As the trend in data science and big data analytics accelerates, organizations are trying to determine whether they should hire a data science team or hire a data science consulting firm. The good news: the options aren’t mutually exclusive.

In fact, you should use a data science company to help you avoid mistakes as you build a team. You will likely have questions like: what should I expect for my first application? What technology decisions make sense for my business? What kind of data science engineer should be my first hire? And, how do I safely try new applications and techniques?

The sad truth is that many organizations fail to learn from others who have already begun the data science and big data analytics journey. Many of these challenges are avoidable. Teaming with a data science consulting firm lowers risk, from the initial planning stages to growing the practice once it is humming along.

As your start and develop your data science and big data analytics plans, consider the following at each stage of the your program maturity.

Beginning a Data Science and Big Data Analytics Strategy

Before you begin your first project, you have decided to consider data science and big data analytics. Perhaps a data science company may have entered your space, and their message has captured the attention of your market. Or perhaps you have identified business opportunities that you believe are ideal for data science. At this early stage, before you go too far in setting plans, think about what kind of guide you need.

It’s important to note that a lack of talent and adequate project planning are the biggest causes of data science and big data analytics project failure.


… (Source: http://www.datascience-pm.com/project-failures/)

This chart notes that Wrong/Inadequate Skills, Incorrect Business Objectives, and Insufficient ROI/Business Case are the top three causes of failure.

Organizations that significantly lower the risk of failure have brought in a partner early to clarify the business case, work with existing internal resources to begin transferring knowledge, help select technology, ensure that solutions are deployed successfully and then managed, and, finally, to clarify skills needs for any new internal team members.

Ramping Your Team and Choosing the Right Balance Between Internal and External Team Members

Once the first project is operational, a data science consulting firm acts as a guide for determining the right balance for internal and external team members. An easy first mistake is to hire a data science engineer without the support and infrastructure that this data scientist needs.

While a data scientist can be a great contributor, often a data engineer, or a developer who embeds data science pipelines is your first hire. A data science consulting firm can help identify the right internal roles and bridge the gap with continued staff augmentation.

Widening Your Lead as Opportunities and Technologies Change

Once you’ve transformed to become, in some ways, a data science company yourself, you will likely spend most of your time and energy dealing with data science problems common to your own environment. A data science consulting firm sees many implementations across many different applications and environments.

Also, with technology changing all the time (see this blog post with three trends for 2019), there is no reason to risk using new techniques for the first time by yourself. Chances are a data science consulting firm sees technologies and applications that you don’t, even if they are not new to the market, but are new to you.

Need a guide on your journey? Over the last 13 years, Syntelli Solutions has helped organizations across industries turn data into success. See the blog post, Choosing a Partner for Data Analytics Consulting – Three Essential Considerations for finding your guide.