Beyond ERP: How to leverage your investments in ERP to drive value and enable powerful financial insights

One question we often hear is that despite heavily investing in Enterprise Resource Planning (ERP) systems, we still struggle to get basic financial insights.
ERPs such as SAP, Infor, Oracle, MS Dynamics have long been the backbone of enterprise operations (e.g. finance, procurement, sales). These systems are designed to transact more efficiently, integrate business processes and offer a unified solution for enterprise operations.
However, when it comes to extracting actionable financial insights from these ERPs, organizations encounter significant challenges.
This blog delves into why operations teams struggle to provide on-demand insights beyond transactional finance and how enterprises can better approach this critical task.

ERPs are mandatory and drive systemic benefits

Over the past 30+ years ERPs have delivered on the commitments – integrated transaction processing, automation and standardization of business process. When the whole enterprise works on a single-instance, operational information is captured and cross referenced within the stack. They provide:

1. Single Source of Truth: Data is consolidated from various business functions into a single repository, ensuring consistency and accuracy.
2. Real-Time Data: Once transacted, ERPs provide real-time data capture capability, which is be crucial for operations.
3. Integrated Processes: By virtue of process chaining, and their impact on financial performance.

ERPs have reduced financial errors, improved efficiency exponentially, limited fraudulent transactions and improved operations and financial accounting substantially.

Then WHY do we struggle with basic finance reporting needs

ERPs are transaction capture engines that have been layered with functional intelligence. The need for reliability (ACID in database terms – Atomicity, Consistency, Isolation and Durability) resulted in the underlying technology structured being engineered for speed of transacting and capture of information. The underlying architecture is based on OLTP framework to protect against duplications, data loss and completeness of transactions. This resulted in:

1. Complexity and Rigidity: ERPs are by design complex as they need to cater to a wide range of business processes. This results in rigid data structures that are not easily customizable. Extracting data is a daunting time-consuming task, requiring specialized knowledge and significant resources – creating huge load on IT and business teams.
2. Data Isolation: To ensure speed of transaction capture and processing, ERPs create data towers within different modules (e.g. finance, procurement, sales). The data for each function and sub function is stored in different tables. For instance, correlating procurement data with sales performance and financial outcomes requires extensive data joining and reconciliation efforts.
3. Limited Analytical Capabilities: ERPs solve for transaction processing and excel at providing operational reporting. E.g. What is my payable to a particular supplier or what is the total volume of sales of a product. However, if you want to know the impact of payment term change on the cash flow, the ERP systems stumble, they are not geared to handle the simulation or the analytics. That is one reason why ERP products often bundle data warehouses with their core systems, at additional costs.
4. User Experience: Enterprise software are meant for heavy lifting. They often lack lack decent data visualization options, such as interactive dashboards or user-friendly graphs, And this makes it harder to interpret the data quickly and accurately. Basic needs like anomaly detection or simulation are challenged due to the architecture. ERP provided reports make it difficult to identify root causes or underlying trends and for most part need programming skills to build or modify.
5. Mergers & Acquisitions, Amplifying the complexity with multiple ERPs: Till now we were discussing single instance of one ERP.  M&A brings its own set of alignment challenges and opportunities – and over 80% of M&A fail because of the inability to integrate effectively. Not only do multiple processes add roadblocks to effective operations, but inheriting ERPs and other enterprise applications, create substantial disruptions to processing financial data as well as reporting on these – let aside analysis for synergy benefits.

• Combining disparate ERP systems, each with its unique configurations, data standards, and processes severely impacts the accuracy and timeliness of financial reports.
• Rapid integration efforts and migrating to one system often results in sacrifice of invaluable past and historical data.
• The challenge is further compounded by the varying compliance requirements and financial regulations applicable to the industry and regions operating in – results in penalties and audits

Inference

ERPs are delivering on what they are meant to do – operational transaction capture. Over the past few decades, the accuracy of transaction recording, the efficiency of operational functions and the extent of automation have all undergone manifold improvement. However, these foundational technologies have also surfaced the potential of using this information for the next level of operational decision-making. And ERPs were not designed to do that.

