- Client
- Challenge
- Our Team & Delivery Model
- Solution
- Effects
- Summary
- What's next
Summary
- Global FMCG company operating in 180+ markets with complex commercial data flows.
- Production-critical data integration platform synchronizing product, promotion, and commercial data.
- System hit performance and scalability limits — some workflows took up to 20 hours.
- Full rebuild was impossible due to zero downtime tolerance and active production use.
- Introduced targeted optimizations inside the existing monolithic architecture.
- Reduced workflow time from 20 hours to ~4 hours (5× improvement) and stabilized daily synchronization.
- Enabled multi-market expansion and more efficient cloud infrastructure usage without replacing the system.
Client
Our client is a global FMCG corporation operating in over 180 markets worldwide.
The organization manages highly complex commercial operations, including:
- Large-scale product portfolios,
- Market-specific promotion mechanics,
- Distributed sales structures,
- Multi-layered contractor and client ecosystems.
Its operational model depends on accurate and timely synchronization of commercial data across multiple internal systems and markets.
Given the scale and geographic spread, even small inconsistencies in data propagation can impact commercial execution, promotion timing, and operational stability.
The organization operates under structured enterprise governance, with clearly defined architectural ownership and approval processes.
Challenge
At the time of engagement, the client operated a production-critical data integration platform initially serving a single market (Italy).
The system aggregated and synchronized product data, promotion logic, and commercial information across multiple internal systems.
However, several structural issues had emerged.
Performance at operational limits
Certain workflows required up to 20 hours to complete.
With daily synchronization cycles, this created structural exposure:
- Risk of overlapping processing windows,
- Promotion misalignment across systems,
- Delayed propagation of updated data,
- Reduced operational safety margin.
The system was nearing its scalability ceiling.
Monolithic architecture under pressure
The application functioned as a large monolith:
- Fully synchronous processing,
- No internal parallelization,
- Large datasets loaded entirely into memory,
- Limited scalability flexibility.
Although a microservices redesign would have been architecturally cleaner, the platform was already business-critical. A full rebuild was not feasible due to:
- Zero tolerance for downtime,
- Ongoing production dependency,
- Continuous release requirements.
Infrastructure inefficiency
Heavy RAM and CPU usage resulted in:
- Expensive vertical scaling,
- Limited elasticity,
- Increased instability risk under high data loads.
Strategic expansion requirement
The client aimed to expand the platform beyond Italy and onboard additional international markets.
Each market introduced:
- Variations in promotion rules,
- Differences in business logic,
- Distinct product-handling requirements,
- Market-specific data dependencies.
The challenge was enabling multi-market scalability without replacing the existing system or interrupting operations.
Enterprise governance constraints
The delivery model required operating within:
- Architectural oversight from the client-side lead architect,
- Defined project scope boundaries,
- Limited direct access to broader business layers.
The solution had to respect corporate governance structures while delivering measurable improvement.
Our Team & Delivery Model
The team collaborated directly with the client-side lead architect and internal developers.
Architectural approval authority remained with the client. Within this framework, the team was responsible for:
- Designing technical implementations,
- Translating business objectives into architecture,
- Proposing structural improvements,
- Delivering production-ready releases.
We were not provided with detailed technical blueprints. We received business requirements and independently designed technical solutions aligned with them.
Scoped autonomy with accountability
Within the defined project boundary, the team:
- Evaluated architectural trade-offs,
- Proposed performance optimizations,
- Investigated and validated incident reports,
- Distinguished system defects from intended business behavior.
Despite limited access to broader business layers, the team developed strong understanding of:
- Promotion lifecycle logic,
- Market-specific rule variations,
- Product–client relationships,
- Data propagation flows.
This enabled responsible decision-making and independent problem resolution within scope.
Continuous delivery under live conditions
Throughout optimization and restructuring:
- Releases were delivered every 2–3 weeks,
- Feature development continued,
- No freeze periods were introduced.
Architectural improvement and operational stability were maintained in parallel.
Long-term engagement
The collaboration has lasted approximately 5 years and continues to evolve with additional markets.
In enterprise environments, sustained collaboration on a growing production system reflects delivery reliability and technical accountability
Solution
For over 3.5 years, a developer from Directio has been a core part of the client’s mobile team. Integrated into the team’s daily work and delivery cycles, he contributes not only to feature implementation, but also to discussions around architecture, planning, DevOps, testing, and continuous improvement.
