By Russ Haskin, Senior Director, Business Consulting, Wilson Allen
Who are your clients? What are your practice groups? Who are the responsible attorneys for a client? What dates did you open or close a matter? In what industry is a client?
These are all common questions regularly asked at law firms around the world. With each inquiry, you would expect each area of operation within the firm to provide a consistent answer. However, if a lawyer asks these questions to finance, marketing, intake, or other operations, very often, the answers are not the same. This inconsistency creates discrepancies in reporting, inaccurate and imbalanced data and frustration for data consumers. More importantly, when data should be leading the way on strategic decisions, these inaccuracies can lead firms down the wrong path.
Trending towards transformation
Over the last five to six years, law firms have been embarking on technology transformation to improve operational processes. A common area of oversight or lack of understanding is how best to approach master data management. This truth is evident in the opening of this blog post. Ask a simple question: “what are your practice groups” and the answer can vary widely. HR’s list of practice groups could differ from the list marketing provides, which also varies from the list finance gives.
Why such disparity? The answers to that question could also vary greatly, but here are a few likely scenarios:
- Changes in source systems do not make it to other downstream systems
- An initiative in one operation altered the list but did not trickle to other operations
- A merger took place, and the information brought over from the merged firm did not assemble appropriately across the organization
- The firm engaged in a technology switch with different data structuring
Whatever the reason, master data management is an area every firm should be exploring, especially if you’re making changes to core software applications.
But what is master data management?
Even the definition of master data management varies from firm to firm. In conversations with several law firms, some technical staff clearly state that master data management is the creation of a warehouse that stores key data. Those folks are only partially correct. When you bring up concepts like “taxonomy” or “data governance,” many quickly brush them aside.
In its simplest form, master data management is the maintenance and governance of a firm’s data assets to assure uniform and accurate information. It also provides accountability for that data to specific functions and individuals. In other words, it is a combination of people, processes, and technology to manage data accumulation and accuracy.
Over the next few blogs, we will explore facets of master data management (golden source systems, core data elements, taxonomy, governance, and more). But before diving in, every firm should perform a bit of self-diagnosis to see where they sit with master data management strategy. Here are a few questions to get this process started:
- Is there a master data dictionary (MDD) that feeds data from core systems to all other systems across all operations?
- Has the firm identified the source system of truth for core attributes?
- If the firm does have an MDD, who is maintaining it? Are there workflows in place to assure data accuracy?
- Has the firm defined its core fields and attributes for reporting?
- Does the firm have data governance specialists for firmwide data as well as operational data?
- Are there normalized and standardized approaches for entering data (i.e., do you enter all names Smith, John A. instead of John A. Smith, or do you use the same format for all addresses)?
- Does the firm report on and flag inaccuracies on data as it transfers from one system to the next (i.e., Intake to a PMS or CRM)?
- And the simplest question of all: Is it clear where data comes from and who manages it?
These questions scratch the surface – but are an excellent place to begin. Then if you’re not satisfied with your firm’s answers, it’s time to focus on master data management.
In the next blog for this series, we will focus on core attributes and the establishment of source vs. downstream systems.