Danielle Crop is the former Senior Vice President and Chief Data Officer of American Express and Albertsons Companies. In these roles, Danielle was responsible for realizing the potential of large, complex data assets to drive revenue and create the world’s best customer experiences. Throughout her career, she has held a series of multi-market roles within the areas of fraud risk management, merchant and cardmember demographics, payment and network data, and global digital products for new cardmember acquisition. She has a strong background in analytics, data management, modeling, digital experimentation, as well as scaled agile digital transformation and product management.
Recently, in an exclusive interview with Digital First Magazine, Danielle shared her insights on the importance of data science in today’s digital era, personal career trajectory, significant career milestones, and much more. The following excerpts are taken from the interview.
Do you think that data science is perceived to be more important than ever before? And what has been the impact of AI on data science?
Absolutely, the advent of the Cloud has brought data science to the fore like never before. The purpose of the Cloud is to bring data together in near real-time across different experiences to create cohesive and contextual decision-making. Remove data science, and this would be impossible. The speed, scale, and interconnections of the data enable entirely new algorithmic approaches. To achieve these goals, data scientists need to be provided with new tools and techniques, meaning a whole new industry of sophisticated processes and tools arise to foster the creation and deployment of data science models (AI/ML Ops). And like before the Cloud, delays or incorrect decisions occur when the data is not accessible, appropriately formatted, labeled, and understood.
What can organizational leaders do to promote a data driven decision-making culture in organizations?
First, they need to understand the importance of accurate and usable data and support investment in foundations, such as data management and governance. Data engineering is not sufficient, it’s main function is to move data from one place to another, not to ensure data is usable or accurate. Second, they need to invest in tools and training to enable data literacy for the organization, such as cataloging, lineage, usable business insights, etc.… Simply making data available is not enough. If it’s not accurate or understandable, individuals will simply make poor decision with inadequate data. There is no short cut to empowering proper data driven decision making.
Danielle, please tell us about your background path to your current role.
I have an unusual path to the Chief Data Officer role. I began my path by getting an undergraduate degree in Forestry, specifically Quantitative Terrestrial Ecology. I wanted to make smarter and more balanced decisions about the environment through data. In order to further that ambition, I went to graduate school to get a Masters in Statistics. When I finished, I was married, and needed to stay put to support my spouse in finishing his degree in Computer Science. I found a job at a small subprime credit card company. In this job, I realized how much the business could be advanced through the massive data assets. It was empowering. Once my husband finished his degree, I sought out a role at the best credit card company, American Express. I spent nearly 20 years at American Express, doing everything from consulting with our partner banks, to fraud risk management, to data science, and digital and data product management across all 23 markets. I ended my tenure at American Express in the Chief Data Officer role, where I rebuilt that function from the ground up. After achieving that, I looked for opportunities to learn and grow outside of financial services, and I began my Chief Data Officer role at Albertsons Companies. In this role, I built the data function from scratch and in less than 2 years the team is driving over 600M in annual revenue through improvements in Supply Chain, Marketing, Merchandising, and Digital User Experience and that’s just the beginning.
Are there still hurdles chief data officers have to overcome in their roles or are CDOs now accepted in parts of the organizational hierarchy?
There are definitely still big hurdles. The cross functional (i.e horizontal) nature of the Chief Data Officer role is still not well understood. The role of a CDO is to foster a culture of data excellence for the organization, as well as to enable and drive business outcomes in partnerships with the P&L owners. Traditional P&L owners often want to own (or to be perceived as owning) all of the functions that help drive their business. The role of technologies has had over thirty years to mature and it is now taken for granted how essential tech teams are to driving P&Ls, yet the role of the data team is a hybrid function (both business and technological in nature). It can be difficult for traditional CFOs, CEOs, and P&L owners, etc. to understand how data functions directly relate to business outcomes, making it hard for organizations to give proper credit to how much business upside is driven by these teams. On the flip side, sometimes the C-suite wants to micromanage what data teams are doing, which given the cross functional and technical nature of the function, is nearly impossible. The C-Suite understanding how to manage sophisticated data and technical professionals by giving them high level goals and then setting them loose to collaboratively work with business partners is the key. If the leadership does not understand this, they will simply get left behind by those companies that do understand it. Additionally, while the costs of a data team are black and white, the business outcomes are cross functionally owned. If the C-suite doesn’t understand this reality, then data teams appear like a large cost and not a revenue driver for the organization. Culture and respect for different skill sets and collaboration in driving business goals is key to the data team’s success.
Apart from your leadership roles, you are also a Board Member of Habitat for Humanity Central Arizona (HFHCAZ). What inspired you to become a part of this nonprofit organization?
I have been very blessed in my life and career and it is important to me to give back to my community. When the opportunity to join Habitat’s board came up, I jumped at it. Habitat for Humanity Central AZ is the biggest Habitat affiliate in the country and through the Board I am able to help facilitate their mission to put God’s love into action by bringing people together to build homes, communities and hope. Affordable housing is such an important issue today and I’m very happy to be a part of an organization helping to achieve “A world where everyone has a decent place to live”.
What has been your most career-defining moment that you are proud of?
There have been many small moments that have defined my career and I think the key is accepting a challenge when it presents itself. If I had let being the only woman in the room intimidate me, I wouldn’t be where I am today. If I had said “No” when I was scared, I wouldn’t be where I am today. It’s about having confidence that I could learn and grow from challenging experiences, and that I could do valuable and meaningful work everyday.
What is the top data issue that kept you awake at night as a CDO?
That poor data and improper analytics will lead to bad business decisions. The data supply chain is very complicated and it is easy for data to get lost in translation. When incorrect analyses occur it can affect a businesses negatively without them even realizing. There is also confirmation bias, where data is often used to prop up existing theories or agendas, and this can also lead to incorrect decision making.
Where do you see yourself in the next 5 years?
I live in the moment and take challenges and opportunities as they come. I feel that if you set out personal goals that are not flexible, you can be closed to something amazing that you would never have expected. I never expected to be a Chief Data Officer, yet here I am and enjoying it. I focus on doing great work wherever I am, to bloom where I am planted, keep my eyes open, and new and exciting things will come.
What advice would you give to aspiring data scientists?
Learn about quantum computing, it’s where the next exciting phase of data science will occur.