Good data is at the heart of the DMAIC process. This phase is devoted to collecting
current baseline metrics as the starting point for process improvement. For law
departments, these could include cycle times, cost, steps in a process, touch points,
and so on. Baseline metrics from this phase will be compared to the performance
metric at the conclusion of the project to determine objectively whether significant
improvement has been made.
A NOTE ON DATA
Relying on data-driven insights rather than intuition or “gut feelings,” process
improvement enables businesses to provide a high-quality product or service,
produced at peak efficiency, with a high level of consistency and predictability.
Because data and statistical analysis are newer to legal practice, legal teams
generally lack maturity in their management and consumption of data relative to
their peers in industrial manufacturing, retail sales, management consulting, or
While legal matters provide significant potential for data analysis, most law
departments and law firms are not necessarily set up to effectively capture
and manage this data. Oftentimes, the integrity of the data collected is not
necessarily very strong, because sample sizes are simply not large enough
from which to draw valid, statistically supported conclusions. That said,
process improvement can underscore the critical need to begin and continue
building data competencies and infrastructure. Any serious process
improvement effort should include mid-to long-term goals to move toward
In the interim, legal teams should rely heavily on qualitative fact-finding methods
and client-facing dialogue to help validate their analysis and findings, and put
forth a concerted effort to inject quantitative approaches wherever possible.
Proper data collection provides valid and useful grist for analysis of the sources of
variation and waste, the ability to quantify their magnitude, and later in the process,
the ability to prove and monitor their elimination and reduction. Without reliable data,
decisions can be made simply based on hunches and personal beliefs, with no way to
provide significant improvements –– all of which means data is fundamental to Lean.