What to Expect from the Data Science Consulting Process and How to Choose the Right Data Science Consulting Company

data strategies, Strategy

You’re probably coming to a data science consulting company because your business has a problem or because you have a large amount of data. You know that data could probably tell you a lot more about the problem than you currently know, but you don’t have the skillset you need within your company to do something with it and find the best solution. 

Data science can be used to solve just about any business problem or to inform just about any business decision. (If you need to know more on that, check out this article.) The question is, how do you use your data effectively as a company and how can you use data science to its greatest potential while still saving as much money as possible? (There’s no need to throw away money on data science technology and investments if you don’t see results, right?) 

How do you know if your business needs to work with a data science consulting company? What does that process look like, and what should you expect when working with a data science consulting company?

In this article, we’ll unpack:

  • The pros and cons of using a data science consulting company as opposed to an in-house team
  • What the data science consulting process looks like
  • Tips for choosing the right data science consulting company
  • And how to know when its time for your business to start using data science consulting

By the end of the article, you’ll know what to look for in a data science consulting company and be prepared to partner toward solving your greatest business problems and informing your most important decisions with data science.

Should I use an in-house data science team or partner with a data science consulting company?

Why wouldn’t you just hire an in-house data scientist or data science team rather than work with a data science consulting company? Whereas in-house data scientists have the benefit of having definite industry expertise and usually are already familiar with your business problem, hiring a full-time data scientist can be expensive if you don’t need them all the time, and oftentimes the hiring process for data scientists is lengthy due to increased demand for data science expertise. Combine that demand with the low average tenure of data scientists before switching companies, and a data science consulting company starts looking like a much more reliable option if your business doesn’t have a constant need for an on-staff data scientist.

Data science consulting companies are extremely dedicated to your problem and to delivering timely, accurate, well-tested results, and they have a whole team of expertise at their disposal. In addition to data science consulting, they may also have other helpful data-related services that your business could take advantage of. When you work with a data science consulting company, you are backed by years of experience, you won’t have to deal with hiring and rehiring, and you can even get their help with ROI assessment for their solution before you ever sign on to make sure using data science is the right path forward for this stage of your business. (We’ll share more about that later.)

Data science consulting companies will help you explore your business problem, analyze it with your current data, brainstorm solutions, and can even help you identify other business problems that might be even more pressing than the one you came to them with (double-edged sword, right?). 

Whereas an in-house data science team may have other internal responsibilities to focus on, a data science consultant will be completely focused on delivering a solution for your specific business problem and tracking results. They have a tried-and-true process for solving your business problem, will have clear deliverables, and can help with training and education after the data science solution is delivered.

Your return on investment will be clearly seen and won’t be lumped in with other miscellaneous company data efforts. By having a clear process and working with the data science consulting company to clearly identify the problem, you’ll be able to track results easily and determine your degree of success for your data science projects.

So what does this process of working with a data science consulting company look like? 

The Data Science Consulting Process

As alluded to above and in our previous data science article, data science consulting starts with the clear identification of a problem, applies data science models and algorithms to solve that problem and explore the data, and then ends with deployment of the insights in an app, software, or other format for easy access.

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1-Identify the Problem

If you don’t already know what problem you’re trying to solve with data science, the data science consulting company will work closely with you to identify your greatest areas of need and find where data science could make the biggest impact for your business. They’ll use your current analytics and data visualization capabilities to assess this and will help you assess your potential ROI for each possible problem.

In some cases, they’ll identify a problem that you don’t have enough data to use data science to solve yet but that could create significant improvement in your business processes or have a significant ROI. In that case, they can help you start gathering the right data to be able to get an accurate picture of the problem and use data science in the future. 

For example, maybe in looking at your data they find that your company’s greatest area of weakness is ineffective new customer targeting, but your company currently only has data on current customers, not potential customers or customers who never made it to your sales pipeline by making a purchase. The data science consulting company would work with you to start gathering that pre-purchase customer information so that you can start seeing what leads those customers to actually make a purchase, what might deter them, and how to remove those obstacles. This could take the form of starting to collect data on how many times the customer added an item to a cart without purchasing, who signed up for emails but never made a purchase, who stayed on your website the longest, etc. You could then use data science to identify a group of potential customers that are most likely to make a purchase and respond to their needs and purchasing habits effectively. 

Once you gather the right data, you can use data science to identify how to effectively strengthen any area of weakness in your business. The more comprehensive your data is around a problem and the more cleanly its organized and ready to be accessed, the more effective the data science consulting company’s efforts will be. (Good data in gets good insight out.)