The application is developed within the Microsoft ecosystem, using technologies like Xamarin (with migration toward .NET MAUI), a .NET-based backend, and Azure for cloud infrastructure. The development process includes a robust CI/CD pipeline, automated testing, and regular release cycles that ensure quality and stability in a highly sensitive, user-facing domain.
At Directio, our approach to team augmentation goes beyond supplying developers – we bring in problem-solvers who think critically, adapt quickly, and make a real impact from day one.
Benefits for the Client
- Stable development flow despite shifting priorities and architectural evolution
- Reduced onboarding time for new team members thanks to in-team support and knowledge sharing
- Higher user satisfaction from faster delivery of app improvements and features
- Better product decisions thanks to input from someone who knows the app’s full history and dependencies
- More resilient team dynamics enabled by flexibility and trusted communication
Effects
Incremental architectural evolution
Rather than replacing the system, we introduced controlled internal restructuring within the existing monolith.
This approach prioritized:
- Business continuity,
- Performance stabilization,
- Scalability,
- Risk mitigation.
A full architectural rebuild (e.g., microservices migration) was consciously avoided due to production criticality and zero tolerance for downtime. The focus was on strengthening what already existed while preserving operational stability.
Effect:
The platform’s performance and scalability were significantly improved without introducing downtime risk or disrupting ongoing business operations.
Workflow optimization
We redesigned processing logic to:
- Reduce operations on large data sets,
- Limit synchronous execution chains,
- Remove unnecessary memory retention,
- Improve execution efficiency.
Effect:
Maximum workflow time was reduced from approximately 20 hours to around 4 hours – a fivefold improvement – restoring safe daily synchronization margins, eliminating the risk of processing overlap between cycles, and increasing overall data throughput capacity.
Memory & resource optimization
Previously, large volumes of data were held in RAM during processing, creating instability risks and infrastructure strain.
We introduced:
- Cloud-based data persistence layers,
- On-demand subset loading,
- Reduced in-memory footprint.
Effect:
The system became stable under growing data volumes while lowering memory pressure and improving overall infrastructure efficiency.
Horizontal scalability
Instead of vertically scaling a single high-tier machine, we implemented:
- Dynamic provisioning of additional compute instances,
- Automatic shutdown after processing completion,
- Use of lower-tier infrastructure where appropriate.
Effect:
Infrastructure consumption became workload-aligned and elastic, reducing unnecessary cloud expenditure and improving cost efficiency under variable data loads.
Multi-market enablement
Following performance stabilization, the platform expanded beyond Italy to three other countries.
To support market-specific business logic within the existing architecture, we introduced structured conditional logic layers inside the monolith.
This increased internal complexity but preserved uninterrupted operations and avoided system replacement.
Effect:
The client enabled international platform expansion without duplicating systems, rebuilding architecture, or interrupting ongoing commercial processes.
Summary
5x Improvement in workflow performance
Processing time reduced from ~20 hours to ~4 hours:
- Eliminated synchronization overlap risk,
- Increased data processing capacity,
- Improved reliability of promotion execution.
Infrastructure cost efficiency
Through optimized resource management and elastic scaling:
- Reduced RAM and CPU load,
- Enabled lower-tier infrastructure usage,
- Converted fixed scaling cost into demand-based usage.
International scalability without system duplication
The platform now supports multiple markets without:
- Parallel regional systems,
- Redundant development teams,
- Fragmented governance structures.
This supports long-term operational consolidation.
Improved maintainability
Structured documentation standards were introduced:
- New functionality requires documentation,
- Modifications require updates,
- Onboarding complexity reduced compared to initial state.
Stabilized, scalable integration platform
The system now operates with:
- Increased performance margin,
- Controlled infrastructure usage,
- Continuous delivery cadence,
- Scalable market support.
The result was not system replacement, but controlled evolution under enterprise constraints.
What’s next?
Enterprise cloud environments rarely fail because of technology alone.
They fail because architecture does not evolve at the pace of scale.
If your organization is:
- Operating a growing monolithic system under performance pressure,
- Facing rising cloud infrastructure costs,
- Expanding to new markets with varying business logic,
- Struggling to balance architectural ambition with operational continuity,
At Directio, we help enterprise teams stabilize, optimize, and scale cloud-based systems without introducing disruption. Whether it involves performance bottlenecks, infrastructure inefficiencies, architectural restructuring, or multi-market enablement – our approach prioritizes continuity, accountability, and measurable outcomes.
If you are evaluating your next step in cloud optimization or architectural transformation, let’s start with a technical conversation.
