Digital Transformation and Data Quality

The term “digital transformation” has been around for quite a while, but the meaning has changed over the years. People first talked about digital transformation as a way to replace traditional paper documents with non-printed alternatives.

As technology advanced and access to data exploded, digital transformation has become a term that describes a revolutionary way to run your business. Traditional business models are fading from the scene. The evolution to digital organizations has already begun, is progressing rapidly, and is fueled by data. Your data better be ready.

The two biggest challenges to digital transformation are an explosion of data and the lack of quality data organizations have on hand. Data by itself has little value. Context turns data into information and from information comes insight which allows a company to take action. None of these steps is possible if the data is a mess.

It takes work to combine data from multiple sources, eliminate duplicates, and standardize data formats. Analysis, insight, and automated intelligence can only be useful if the data is consistent and reliable. Great data quality software cleanses, standardizes, and enhances the data for you, making data quality the first step in data transformation projects.

Once you’ve taken data-enabled actions such as customer experience improvements, you’ll be creating more data from A/B tests and customer feedback. This data will feed into your analytical processes and affect decisions about future actions.

So why are companies so hot about digital transformation? What do they expect to accomplish?

Most organizations cite customer experience improvements, personalization, and leveraging the power of artificial intelligence as the benefits they anticipate from embracing the concept of a digitally powered enterprise. They are racing at full speed towards a digital-first environment. To compete, companies must make decisions quickly and be ready to jump on new opportunities as they arise. Bad data can lead you down a dangerous path – especially as organizations rely more heavily on decisions guided by artificial intelligence.

A superior customer experience relies on a complete and accurate view of each customer’s activity and their relationship with the company. Few organizations have developed this single customer view. Again, data quality is a precursor to success in this area. Companies can’t begin to correlate internal and external customer behavior metrics until they’ve cleaned and standardized the data.

Personalization is another area where inaccurate data can damage customer relationships instead of bolstering them. The aim of personalization is to foster individual relationships with each customer. Mistaking a customer’s gender or mismatching their buying history or stated preferences sends the opposite message – the organization doesn’t really know their customers.

A single customer view requires organizations to match and combine data from multiple sources.

Before embarking on enterprise-wide projects, organizations should have data management policies in place and invest in the tools necessary to comb through their vast collections of unrelated customer data. Firstlogic’s DQ10 Software Suite includes the modules you’ll need to get your data ready for your digital transformation. Contact us at Firstlogic to learn more about how our data quality software can be an integral component of your digital transformation initiatives.