8 Game-Changing Lessons from Advertising Week 2024
At this year’s Advertising Week, our panel titled Changing the Game by Getting Back to Basics explored the impact of data standards on modern marketing and business strategies.
Experts including Lauren Fisher from Advertiser Perceptions, Natasha Templeton from AWS, Parvati Vaish from Havas Media Network, and Annie Stickney from JPMorgan Chase shared their experiences and insights on why establishing clear data standards is critical for achieving better ROI, enhancing AI efforts, and reducing business risks.
Here are eight big takeaways from our conversation. 👇Scroll down to watch.
1. Start with Use Cases, Not Standards
A common mistake is to implement data standards for the sake of compliance rather than aligning them with clear use cases. As Parvati Vaish advised:
“Start with use cases—what you’re trying to accomplish. That way you start with the right idea and build toward the end goal.”
Identifying specific business needs first helps teams understand what data they need, how it should be organized, and who will use it, making the adoption of standards more meaningful and aligned with business goals.
2. Excel Is Convenient—But It Carries Risk
Despite all the advanced tools available today, Excel is still widely used across organizations for data management. Its familiarity makes it the default choice, but it creates inefficiencies, silos, and privacy risks. Panelists like Natasha Templeton encouraged teams to start moving beyond Excel:
“Exel is an easy button. But you need to consider it from a lens of data security and privacy and everything that’s at stake—the cost of doing business there.”
To drive change, they recommended starting small—test new tools and processes with isolated use cases and build proof of value before scaling.
3. Data Standards Prevent Costly Mistakes
Annie Stickney put it bluntly:
“Without data standards, I have lawsuits. I have millions of dollars that are worthless. With data standards, I see real-time actionable insights we can optimize on.”
When data standards aren’t in place, businesses risk financial losses, legal issues, and skewed analytics that misinform strategy. Clean, well-organized data is essential to drive real-time, actionable insights. This clarity helps optimize campaigns, improve customer experiences, and support more informed decision-making.
4. Use the 1-10-100 Principle
Natasha Templeton introduced a powerful concept for understanding the cost implications of poor data management: the 1-10-100 Principle:
- $1 to prevent a data issue,
- $10 to fix it after processing, and
- $100 to correct it once it impacts customers.
This framework – which some argue has grown to $10-$100-$1000! – underscores why investing in preventive measures is not only practical but vital. Addressing data quality issues early on saves significant time, money, and resources.
5. AI’s Success Depends on Data Quality
AI is often touted as the future of marketing and analytics, but its effectiveness is directly tied to data quality. Parvati Vaish emphasized:
“If you want to do exciting, cool, new, innovative things, but in a way that’s ethically sound, you need data standards. Because AI models can be biased. They can point you in the wrong direction for the wrong decisions if you don’t have high quality data going into them.”
Without a foundation of clean, standardized data, AI models risk amplifying biases or producing flawed outputs. Establishing data standards is not only about efficiency; it’s about making AI more reliable and impactful.
6. ROI Isn’t Just About Efficiency—It’s About People
Think this is just about data? Surprise! There is a big connection between data standards and employee satisfaction. Parvati Vaish explained that clean data not only improves ROI but also frees up talented teams to focus on strategic work rather than manual cleanup:
“There’s a return on investment in people because now you can move your brilliant minds away from handling data cleanup to more important work, like actually finding insights.”
Investing in data standards can also help retain talent by making their roles more impactful and fulfilling.
7. Find a Data Champion at the Leadership Level
Implementing data standards requires buy-in across teams, but it’s crucial to have a champion at the leadership level. Lauren Fisher noted that having someone with authority push data initiatives can help drive change faster and ensure consistent adoption:
“You need a champion at the organization, someone high up who is going to push this through.”
Having a champion not only sets the tone for adoption but also reinforces the importance of data quality as a strategic asset.
8. Leverage Your Partners for Support
Implementing data standards can be daunting, but companies don’t have to go it alone. Natasha Templeton encouraged brands to rely on trusted partners—agencies, systems integrators, or tech providers—to facilitate the transition:
“Don’t be afraid to take off these bite-sized chunks and try new technologies. Reply on partners who can guide you and help evaluate different tools.”
Collaboration with partners can provide the guidance, tools, and proof of value needed to ensure data standardization efforts are successful and sustainable.
Data Standards as a Strategic Advantage
This year’s session underscored the importance of data standards as more than a technical necessity—they’re a strategic advantage. From preventing risks to enabling innovation and improving ROI, data standards play a pivotal role in driving modern marketing success.
The key is to start small, align with clear use cases, and bring the right stakeholders on board. With the right foundation, businesses can unlock the true potential of their data and take a step forward in today’s fast-evolving digital landscape.
Are you ready to start your data standardization journey? Talk to our team.