If you already know what problem you’re trying to solve with data science and your data is ready to be used, the data science consulting company will fully explore all aspects of that problem in this first stage. They’ll work closely with your subject matter experts and use data visualization to paint a clear picture of the problem with all the information you already have. They’ll also identify any missing data and work to gather the data needed to start feature selection.

2-Select Features

Feature selection is the process of brainstorming potential models and selecting what features (or data categories) should be a part of the model in order to gain the most effective results. For example, let’s say a political or advocacy organization wants to build a model that would most accurately identify a subset of voters that would be most likely to be persuaded in the topic area of the organization. In the feature selection part of the process, data scientists would work to select features or categories of data that are most likely to give accurate results. They might include features like family size of the voter, political affiliation, income level, location, etc., and they would be careful to not include features that were repetitive or could lead to skewed results in the model. For example, they wouldn’t include both “annual income” and “bank account balance” because those features would be too similar and likewise could skew results.

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Feature selection is an important part of the process to ensure that the model will be as accurate as possible and also include all possible variables to give the clearest and most comprehensive picture of the problem.

3-Build the Model

In this stage the data science consulting company will decide what model would be most effective for your problem and build the model. Your company will have the least direct involvement in this stage, but rest assured you will hear from the consulting company again soon, as they’ll come back with results for you in the next stage of the process.

For those who don’t work in the data science field, the phrase “build a model” can sound very nondescript and doesn’t do much to help you understand how data science is actually applied. What exactly is involved in building a data science model? Building a model involves inputting the selected features or a combination thereof into an algorithm that best achieves your business objective. The model is designed to communicate to the computer system how each feature and piece of data relates to other pieces of data. The data model design ensures that the computer system will know how to read and relate the data accurately.

There are several types of algorithms and machine learning models that data scientists use depending on the insight you’re looking for from your data, but you most likely won’t have to familiarize yourself with those options. All the preparation, research around your problem, visualization of current data, and discussions with subject matter experts has prepared the data science consulting company to create an effective model. They will collect all the data needed for the model, design it, and run the model for the first time. Soon they’ll come back to you with the output and be able to tell you the model’s degree of accuracy.

4-Verify Results

In order to improve the accuracy of the model’s results, the data science consulting company will then test the model iteratively. As they test, they will fine tune the model or add or remove features to get the model to produce the optimal outcome(s) that both they and you are comfortable with. 

This stage is paramount to making sure you get the most out of your investment in data science consulting. An increased degree of accuracy could mean responding to your customers’ preferences more acutely, equipment breaking down less often saving countless repair and production hours, or losing less customers. For example, if a financial trading company is looking to identify when employees are about to make a trade or sale that isn’t advisable, making the model even more accurate in this stage could save the company millions of dollars by preventing unadvised trades.

This iterative testing stage can take a while, but it will be worth it in the long run. With greater accuracy comes a greater return on your investment. Once the data science consulting company is pleased with the degree of accuracy, they will present the model to your organization’s key stakeholders for feedback.


Finally, the data science consulting company will work with your subject matter experts to determine the best form of deployment for your data science solution. Whether through the use of a web or mobile app, deploying within software your company already uses, using a data visualization solution, or any other form of deployment that’s best for your company, the data science consulting company will ensure that you are able to easily access the results of the model and regularly use the insights for your business. 

How to Find the Right Data Science Consulting Company

With the rising popularity of data science and hundreds of data science consulting companies to choose from worldwide, how do you choose the right data science consulting company? Here are a few characteristics you should look for in a data science consulting company in order to find the best fit for your business.

1- They should be curious and creative.

Data science is as much art as it is science. Data science consulting starts with a problem and then creatively applies statistical analysis and algorithms to bring up new information and insight for your company. There isn’t a straightforward path for deciding what model to use to generate that new insight, so it takes an experienced data scientist to exercise creativity and come up with the best model that fits your business problem. Models are specifically designed to fit the needs of your business, and that specific design takes a creativity and a curiosity that can be offered by the best data science consulting companies.

What does it look like to be curious and creative when it comes to data science? It looks like starting with a blank canvas every time and looking at each variable afresh. It includes the intentional use of a cross-discipline team-oriented approach, utilizing expertise from business and sales, data engineering, data science, and your business’ industry. It includes communicating freely with subject matter experts to come up with the best case scenario or goal for your business then brainstorm all possible options for getting you there- whether with data science or otherwise.

The staff at CSG takes pride in our cross-functional team approach to data science consulting, because we think this dynamic creativity truly energizes every good data science solution. Rather than forcing your business problem into the box of data science solutions, we start with a blank canvas, bring a diverse set of expertise into the conversation, and think about what your business needs to get to the next stage of success. That often involves gathering more data and using data science to get there, but we don’t start with those methods. We start by thinking big and getting curious about your business problems so that we can brainstorm all possible solutions. Your data science consulting team should most definitely be curious, creative, and have cross-functional expertise to think dynamically about your problem and explore every option. 

