Make Sense of The Improvement Data You Collect

Posted by on Oct 27, 2019 in Continuous Improvement, Data Collection, Organizational Goals, Process Improvement | 0 comments

Most organizations can honestly say they have an abundance of data, but many flounder when it comes to having the right information to lead their companies to improvement.  We collect data on all kinds of things but we rarely take the time to analyze it properly to learn what it tells us.

Some Basics Regarding Data

First of all, data is all around us!  Everything we do produces data, every action, every process, and every system we interact with produces some kind of data.  It’s available and we can capture it if we want.  But a lot of it is not worth capturing and it just ends up confusing us and causing us to get side tracked doing something that is often of very little value.

It’s important that we determine what data are important to gather.  One place to start is with the customer.  What indicators tell us if we’re routinely serving our customers’ needs and delighting them?  Other areas are those in which you feel pain.  What indicators do you have in place that will help you monitor the causes and occurrences of known, chronic problems?

When you review these indicators, it’s important to remember that they will vary day to day.  You should analyze the data and take care to do it in such in a way that it allows you to see the range and variation of your data and its’ affect on your systems.

Guidelines for Data

There are four types of data: opinion data, observable data, results data, and process data.  Opinions are what people think and are related to the feelings they have for products or services which often leads them to buy the product or service.  Observable data comes from seeing what is going on and recording it.  Results data are the end-all after everything has happened and what you’re left with when products are manufactured, services delivered, errors are made, deliveries are missed, scrap and rework occurr, etc.  You cannot avoid these results because they have already occurred.  You can only hope to do better next time.  Process data are those that are early indicators such that we can make an adjustment to the process before some undesirable result occurs.

Before Collecting Data, Start With a Purpose In Mind

Purpose is a necessary ingredient for success.  What is the purpose of measuring the item of interest?  What will you do with the data?  Who will do the measuring?  How will it be recorded?  How will they analyze and interpret the data?  If necessary, you may need to develop operational definitions so that everyone taking the data has a common understanding of what’s acceptable and what is not.  You’ll want to make sure the data is gathered properly and analyzed, that it is reliable, consistent, and accurate.

Make sure the data you collect and share won’t create fear and distrust in the organization.  The data collected and the information shared should be used to drive improvement in your organization and not create fear and distrust.

Hints For Getting Started

Here is an six step process to help you get started:

  1. Define your purpose for the data-gathering system you want to put in place.
    • How will you use your data-gathering system to improve?
    • How will it benefit your customers, your employees, and your organization?

2.    Pick a priority measurement target to start.

    • Why is this measurement a priority?
    • What benefit will your and your customer gain from improvement in this area?

3.    How will this measurement fit into the larger system of measures your organization uses?

    • What key customer issue will it address?
    • How does it fit into other key customer issues you’re addressing?

4.    Develop operational definitions.

    • Make sure the measure is properly defined so everyone involved has a complete understanding of what is and isn’t acceptable.
    • Make sure your operational definition addresses the what, how, who, when, etc. to ensure accuracy and consistency of the measurement.

5.    Prepare and plan for data collection.

    • Wherever possible try to stratify your data to capture patterns that may exist due to differences in people, equipment, materials, methods, environment, etc.
    • Decide on the method for gathering your data.  Design and test checklists, data collection sheets, measurement methods, analysis, etc.
    • Make sure to train your data gatherers.

6.    Gather the data.

    • Pilot your process on a small scale.  Iron out any issues before going to a larger scale.
    • When you have this measurement process in place, standardize it to assure it continues as you want it to before moving on to another measurement target.

Leave a Reply

Your email address will not be published. Required fields are marked *