The Future in Law Firm Technology

Predictive Analysis

So what's next? Tomorrow's technology will help you figure out what you need to know. For example, instead of users asking the question “are our devices in the right places? Let's run some reports to find out,” next-generation systems will automatically track and alert users about device optimization. Financial analysts will not have to run a report in order to know which clients are likely to be bad payers.

Technology like this is already in place in many environments, including legal. One trend we are watching from the sidelines is “predictive coding,” today's hottest trend in electronic discovery. In a nutshell, predictive coding speeds document review by predicting how document reviewers will organize discovery documents. Documents coded as non-responsive need not be reviewed at all (although best practice is to review a random sample). Documents coded as privileged or responsive must be seen by an attorney's eyes. The system can even prioritize the documents so the most important ones are reviewed first.

How does predictive coding work? To oversimplify, document reviewers manually review a small random sample, and highly sophisticated software determines which electronic documents are most like those that have been deemed responsive. Basically, attorneys tell the software what's important and the software acts on it.

Soon, this type of analysis will not be limited to discovery projects and will be a tool used to manage, with law firm leaders deciding what's important and software analyzing its own data to lead to the best decisions.

Instant Benchmarking

Where this gets really interesting is when we consider what impact cloud computing will have. Over the past few years, “the cloud” has become more secure and accepted, reducing overhead and administrative expenses for organizations of all types, including law firms. Value from the cloud also accrues from the fact that it's easier to leverage information (and work) across geography and in-house servers are not required. But one change that hasn't caused much impact yet is that firms' data is residing with greater frequency with their service providers. And this gives those service providers the opportunity to provide new ' and extremely valuable ' services to users.

By aggregating and cleaning all that data, service providers will be able to deliver instant benchmarking to its clients. What's the average amount that firms are billing for copies? How many days does it typically take to get paid? How many hours should a certain type of matter take? Future law firms will have this information at their fingertips.

Moreover, the information will be perfectly accurate. Today, benchmarking is typically done in two ways. One is by “reference” where a manager calls other managers to find out what they are doing. This is obviously statistically flawed (at best) due to extremely small sample size. The other is by comparing your information with the results of benchmarking surveys, the results of which are also likely skewed by respondents' unfamiliarity with their own data ' and by some who provide answers they think they should give rather than the honest truth.

Currently, a manager has to first identify that there might be a problem. From there, he or she can pull the firm's own data and analyze it against those results determined to be typical at other firms. Future managers, however, will have it much easier. Their own technology will tell them when they are “off the bench” and allow them to take corrective action.

Smartphones = Accuracy

Future managers will also be able to leverage smartphones to capture data more consistently and accurately, as software companies start to take advantage of the fact that these devices have turned users into walking and talking databases. These devices can capture data on the fly and in real time. For example, cab receipts can be entered instantly and documents can be tracked by enabling all attorneys and staff to scan barcodes. One thing we are working on in our business is the ability to create scan and copy jobs on a smartphone before even walking to the MFP, which is then transferred to the printer as the smartphone approaches. This will save time (and reduce lines) at the devices while minimizing errors by allowing decisions to be made within a personalized interface at one's own workstation.

The key to fully leveraging smartphones is better integrations across applications, another product of which will be more pre-populated data. Users will not need separate “favorites” for their time-and-billing, cost recovery and document management systems. These will be stored by user, not by application. We will see more productivity and more accuracy ' all with a simpler experience for all users.

Conclusion

Just a few years ago, law firms were forced to take a bottom-up approach to data-driven decision making. All they could do was look at what data was available and use it to the extent possible. Other decisions were made by instinct simply due to the lack of available data. Today, most decisions are data-driven. It's a top-down approach, and we are quickly creating tools to better capture all this data. But as we do so, and make it even more readily available, I believe we are headed back to a bottom-up approach, albeit a different one. Instead of data only informing decisions when it is available, the data will start by telling us what needs to be decided.

When I started in law firm technology in the late 1980s, the key phrase was “data processing.” In fact, that was my title at the law firm: Data Processing Manager. We had a variety of proprietary technology from IBM, Wang and a litigation support company that I can't even remember. The challenge was to provide access to this data regardless of source or location. As technology has evolved and we've gone from proprietary systems to open ones with standard data types, access to data is much easier. In fact, today's challenge is not accessing information, it's deciding what to access and what to do with it. While in the past one needed to be a computer scientist with the right training ' and even that only helped if the data was actually there ' today there is so much information at the fingertips that it is overwhelming.

