If there is one thing that technology has given us in life and work, it’s choices. Sometimes those choices can be a little overwhelming to navigate. In life, something as simple as “I want to watch The Goonies,” can lead you down a path of navigating streaming services, pay-per-view options, or figuring out which of your neighbors still has a DVD or VHS player you can borrow. In work, it can be an even greater challenge when you have to navigate between Generative AI (Gen AI) and legacy solutions to find the best tool(s) for your project.

Define the Need or Problem You Are Trying to Solve

The same Lean Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) methodology that we use for process improvement and quality control measures is a great place to start when evaluating solutions for data challenges or projects.

What are the needs or challenges that you are trying to solve? Specificity isn’t always needed, but a lot of times a basic “X to Y by When” statement (i.e. current state to future state by a specific date) can help to clearly define the challenge and determine the best tool(s) to solve it. For example:

  • I have 100,000 documents that require redactions in 1 month.
  • I need to speed up and prioritize my 500,000 document review project to meet a client deadline and budget.
  • I just received 1 million produced documents from opposing counsel, and I want to understand the story these documents tell before next month’s depositions.
  • I have 10GB of data that I need to review and produce over the next 3 months.
  • My family wants to watch The Goonies on Saturday, and I don’t want to pay to watch something I’ve seen 100 times since 1985.

Gen AI can be a great solution to solve for redactions, data extraction, document review, data/case analysis, or summarization, but having a clearly defined need or problem can put you one step closer to selecting the best option(s) for your project.

New Tech, Old Tech, No Tech - Same Holistic Approach

While Gen AI is new, the process driven approach used to evaluate solutions is still very much the same. In addition to measures like time, cost, risk, and quality, there are a few key areas of focus when taking a holistic approach to selecting the right tool for the job.

  • Security: Does the solution align with security requirements? Does it require a security assessment before it can be utilized? Is key security documentation readily available (e.g. SOC2, network/data flow diagrams)?
  • Data: What are the data inputs and outputs? Where will the data go and how will it be used? Are additional data culling or clean-up steps needed to use the solution (e.g. document level deduplication, ‘bad’ file removal, excluding documents with large text)?
  • Processes: How, when, and where does the solution fit into existing workflows? Does it improve overall processes? Are there any negative impacts to processes prior to or after the solution is utilized?
  • Technology: How is the tool utilized with existing technology? Does the solution supplement or replace any existing technology? What is the time and cost to implement and maintain?
  • People: Do you have the right resources to utilize and support the solution? How will the tool impact overall resources – will it add to or reduce? What is the overall interaction and impact to different resources and stakeholders across a project?

As the saying goes, “you don’t need a bazooka when a fly swatter is sufficient.” It is certainly okay if you work through all your analysis and determine that traditional tools are a perfect fit. But, if you do need to branch out to Gen AI or other emerging technology solutions, taking a holistic approach will help to ensure you are getting the right tool for the job.

Don’t Forget Documentation

You’ve selected your tool(s), you’ve implemented, and you’ve executed the work needed. So, what’s next?

Do not forget to document. This can go a long way to leveraging the lessons learned for future needs or challenges that arise. It isn’t always easy to do in the middle of trying to get a job done, but it can make all the difference. Whether you do it yourself or enlist the help of a colleague, it is good to document things such as:

  • Overall description and features of the tool(s) utilized (Note: If the solution came with existing documentation, even better!)
  • What went well and what needs improving
  • How the solution was utilized (or can be utilized)
  • Implementation or technical requirements and limitations
  • Cost, time, and risk considerations

Documentation can go a long way to streamlining future decisions and solving problems, especially when it is maintained and shared within and across teams.

The selection of the right tools is very much like their implementation and use – it’s a process. Whether you are landing on a new Gen AI solution or relying on a go-to legacy option you have utilized many times in the past, following a well-documented process to get there can help you select the right tool for the job. And unlike my solution for watching The Goonies, you aren’t always going to have a Roku or 12-year-old to help you find it.

Dave York

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Dave oversees TCDI’s Litigation Services team involved in projects and data relating to eDiscovery, litigation management, incident response, investigations and special data projects. Since his start in the industry in 1998, Dave has made the rounds working on the law firm, client, and now provider side of the industry, successfully supporting, executing and managing all phases of diverse legal and technical projects and solutions. During his career he has been a NC State Bar Certified Paralegal, holds a certification in Records Management, is a Certified eDiscovery Specialist (ACEDS), and has completed Black Belt Lean Six Sigma training. Learn more about Dave >