The Impact – Finance and Ops teams’ functions are still manual and error-prone

Finance & Accounting:

• Baseline Expectation: Cash Flow Forecasting.
• Underlying Data Elements: Accounts receivable, Accounts payable, Inventory, Bank transactions, borrowings and leverage and historical cash flow data.
• The Gap: Cash flow is a factor of working capital, fund leverage and margin realization. None of these are effectively supported with due dates and forecasting drivers in ERP systems. Compound this with feeder applications for collections and procurement, the accuracy levels go down substantially. All major ERPs claim to solve this (e.g. SAP SAC, Workday Prism, Oracle OAC) but their capability is very constrained, and this doesn’t even consider the complexity of multiple ERPs or feeder systems.

Procurement:

• Baseline Expectation: Supplier Performance Analysis.
• Underlying Data Elements: Contracts, Purchase orders, Incoterms, delivery dates, quality, and cost metrics.
• The Gap: ERP systems have the contracts, the purchase and delivery records and invoices. However, there is no repository or ability to use external industry price data, benchmarks and time series analysis. The depth of analysis required informed sourcing decisions, goes beyond the scope of basic ERP operational reporting and results in being done manually, if at all.

Sales Operations:

• Baseline Expectation: Sales Forecasting and Pipeline Analysis.
• Underlying Data Elements: Historical sales data, customer interactions, lead conversion rates, and market trends.
• The Gap: ERPs capture only the transaction details. Leads and pipeline data are in CRM, Inventory and Production capacity constraints are in SCM systems and market and environmental information is external feeds. An ERP report might summarize past sales performance and current order status, but insights required to predict future sales trends, identify potential high-value opportunities, and suggest optimal sales strategies are completely missing in ERPs.

How have leading companies addressed this ask?

The larger enterprises have converted their disadvantage of multiple ERP systems, varying processes and federated business models to their advantage by supplementing their ERP with ancillary enablers. The strategy that has worked for them is:

1. Adopt Cloud: Many enterprises have leveraged the accelerated enablement of cloud to gather the data both from their multiple ERP and non ERP systems, giving them the ability to leverage the flexibility of modelling and using their data to drive both insights and microservices applications. Amazon Web Services, Google Cloud, and Microsoft Azure are all highly resilient and scalable platforms at a fraction of the cost of legacy data servers.
2. Invest in Data Integration and Analytics Platforms: Leverage specialized data integration and analytics platforms that can seamlessly extract, transform, and load (ETL) data from ERPs into a more flexible environment. Tools like data lakes, data warehouses, and advanced BI (Business Intelligence) platforms can offer the necessary analytical capabilities that ERPs lack. Snowflake, Databricks, Apache Iceberg, DBT labs, and a series of subscription and free software are available to make this real.
3. Empower Business Users: Provide business users with intuitive self-service analytics tools that allow them to explore data, create reports, and generate insights without relying heavily on IT support. Training and empowering business users can significantly enhance their ability to derive meaningful insights. Microsoft PowerBI, Tableau, Domo, Looker, etc are excellent user enablement and citizen analytics toolsets
4. Adopt a Bi-modal Approach: Consider a two-pronged approach where ERPs handle transactional processing and operational reporting, while specialized analytics platforms are used for deep dives and advanced insights. This allows organizations to leverage the strengths of both systems.
   

Conclusion

The inherent complexity, data silos, limited analytical capabilities, and user experience challenges make it difficult for business teams to directly extract actionable insights from ERP systems. While ERPs like SAP and Oracle play a crucial role in managing enterprise operations and have leading analytics platforms (such as OAC, Prism, SAC), they are not effective to become as the best tools for providing financial and operational insights due to their being architected for the parent ERP. By investing in complementary data integration and analytics platforms, adopting cloud, empowering business users, and adopting a bi-modal approach, enterprises can overcome these challenges and unlock the full potential of their data.
In the rapidly evolving business landscape, the ability to derive timely and accurate financial insights is a competitive advantage. In the next set of blogs, we will examine on HOW to simplify data and empower the financial and operations teams to drive competitive advantage for the enterprise.

We at Midoffice Data work with enterprises to help them navigate the complexities of ERP systems by harnessing their data to achieve strategic objectives. By leveraging a data led approach that aligns to using the appropriate technology additions, organizations can turn their ERP data into a powerful asset for operational and financial insight and to drive enduring benefits.