Law Firm BD Intel Part 1: Challenges

 Law Firm BD Intel Part 1: Challenges

Law Firm BD Intel Part 1: Challenges

This series of blog posts describes challenges law firms face with regards to researching new opportunities and target clients. We outline an approach that improves the Business Development (BD) opportunity intelligence process and fuels revenue generation. This approach combines Mind-Alliance consulting and the MindPeer Strategic Intelligence Management System.  

This first post in the series focuses on the key challenges.

Law firms face a few common, fundamental challenges when it comes to Business Development (BD) research to gain intelligence about opportunities and target clients.

1. NO STRATEGIC VIEW OF BD RESEARCH

BD directors often cannot systematically determine, based on data, whether the firm is adequately supporting BD pursuits with the required research services. At a strategic management level, they have not assessed the maturity of their BD research capabilities –  people, process, technology, data, and governance.

Moreover, they don’t know whether they have enough research analysts around the clock to support a growing volume of BD research support requests.

Without dashboards and reports that show a bird’s eye view of BD research activities, and the dossier of reports associated with each prospect, law firms cannot easily leverage all of their data resources and align different parts of the firm around the pursuit.

[Find out more about how to evaluate a firm’s BD intelligence capabilities.]

2. KNOWING WHAT QUESTIONS TO ASK, AND WHEN

Often, lawyers don’t consistently ask for the research support that could help them maximize their success at critical phases in the business development process. Some submit ambiguous requests for information about people, industries, and companies, only clarifying what they need via back-and-forth email exchanges, which wastes time.  If everyone involved in BD processes knew what to ask for, whom to ask, and when to ask, before meetings, events, and pitches, then the research process could be more effectively planned and resources could be lined up to fit the expected workload.

3. OVERWHELMED RESEARCH TEAMS BECOME OVERLY REACTIVE

Many law firms do not have enough research analysts in-house to satisfy the growing volume of BD research requests that arrive around the clock. When understaffed research teams are overwhelmed by requests, they often become excessively reactive. They respond to requests rather than anticipate and align resources with the research support needs at each phase of the BD process for each pursuit.

With advanced analytics technology, law firms can build a typology of common research requests and map them to phases in the BD process.  Law firms can identify internal and external news events that trigger BD opportunities and associated research requests. For example, sharp stock price drops and insider trades could indicate future securities fraud litigation. Research departments can set up monitoring and analysis of these indicators and proactively offer to initiate research.

4. DATA ABOUT OPPORTUNITIES IS FRAGMENTED

Data relevant to BD is trapped inside email messages and disparate IT systems, including CRM, Finance, Experience, and premium databases managed by the library.   This makes it difficult to rise above the silos and think about BD opportunities in a comprehensive way.

Intranets and Customer Relationship Management (CRM) software systems don’t adequately facilitate BD research workflow.   They also do not automatically connect people to relevant research questions, analytical templates, data resources, or experts.

Also, typically, only library and research analysts use ticketing systems to manage incoming research requests. Attorneys and various staff departments involved in BD and marketing also do BD-related research themselves and communicate about it via email.  Consequently, inefficient data flows and poor collaboration hampers the ability to spot new business opportunities quickly. Without a dossier bringing together all the resources and relevant communications, it is easy to end up with gaps in research or duplicative efforts.

5. INSUFFICIENT USE OF AUTOMATION

Producing BD research products such as basic company profiles, business background reports, and tear sheets often involves a lot of manual searching, copying, and pasting.  This manual labor could be eliminated or reduced with automation. Also, research analysts typically need to manually specify keywords in current awareness monitoring systems and read thousands of alert emails each week. When they see alert emails with a potential opportunity they copy information into new emails, add data from premium subscription resources and then send them to partners to notify them about opportunities.  Some of this work can also be automated or outsourced to increase speed and reduce cost. Large law firms subscribe to dozens of data resources, but these resources are siloed and cannot be searched via one interface. They do not share a standard data or metadata model. If law firms had a semantic model of the data needed in BD research (ideally expressed in an ontology), they could automatically trigger suggested research in context while people worked.

The next post in this series will examine a better approach, considering problem diagnosis, hi-level prescriptions for ideal processes, and training for staff required to enable these processes.

David Kamien

Mind-Alliance Systems, LLC helps law firms and legal departments enhance their business development research, knowledge management, and data management capabilities. We provide strategic management consulting services, deliver training, and develop user-friendly software solutions. Using proprietary methodologies, technologies, and analytical frameworks, our consultants diagnose issues and prioritize critical improvements. To design successful solutions, we consider strategy, business processes, human capabilities, and system design. Mind-Alliance finds practical ways to integrate intelligence into decision-making, streamline knowledge-intensive processes, and build more effective collaboration.

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