Data Collection Plan

When using the DMAIC methodology, you should create a data collection plan during the Measure phase. You will find that the data collection plan is a useful tool, especially when trying to focus your data collection efforts.

Why Do You Need a Data Collection Plan?

Achieve Context

Simply getting “all of the data” and looking at it overwhelms even the best analysts. In addition to being difficult, you will find that this approach does not yield great results either. Another pitfall: you could interpret the data in an incredibly unhelpful way. Here’s a brilliant 5 min TED talk that illustrates great data analysis flawed by not setting the great context:

Save Resources

How many people work on projects with unlimited resources, no deadlines, and an unlimited budget? Not very many, right? Getting data takes a lot of time and may be expensive. It seems the rest of us need a better way.

Bounds of Reality

It may not be possible to get all the data we want.

This is Six Sigma! We want to be efficient! By creating a data collection plan, you can focus on answering questions with business value. The directed approach helps you avoid locating & measuring data just for the sake of doing so.

“Acknowledging what you don’t know is the dawning of wisdom.” —Charlie Munger

Data Integrity

Data integrity is crucial for data collection and is a huge benefit to creating a data collection plan. You want to ensure the data you’re gathering is complete, accurate, reliable, and consistent. Additionally, a well-assembled plan will give you a sense of security, indicating that you collected the data while adhering to standards and compliance.

Data Integrity ensures that the data accurately reflects the actual observations or measurements and is free from errors, omissions, or biases. Maintaining data integrity is crucial for drawing valid conclusions and making informed decisions based on the collected data.

To ensure data integrity, a well-defined data collection plan typically includes detailed procedures, training for data collectors, data validation checks, and mechanisms to address and correct errors. Implement regular monitoring and quality assurance processes to maintain data integrity throughout the data collection period.

Accuracy

Collect data precisely, reflecting the actual values of the variables being measured. This involves minimizing errors in data entry, measurement, or observation. Data accuracy is essential in data collection.

Creating a data collection plan helps ensure you collect data with minimal error. Some examples of how data collection plans can provide more accurate data include creating a centralized database, establishing procedures to protect data permissions, syncing data sources, etc. If the data occurs in a time sequence, record the order in which it happened. Remove data entry errors, digital data transportation errors, and unnecessary rounding errors.

Processing Tools

Finally, data collection plans are great avenues to implement and manage processing tools within Six Sigma. Certainly, you can purchase and install any tool you want. Various data processing tools cater to different aspects of data handling, manipulation, and analysis.

The choice of tools often depends on the data’s specific needs, scale, and nature. Various online tools are available for data collection across different purposes and industries. The choice of tool often depends on the type of data you need to collect and the specific requirements of your project. However, without a plan that outlines the responsibilities and expectations of the processing tools, they can skew and alter data.

How to Create a Data Collection Plan

Step 1: Identify the Questions we want to answer.

Our data must be relevant to the project. What is your project’s hypothesis? And what are we trying to answer? The entire reason to have a DMAIC project is to improve a process so these questions should be centered around what the reality of your process is. And that’s best discovered by defining the current state.

What happens if we gather data instead of making a data collection plan?

Collecting data ‘just to see what’s out there’ is a poor approach that leads to bloat and wasted effort. It may lead you to collecting the wrong data – or collecting the data a wrong manner. By starting with the questions you want to ask you can then determine what kind of data (and in what manner) would help you definitively answer those questions. This will lead you to higher-quality solutions.

Don’t Forget: A data collection plan begins and ends with people.

To better avoid errors, you should talk to people who disagree with you and you should talk to people who are not in the same emotional situation you are.” — Daniel Kahneman

“When a possibility is unfamiliar to us, we do not even think about it.” — Nate Silver