VLADISLAV SECRIERU
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Financial Clarity for Complex Organizations

When financial data is spread across multiple ERPs, spreadsheets and regional systems, leadership loses visibility into what actually drives performance.

We design centralized financial data architectures that turn fragmented operational data into reliable decision intelligence.

From automated consolidation to transaction-level profitability analysis, the goal is simple: give leadership a clear and trusted view of the business.

Request Data Architecture Assessment

THE CHALLENGE

When Financial Reporting Stops Scaling

Most growing organizations reach a point where financial reporting stops scaling with operational complexity.

Different regions operate on different systems. Finance teams maintain dozens of spreadsheets. Reconciliations become manual and slow.

Common symptoms

  • Financial close takes 7-10+ days
  • Numbers differ between departments
  • Profitability cannot be traced to transactions
  • Forecasting relies on manual spreadsheets
  • Leadership dashboards raise more questions than they answer

These are rarely reporting problems. They are data architecture problems.

THE INSIGHT

Why Most Data Projects Fail in Finance

Many organizations try to solve reporting problems by adding dashboards.

But dashboards sit on top of fragmented financial data structures. When KPI definitions differ across departments and systems remain disconnected, every new report creates another version of the truth.

Real transformation requires redesigning the financial data architecture itself: how systems integrate, how entities relate, and how performance metrics are defined.

THE OUTCOME

What a Governed Financial Data Architecture Enables

Daily Financial Visibility

Financial performance updated automatically instead of weeks after month-end close.

Transaction-Level Profitability

Drill-down from executive P&L to individual transactions, deals or invoices.

Unified KPI Logic

One consistent definition of revenue, margin and cost across all entities and regions.

Faster Decision Cycles

Leadership sees issues early and can react before problems escalate.

CASE STUDY

Global Energy Trading Company

The Situation

A multinational energy trading group operating across APAC, EMEA and North America faced severe reporting fragmentation.

  • 25 legal entities
  • Multiple ERP systems
  • Separate CRM and trading platforms
  • Dozens of Excel-based reporting files
  • 10-day reporting delay after month-end close

Leadership lacked transaction-level visibility into profitability.

The Transformation

A centralized financial data architecture was designed and implemented, integrating ERP, CRM, ETRM and accounting systems into a governed Snowflake-based platform.

The project included:

  • Reverse engineering undocumented system logic
  • Designing a unified financial data model
  • Building automated ELT pipelines
  • Standardizing profitability reporting across regions

The Impact

  • Reporting cycle reduced from 10 days post-close to daily refresh
  • P&L statements drillable to transaction level
  • Clear profitability visibility across entities and business lines

THE APPROACH

Our Approach to Financial Data Transformation

01

Architecture Assessment

Mapping systems, entities and reporting logic to identify structural bottlenecks.

02

Financial Data Model

Designing a unified data architecture that standardizes KPI definitions and entity structures.

03

Integration & Automation

Building scalable data pipelines connecting ERP, CRM, ETRM and accounting systems.

04

Executive Intelligence Layer

Delivering reporting environments that allow leadership to move from high-level financials to transaction-level detail instantly.

ABOUT

About Vladislav Secrieru

Senior Finance & Data Transformation Specialist based in Oslo.

Specializing in building financial data architectures for multinational and multi-entity operations.

Background includes consulting and financial analytics roles across finance, data and performance governance.

  • Former consultant at KPMG
  • Former consultant at EY
  • Experience integrating 25+ legal entities into unified data platforms
  • Expertise in Snowflake, SQL, Python and modern BI environments

IDEAL CLIENT

Who This Work Is Most Valuable For

This work is typically relevant for organizations with complex operational structures.

  • Multiple legal entities
  • Operations across several regions
  • Several ERP or operational systems
  • Heavy reliance on Excel reporting
  • Finance teams spending weeks preparing reports

Typically mid-market and enterprise companies with significant operational complexity.

GET STARTED

Regain Control of Your Financial Data

If your organization struggles with fragmented systems, slow reporting or inconsistent numbers, there is usually a structural reason behind it.

Fixing it requires more than dashboards. It requires the right financial data architecture.

Request Financial Data Architecture Assessment

CONTACT

Let's Discuss Your Data Challenges