Detectives and data analysts have a lot in common. Both depend on facts and guidelines to make decisions. Both collect and review evidence. Both are talking to people who know part of the story. And both can even follow some tracks to see where they lead. Whether you’re a detective or a data analyst, your job is to follow the steps to gather and understand facts.
There are six steps that Data analysts use to make data-driven decisions. These steps are as follows:
Ask
Prepare
Process
Analyse
Share
Act
Let us look at what these steps tell to make an efficient analysis.
First, the analysts had to define what the project would look like and what would be considered a successful outcome. So to determine these things, they asked powerful questions and worked with leaders and managers who were interested in the outcome of their people analysis. They asked these kinds of questions:
What do you think new employees need to learn to be successful in their first year on the job?
Have you gathered data from new employees before? If so, may we have access to the historical data?
Do you believe managers with higher retention rates offer new employees something extra or unique?
What do you suspect is a leading cause of dissatisfaction among new employees?
By what percentage would you like employee retention to increase in the next fiscal year?
Everything started with solid preparation. The group created a three-month timeline and decided how they wanted to communicate their progress to stakeholders. Also during this step, the analysts identified what data they needed to achieve the successful outcome they identified in the previous step — in this case, the analysts decided to collect data from an online survey of new hires. These were the things they did to prepare:
They created specific questions to ask about employee satisfaction with various business processes, such as recruiting and onboarding, and their overall compensation.
They set rules for who would have access to the collected data — in this case, anyone outside the group would not have access to the raw data, but would be able to view the summary or aggregated data. For example, an individual’s compensation would not be available, but it would be possible to display salary ranges for groups of individuals.
They finalized what specific information would be collected and how best to present the data visually. Analysts addressed potential project and data issues and how to avoid them.
The group sent out a survey. Great analysts know how to respect both their data and the people who provide it. As employees provided the data, it was important to ensure that all employees gave their consent to participate. Data analysts also ensure that employees understand how their data will be collected, stored, managed, and protected. Collecting and using data ethically is one of the responsibilities of data analysts. To maintain confidentiality and effectively protect and store data, they have taken the following steps:
They restricted access to the data to a limited number of analysts.
They cleaned the data to make sure it was complete, correct, and relevant. Certain data was aggregated and summarized without revealing individual responses.
They uploaded raw data to an internal data warehouse for an additional layer of security.
Then the analysts did what they do best: they analyzed! From completed surveys, data analysts found that an employee’s experience with certain processes was a key indicator of overall job satisfaction. These were their findings:
Employees who experienced a long and complicated hiring process were most likely to leave the company.
Employees who experienced an efficient and transparent evaluation and feedback process were most likely to remain with the company.
The group knew it was important to accurately document what they found in the analysis, regardless of the results. Doing otherwise would reduce confidence 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 to share the message. Here’s how they shared their findings:
They shared the report with managers who met or exceeded the minimum number of direct reports with submitted responses to the survey.
They presented the results to the managers to make sure they had the full picture.
They asked the managers to personally deliver the results to their teams.
This process gave managers the opportunity to communicate results in the right context. As a result, they can have productive team conversations about the next steps to improve employee engagement.
The final stage of the process for the analytics team was to work with leaders within their company and decide how best to implement changes and take action based on the findings. These were their recommendations:
Standardize the hiring and evaluation process for employees based on the most efficient and transparent practices.
Conduct the same survey annually and compare results with those from the previous year.
Reference: https://bit.ly/3NVbMHY
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