The Trouble with Unrefined Lateral Moves Data

Rooting your decision-making strategy in data is always a wise decision. But considering the source of the data before taking action is imperative. The data-driven decisions your law firm makes are only as good as the quality of that data: Do you know how well is it collected, corrected, and categorized?

Using raw or unrefined lateral moves data can give law firms a false sense of security about the reasoning behind crucial strategic decisions. While under the impression that their choices are supported by actual and accurate data, law firms that use raw numbers are often making ill-informed and misguided decisions that waste resources and don’t deliver an acceptable return on investment.

At Decipher Investigative Intelligence, we are championing an innovative approach for how lateral moves are measured, evaluated, and ultimately used in the decision-making process. In this article, we will explain the trouble with unrefined lateral moves data, how we fixed the problems, and why our standardized methodologies create data that help firms make better decisions.

What’s Wrong with Unrefined Lateral Moves Data

There are five primary reasons why raw lateral moves data presents a real danger for law firms:

  1. Different lateral move definitions: Sometimes lateral moves are counted with a broad definition, and include attorneys who depart a firm without having a specific job lined up. This leads to duplicate records and inflated aggregate numbers when the lateral is recorded as a hire at a later date. On the other extreme, by using a closed definition, “lateral moves” only count if both a departure and the new landing spot are identified, which leads to a significant undercounting. Furthermore, some sources even count partner promotions and first-year associates as lateral moves.
  2. Unstandardized data: Attorney titles, practice areas, legal specialties and industry definitions can vary widely. AmLaw 100 law firms list, on average, more than 55 different practice areas on their websites, often leading to contradictory categorization. One firm’s “private equity” partner is another firm’s “banking & finance” attorney, and would be categorized as a member of a third firm’s “corporate” practice. Without clear definitions and practice standardization, meaningful analysis is nearly impossible.
  3. Inaccurate data: Decipher analyzed raw moves data and found that between 9 and 20 percent of these records were inaccurate. Among the common inaccuracies were first and middle name variations (Jim leaves one firm and is announced as James at another), errors in data entry, incorrect practice areas, duplicate records, and false positives (sometimes automated solutions scan law firm websites or LinkedIn for updates, causing a record to be counted when the individual hasn’t moved jobs at all).
  4. Inconsistent data: One critical component of a lateral moves record is what date a hire or a departure occurs. Analysis based on this data can change drastically based on when a lateral move was recorded. Short-term data highlights more immediate dynamics and can identify real-time market shifts, while longer-term moves data reveals broader trends or the cumulative impact of sustained events.
  5. Incomplete data: Up to 45 percent of moves records fail to provide a lateral’s law school graduation year—a key data point when determining trends in the experience level of market movers. Other frequently missing data: profile links, career history details, specific legal specialties, and industry focus. The latter two are critical pieces of information for firms attempting to assess market trends in particular practices.

How Decipher is Revolutionizing Lateral Moves Data

We addressed the shortcomings of raw moves data in several key areas, starting with the creation of a fixed definition of a “lateral move” that avoids duplicate entries. We also analyzed over 300 law firms and standardized the legal profession’s inconsistent terminology into core practice areas, industries, unique practice terms, and legal specialties.

In addition to presenting law firms with standardized and accurate data, Decipher goes beyond the core moves data by creating models that can identify successful lateral candidates using a complex network of different data sets. We augment the data with meaningful context from both proprietary and open sources, including firm, practice, and location data; rate/hours standards; book of business benchmarking; compensation ranges; and career/moves history.

Decipher’s proprietary metrics give firms the power to benchmark themselves against their peers in real-time or historically. These metrics can be calibrated and adjusted to provide valuable insights for attorney title, location, office, practice area, firm type (size/rank), and more.

Law Firms Can Use Decipher’s Metrics to Boost ROI

Because of unstandardized and incomplete data, unrefined lateral moves data can lead law firms to misdirect their targeting, misread the market, and lose out on opportunities. By utilizing Decipher’s standardized data and proprietary metrics, law firms can optimize their recruitment and retention strategies, benchmark their performance against peer firms, and make informed decisions about their future growth and staffing needs.

Our data can also help your firm identify strategic candidates, assess candidates’ books of business and cultural compatibility, and provide realistic benchmarks for compensation.

Is your firm ready for a more purposeful, profitable growth strategy? Contact us today.

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