return on investment at each phase.

Adapting the Ecosystem to Actual Usage

Rather than imposing a generic software solution across all functions, consider modular or custom solutions tailored to specific contexts. This may involve light development work or fine-tuning open source platforms.

This flexibility limits the number of tools while providing a unified user experience. Interfaces can be consolidated through portals or standardized APIs to mask underlying complexity.

Example: An industrial firm used five separate portals for production order management, maintenance tracking, quality control, procurement, and reporting. By migrating to a composable platform and developing custom microservices, the company reduced its software portfolio by 40% and improved the speed of critical data processing.

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Establishing a Coherent and Scalable Software Architecture

A modular, composable architecture ensures flexibility and longevity of your information system. It simplifies integration, scalability, and ongoing maintenance.

Choosing Modular Platforms

Modular solutions rely on independent building blocks (microservices, functional modules, APIs) that can be activated or deactivated as needed. This approach limits the impact of changes on the entire system.

By prioritizing open source platforms, you retain control over your source code and avoid vendor lock-in. You can customize modules without being constrained by closed licenses or prohibitive migration costs. For a scalable software architecture, explore our guide.

Composable Architecture and Microservices

Composable architecture involves assembling services and features at a granular level. Each microservice handles a specific functional domain (authentication, inventory management, billing, etc.) and interfaces through lightweight APIs.

This granularity simplifies testing, deployment automation, and monitoring. In the event of an incident, one service can be isolated without affecting the whole system, reducing the risk of a widespread outage.

Prudent decomposition also limits cognitive complexity and promotes clear responsibility boundaries among engineering teams.

Integration and Data Flow Automation

Once components are defined, you must orchestrate data flows to ensure information consistency. Enterprise Service Buses (ESBs) or integration Platform-as-a-Service (iPaaS) solutions facilitate this integration. For total automation, read our article on designing processes to be automated from the start.

Automation relies on CI/CD pipelines to deploy, test, and monitor each version. Continuous end-to-end testing ensures the stability of business flows.

This DevOps approach strengthens collaboration between IT and business teams, accelerates deployments, and enhances system resilience in the face of change.

Implementing Agile Governance and Streamlined Management

Governance must reflect actual usage dynamics and evolve with business priorities. Clear management enables performance measurement and continuous refinement of the software portfolio.

Managing Applications Through Catalogs and Metrics

A centralized catalog lists each application, its usage, cost, and user satisfaction level. It becomes the reference tool for purchase or decommissioning decisions.

The right KPIs to steer your information system in real time (adoption rate, time spent, functional ROI) are tracked regularly. These data-driven insights, including OKRs, facilitate trade-offs and justify system changes to senior management.

Iterative, Cross-Functional Governance

Instead of IT steering committees every six months, it’s better to hold quick, regular reviews that include the IT department, business representatives, and architects. These sessions allow you to reassess priorities and align them with strategic objectives. To learn how to effectively scope an IT project, consult our guide.

Ongoing Training and Adoption

Tool implementation doesn’t end at go-live. Training must be continuous, context-specific, and integrated into teams’ daily routines.

Short sessions focused on real use cases, combined with accessible documentation, boost adoption and reduce resistance to change. Feedback is collected to fine-tune configurations and processes.

This continuous improvement loop ensures chosen software remains aligned with usage and truly meets business needs.

Simplify Your Information System to Unlock Operational Efficiency

Software proliferation is not inevitable. By accurately diagnosing friction, refocusing your system on usage, adopting a modular architecture, and implementing agile governance, you can rationalize your application portfolio while strengthening oversight.

Simplicity—combined with clear process understanding and relevant metrics—becomes a lever for lasting performance. Your teams gain productivity, your IT department frees up resources for innovation, and your information system fully supports your strategic goals.

Our Edana experts are available to guide you through this pragmatic, context-driven process, leveraging open source, scalability, and security without vendor lock-in—always ROI-focused.

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