As more businesses rely on big Data Analyst to improve their processes, there is a shortage of people skilled enough to interpret this information and use it to their advantage accurately. With the exponential growth in the number of boards needing the help of data analytics experts and increasing competition to fill more jobs than qualified people, what can your business do to appeal to and retain talent in this critical role?
What Is Data Analysis?
Data analysis systematically applies statistical methods to collect info to improve insight. In other words, data is collected and taken, and the results are used for evaluation and decision-making. A typical data analysis process can be broken down into five distinct steps:
1. Define your goal.
What are you trying to measure? You can’t get the answer without first defining the question. Do you want to analyze sales volumes, revenue streams, inventory, or customer retention rates? Creating a systematic data-driven process, such as a decision support system, is impossible without first defining the topic. As a business owner, you may know what needs to be looked into, or you can rely on others in your company to make that decision.
2. Collect data.
After determining what your commercial wants to measure, the data analyst must develop an effective and thorough method for collecting the necessary information. Data is collected internally or externally. Internally, the analyst collects information through surveys, customer relationship management (CRM) software, or product data. Externally, the analyst collects information from secondary sources such as government reports, social networking programming interfaces, or market trends.
3. Clear data.
This is the stage of preparing data for analysis. Removing duplicate information, correcting errors, and standardizing data formats usually make up most of the work in this phase. This is often tedious, but companies can use automated systems or artificial intelligence to speed up the process.
4. Analyze the data.
A data analyst manipulates raw data using various statistical and logical techniques. This step aims to identify trends, outliers, and differences to gain possible insight into the market, product, or customer base.
5. Interpret the data.
The final step is to apply data analysis to the real world. Did the analysis answer your question from Step 1? Does this data allow you to improve business operations, such as social media marketing or client interactions? Often, a data analyst’s job is to present data analysis to the business owner in an understandable format or presentation.
Why Are There Not Enough Data Analysts?
Data science will be the fastest-growing IT skill in 2021, according to DevSkiller. The driving force behind the development of data science is the sheer volume of data being generated. However, even as more people are educated in the field, there is still a shortage of data analysts. Here are four reasons why:
Highly skilled work
Working as a data analyst requires a high level of technical skills. A fully trained analyst will have robust statistics, mathematics, programming, probability, and data systems skills. The time required to study and master these topics is one of the reasons why companies typically need a master’s degree in data science when hiring for this position. The number of qualified candidates decreases when you have an advanced degree as a job requirement.
Lack of experience
Data science is a relatively new profession option, which is one reason for the massive shortage of experienced data analysts. It is not enough to understand the data analysis process; Candidates must have experience collecting and processing data to gain insight into solving unique company problems. People new to the field are unlikely to have experience applying data analytics concepts to real-life business situations.
Intense competition
Large and small businesses use data analytics to make informed decisions, increasing competition for quality candidates. This demand for data analysts is likely the main reason for the lack of data analysts in the hiring market. Many companies prioritize this aspect of their business, making it a crowded market as all these organizations compete for the best analysts.
Lack of leadership
In any new career field, there is usually a lack of standardization or control. Many employment sectors have governing bodies that help aspiring candidates while connecting bosses with future employees. The data analytics industry needs an organization to regulate, certify, and train the next generation of data analysts. Such a group can also promote networking opportunities and set up recruiting pipelines—mainly lacking in this area—making it difficult for companies to find the people they need.
How to find data analysts for your business?
Due to the talent shortage, finding data analysts for your company may not be easy. However, there are some actions you can take to improve your risks of finding suitable workers. These techniques include rethinking how many data analysts your business needs and considering what existing talent resources you can leverage in this area.
Hire from within.
Hiring external candidates is more expensive than hiring internally, which saves time and can be an ideal solution when there is a shortage of external candidates. Plus, an internal employee will already have an understanding of your company’s culture, people, and processes, meaning you’ll have to spend less time on onboarding procedures for new employees. However, for this option to succeed, you must take several steps.
First, you must identify existing employees with the skills and interests required to become a data analyst. As mentioned earlier, the data scientist role is a highly skilled position. If hiring from within, you’ll likely need to train your employee to become a full-fledged data analyst. They will need time to develop the skills to perform data analytics tasks. But with patience and proper training, current staff can fill this critical gap.
Redefine the role of the data scientist.
Hiring an entire team of data analysts is expensive, and the talent shortage makes it difficult to find many qualified people easily. Fortunately, sometimes, a company can rely on multiple data experts (or even just one) added by employees with different backgrounds. Some steps required to perform data analysis can even be delegated to less skilled staff who may have a free period to fill on such projects.
For example, if you have at least one data analyst who can develop a better data collection method, a less qualified employee can do the collection work. Then, once the data is collected, the analyst can supervise a less-skilled team that looks for common errors, corrects data formatting, and removes duplicate records. This way, you don’t have to hire multiple data analysts to perform each step of the analysis process; instead, you can use some of the stuff you already have.
Combine external work and internal development.
Sometimes, the best approach to developing a capable workforce combines external work and internal development. This dynamic works best for a business building a data analytics division from the ground up. Hiring at least one skilled data analyst with management skills is an essential first step. This outsourcing can be a valuable resource for developing and defining how to run your business and manage your data without hiring many experts.
Here are some shared ways a single Data Analysis can work with your existing staff to meet your company’s data analytics needs:
Sales team. A data analyst can identify and grow data collection devices that your sales team can use to perform daily sales tasks such as calls and inventory.
Customer service. A Data Analysis can find many uses for customer service data. This department can identify product problems, collect customer data, and provide information about public perception of the business.
Human Resources: Recruiting typically requires a lot of data. Your HR team can work with an analyst to interpret this data and thereby improve the efficiency of your hiring process.
Define your business goals.
Data Analysis is a diverse field, so it is essential to determine how your business wants to use data analytics to develop or improve its operations. This step can narrow the search for suitable data analytics candidates during hiring. For example, if you want to look at customer retention data, try to hire a data analyst with experience working with customer service data or conducting customer surveys. If you hire exactly what you need, rather than focusing on data analysts, you’re more likely to find the right person for the job.
