Excel’s powerful capabilities, integrations and flexibility make it a favored tool for all financial and accounting professionals. Like many middle market companies, we considered moving from an Excel dominated financial planning and reporting process to an “enterprise grade” solution. A very difficult decision, we set aside Excel for a unified financial planning tool, also known as Enterprise Planning Management (EPM) systems.

After a review of solutions and recommendations, we decided to move our financial planning to Workday’s Adaptive Planning (WAP). Our financial forecast in Excel is a complete system: It handles recurring revenue waterfalls, consolidations by products and business units, eliminations between business units, balance sheet forecasting, among other complexities. Nevertheless, the transition, despite a good plan on paper, became never ending.

We faced two core problems, which we thought we could overcome. First, the precision and complexity of our Excel forecasting model was hard to replicate in WAP. Second, our lack of deep knowledge in WAP modeling, forced heavy reliance on consultants and a time-consuming iterative process to make any headway. To minimize the obstacles and make some use of WAP, we paused our forecasting transition efforts and focused on WAP as a reporting tool. We had modest success, but we ended up having a hodge-podge system of exceptions and frequent error checking that was worse than the status quo.

During this failed transition period, the analytics team, which is part of our finance team, dramatically increased its expertise and capabilities in PowerBI. (While I am going to focus on PowerBI, I encourage the finance pros reading this to think about this solution using whatever business intelligence platform that is available. This should work with any BI platform.) PowerBI’s integrations with Excel and our accounting system (Microsoft NAV) provided the light-bulb moment for moving forward with an in-house automated financial reporting system connecting our Excel forecasts to accounting results and producing polished reporting in real-time.

In order to get there, we assigned a skilled data analyst to work directly with accounting and FP&A to create an ETL (extract, transform and load) template in PowerBI that could take our GL-coded accounting records and match them to financial reports that were business friendly and consistent with our forecasting templates. Here are the key success criteria that made this possible.

1. Our data analyst had PowerBI, SQL skills needed for the entire buildout.
2. We were lucky that our data analyst also had solid accounting/finance knowledge to work directly with FP&A and accounting teammates. However, this could have been another team member working in tandem.
3. The financial reporting templates were already matched to our excel forecasting outputs. This line-for-line matching eliminated the need for another ETL template, but that could have been created if necessary.
4. Our data analyst spent time mapping GL codes to our financial reporting templates. Without this, the ETL development would have been impossible.
5. In addition, the data analyst methodically mapped our eliminations entries between subsidiaries and hierarchical entities.
6. Then, it was time for record matching so that financial reporting template, forecast and GL Codes could be connected in sample data with a clear line of sight to each other.
7. Finally, the ETL template was ready to be programmed and tested.
8. PowerBI reporting dashboards were then developed and tested with initial data flows. Here the finance team compared PowerBI financial reports to our previous reports. Checking for accuracy at the line-item, subtotal, and total levels. Any errors were traced all the way back to GL-codes to ensure the fixes could be implemented in the ETL template.
9. We then iterated step 8 until multiple periods showed no errors and everything tied out to the most important GL line items such as net income, fixed assets, total revenue, cash balance in every grouping variation we needed (e.g., consolidated, product, business unit, geography, etc.).

The above process took about 120 days to get through Step 8 and then another 60 days (2 reporting cycles) to get through Step 9. All of this was achieved with one resource dedicated to the project and all other FP&A and accounting teammates being on call as needed.

With our financial reporting now published in an automated way, we have dramatically reduced the processing time and eliminated exceptions handling for information flows from accounting to financial reporting. While the EPM also promised financial modeling automations, we never went back to that. Instead, we have improved our Excel-based forecasting models in ways that would be hard to replicate in a new system given the resources we have and the connections of these models to our PowerBI reporting system.

If you are considering an EPM, especially for reporting, it might be worth looking at your existing business intelligence platform for an easier and more manageable solution.

See my post on Lifetime Customer Value here.

FAQs about this Blog Post

1. Why did the company decide to transition from Excel to an Enterprise Planning Management (EPM) system, specifically Workday’s Adaptive Planning (WAP), for financial planning? The company considered transitioning from Excel to an EPM system to enhance its financial planning and reporting processes. Despite Excel’s capabilities, the decision was made to move to an “enterprise-grade” solution for improved precision and efficiency. After reviewing various options, Workday’s Adaptive Planning (WAP) was chosen for its promising features and capabilities.
2. What were the core problems faced during the transition to Workday’s Adaptive Planning (WAP), and how did the company address them? The transition encountered two main challenges: difficulty replicating the precision and complexity of the Excel forecasting model in WAP, and a lack of deep knowledge in WAP modeling leading to heavy reliance on consultants and a time-consuming iterative process. To address these challenges, the company paused the forecasting transition efforts and focused on using WAP as a reporting tool. However, this approach resulted in a hodge-podge system of exceptions and frequent error checking.
3. How did the company leverage PowerBI to create an in-house automated financial reporting system, and what were the key success criteria for its implementation? The company assigned a skilled data analyst to work directly with accounting and FP&A to create an ETL (extract, transform, and load) template in PowerBI. Key success criteria included the analyst’s PowerBI and SQL skills, solid accounting/finance knowledge, mapping of GL codes to financial reporting templates, mapping of elimination entries, and record matching to connect financial reporting templates, forecasts, and GL codes. The process involved programming and testing the ETL template, developing PowerBI reporting dashboards, and iterating until accuracy was achieved. This approach significantly reduced processing time and eliminated exceptions handling, resulting in a more efficient financial reporting process.

With a focus on strategic financial leadership, my role as a CFO has been pivotal in guiding companies through periods of growth and transformation. My proficiency in analytics and data science empowers me to drive informed decision-making and optimize financial performance. Let’s connect on LinkedIn to discuss how my Fractional CFO expertise can contribute to your company’s success with CFO PRO+Analytics.