Digitization, digitalization, and digital transformation: what is the difference?

The insurance business is data-driven: all operations, whether policy administration, claims processing, or fraud detection, require data. Mountains of data.

Data is the key to unlocking insights, powering innovation, and driving growth. For insurers, data is especially critical, given the nature of the industry. Accurate data is needed to price risk correctly, assess liability appropriately and pay claims promptly. Yet despite its importance, data has largely remained locked away in legacy systems, inaccessible and unusable.

This is no longer the case. Thanks to advances in technology, data is now being liberated from its silos and is being put to use in new and exciting ways.

The buzzwords associated with this data liberation are "digitization," "digitalization," and "digital transformation." But what do these terms really mean? And how do they differ from one another?

The difference between digitization and digitalization might seem small, but it makes a significant impact. This is not just a matter of word choice — it's a question of scope and potential value to your business.

It's becoming more important than ever to understand the distinctions between these three approaches.

Digitization vs. digitalization vs. digital transformation: the three approaches to data

Defining digitization

In the past, data was largely unstructured and paper-based, making it difficult and time-consuming to access the information needed to make decisions and take action.

Data digitization was the first approach that began to address this problem. Data digitization is the process of taking data that exists in an analog format and converting it into a digital format.

This can be done using a variety of methods, such as scanning paper documents into an electronic format, or using specialized software to convert audio or video recordings into digital files.

The goal of data digitization is to make data more accessible and useful by making it easier to store, search, and share.

However, data digitization is only the first step in making data more accessible and useful. The data still needs to be organized and structured in a way that makes it accessible.

This is where the next step in the process, the digitalization comes in.

Defining digitalization

Digitalization is the process of taking data that exists in a digital format and making it more accessible and useful for the business.

Digitalization typically involves organizing data into a database or data warehouse, making the data more structured and easier to query. It also makes it possible to run analytics on the data to generate insights.

Digitalization goes a step beyond data digitization by organizing the data and  making it more usable. However, it does not necessarily change the way that data is used.

For example, a company might digitalize its customer data and then use that data to generate insights about customer behavior. However, the company might not use those insights to change the way it interacts with customers or sells products. Digitizing data doesn’t necessarily means acting on the insights it generates.

In this case, data has been digitized and digitalized, but the business hasn't digitally transformed.

Defining digital transformation

Digital transformation is the process of using technology and digital data it generates to change the way a company does business.

Digital transformation typically involves collecting data digitally from the get-go, using data to automate processes, improve customer experience, or develop new products and services.

For example, a company might use data to develop a new pricing model that is more responsive to changes in customer behavior, or to automatically route customers to the best-suited customer service representative.

[.emph]In short, digital transformation goes beyond data digitization and digitalization by changing the way data is used to drive business value.[.emph]

The three approaches to data: which is right for your company?

The answer to this question depends on your company's digital maturity and is also a matter of scope.

If your company still relies on analog data such as paper forms, then data digitization is the right place to start. This will give you a foundation on which to build more sophisticated data-driven processes and applications.

If your company has already digitized its data, then digitalization may be the next logical step. This will make your data more accessible and useful.

And if your company is looking to use data to drive business value, then digital transformation is the right approach.