7 Ways Businesses Can Make Better Data-Driven Decisions While Protecting Privacy
If you run a law firm, you’re probably sitting on more useful data than you realize. Between client surveys, website analytics, matter and case information, billing records, support requests, employee records, and financial information, there is no shortage of information you could use to guide your next decision.
That can be incredibly useful, especially when you’re trying to understand which services clients actually want, where your intake process could be improved, or how your firm is performing operationally. The problem is that having access to more data doesn’t automatically mean you’re making better decisions. The more information you collect, the more you also need to think about how it’s stored, who can access it, why you collected it in the first place, and what happens when you no longer need it.
So, how do you get useful insights without collecting personal information simply because your systems make it easy to do so?
1. Start With the Question You Want to Answer
It’s easy to start with the data. You have a new analytics tool, so you collect everything it can give you, or you put together a customer survey with every question you can think of because you might find the answers useful later. Before long, you’re sitting on a huge amount of information without a particularly clear idea of what you’re supposed to do with it.
Try working backwards instead. Start with the decision you’re trying to make and then figure out what information would actually help you make it.
You don’t need someone’s full home address to understand which product features they prefer, and you may not even need their name. Likewise, if you’re trying to understand how clients feel about your firm’s communication, you may need their feedback without needing to attach every response to a specific matter or individual.
2. Don’t Collect Personal Information Just Because You Can
Modern business software makes data collection incredibly easy, which can make it tempting to ask for more information than you really need. A client intake form can have twenty fields instead of five, your practice management system can store dozens of details about a matter, and your analytics platform can track all kinds of website behavior in the background.
If you’re running a client satisfaction survey, for instance, look at every question and ask yourself what you’re actually going to do with the answer. Do you need someone’s name, exact location, or date of birth to understand how satisfied they are with your service? If the answer is no, leaving those questions out makes the whole process simpler.
There are also situations where you can get the insight you need without being able to identify individual people at all. You might want to know that clients in a particular practice area are more likely to be satisfied with one type of communication, for example, without needing to know exactly which clients gave those responses.
That distinction matters because reducing the amount of personal information you collect also reduces what you need to protect. It can make analysis easier too, particularly when your team isn’t spending its time sorting through information that doesn’t actually answer the question you’re trying to solve.
It also gives you a useful reason to look at your existing intake forms, databases, and other systems and ask whether every piece of information you’re storing still has a purpose.
3. Think About Privacy Before You Start Analyzing the Data
Privacy shouldn’t be something you think about after you’ve already collected, copied, exported, and analyzed a large amount of client or business information. By that point, the data may have passed through several systems and been accessed by several people, making it much harder to work out exactly where it has gone.
Instead, think about the process before you start. Who is going to work with the data, where will it be stored, which people actually need access to the raw information, and are you sending any of it to another company or software platform? If you’re not sure where to start, Cookiebot’s guide on how to implement privacy by design can help you build privacy considerations into your processes from the beginning.
Those questions become particularly important when you’re using AI and analytics tools. You might have a platform that can analyze customer feedback in minutes, but before you upload a dataset, you need to understand what happens to that information once it leaves your system.
4. Automate the Boring Parts of Data Analysis
A surprising amount of data analysis involves work that doesn’t require much strategic thinking at all. You might spend hours cleaning spreadsheets, sorting responses, categorizing open-ended answers, running calculations, creating tables, and moving everything into a report before you even get to the interesting part: working out what the data is actually telling you.
This is where automation can take some of the pressure off. For example, Attest’s guide on how to speed up survey data analysis looks at ways to automate parts of the survey analysis process, including data cleaning, open-text coding, descriptive analysis, cross-tabulation, and reporting.
There’s a privacy benefit here as well. Every time someone manually copies personal information from one spreadsheet or system into another, there’s another opportunity for that information to be misplaced or shared with the wrong person. Reducing some of that manual handling can reduce those opportunities.
5. Don’t Let the Data Make the Decision for You
It’s easy to put a lot of confidence in a dashboard or an AI-generated analysis, particularly when the numbers look convincing and the technology presents the result with a lot of certainty. The problem is that data can be accurate while your interpretation of it is completely wrong.
Say your firm’s data shows that one practice area takes significantly longer to resolve matters than another. That doesn’t automatically mean the attorneys working in that area are less efficient. The cases might simply be more complex, involve more parties, or require a different type of work.
This is why someone still needs to look at the result and question it:
- Does the finding make sense in the context of your firm and the work you do?
- Could something else explain what you’re seeing?
- Is there information missing from the analysis, and would you reach the same conclusion if you looked at a different group of clients or matters?
That becomes even more important when you’re using data to make decisions that affect individual people. An automated recommendation can be useful, but it shouldn’t automatically become the final answer simply because a system produced it.
6. Give People Access to What They Actually Need
There’s a good chance that most people in your law firm don’t need access to all of your data. Your marketing team may need aggregated client trends, for example, while your billing or finance team needs financial information, and the person building a client research report may only need the survey responses relevant to their work.
Look at what each person actually needs to do their job and give them access to that information rather than everything available in the system. If someone only needs aggregated customer trends, they probably don’t need a spreadsheet containing names, email addresses, and individual responses as well.
You can also revisit those permissions over time. Someone who needed access to a particular dataset six months ago may have moved onto something completely different by now, but their permissions often stay exactly where they were.
Then there are the third-party tools your firm uses. Your marketing agency might need access to website analytics, for example, without needing access to client information. A survey platform may need responses, but not every piece of information associated with the person who submitted them.
7. Check Whether Your Data Is Actually Helping You Make Better Decisions
Collecting data isn’t the same as using it well, and it’s surprisingly easy for a business to end up maintaining reports, surveys, and databases that aren’t really influencing anything.
Maybe your team spends hours every month putting together a client feedback report that nobody looks at. Perhaps you’ve been collecting a particular client detail for years because it was included in an old intake form, but you can’t remember the last time anyone actually used it. You might even have a survey that produces hundreds of responses but rarely results in a change to how your firm communicates with clients.
That’s a good point to stop and take stock. Look at what you’re collecting, how you’re using it, and whether it still helps you make decisions. If a particular dataset isn’t contributing anything useful, you can ask whether there’s a reason to keep collecting it in the first place.
Better Data Doesn’t Have to Mean More Data
You don’t need to collect every possible piece of information to become a more data-driven business. In fact, collecting less can sometimes make it easier to find the information that actually matters.
Start with the decision you need to make, work out what information will help you make it, and then think carefully about how that information should be collected, stored, accessed, and analyzed. Use automation where it genuinely makes the process easier, but don’t hand over your judgment just because a tool can produce an answer in seconds.
