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FIMA Europe Takeaways: AI, Analytics & GDPR

Across industries, data is becoming ever more important. But companies struggle to derive true value from it. While they look to drive more revenue-generating initiatives like customer or client insights, they generally fall short of their ambitions. The key to unlocking data is making it accessible and flexible to open the door to new ways of leveraging it as a strategic asset. 

I recently attended FIMA Europe in London, and one of the main themes to emerge was the ability for organizations to not just gain control and drive more insights from their data but actually create deeper, more useful insights. This could be to generate a greater understanding of how to serve your customers or to ensure you have 360-degree view of your customer with the General Data Protection Regulation (GDPR) deadline looming.

Data and analytics 

The topic of data and analytics continues to be a key discussion point. Within many organizations today, the distance and silos between the practice of data “management” and the practice of data “analytics’” is far too large. What’s more, chief data officers (CDOs) themselves often fall into one of two groups. On the one hand, you have the traditional CDO (CDO 1.0) mentality where the focus is on data standards, governance and control. On the other hand, you have a CDO (CDO 2.0) who relies more heavily on analytics to help define business strategies.

Neither of these approaches help CDOs or organizations gain better control of data flowing in and out of the enterprise. That’s not to say that a CDO shouldn’t worry about the traditional data management responsibilities of understanding data elements, lineage and governance. It’s also not to say that a CDO should ignore the capabilities analytics can deliver either. Rather, it should be the aim of any CDO to align these two approaches or silos within an organization so data and analytics work together.

Without such an alignment, you might have the tools and analytics capabilities to generate insights, but those insights may not be as accurate or reliable without the proper governance standards in place. Similarly, if you’re solely dedicated to controlling data, you’re missing out on the enormous opportunity analytics can deliver such as customer behavior insights. 

GDPR is coming 

Bridging the gap between data and analytics will also play a significant role when GDPR comes into effect on May 25, 2018. GDPR presents an obligation to respect and keep an accurate and complete record of a customer’s data in a way that is safe and secure. It also gives the customer the right to be forgotten.

However, you cannot uphold these standards and “forget” a customer if you don’t know where all of their data lives and comes from within the enterprise. While meeting GDPR requirements will certainly be a major challenge for many organizations, it also provides an opportunity to revamp your data infrastructure.

In many respects, data professionals are often defensive when it comes to governing and managing data. But with GDPR, there is an opportunity to be proactive and more aggressive, using it as a business driver to effectively manage and store your data, which in turn enables you to optimize analytics pulling out meaningful customer insights to create effective customer journeys.

While the laws are different globally, this type of data approach can take a global view and give the opportunity to drive data governance, compliance and analytics more holistically across the organization.

Overcoming challenges 

With many organizations tasked with establishing better control over their growing data while trying to generate insights from both structured and unstructured data, challenges remain. What particularly makes this a tall order is the bottlenecks created from legacy systems and architecture in terms of understanding where data elements have or should come from.

A good starting point for any organization begins with a focus on the basics. This includes making sure you understand your underlying data architecture and overall data quality. Next, start thinking about where your data lives and the different types of information in your possession. What insights can you derive from this data? How can it be efficiently accessed and utilized across the organization (compliance, analytics etc.).

With a handle on these core elements and an alignment between data and analytics, you can build a strategy and rationalize what advanced tools you need leverage to gain better insights from structured and unstructured data, which may include tools such as robotic process automation (RPA) and machine learning.

Author

Paul Gibson, Business Consultant
Paul Gibson is a Business Consultant currently based in New York. As part of the Sapient Consulting strategy team, he conducts research and devises strategies for exploring potential investments and strategic alliance opportunities in the form of partnerships and acquisitions. Paul has extensive experience in how new business and regulatory drivers are impacting the capital markets industry.