Why Data Alone Won't Improve Customer Experience
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Why Data Alone Won't Improve Customer Experience

Phil Thomas, EVP Customer Insights Data & Analytics, Scotiabank
Phil Thomas, EVP Customer Insights Data & Analytics, Scotiabank

Phil Thomas, EVP Customer Insights Data & Analytics, Scotiabank

The accelerated adoption of technology amid the global pandemic is forcing companies to adapt to a new dynamic environment at lightning speed. All eyes are on the use of data and AI, given the ability to leverage both for improved responsiveness to customer needs. It’s no surprise organizations across the globe are clamouring to integrate new and emerging tools and technologies, to provide an improved customer experience and advance their business goals. In order to capture the full value of big data however, companies must take a hard look at the foundation they have built to support their innovation.

When Scotiabank started its data and analytics journey in earnest 18 months ago, like many organizations, we had been learning by trial and experimentation, iteratingto perfect our approach towards big data and advanced analytics. While there is no secret sauce for transforming into a data-driven organization, and each journey is unique, we have learned that there are a few simple principles that can help accelerate the progress.

Partnerships

First and foremost, partnerships are paramount. This means shared goals and accountability across the organization.  With customer needs at the center of Business team goals, it is essential that Data, Analytics and Technology teams are also driving towards these objectives. When these partnerships are made across organizations, teams are working in a coordinated effort towards the same North Star.

For example, Scotiabank has not only aligned our Analytics and Data teams under one leader, the decision to share strategic targets and goals with our Business teams, has been a real driver in our ability to respond quickly to changing customer needs. The success of this alignment was most evident during the onset of the pandemic. Scotiabank’s Analytics teams used AI to identify our most vulnerable retail customers impacted financially by Covid-19. For these vulnerable customers, our Business teams quickly built targeted multi-channel outreach campaigns to ensure that our customers had the financial tools necessary to navigate this period of uncertainty.

The goal is that data and analytics is not viewed as something separate from the day-to-day operations of the business. It needs to be embedded into the organization, integrated across customer engagement, customer service and product and service development.  

People and The Organizational Construct

Secondly, people and organization are key. While customer goals are the driving force behind the need for strong partnerships, it is the team that develops and executes the strategy to meet customer goals, that is integral to success. Hire leaders that can build trust and are willing to work with others, as collaboration and developing credibility will be critical to gaining momentum and scaling up integration across the business. Make sure your data, analytics and technology leaders are aligned. Triangulating this leadership will continue to foster the spirit of collaboration, so essential to project execution. Don’t be afraid to right size and re-build. Gain an understanding of the talent on your team and identify where you need to invest or redeploy people, in order to support business strategy and execution.

At Scotiabank, a key part of our strategy has been to build a strong talent pool of data scientists, data strategists, and data engineers, fully integrating them with business analytics professionals who have deep banking knowledge.

Technology

Third, underpinning any good data and analytics strategy and critical to execution is technology. Build a strong foundation and don’t be distracted by shiny objects. Ensure focus is on the practical application of technology. Pay for what you need now, and down the line. We’ve found that designing our infrastructure with the flexibility to scale-up in the future, works best for where we are in our data and analytics journey. Through this approach we’ve been able to take advantage of the benefits of open-source tools and, coupled with disciplined model deployment practices,move quickly to market.

Getting the Basics Right

As the power of data continues to be unleashed to bring added value for customers, AI will be a gamechanger to improve the customer experience, providing customers with the financial services that better suit their needs, while consistently reducing operational costs. Getting the basics right is critical to any data and analytics journey, but once the foundation is built, thoughtful change management is the key to making sure these technologies are seamlessly integrated into operations, and a real business driver for years to come.

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