Six step process of Data Analysis

Hello Everyone

In this Blog, I’m going to briefly go over the the required steps to follow while you’re working on a Data Analysis project.

The six steps of the data analysis process that you have been learning in this program are: ask, prepare, process, analyze, share, and act . These six steps apply to any data analysis. Continue reading to learn how a team of people analysts used these six steps to answer a business question.

An organization was experiencing a high turnover rate among new hires. Many employees left the company before the end of their first year on the job. The analysts used the data analysis process to answer the following question: how can the organization improve the retention rate for new employees?

Let’s break down what this team did, step-by-step.

First up, the analysts in our example needed to define what the project would look like and what would qualify as a successful result. So, to determine these things, they asked effective questions and collaborated with leaders and managers who were interested in the outcome of their people analysis.

It all started with solid preparation . The group built a timeline of three months and decided how they wanted to relay their progress to interested parties. Also during this step, the analysts identified what data they needed to achieve the successful result they identified in the previous step - in this case, the analysts chose to gather the data from a survey of new employees. They identified specific questions to ask about employee satisfaction with different business processes, such as hiring, onboarding, and compensation. Rules were established for who would have access to the data collected, what specific information would be gathered, and how best to present the data visually. The analysts brainstormed possible project- and data-related issues and how to avoid them.

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The group sent the survey out. Great analysts know how to respect both their data and the people who provide it. Since employees provided the data, it was important to make sure all employees gave their consent to participate. The data analysts also made sure employees understood how their data would be collected, stored, managed, and protected . In order to maintain confidentiality and protect and store the data effectively, access was restricted to a limited number of analysts. Collecting and using data ethically is one of the responsibilities of a data analyst. Then the data was cleaned up to make sure it was complete, correct, and relevant, and uploaded to an internal data warehouse for an additional layer of security.

Then, the analysts did what they do best: analyze! From the completed surveys, the data analysts would discover that a new employee’s experience with the hiring process was a key indicator of overall job satisfaction. The analysts found that employees who experienced an efficient and transparent hiring process were most likely to remain with the company. Employees who experienced a long and complicated hiring process were most likely to leave the company. The group knew it was important to document exactly what they found in the analysis, no matter what the results. To do otherwise would decrease trust in the survey process and reduce their ability to collect truthful data from employees in the future.

Just as they made sure the data was carefully protected, the analysts were also careful sharing the report . For example, in order for a manager to receive the survey report, a minimum number of their team members had to have participated in the survey. The group presented the results to leaders first to make sure they had the full picture, then asked them to deliver the results to their teams. This gave leaders an opportunity to communicate the results with the right context and have productive team conversations about next steps.

The last stage of the process for the team of analysts was to work with leaders within their company and decide how best to implement changes and take actions based on the findings. The analysts recommended standardizing the hiring process for all new hires based on the most efficient and transparent hiring practices. A year later, the same survey was distributed to employees. Analysts anticipated that a comparison between the two sets of results would indicate that the action plan worked. Turns out, the changes improved the retention rate for new employees and the actions taken by leaders were successful!

Thanks for reading.

Happy Learning.