To date, software providers have solved this problem with dashboards, portals and reports. But these tools only scratch the surface: it's still too hard to know what's important as the decisions on what is tracked qualitative. In order to get truly quantitative, the data, not our preconceived assumptions, has to tell us what's important.

In our business, the historical value has been in cost recovery. What information was important? Costs related to photocopies, faxes and phone calls that can billed back to clients. So the goal of law firm technologists and finance professionals was pretty simple: get that information out of the cost recovery systems and onto the bills. For the past decade or so, firms have also been able to unlock more data to improve decision-making. For example, many firms were able to track which MFDs were used most and remove devices that weren't. Other firms created a strict set of rules to determine which machines printed which documents and which were sent to facilities management.

Predictive Analysis

So what's next? Tomorrow's technology will help you figure out what you need to know. For example, instead of users asking the question “are our devices in the right places? Let's run some reports to find out,” next-generation systems will automatically track and alert users about device optimization. Financial analysts will not have to run a report in order to know which clients are likely to be bad payers.

Technology like this is already in place in many environments, including legal. One trend we are watching from the sidelines is “predictive coding,” today's hottest trend in electronic discovery. In a nutshell, predictive coding speeds document review by predicting how document reviewers will organize discovery documents. Documents coded as non-responsive need not be reviewed at all (although best practice is to review a random sample). Documents coded as privileged or responsive must be seen by an attorney's eyes. The system can even prioritize the documents so the most important ones are reviewed first.

How does predictive coding work? To oversimplify, document reviewers manually review a small random sample, and highly sophisticated software determines which electronic documents are most like those that have been deemed responsive. Basically, attorneys tell the software what's important and the software acts on it.

Soon, this type of analysis will not be limited to discovery projects and will be a tool used to manage, with law firm leaders deciding what's important and software analyzing its own data to lead to the best decisions.

Instant Benchmarking

Where this gets really interesting is when we consider what impact cloud computing will have. Over the past few years, “the cloud” has become more secure and accepted, reducing overhead and administrative expenses for organizations of all types, including law firms. Value from the cloud also accrues from the fact that it's easier to leverage information (and work) across geography and in-house servers are not required. But one change that hasn't caused much impact yet is that firms' data is residing with greater frequency with their service providers. And this gives those service providers the opportunity to provide new ' and extremely valuable ' services to users.

By aggregating and cleaning all that data, service providers will be able to deliver instant benchmarking to its clients. What's the average amount that firms are billing for copies? How many days does it typically take to get paid? How many hours should a certain type of matter take? Future law firms will have this information at their fingertips.

Moreover, the information will be perfectly accurate. Today, benchmarking is typically done in two ways. One is by “reference” where a manager calls other managers to find out what they are doing. This is obviously statistically flawed (at best) due to extremely small sample size. The other is by comparing your information with the results of benchmarking surveys, the results of which are also likely skewed by respondents' unfamiliarity with their own data ' and by some who provide answers they think they should give rather than the honest truth.

Currently, a manager has to first identify that there might be a problem. From there, he or she can pull the firm's own data and analyze it against those results determined to be typical at other firms. Future managers, however, will have it much easier. Their own technology will tell them when they are “off the bench” and allow them to take corrective action.

Smartphones = Accuracy

Future managers will also be able to leverage smartphones to capture data more consistently and accurately, as software companies start to take advantage of the fact that these devices have turned users into walking and talking databases. These devices can capture data on the fly and in real time. For example, cab receipts can be entered instantly and documents can be tracked by enabling all attorneys and staff to scan barcodes. One thing we are working on in our business is the ability to create scan and copy jobs on a smartphone before even walking to the MFP, which is then transferred to the printer as the smartphone approaches. This will save time (and reduce lines) at the devices while minimizing errors by allowing decisions to be made within a personalized interface at one's own workstation.

The key to fully leveraging smartphones is better integrations across applications, another product of which will be more pre-populated data. Users will not need separate “favorites” for their time-and-billing, cost recovery and document management systems. These will be stored by user, not by application. We will see more productivity and more accuracy ' all with a simpler experience for all users.

Conclusion

Just a few years ago, law firms were forced to take a bottom-up approach to data-driven decision making. All they could do was look at what data was available and use it to the extent possible. Other decisions were made by instinct simply due to the lack of available data. Today, most decisions are data-driven. It's a top-down approach, and we are quickly creating tools to better capture all this data. But as we do so, and make it even more readily available, I believe we are headed back to a bottom-up approach, albeit a different one. Instead of data only informing decisions when it is available, the data will start by telling us what needs to be decided.