Data governance best practices for professional and financial services firms

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At any professional and financial services firm, data is one of the most valuable organizational assets. It should always be treated accordingly, with sound, formal data management strategies and practices. However, many firms lack these critical protocols, and continually struggle to solve their data problems — then regularly pay the consequences in the form of wasted resources, dissatisfied clients, and lost or untapped revenue.

Through the course of everyday work, missing, inaccurate, and miscategorized data surfaces when firm professionals create reports, raise invoices, and conduct risk checks. Bad data going in means a bad analysis or report coming out — so when firms bill their clients or run their checks, they’re unable to get it right the first time. Subsequently, they lose valuable staff hours — and, more importantly, client trust and goodwill — when faced with addressing avoidable errors.

The outputs from good data practices, on the other hand, enable accurate and meaningful reporting for your professionals and partners. Using clean, relevant data, they can understand strengths, identify and share business development opportunities, deliver a better client experience, increase revenue and returns, and better manage risk and compliance.

It’s possible to solve your data problems and harness the power of good data with the help of a sound data program. As Head of Risk Solution and Project Strategy at Intapp, I’m experienced in helping clients establish these programs. While I acknowledge that it does take time to do it right, it’s well worth the effort — and once the fundamentals and discipline are in place, data gets much easier to manage.

So what are data governance fundamentals, and how should firms begin? In this post, I’ll share some best practices and considerations for implementing a data governance program at your firm.

The essentials of data governance

Data governance refers to the processes and systems a firm or organization uses to manage its data, and a data governance framework is the model for managing that data. Your framework should establish guidelines and boundaries around data gathering, creation, and modification. These should be clearly documented, defining relevant principles, processes, roles, responsibilities, and tools. They may also include data privacy considerations, and document practices and processes for the secure collection, storage, sharing, and deletion of data gathered during the course of firm operations.

1. Build a business case to get executive buy-in

Many leaders already know that poor data quality and management are problems for their teams. To convince them to commit to driving change, it’s important to effectively convey the benefits — as well as the cost of doing nothing.

To secure buy-in and sponsorship from leaders who will be involved in the process, build a strong business case by clarifying the benefits and opportunities of improved data quality for your firm. Share how a sound governance strategy can create a better customer experience, greater efficiency, more accurate resource allocation, more effective targeting, and increased revenue. Set the vision and prepare everyone involved for the sustained effort required to reap the eventual rewards, such as less back and forth between teams and with clients, less time wasted, and more accurate results.

While you’re at it, be sure to measure your baseline data before, during, and following your data clean-up initiative so you can track progress at key checkpoints and highlight the quantifiable improvements later.

2. Map your firm’s data processes

I like to begin a data governance initiative by mapping a firm’s existing processes. Through process mapping, we can confirm whether the correct and necessary data points required are being collected, identify where the pain points are, and determine whether a client has the right teams and expertise in place to perform the right tasks.

This step is so important because all too often, data inaccuracies are not caught or corrected early enough in a firm’s processes — so erroneous data continues to flow downstream through multiple teams and systems until it’s eventually caught at the point of output, when correction is forced. To truly solve this problem, the mapping process requires input from a variety of stakeholders across teams involved in the collecting, sharing, or processing of data in order to produce some form of output for the client and firm, such as a service, risk check, or bill.

Process mapping allows teams to gain visibility into the process stages involved, take a more holistic approach to how they work, and streamline their practices. At an individual level, team members also gain a better understanding of how their work and contributions support the data governance program and strategy. Then, teams can start addressing more in-depth issues, such as “Who should be responsible for what along this data lifecycle?” and “What data is each individual responsible for providing?” — essentially focusing on getting the right data provided by the right people at the right time.

Consider client onboarding as an example of potential cross-team process collaboration. All team groups involved in the data process — from your front-office client-facing teams to your middle- and back-office teams, such as risk, finance, and billing — need to take accountability for checking and correcting data at the earliest opportunity and collaboratively working together.

