Leading Digital Transformation

The role of data in digital transformation

Digital transformation is a word that has been thrown around a lot over the past decade – some might even call it a buzzword at this point. But it’s still something that’s crucial to organizations as technology rapidly changes the way we do business. We sat down with Donna Hamilton of Alliant to discuss what digital transformation looks like in today’s global economy and how companies can use data to power their business decisions and stand out from the competition in an increasingly competitive market.

Meet the expert
Donna Hamilton
Donna Hamilton
SVP, Data Strategy, Alliant

Donna Hamilton is a highly skilled data strategist and a catalyst for innovation. Her thought leadership and commitment has led Alliant’s digital transformation, enabling marketers to diversify their efforts with a range of multichannel data solutions. She continues to evolve Alliant’s product suite and drive client success by constantly improving upon solutions, developing strategic partnerships and ensuring the compliant use of data. Donna came to Alliant following a successful 14-year career with Millard Group and InfoGroup, where she worked on business development efforts to transition traditional mailers to email, online, mobile, database, and modeling programs. Donna holds a B.B.A. in Marketing from National University, San Diego, CA.

1

How would you define “digital transformation”? Why is digital transformation important to a company’s growth?

Digital transformation goes beyond what products & services a company offers, markets and delivers. It’s about how a company transforms their internal operations to take advantage of new technologies, from advanced data integration and CRM tools to cloud processing. The ability to efficiently process massive amounts of digital data enables a company to be more competitive and create more seamless cross-channel customer experiences.

2

What role does data play in digital transformation?

Harnessing data is foundational to everything, but just collecting data will not automatically lead to transformation. There needs to be a strategy in place to maximize the value of the data and have it translate to improved operations and customer experiences. We keep hearing about disparate data sets that companies need to connect and I think some brands are further along than others. With the sea of changes going on in industry though, the window to get moving is shrinking.

3

How can companies keep their data clean, accurate and actionable in order to best facilitate their digital transformation?

Organizations have many sources of data, from the web and e-commerce, loyalty programs, to promotion and response data. They are trying to identify the data at their fingertips but often have trouble organizing and mining it. A centralized repository of metadata, or data dictionaries, will help them going forward. Knowing what data your company is capturing across the entire business, the accuracy and proper use of the data is critical. Additionally, roles for data governance and strategy that specialize in these areas are needed to ensure all that’s required for data accuracy and compliance. In addition to internal resources, companies can look to external sources that can be used to validate accuracy or enrich a marketer’s data assets.

4

What are some of the common barriers you see that are stopping companies from achieving digital transformation?

Sometimes it’s just a matter of not knowing where or how to get started. It takes a large commitment of resources including time, expertise and investment and it can be hard to take away from current priorities to make it happen. There needs to be alignment at the leadership level to make it a priority, and then get buy in from their broader teams.

5

What tools can they use to overcome these barriers?

A future-proofed strategy centered around data will require a balance of tools to manage 1st party data, as well as a network of trusted partners to support and advise. This can include customer data platforms (CDPs), data cooperatives (like Alliant), data collaboration platforms (i.e. Snowflake, AWS) and other identify resolution solutions.

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