2- They can deliver proof of concept (POC).

Moving on to a more practical/quantifiable trait of a good data science consulting partner - they should be willing to provide a proof of concept (POC). In the case of data science this would look like assigning a benchmark that, if met successfully, would demonstrate the value of the project and that the concept will work. Showing POC ensures that any foundational questions around the project are answered and worked out before committing to a longer project or partnership with the data science consulting company.

In order for the POC to be successful, its critical that you give the data science consulting company access to all the resources they need to be equipped to make the project successful. While still protecting yourself from a legal perspective, ensure that you make everyone and every asset available to them to make a substantial impact for your business with the POC. This will allow you to truly get a taste of the potential business value of data science efforts. Being open with the data science consulting company in this stage will allow them to fully explore the problem, get to the root cause, and then truly deliver the most value possible.

3- They will calculate your potential ROI.

Lastly, the data science consulting company should help you assess your problem by pinpointing definitive estimates of your potential return on investment. You have to know if this data science project will be worth it to you and when

At what point will you start seeing a return on investment? If you’re trying to prevent loss, how many saved accounts or assets will it take to get as much of a return as you’d like? How much are you losing by not solving this problem with data science? Are there other key problems the consulting company could help you solve after showing POC that will help you get even more out of your initial investment?

A reputable data science consulting company will be completely willing to help you assess your ROI. And of especial importance – they should be honest with you about whether you need data science or not. Companies frequently come to CSG thinking they need data science and machine learning, when what they really need is just a more effective set of excel spreadsheets or to learn how to use their current analytics solution to its full potential.

We believe in the power of using data science to solve business problems, but most importantly we believe in finding solutions that are a fit and deliver the most value— no matter what that solution is. If your business isn’t ready for data science consulting or could benefit just as much from a cheaper or simpler solution, a good data science consulting company should tell you that. Unless you’re already sure you need data science, be sure to bring that question into any meeting with a new data science consulting company. It’s okay to ask—“Do I truly need data science or is there another solution that I should be looking into?” 

This is absolutely another reason why you should consider data science consulting companies that have cross-functional teams and a wide set of data services to offer—so that after exploring your problem, if you need a solution other than data science, they could seamlessly help you with that initiative. At CSG we often work with business to set up their data strategy and initial data analytics solutions, then years down the road they realize that they are at a point where they need more predictive analytics through data science or that they have questions that their current solutions won’t answer. Already accustomed to their business, industry, data strategy, and current analytics capabilities, CSG helps them apply data science to inform their decision making further. 

All in all, find a data science consulting company that is in it for the benefit of your business as a whole - not just for the purpose of coming up with specifically a data science solution. They should be able to objectively analyze what is best for your business and help you get as much out of your investment in data science consulting as you’re hoping for.

When Do You Know Your Business Needs Data Science Consulting?

There is a point when looking at your data through your current analytics solutions where you’ll find that exploring the data on what happened in the past just isn’t enough. If you need to be more informed about the impact of potential decisions on your company’s future, that’s when you know you need data science.

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If your historical data doesn’t give you enough to go off, and if you feel like your intuition and data on past transactions, operations, sales, etc. doesn’t help you decide what to do next, it is probably time to start using data science. While your current analytics solution can probably tell you how sales have gone for the past 20 years, it can’t tell you how your sales will be impacted if you decide to expand to a new market that you’ve never even considered. Data science can. And it can tell you within a degree of certainty how successful that expansion will be if you do actions A, B, and C. That’s powerful. Having that guidance will help you move forward more assuredly and determinedly as a business than ever before. That’s the power of data science.

If you feel like you could be preventing loss or risk intentionally, better assessing which customers to target, or finding new markets more effectively, but you don’t know how to get to that point, its probably time to start using data science and to reach out to a data science consulting company. Explore all the uses for data science here to see if your business is at that point, and consider starting the conversation with a data science consulting company so they can help you further identify the problem and then assess if data science is really what is going to solve it.

One last point - if your competitors use data science to project their success and mitigate risk, you might need to start using data science methods too. We definitely don’t propose doing things that aren’t right for your business just because your competitors are, but if competitors are able to move forward with their initiative more confidently and run an extremely lean, decisive organization based on their data, there’s absolutely the possibility that they’ll be using that data to get ahead.

When you add data science to your operational efficiency and effectiveness efforts, you close that competition gap and lessen the chance that another company will know their customers better, deliver more effectively, or expand into markets you hadn’t thought of before. Data science can help you make sure your business is at the front of the pack and calculatedly explores every possibility to create success.


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