For years, legacy systems have supported the core processes of many organizations. SAP, on-premise SQL Server, and countless Excel spreadsheets remain the operational backbone of logistics, procurement, HR, and production departments.

However, their rigidity, lack of integration, and limited scalability are holding back companies from adapting, optimizing, and making decisions in real time.

One of the biggest challenges? Accurately estimating effort, routes, and cycle times in critical processes. This requires seamless, reliable, and real-time data access — and that’s where the cloud becomes a key enabler.

The Problem with Legacy: Silos, Slowness, and Low Visibility

While once robust, legacy systems now pose significant challenges:

• Not designed to easily integrate with new technologies (IoT, analytics, AI)

• Difficult and time-consuming to access or share data across departments

• Expensive to maintain and inflexible to change

• Data visualization and analysis often require intensive manual effort

As a result, estimating how long a task will take, what resources are needed, or how to optimize a delivery route becomes complex, slow, and costly.

Why Migrate to the Cloud?

Migrating legacy systems to the cloud isn’t just “modernization for the sake of it” — it’s about enabling tangible capabilities:

• Unified, centralized access: Data from multiple systems in one place

• Scalable processing: Infrastructure that adjusts to usage peaks

• Integration with analytics and prediction tools: From Power BI to machine learning models

• Workflow automation: Seamless connectivity between platforms (SAP + Excel + sensors) using Azure Data Factory, Synapse, or APIs

With cloud integration, data becomes available, ready, and purposeful — empowering teams to estimate, anticipate, and act with agility.

What Capabilities Does This Unlock?

a) Operational Effort

• How long does it take to fulfill an order?

• Who’s involved?

• What resources are available?

• Analyze historical data to detect bottlenecks or inefficiencies

b) Logistics Routes

• Map routes, compare estimated vs actual times, and assess external factors (weather, traffic)

• Optimize delivery paths based on real data and predictive analytics

c) Cycle Times

• Visualize time from order intake to closure

• Project outcomes based on workload, inventory, or availability

To achieve this, you must consolidate sources such as SAP (orders and time data), SQL (transactional data), and Excel (auxiliary or unstructured data) into a unified environment.

The result? Greater visibility, agile decision-making, enhanced collaboration, lower infrastructure and maintenance costs, and access to advanced analytics.

So, migrating legacy systems to the cloud is not just a technical initiative — it’s a strategic lever for efficiency and competitiveness.

When SAP, SQL, and Excel are integrated into a modern ecosystem, the possibilities for analysis, automation, and optimization multiply.

For technology leaders, this is the moment to lead with purpose: modernize with intent, connect with agility, and deliver real business value.

Because better estimation means better decisions.
And for that, we need the data to speak.

Need support with your implementation?
Let’s talk.