It’s true what they say ― data can tell you a lot more about your current business problems than you know, but there’s a catch. In order to get that data to unleash all its secrets, you need the right skills. Otherwise, you’re playing a dangerous, time-consuming guessing game that likely won’t yield the results you’re after.

This is why many businesses make the mistake of immediately hiring a data science consulting firm. They figure if a professional team can come in and solve all their data-centric problems, then they don’t need to worry anymore.

But things are rarely that easy, especially in business. There are a few factors to consider before hiring a data science consulting firm. Skipping this step could prove costly since you might hire the wrong team, or find out an off-the-shelf solution was all you needed.

So, if you’ve been wondering what to do about the copious amounts of data you need to wrangle, this is the guide for you.

Let’s dive in.

What does the data consulting process look like?

Before we touch base on what to look for in a data consulting firm or when to consider hiring one, it’s important to understand how the process actually works. It’s expensive and involved, with tons of iteration along the way. So, ensuring it’s worth your while is critical before committing months to the project.

In a nutshell, before a data consulting firm kicks off a project, they like to assess the existing problem. They’ll sift through your data, identify any serious issues you might be unaware of, and determine where data science could make the most impact. It’s a techie process since they’ll have to take a hard look at your current analytics and determine the potential ROI for each problem they’re solving.

Once you greenlight their plan, it’s time to move onto feature selection. At this point in the process, they’ll dive into your goals and the kind of data you need to reach those milestones. The features the firm suggests will depend entirely on this information, so it’s crucial that you’re as detailed as possible.

After that, the data science firm starts building the model. If it feels like an eternity later, that’s because it usually is. However, the good news is that they’ll build a model that suits your business based on your specific needs.

Once everything’s in place and crucial testing is done, they’ll deploy within the software your company already uses. This seamless integration keeps everything running smoothly across teams and departments.

What are some instances where hiring a data science consulting firm would be a better option than handling things yourself?

Overall, there are five instances where hiring a data science consulting firm is preferable to handling your data on your own:

  • Your budget doesn’t accommodate an in-house team, but you need skilled professionals to handle the data-related problems you can’t.
  • Your project doesn’t require unique proprietary data, which means consultants have worked with similar data.
  • You’ve checked off-the-shelf solutions for your use case and didn’t find a suitable option that featured everything you feel you need or want.
  • Your data doesn’t contain any sensitive information, or you use data masking to help prevent accidental sharing.
  • Your company needs professional guidance on things like strategy and implementation, despite being specialized in the market.

Now, if these specific situations do not apply to you, but you’re still curious about data science consulting, keep in mind that these are just some examples. Working with a consulting firm is extra beneficial in these circumstances, but it doesn’t mean you shouldn’t hire external help if you feel like you need it.

After all, an excellent consulting firm will be upfront and clear with you before kicking off a project. If they feel as though there’s a better option out there for you, they’ll point you in the right direction.

What should you look for when hiring a data science consultant?

If you’ve established that you do need to work with a data science consulting firm, make sure you look for the following criteria:

  • Do they have enough experience?
  • Can they provide both a short-term and long-term plan?
  • Are there any analytics translators on their team?

Ideally, the consultants should all academic, Ph.D. level. It might seem excessive at first glance, but the data science industry is filled with people claiming to be experienced professionals with proper training. It’s easy to be misled, especially in an age where information is so readily available and falsifiable.

Other essential skills include:

  • Coding languages
  • Data management skills
  • Knowledge of ML algorithms and models
  • Knowledge of frameworks like PyTorch and TensorFlow, or Skicit-learn

And that’s just scratching the surface. If you’re looking for a job done correctly the first time, you want to work with a team with experience working with Python, Java, regression models, Theano, Decision Trees, and much more.

On the domain knowledge front, this data consulting team should also understand your company goals, problems you’re facing, and ways to leverage data to exceed your expectations. After all, what’s the point in hiring a team, working on an extensive project for months, and getting the bare minimum?

In other words, determining whether you need to work with consultants, investing the time necessary to get the results your business requires and ensuring that you choose the right team to work with in the first place all take time.

And yet, it’s all worth it. With the right consultants, you could finally move beyond the obstacles holding your business back. More so, you’d have a roadmap to guide you through the next several years. And isn’t that worth more than any amount of research or time investment you might initially have to dedicate to the journey?

Looking for the right software development partner? RTS Labs has helped hundreds of businesses of all sizes successfully develop the right outsourced custom software for many business needs. Get in touch with us today to learn more about how we can help.