Big Data, Big Problem: Coping With a Shortage of Talent in Data Analysis

What is data analysis?

Broadly defined, data analysis is the systematic application of statistical techniques to a collection of information to gain insight. In other words, after collecting and interpreting data, the results are used to make assessments and guide decisions. The typical data analysis process consists of five distinct steps:

1. Identify the objective.

What are you trying to measure? You cannot receive an answer without first identifying the question. Do you want to analyze sales figures, revenue streams, inventory or customer retention rates? It is impossible to create a data-driven systematic process, like a decision support system, without first identifying the topic. As a business owner, you may know what needs to be studied, or you might rely on others in your company to make that determination.

2. Collect the data.

After determining what your business wants to measure, the data analyst must devise an efficient and thorough method of collecting the relevant information required. The analyst gathers the data either internally or externally. Internally, an analyst collects information through surveys, client relationship management (CRM) software or product data. Externally, an analyst collects information through secondary sources, such as government records, social media programming interfaces or market trends. [See our top picks for the best CRMs, which provide valuable customer data.]

3. Clean the data. 

This is the step that prepares the data for analysis. Deleting duplicate information, rectifying errors and standardizing data formats usually make up the bulk of the work in this phase. It is often a tedious task, but companies can take advantage of automated systems or artificial intelligence to expedite the process.

4. Analyze the data. 

A data analyst will manipulate the clean data using various statistical and logical methods. The goal of this step is to identify trends, outliers and variations to gain possible insight into a market, product or customer base. 

5. Interpret the data. 

The final step is to apply the data analysis to the real world. Did the analysis provide an answer to your question from Step 1? Did the data give insight into improving various business operations, such as social media marketing or customer interaction? It is often a data analyst’s job to present the data analysis to the business owner in an easy-to-understand format or presentation. The data analyst will use big data to their advantage with social media metrics. 

Why is there a shortage of data analysts?

The U.S. Bureau of Labor Statistics has projected the data science industry to grow 35 percent through 2032. The driving force behind the growth of data science is the sheer quantity of data being generated. But even as more people become educated in this field, there still aren’t enough data analysts to go around. Here are four reasons why:

Highly skilled job

Being a data analyst requires a high level of technical skill. A fully trained analyst will have strong abilities in statistics, mathematics, programming, probability and data systems. The time it takes to gain and master these subject areas is one of the reasons companies typically require a master’s degree in data science when hiring for this role. Whenever you have an advanced degree as a job requirement, the pool of qualified candidates will be smaller.

Lack of experience

Data science is a relatively new career option, which is one reason there’s a significant shortage of experienced data analysts. It is not enough to simply understand the process of analyzing data; candidates must have experience in gathering and manipulating data to provide insight into solving a company’s unique challenges. People who are new to this field are unlikely to have experience with applying data analysis concepts to real-world business situations.

Intense competition

Both big and small businesses are using data analytics to make informed decisions, thus increasing the competition for finding quality candidates. This demand for data analysts is probably the biggest reason for the shortage of such analysts in the hiring market. So many companies are prioritizing this aspect of their business, essentially making it an overcrowded marketplace as all of these organizations vie for the best analysts.

Lack of guidance

Any new career field usually lacks standardization or supervision. Many job sectors have a governing body to guide aspiring candidates while connecting employers with future employees. The data analytics industry is in dire need of an organization to standardize, certify and train the next generation of data analysts. Such a group can also foster networking opportunities and set up hiring pipelines — two things largely missing in this field — making it easier for companies to find the people they need.

How can you find data analytics professionals for your business?

Given this talent shortage, it can be challenging to find data analysts to hire for your company. However, there are a few actions you can take to improve your chances of finding suitable workers. These strategies include rethinking how many data analysts your business really needs and considering what existing personnel resources you can utilize in this area.

Hire from within.

Hiring externally is significantly more expensive than promoting from within your company, which saves time and can be the ideal solution when there is a lack of external applicants. Plus, an internal hire will already possess an understanding of your company’s culture, staff and processes, which means less time will have to be spent on new-hire procedures. Still, there are a few steps to take for this option to succeed.

For starters, you need to identify current employees with the aptitude and interest required for developing into a data analyst. As previously noted, a data analysis role is a highly skilled position. If you’re hiring from within, you’ll likely need to provide employee training to adequately develop your worker into a full-fledged data analyst. It will take time for them to foster the skills necessary to execute data analysis tasks. But with patience and proper teaching, a current staffer could fill this critical vacancy.

Redefine the data scientist’s role.

It is expensive to hire an entire team of data analysts, and the talent shortage doesn’t make it any easier to find multiple qualified people. Fortunately, sometimes a business can rely on just a few data experts — or even just one — supplemented by employees with various backgrounds. Some of the steps required to complete a data analysis can even be offloaded to less-skilled employees who may have free time to spend on such projects.

For example, if you have at least one data analyst who can devise the best way of collecting data, a less-skilled employee can carry out the collection task. The data analyst can then supervise a less-skilled team that searches for common errors, corrects data formatting and purges duplicate records from the gathered data. This way, you don’t need to hire multiple data analysts to carry out every step of the analysis process; instead, you can utilize some of the staffers you already have.

Merge external outreach and internal development.

Sometimes, the best approach to building a capable workforce is a combination of external outreach and internal development. This dynamic is best suited for a business that is creating a data analytics division from the ground up. Hiring at least one experienced data analyst with management skills is an essential first step. This outside hire can be an important resource for developing and identifying ways for your business to begin working with and managing data without having to hire multiple experts. 

Here are some common ways a single data analyst can work with your current staff to meet your company’s data analysis needs:

• Sales team: A data analyst can identify and develop data collection methods that your sales team can then implement while completing daily sales tasks, such as calls and inventory.
• Customer service: A data analyst can find various uses for customer service data. This department can identify problems with products, collect customer data and provide insight into a business’s public perception.
• Human resources: Hiring usually involves a lot of data. Your HR team can collaborate with the analyst to interpret this data and thus increase the efficiency of the hiring process. [Read related: Hiring Process Timeline Best Practices]

Define your business objectives.

Data analysis is a diverse career field, so it’s vital to define how your business wants to use data analysis to develop or improve its operations. This step can narrow down your search for relevant data analyst candidates during the hiring process. For example, if you know you want to look into customer retention data, aim to hire a data analyst with experience in manipulating customer service data or conducting customer surveys. By looking to hire specifically for what you need, instead of focusing on data analysts in general, you’re more likely to find the right person for the job.

Kimberlee Leonard contributed to the reporting and writing in this article.