Selecting the Right Technology for Data Management: A Practical Problem-Solving Model

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Ricci Dipshan’s recent piece on LegalTech News brought back memories from past developmental psychology classes, mathematics courses and even information technology training. While the intersection between psychology, math and IT may not be readily obvious, I was reminded of a five-step problem-solving process that I learned early in my life from each of them.

With over 20 years of technology experience assisting lawyers and legal personnel, these five steps work well for me in a variety of diverse situations.  Here, I’ll use them while exploring the process of selecting technology for helping with information governance, data disposition and legal matter management, but this process can be used to work through any problem.

Identify the problem

While it might seem like an obvious place to start, it’s crucial to understand causality when identifying the problem. Oftentimes individuals solve for the symptom, mistaking it as the cause. Software and technology solutions are only helpful if they get to the root of the issue. If selected to solve a symptom, the software is usually later abandoned.

So how do you identify the root problem? It might seem simple: look at it from different perspectives.

Start with this: observe the problem through the eyes of all stakeholders. Step into their shoes, interview them extensively and structure questions to get a different outlook on the same question. Second, explore those answers against objective facts and come back to ask follow up questions until you are completely comfortable that you understand the 360-degree view of the problem.

Walk away from the problem and your initial thoughts on how to solve the problem. Continue to reflect for a few days in a different environment – new ideas may emerge, wrong facts may display themselves and you may see things from a third-party perspective.

Educate yourself on the technologies that are available to solve your identified issues.  In addition to traditional courses or webinars, use new media, such as YouTube or Coursera, to provide well-rounded and fresh ideas for the technologies that can be used. On top of that, don’t be afraid to get others’ opinions!

That the best way to get others’ perspectives is to simply ask them.

Once you have worked through these identification steps, it is essential to take action.

Problem identification example: After implementation of Office365, your legal department realizes that the disposition of older data has not been analyzed for input into the Office365 eDiscovery solution.

People to interview: Legal Department, IT Department, Business Unit Stakeholders

Others’ opinions:  Business Units, Strategic Data Providers, Outside Counsel

Identify an actionable plan

Once you identify the problem, break it into distinct sub-classes so that you can begin to tackle each area individually. Each smaller subsection has specific actions that can fix them. Make a list of those action items and develop 2 to 3 different methods for solving the problem. If you determine a hypothesis for each of these methods you will more easily be able to analyze how each was successful.

One strategy that helps me is starting with the end in mind – what are you trying to solve?  The best solution should meet the goal, be affordable and limit risk during implementation.

Plan for problem identification: Implement a technology that analyzes data content, allows for remediation of data through automated moving and analyze different processes to achieve this goal.

Methods: Manual Tools, Automated Tools, Hybrid Solutions and Enterprise-Wide Total Package

Goal: Identify a software and service provider to manage data solutions

Determine the “what if?”

I am a firm believer in brainstorming, especially in a large conference room with multiple whiteboards or outside the office in an unconventional location.  This brainstorming should be done to determine all of the “what if” components.  These can be both positive and/or negative but all should be considered so that your team can leverage opportunities and mitigate risks.

Positive what ifs: Existing software may be able to solve the problem; Integration with other technologies can enhance seemingly standalone technology

Negative what ifs: Technology could accidentally delete data or move data to the wrong, insecure locations. Office365 may need to be upgraded to handle potential solutions.

Work the plan and strategize

At this point, you’ve identified the problem and plan and have a good idea of the “what if” components. The next part is actually working the plan; I know a lot of people that are full of ideas and a lot that are great at implementation.  These individuals are often not the same person, so be honest with yourself (and encourage your team to consider this) if you are the idea generator – are you also the implementer or is there a better person to implement? If someone else brings up an idea and says they want to tackle implementation, is that the right choice? As the solution is implemented, make sure that the steps taken work for you and for the technology team throughout the matter.

 Work the plan: Develop a true project plan with deadlines, risk mitigation strategies and ensure that there are no distractions (such as other projects) that could interfere with the plan.

Implementation: Make an implementation schedule with major deadlines, minor tasks completions and identified resources.  Make a communications plan to ensure all stakeholders are on the same page.


Once implementation is complete, many people believe that their problem-solving is over. However, most new technology requires initial pilot review (usually 2 – 3 months), ongoing maintenance and potentially could require long-term resource challenges. Determine and track the associated metrics. The art of a good project occurs often after the project is “over” – the software and staff maintenance became routine and the tool needs to be updated, reviewed and analyzed.

The goal should be to measure the implementation, what ifs and initial plan against ongoing metrics to ensure that the problem that you solved is still an issue and has a resolution, and how you can help support the overall solution. If there are any new problems to solve (go back to Step 1).

Big data is getting too big to still use the manual tools defined in the article and survey that I read (for reference, it’s here).  If you’re beginning to think about automation, advanced data management, and new processes for data disposition and legal matter management problems, reach out! Let’s continue the conversation – you know where to find me (and if not, we made it easy to link directly to me 🙂 )!


Written by Todd Haley, Vice President, Business Intelligence, eTERA Consulting. Todd can be reached at

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