The Problem
A Mountain of Data You Can't Use
Every legal matter generates a detailed narrative record. Time entries describe tasks performed. Billing records capture hours and fees. Documents tell the story of how deals closed or cases were resolved. Over years of practice, a law firm accumulates millions of these data points — a comprehensive record of its collective expertise.
Yet for most firms, this data remains effectively inaccessible.
Time entries sit in billing systems as unstructured text. Matter outcomes live in closing memos or partner memories. Experience lists are maintained in spreadsheets by individual practice groups, often incomplete and outdated. When a partner needs to find similar matters for a new pitch, they rely on personal recollection or ad-hoc searches through old files.
The result: firms know less about their own work than they should.
The Real Cost of Unstructured Data
RFP Response: 20+ Hours of Scavenger Hunts
The 2024 LMA/ikaun RFP Impact Report reveals the scale of the problem:
54% of RFP responses take more than 20 hours to prepare (see LexisNexis survey)
42% of that time is spent simply finding past work and relevant experience
31% more is spent reading past RFPs to find reusable content
Only a fraction goes to actually tailoring the response to the client
For a firm responding to 100 RFPs per year, that's roughly 2,000 hours of non-chargeable time — worth approximately $1.2m in staff costs — spent on manual data gathering.
Win Rates: All That Effort, Low Success
Despite this investment, the average law firm RFP win rate is just 18%.
The problem isn't effort — it's effectiveness. Proposal teams spend their time on low-level tasks (searching archives, formatting data) instead of high-value activities (tailoring solutions, demonstrating client understanding). Without structured data, even the most experienced BD professionals struggle to quickly surface the firm's most relevant credentials.
Pricing: Guesswork Over Data
Pricing directors face a similar challenge. When scoping a new matter, they need to answer:
What did similar matters cost in the past?
How did hours break down by phase?
What drove overruns or write-offs?
What's a realistic timeline?
Is this deal worth pitching for in the first place?
Without organized historical data, these questions go unanswered — or get answered by gut feel. As one legal pricing expert noted, many firms have "yet to capture and quantify" how past matter data can inform pricing decisions.
The consequences:
Underpricing leads to budget overruns and write-offs
Overpricing loses competitive bids
Inconsistent pricing erodes client trust
The Hidden Opportunity Cost
Beyond direct costs, there's an opportunity cost that's harder to measure:
Missed connections: A partner doesn't realize a colleague handled a similar matter last year
Lost institutional knowledge: When lawyers leave, their experience leaves with them
Slow response times: While your team searches for data, competitors submit first
Weak credentials: Proposals cite generic experience instead of specific, relevant examples
In a market where 50% of clients adjusted their law firm rosters in the past year, firms that can't quickly demonstrate relevant expertise are at a serious disadvantage.
Why Traditional Approaches Fail
The Spreadsheet Problem
Many firms track experience in Excel spreadsheets maintained by practice groups or BD staff. These lists are:
Incomplete: Relies on lawyers remembering to report matters
Inconsistent: Different formats, fields, and levels of detail across groups
Outdated: Updated sporadically, if at all
Siloed: Each group maintains its own list, with no firm-wide view
As one industry analysis noted, a firm's expertise is often "locked inside siloed systems or trapped in a chain of manual processes."
The Data Quality Problem
Even when firms try to use billing system data, they encounter quality issues:
Vague narratives: "Research," "Drafting," "Attention to matter" — entries that describe nothing
Inconsistent coding: The same task coded differently by different timekeepers
Wrong phase codes: Work attributed to the wrong stage of a matter
Missing context: Entries that make sense only to the person who wrote them
These issues compound over time. Without cleaning and normalization, raw time entry data is often too messy to analyze reliably.
The Integration Problem
Matter data lives in multiple systems:
Practice Management System (PMS): Time entries, billing, rates
Document Management System (DMS): Engagement letters, closing memos, key documents
Data Lake/Warehouse: Aggregated exports, financial summaries
CRM: Client relationships, BD activities
Spreadsheets: Ad-hoc experience tracking
No single system has the complete picture. Pulling together a comprehensive view of a matter requires manual effort across multiple platforms.
The Market is Moving
Clients aren't waiting for firms to figure this out.
Recent surveys show that corporate clients are asking firms in RFPs how they leverage AI to reduce costs and improve service. They increasingly expect data-driven pricing, transparent scoping, and demonstrated relevant experience — not generic pitches and hourly rate cards.
Firms that can't meet these expectations will lose work to those that can.
The Opportunity
The data exists. Every time entry, every closed matter, every billing record contains information that could inform better pricing, faster proposals, and smarter matter management.
What's missing is the ability to:
Structure unstructured narrative data at scale
Normalize inconsistent coding and terminology
Enrich sparse entries with contextual understanding
Connect data across systems into unified matter profiles
Search and compare matters by relevant attributes
This is what Narrative was built to do.
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