The Businessperson’s Guide to Data Harmonization


Share on LinkedIn

What is data harmonization? How does it work, and why is it valuable for your business?

The business world is awash in data analytics. Its flashier aspects get most of the attention: Artificial Intelligence, predictive analytics, and the like. But the truth is that without data harmonization, these technologies can’t perform up to their potential.

What Is Data Harmonization?

It’s a universal truth that decisions (and data analytics) are only as good as the information they are based on. Today, we have more information than ever before. But we have it all over the place, from different sources, collected in different ways, and at different stages of completeness.

When you take all this data and make it work together as a cohesive whole, you’ve got data harmonization. Essentially, data that’s been harmonized has had misleading and inaccurate information removed. It’s then compiled into a single source of truth that an entire organization can use. However, the process behind data harmonization isn’t as easy as it sounds.

How Does Data Harmonization Work?

Stop for a moment and think about all the studies your company has done, how much data you have on hand, and whatever research you have access to. Chances are that each item has been designed to collect data in a slightly different way, for various purposes, and in multiple formats. So while you have a lot of information available, not all of it is readily accessible. And not all of it is compatible.

The data harmonization process turns all these data shards into a complete picture. Here’s a general description of what happens:

Organizational goals and objectives are defined.

Harmonization and research protocols are established that support these objectives.

Studies and other information are selected for harmonization. This includes carefully choosing information sources and documenting their design, the data gathered, the data quality, and the various data formats.

Variables are selected for harmonization. This can be quite tricky, since variables from multiple sources are rarely uniform! A balance has to be struck between practicality (finding information that is similar and works together) and purity (information that corresponds exactly).

The data is processed, converted to a common format where needed, and pooled.

A quality check is run on the data to make sure it has maintained an acceptable level of integrity and validity. If data is misleading or of poor quality, it won’t be much good!

After passing its final exams, the data can be stored for use as needed. Data that has been harmonized is not static; it can continue to be updated, either periodically or in real time.

Now, every part of an organization can access the same up-to-date data. It can be filtered and presented to suit each department’s needs. But what’s the bottom line?

What Can Data Harmonization Do for Your Business?

The first and most obvious benefit of data harmonization is the completeness of the data. Your ‘source of truth’ is richer, more rounded, and more consistent across departments. And as a result, you get full value from your analytics. However, data harmonization can offer still more:

Faster Deployment. Collecting, aggregating, and preparing data takes time. When you use a harmonized data source, you already have a repository of knowledge to draw from, making the deployment of new analytics technologies easier and quicker.

Reduced Expenses. This plays along with the above point: less time is spent on finding data and on implementing new processes. Ergo, less money is spent.

More Agility and Confidence. You don’t have to constantly verify, sort, and quality-check new data; the information is already there, ready to be used. This means that your company can make decisions quickly and confidently.

These benefits are not limited to a single department. For example, suppose you start using harmonized data in your marketing department. As the process matures, you can begin to implement it in other departments. The system continues to add information to its stores, becoming a truly robust source of data.

Remember, data analytics isn’t really about complicated technical processes. In the end, its usefulness boils down to the quality of the data. Data harmonization provides a unified and robust information source that can effectively power your organization’s analytics.

Anil Kaul, Ph.D
I have over 22 years of experience in advanced analytics, market research, and management consulting. Very passionate about analytics and leveraging technology to improve business decision-making. Prior to founding Absolutdata, I have worked at McKinsey & Co. and Personify. Also, on the board of Edutopia, an innovative start-up in the language learning space. An in-demand writer and speaker, I have some articles published in McKinsey Quarterly, Marketing Science, Journal of Marketing Research and International Journal of Research.


Please use comments to add value to the discussion. Maximum one link to an educational blog post or article. We will NOT PUBLISH brief comments like "good post," comments that mainly promote links, or comments with links to companies, products, or services.

Please enter your comment!
Please enter your name here