3. Clarify roles and responsibilities

Ultimately, data governance is about processes, technology — and people. Good governance requires collaboration, with participation from all your departments and teams.

Clearly defined roles are critical to every governance program, and it’s important to determine levels of ownership across your firm. By gaining sponsorship and assigning authority and responsibility, you can create an effective structure for implementing data programs as a unified team.

A successful governance program also provides a clear view of data sources and data ownership, and includes documented processes for data usage and modification. So, when beginning a governance initiative, it’s critical to look at all the data points coming into your firm, how they’re being managed, and what gaps exist when onboarding that data. That’s why governance and management go hand in hand: So much of good governance comes down to establishing policies and practices for every team and individual involved in gathering, changing, or otherwise managing data.

4. Assemble an operational leadership team and consult experts

There are so many data touch points within an organization that if you have solely one team or one person leading your data governance effort, it is likely to fail. Instead, it’s ideal, if not essential, to create an operational task force for your data governance program, with leaders, team members, and other experts drawn from across your firm.

Allocating a team of this nature to engage in the program allows the group to understand the broad variety of work tasks performed and the entirety of services offered to clients. This supports a more client-centric, end-to-end approach, and enables a deeper understanding of how other teams contribute needed data, and how that data is sourced and used across the firm. Again, consider client onboarding as an example. Data and reporting gathered during the client onboarding process can help educate and support the business development team, informing their processes regarding current client-service offerings and opportunities for expansion or new service lines.

In this way, a cross-section of leaders and representation from multiple teams can ensure a less fragmented approach to collecting, sharing, and managing the important data required to successfully service your clients and produce the outputs needed to efficiently progress through your process steps.

An additional benefit of firmwide leadership representation: This group can champion and support the data governance program and its management, and ensure that every team understands the importance of having good data — both for their team’s own efforts and for the firm as whole.

In addition to operational considerations, it is vital to consult with your Chief Information Officer, general counsel’s office, and/or a data privacy expert to ensure that you’re following best practices and applying policies and controls around data gathering and maintenance, including data privacy, storage, preventative leakage measures, retention, and destruction. Proactively including these considerations in your data governance program implementation helps to set standards within your firm and mitigate a host of associated risks.

5. Leverage industry-specific technology with robust data capabilities

In addition to considering who should sponsor and be involved in a data governance initiative, it can be beneficial to consider software solutions needed, and how firm professionals can and should leverage upgraded technology for more consistent, accurate data gathering and use. Significant volumes of data are exchanged with and within an organization, so considering the means by which this data is shared is important.

Consider using a workflow tool, increased automation, and integrations to support consistency and accuracy across systems. Validate data using third-party data checks, monitoring, and alerting to help govern the integrity of your data on an ongoing basis. This ensures that you can rely on your data being current, which is particularly important for existing client records.

6. Manage change through two-way communication

The truth is, change management is always challenging. Although change is inevitable, it can feel very personal, and we all respond to it in different ways.

To address that reality, it’s important to talk to people across your firm to learn about their needs, concerns, challenges, and suggestions. You should also explain to these stakeholders what the firm is looking to achieve, its plans to accomplish those goals, and how each individual’s role contributes to that strategy. You might not always like what you hear — and your stakeholders might not either — however, by giving them a voice, learning about their challenges, and building this network, you can help people across your organization see the big picture, and you can better develop a stronger narrative in support of change.

Then, keep communicating regularly with your stakeholders, making sure your updates are easy to access and understand. Consistent, thoughtful communication is essential to sharing your program’s successes, demonstrating its effectiveness — and, when necessary, transparently acknowledging setbacks or areas that can be improved.

Remember that data governance is a firmwide discipline

For a data governance program to succeed, it is beneficial to treat it like a strategic project. It requires senior-level sponsorship and buy-in from firm leadership, and needs to be a shared responsibility by individuals across the firm — with many different teams involved and educated about its importance and necessity.

At its core, good data governance is a discipline — and it’s everyone’s job.

Read part 3 of the series, “Breaking down data silos: 5 key benefits for professional and financial services firms.”