What is Master Data Management? (And Why Is It So Hard for FP&A?)

In my years as a financial analyst, I spent a crazy amount of time battling one surprising source of frustration: master data. Yet, I’ve noticed that master data management often gets overlooked by FP&A tools and planning platforms as though it isn’t a critical part of the job. 

But strategic financial planning requires clean master data. Without a strategy for master data (and the right FP&A tool to help), you’re stuck with extra days of manual, frustrating work tacked onto basic tasks like month-end close and BvA reporting. 

Let’s break down this important, but ignored, aspect of the FP&A workflow. Plus, I’ll share four ways your FP&A platform should help you do MDM better. 

What is master data?

Master data refers to the foundational categories of data that are essential for the operations of an organization. Master data records and categorizes the key entities and attributes that define the business, like products, customers, and suppliers. 

Master data is typically static or slow-changing, compared to transactional data, which records day-to-day operations. That’s because master data represents the accurate, ‘gold standard’ of how your business will refer to certain customers, departments, or products across various IT systems that different departments are using (for example, CRM for the sales department and GL for accounting).

What is master data management, and why is it important?

Businesses operate with so many different systems generating mountains of data. For those systems to integrate and communicate coherently, you need to merge that data intelligently and stay organized. That’s the process of master data management: creating, maintaining, and standardizing a single source of truth to reduce confusion and ensure accuracy. 

Messy master data creates chaos. I’ve seen it happen many times. Unfortunately, financial analysts are often stuck fixing these inconsistencies – because the resulting errors are costly!

For example, if different entries in the GL call the same vendor “Amazon Web Services” and “AWS”, analysts need to find and clean up every instance of that confusion to do their reporting and planning. Then they must remember to streamline different entries for AWS every time, plus stay alert for similar issues. 

What does master data management mean in finance?

CIOs or data analysts may share responsibility for master data, but financial analysts can’t avoid MDM completely. FP&A needs accurate master data to: 

• Create, track, and manage the financial plan.
• Report and analyze budget vs actuals to answer the essential FP&A questions: What happened? How does that compare to what we planned? 
• Produce accurate and standardized reports for budgeting and forecasting across the entire organization, sharing with stakeholders to advise in decision-making. 
• Mitigate risk and stay legally compliant. 
• Improve collaboration and communication between different business units, no matter what systems they work in. 

Effective financial planning and analysis requires good master data management. But, FP&A Trends recently shared that 33% of FP&A professionals struggle with data that has multiple definitions and is difficult to consolidate. I’ve seen this frustration play out in a few specific ways. 

How are FP&A teams doing master data management today? Why is it so frustrating?

Labor Intensive 

In my experience, managing and cleaning up master data is a laborious process of sifting through various spreadsheets, and hunting for inconsistencies with pivot tables and vlookups.

MDM added a lot of extra time to my monthly close and BvA report process. I had to find and fix all the master data errors before I could get to the important part of identifying which deltas were noteworthy. For example, a variance on cloud computing spend meant using valuable time extracting transactions from one system and comparing them to planned expenses – only to discover that it was all down to mismatched vendor names.

Managers weren’t getting their BvA until week 3 of the following month, so they had no chance to react to our findings and course correct their spending or plans. It was a vicious cycle and I couldn’t do the valuable work that I wanted to do! 

Restrictive hierarchy structure

FP&A tools haven’t laid a great foundation for master data. Once data is clean and consistent, analysts often need to re-arrange expense and workforce data into a hierarchy that makes sense for reporting and planning. Data imports from other systems like GL are usually in a different hierarchy. But in many popular FP&A tools, you only get one master data hierarchy. If you integrate new data automatically from other systems, your planning hierarchy will get overwritten!  

Analysts really need the ability to create multiple hierarchies (like one that matches the GL, one for reporting, and one for a reorg scenario) without overwriting master data. 

Solving these problems would significantly improve FP&A efficiency, speed, accuracy, and job satisfaction. 

How to streamline master data management in FP&A

You might assume that any FP&A software would make MDM easy, since it is such a big source of frustration and busy work. Unfortunately, in my experience, that’s not the case. 

Be sure your vendor has these 4 capabilities to handle master data: 

1. Seamless integrations 

Master data integration is a big source of errors. Look for an FP&A tool that ensures flexible and automatic data integrations from your ERP, CRM, HRIS, and more. You need your workforce and expense plans to be completely in sync with your systems of record (SOR) – no hiccups.  

2. Allows multiple data hierarchies

Choose a tool that allows you to reorganize accounts or departments in a different hierarchy than your SOR. For example, analysts using Stratify can move, regroup, and create additional rollups without that data being pushed back into the SOR and compromising their master data. 

3. Data import mapping 

In many popular FP&A platforms, you would have to switch off your master data integration before importing new data. Otherwise, errors would flood in, creating more work. Look for an FP&A tool that can flag the names of new or different master data categories within a new dataset (like a differently spelled vendor or customer name), and allow you to review and approve for accuracy. Stratify will flag those differences rather than blindly creating a new data entry, and remember your master data preferences moving forward. 

4. Tombstoning 

Find an FP&A tool that securely saves a record of your master data version history. Let’s say someone at your organization preemptively deleted a vendor, expecting to switch – but that never panned out. ‘Tombstoning’ prevents that chaos! Your FP&A platform should be able to turn back time and help you restore your master data before that change. You can go back and see the record of changes to pinpoint and prevent errors, so your master data stays ‘clean’ and workable.

Stratify has solved the MDM dilemma 

At Stratify, we’ve invested heavily in master data management to solve this persistent problem. We’ve been obsessive about simplifying MDM, leading the way with innovative features like data import mapping and tombstoning.  

Your business needs a unified and definitive source of truth, and FP&A needs to be freed from the burden of master data management to focus on strategic finance business partnership. With Stratify, those two things are finally possible.