Wilson Allen: The data science of relationships
Every significant economic event, from the global banking crisis to the present impact of the pandemic, prompts questions about the best approaches to winning new business and measuring the ROI of those approaches.
In the past, law firms have tended to focus on systems that affect existing client management, specifically client onboarding, conflicts and time and billing. Applications and information used to support business development and marketing have not received the same level of attention. But the trend is changing.
New definitions of client engagement
Law firms now have an unparalleled opportunity to redefine how they measure client engagement and how they use data to make strategic decisions. Artificial intelligence, machine learning, and other technologies are now available to law firms to study data that was once disconnected and to convert it into meaningful insights, accessible across the firm. But siloed and unstructured data, built on rigid architecture models, pose challenges to this evolution. That’s because analyzing data from only one silo doesn’t provide a true picture. For example, if you only look at financial metrics, you might see all clients for which you are achieving the same margin as equal. But if you consider the cost of winning that work, and the feedback the client gave when you closed the matter, you might get a vastly different picture.
Combining data from multiple sources can help firms to identify the most promising business opportunities. Best practice in the past was to push all data to track client engagement to the CRM system. By combining data science with master-data strategies, that is no longer necessary. You can build a Power BI dashboard using Excel without having to create a massive data warehouse before you can deliver a meaningful output.
Cross-organization collaboration
As the heads of the business operations departments collaborate to align their plans, there’s more of a process-focused approach to system implementation and information management. Rather than implementing systems to achieve specific business functions, firms are looking at business processes holistically and the data needed to support them. More importantly, they are looking at data from different engagement touchpoints across the client journey to measure the impacts of client engagement.
By taking this approach, firms are identifying weak links in the chain when it comes to data capture. This clarity is enabling them to rethink integration strategies based on how data moves, who needs it and when, rather than which systems need to connect.
Focusing the effort
Sorting out ‘the pipework’ is only one step in getting the information flowing. Ultimately it would be best if firms focused on the questions to answer. When asked what partners want the most, it usually boils down to a relatively short list of needs, including:
- Protect and maintain existing client relationships
- Cross-sell and grow clients with development potential
- Secure new business
- Manage the wider relationship network (for example referrers)
- Manage the internal relationship network (who is the best person to speak to?)
- Connect the experience the firm has to the needs of their clients.
Reports generated in most firms tend to be data dumps, not actionable insights. There’s also a tendency to focus on quantity of data, not the quality. It is far more important to ensure you can deliver consistent, accurate, actionable and real-time data to produce reliable, insightful analysis.
Marketing and business development should be seen as a science, not an art. While there is always a need for artistic flair in anything with a human dimension, it’s essential to place client metrics at the heart of your strategy. Everything the firm does in terms of client engagement must be measured, and must ultimately be able to be brought together.
For example, firms should be looking at these metrics as indicators of the impact of their client engagement efforts:
- Client revenue total – How much is the client worth?
- Client revenue trajectory – Is the revenue declining, growing or flat?
- Practice penetration – How many practices are working with the client?
- Level and volume of engagement – How many relationships do you have and at what level?
- Client feedback – how do they rate you in terms of service, quality of work, value for money? Include Net Promoter Score as a metric here if you capture it.
A decline in a client’s engagement, for example, is a predictor of a decline in revenue and satisfaction. This outcome is expected. However, the point of introducing data science is to prove empirically that which you already believe to be true instinctively. The result is greater value placed by stakeholders on the systems and support that marketing and BD provides, and more importantly more focus on the behaviors that drive client satisfaction and engagement.
This article was taken from Briefing February 2020: Hybrid powers. Read the full magazine here.
