From data fragmentation to financial clarity: a modern approach to handling Accounts Payable spend
Many organizations struggle with visibility into their vendor spend. This is especially true for companies that have grown through acquisitions, leaving them with multiple disparate Enterprise Resource Planning (ERP) and financial systems. Finance teams often find themselves looking across multiple databases just to answer basic questions about vendor relationships and spending patterns, but what if they could consolidate this fragmented view into a comprehensive, unified understanding of the entire vendor ecosystem?
Conventional (outdated) approach to vendor data management:
The most common way to access vendor data involves leveraging one-time data extracts from disparate systems, often owned by different business units. Analysts consolidate and transform the data to create high-level reporting relevant for only a single point in time. These reports are distributed throughout the company where end users interpret and potentially manipulate the data further.
Though this conventional approach typically covers several of their needs in the short term, companies frequently face five common data-related hurdles that hinder efficiency and impact outcomes of managing spend tracking and vendor management over time, including:
- Resource inefficiencies – Analysts spend significant time on a recurring basis manually extracting data from multiple sources (e.g., different financial data systems for each division) and consolidating it for further analysis rather than focusing on strategic activities
- Inaccuracies – Analysts are more likely to make errors when manually preparing and consolidating disbursement data
- Software limitations –Analysis via Excel creates limitations such as difficulty creating advanced visualizations, poor handling of large datasets, and inefficiency in combining multiple data sources
- Lack of real-time reporting – Manual data consolidation creates weeks-long reporting delays; by the time reports are compiled, the data is outdated
- No single source of truth – Multiple versions of data reports across departments create risks of version control, documentation errors, misunderstanding, and misalignment
Modern approach:
To overcome these challenges, companies can integrate their data across systems to prepare advanced visualizations and analytics. The diagram below outlines a streamlined approach to building a modern data infrastructure for strategic sourcing, from raw data sources to actionable insights.
A Power BI dashboard provides dynamic views with interactive elements like advanced filtering and drill-down capabilities, improving time-to-insight over conventional static reporting.
The right combination of cloud-based data software allows cost-effective automation of spend analytics, removing Excel entirely out of the equation. Ingestion tools like Fivetran pull data into centralized warehouses such as Snowflake. In this centralized data warehouse, teams can develop and consolidate business logic and consolidate data flows in a governed setting, creating an agreed upon source of truth. Visualization and reporting platforms like Power BI then provide automated reports for a variety of users, enabling broader analytics and ensuring consistent, organization-wide reporting.
This combination of tools improves efficiency and provides visibility for consolidating AP spend, including:
- More informed decision-making – Automated ingestion and transformation of robust datasets allows for instant, accurate insights available for interpretation
- Reduced admin time – Time spent on manual report preparation can be diverted to higher value activities such as strategic sourcing
- Traceability of data – Direct, live connection to ERP and finance systems allows data lineage and ensures high fidelity of data
Beyond improved data access and process efficiency, organizations can create substantial value through faster decision-making and advanced AP reporting. These advantages often drive improvements in EBITDA and liquidity, including:
- Reduce AP cost – Manage payment schedules to tactically capture early payment terms to lower spend and automate alerts to ensure payment discipline and avoid late fees
- Improve vendor management – Uncover duplicate or underperforming vendors across business units to consolidate spend and focus on strategic partnerships
- Strengthen negotiation leverage – Empower procurement teams to secure volume discounts or preferred supplier status
- Optimize cash flow and working capital – Gain visibility into timing, recurring spend, and invoice aging to support more robust planning and prioritize payments dynamically each pay period to improve working capital
- Enhance compliance – Reduce fraud risk by detecting anomalies, such as duplicate invoices, round-dollar amounts, off-contract spend and accelerate audits through lower compliance burden and reduce FTE-hours
In this specific case, an operationalized procurement dashboard identified $8M-$12M in spend reduction prior to capital expenditure analysis. The flexibility of this reporting structure allows for detailed analysis of spend, high level tracking of spend metrics, and tracking of procurement initiative impact at a categorical level. Over a five-week engagement, the team was able to identify immediate contract negotiation opportunities in addition to providing a comprehensive tool to identify and consolidate company-wide procurement opportunities.
Sample procurement dashboard:
Conclusion
The path to spend visibility does not have to be complex. By embracing modern data infrastructure, organizations can turn their fragmented vendor landscape into a strategic advantage. Whether the organization is managing multiple data systems from past acquisitions or simply seeking to optimize their current vendor relationships, the right data strategy can illuminate opportunities that were previously hidden in the shadows of disconnected systems.
Click here to learn more about how MERU can help your organization harness the full potential of your data. Our team of experts is ready to partner with you to design and implement a data strategy that meets your specific needs.
Authored by: Sloan Jinks, Analytics Engineer; Hewitt Cai, Vice President
The authors wish to thank Fréderique Lotin, Sam Stein, Sean Bissell, Vadim Grakhovskiy, and Jacob Gordon for their contributions to this article.