If your business is looking to keep pace with competition, you’ll need to understand the data you collect. Often, the difference between thriving and shrinking companies is their capability to collect and analyze information.

It's not only difficult to find experts in the data field; it’s also expensive. That’s why many organizations are turning to apprenticeship programs as a way to fill their data needs.

Data apprenticeship programs offer students the opportunity to learn on the job and develop the skills needed for a successful career in data science, data analytics, or other data literacy fields. At the same time, they offer employers the opportunity to save money and hire diverse, qualified data talent.

In this article, we’ll discuss how businesses can identify when it’s time to hire a data science or data analytics team, what that process should look like and how your organization can benefit from hiring data apprentices instead of traditional data professionals.

Why is having an effective data team so vital?

One of the main differences between high-performing companies and lesser-performing companies is their familiarity with data. Amid rising competition, understanding your data is important to help drive growth and connect customers with the solutions they need.

A data team can help your organization draw valuable conclusions from the internal and external information you gather. Today, 60% of global organizations examine their own data to drive growth. This dedication to the data you gather can easily help influence sales, improve efficiency, and help customers address the challenges they face.

Effective data teams fulfill a critical role as part of your organization’s larger marketing workflow: they help your company take control of the data you gather, identifying trends in that data to help inform future decisions.

In short, having a difference-making data team in place is critical for any organization that wants to maintain insight into customer behaviors, best-performing products, and other important KPIs.

How do I identify my organization’s data-related needs?

The first step in hiring a data team is to assess your organization's needs.

Do you need someone to identify the best touchpoints to gather data from? Do you need someone committed to gathering that data? Do you need someone to do both?

Perhaps you’ve even had data-related challenges in the past, and you need someone to revamp — or entirely refresh — your organization's approach to data analytics and data science.

The exact data needs of your business will vary depending on the size and type of your organization, as well as the industry you're in.

For example, a small business that primarily sells products online will have different data needs than a financial institution that deals with sensitive customer information.

Once you've identified your data needs, you can begin searching for candidates who have the skills and experience necessary to meet them.

How to build an effective data team

Building an effective data team requires more than simply hiring a few qualified individuals.You’ll also need to ensure that your team has the right mix of skills, knowledge and experience to keep your company’s internal and external information safe.

We've put together a few tips on how to build an effective data team.

1. Identify a need for improved data management

To build an effective data team, you’ll need a clear idea of what your organization's data needs are.

Take some time to assess how well your organization collects data, and how well you use that data to inform future decisions.

Remember, every organization has different data-related needs, so don't try to compare yourself to other businesses. Instead, take the time to grow familiar with your company’s data needs, and the current state of your data science and analysis efforts. Consider asking current employees, and particularly any members of your marketing team, where they see a need for enhanced data aggregation, cleansing, analysis and trends identification.

Focus on identifying areas of opportunity for your organization — where data might be able to inform quick growth.

2. Identify the type of data team you’re looking for

Before you start searching for candidates, it's important to have a clear idea of what you're looking for.

Start by identifying the specific skills and experience your ideal candidate or candidates would have. Then, consider how those skills and experiences would fit into the overall structure of your team.

For example, if you're looking for someone with experience in data science, they might be responsible for building algorithms to automatically analyze collected information. If you're looking for someone with experience in data analytics, they might be responsible for identifying the KPIs worth tracking across collected data sets.

Once you have a good understanding of the skills and experiences you need in a data team, you can begin searching for candidates.

3. Create a job description that attracts the right candidates

Once you know what your organization needs, you can start writing a job description that will attract the right candidates.

Here are a few things to keep in mind when writing your job description:

  • Be clear about the skills and experience you're looking for
  • Describe the team's culture and how the role will fit into it
  • Offer a competitive salary and benefits package

These and other qualifications can help you separate the best data candidates from the rest.

4. Ask the right interview questions

Once you've written a great job description and started receiving applications, it's time to interview candidates for your data team.

During the interview process, be sure to ask questions that will give you a sense of how the candidate would perform in the role. For example, you might ask them to describe how they would use collected data to inform growth decisions.

The interview process is a great opportunity to get to know the candidate's personality and see if they would be a good fit for your team. Ask specific questions about your team’s data needs, to get a better idea as to how they would function as a member of your organization.

5. Select candidates that fit your company culture

Once you've selected a few candidates, it's time to start the hiring process.

The first step is to check their references.

Be sure to ask their previous employers questions about their work ethic, how they handled difficult situations, and if they would recommend the candidate for the job.

You'll want to make sure that the people you are hiring fit into your company culture and positively complement the team you’re actively compiling.

The next step is to conduct a background check.

This is important to do for any new employee, but it's especially important when you're hiring someone for a position that requires handling sensitive information.

You'll want to verify the identity of each potential data employee.

Once you've done your due diligence, it's time to make an offer.

How a Pace data apprenticeship can solve your data-related challenges

There are a range of benefits to hiring a data apprentice instead of paying top-dollar for a traditional data scientist or data analyst.

For one, a data apprenticeship program is more cost-effective. Hiring an apprentice will cost you a fraction of what it would take to hire a full-fledged data professional.

In addition, data apprentices are trained to handle today’s biggest data-related responsibilities. Pace continually trains data apprentices for one full year after they are hired, to keep them continually informed as best practices change.

Get in contact with our Solutions team today, for more information about hiring diversely talented cybersecurity apprentices for your organization.