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Most firms struggle with data and systems integration. The firms that successfully navigate these challenges become industry leaders. In a recent webcast, VettaFi CMO Jon Fee, J.P. Morgan Asset Management’s Danius Giedraitis, and Microsoft’s Gaby Marano discussed how asset managers can turn data into sales.
Jon Fee kicked off the virtual event with brief remarks on the value of data and introduced his co-panelists. Fee said, “Data used wisely can make your organization so much more effective and efficient at the same time.”
Marano and Giedraitis introduced themselves and shared their data “a-ha” moments. “When I first started in the industry, data was a foreign language,” Giedraitis said, sharing how it later became the driving force behind the firm’s distribution strategy.
Gut decisions or decisions based on optics have their place, but Fee noted information stored in someone’s “gut” can’t be shared across a team, whereas data can.
Financial services lags when it comes to using data to drive distribution and growth. Yet organizations that leverage customer behavioral data outperform peers by 95% in sales growth and more than 25% in gross margin, according to McKinsey & Co.
Giedraitis commented, “There are probably some things that are far along relative to other industries, but there’s a lot of opportunity to do things more thoughtfully.” Though the finance industry has come a long way in regard to data, Giedraitis sees plenty of room for improvement and innovation.
In contrast, Marano noted GPS apps and even food service apps are quite advanced in their data usage and deployment, saying, “I think that sets the bar really high on the consumer side.” In other words, there are industries that are further along in their data maturity journey, and those industries know when to use data to push their consumers to make a purchase. Uber Eats or Seamless will ping consumers when their usual go to restaurants are having a special deal at a time when the data says the customer could be most eager to purchase, as an example. Looking at finance, she added, “Those using AI are closing 10% more pipeline.” Marano continued, “The numbers are there.”
Fee offered that there are misconceptions that hijack effective data usage in asset management. The first misconception was “more data equals better outcomes.” Other myths included, “Having data means you are data driven,” and “AI will replace human decision making.”
Speaking to the first myth, Marano agreed. “Getting your data sets to talk to each other is a prerequisite for getting the results you are seeking to drive,” she said. “[If] I had to add one more [myth] I’d say, ‘Data isn’t just numbers, it's text too.’” Language can be data too, and conversations that sales teams have matter.
“Data teams feel like every number, attribute, or field they can report on they should,” Giedraitis said. “With respect to all other metrics, a few metrics matter more.” Finding the metrics that drive the most important signals is critical, and it is easy to get lost in the weeds if you over-engineer. Speaking to AI misconceptions, Giedraitis said “The biggest misconception is people think it will cure all their problems. It won’t.”
Fee shared that the relationship between different pools of data is critical in making informed decisions. “It's never going to be a singular data point, it's going to be multiple data points you are triangulating that give you the trendline that helps you course correct.” When working with clients, he frequently asks what people do when a metric is positive or negative. Many don’t have an answer. “I typically encourage folks to go back and rethink the data that they are pulling.”
Organizations move through multiple phases in their data deployment evolution. Starting from an underdeveloped place, the initial integration of data can provide information from which they can make ad-hoc reactions. At this stage they have no data-specific roles, but they are beginning to see the value of data. From here, companies evolve into being proactive. Proactive companies start thinking about data quality and metrics, eventually becoming “optimized companies” that have data professionals on staff and implement procedures.
Sharing a graphic about the process of becoming an underdeveloped organization when it comes to data use, Marano said, “The message here is it's a journey, but it requires many foundational pieces to get there.”
Giedraitis added, “You can’t jump from undeveloped to optimized, because that scares people.” It requires a slow articulation toward being optimized. “Crawl before you walk before you run,” he said, sharing the old adage.
“The most important thing is the level of trust in data,” Fee said. When firms, enterprise wide, buy into and trust the data, that leads to success. “There’s a caveat to this — nobody trusts data until they're knowledgeable on what that data means.”
Driving impact demands organizations to buy-in. Giedraitis shared, “What works well is finding the power users, the more data-literate individuals across teams.” These individuals can articulate the value of data from within and help build trust. “Doing that from just a small, centralized group is very hard.”
“Innovation is inherently uncomfortable. In disruptive times, trust is more important than ever,” Marano said. Building trust, camaraderie, and joint visions is crucial to getting an organization on board with building data practices.
Within organizations, some people are “super users,” some are “data explorers,” and some are “time-constrained decision makers.” Each will have a different relationship with data. Super users will try new things and be a champion for new technologies and ideas. But some folks are busy. The time-constrained decision maker isn’t interested in experimenting. “Eventually we try to look and empower each of these people differently.”
There are clearly other personas than these, and unpacking where the individuals in a firm are on their own journey and relationship with data can help firms evolve their organizational thinking and data practices.
Clients engage in products and services in a variety of ways. “Being able to see someone from all angles is paramount,” Marano said. “AI is only as good as the information it has.” Clients and customers are more than just purchases. What events do they attend? How do they behave digitally?
“One of the things that’s important to think about,” Giedraitis said, “is to connect the engagement across these often fragmented systems.”
Marano also noted that sometimes organizations try to measure everything and flip what they are prioritizing frequently. Less can be more, and every decision requires time to pan out. Teams need the right data delivered in the right way to truly drive impact. Answering an audience question, the group agreed that six to eight key metrics is a healthy number. More can be too much, while less can limit the full 360 view.
Mapping out a work system can be helpful for organizations. Fee compared growth to a baton, noting that teams have to pass opportunities to one another and everyone needs to be prepared to give it their all. Automating these systems and being able to pass data around easily and coherently can be a difference maker for an organization.
Within the space of distribution, technology is constantly changing the landscape. Phones, social media, and AI are all big things that have changed the way distribution happens.
Marano said, “I still think we’re in very early innings.” Having machines handle administrative tasks, like taking meeting notes, can help free up time for employees to do what’s most important and interesting about their job. Done well, AI could improve productivity and help manage risk and compliance.
“Doing more with the same is how we’ve been framing it,” Giedraitis said. Transforming client experience and modernizing market and data platforms are green spaces where the tech can improve, but Giedraitis agreed that taking out the “no joy” parts of work can be hugely beneficial.
“I think the AI era is here, and it's here to stay,” Marano said.
Giedraitis added, “Every minute that you wait is a minute that someone else is moving forward.”
Most firms struggle with data and systems integration. The firms that successfully navigate these challenges become industry leaders. In a recent webcast, VettaFi CMO Jon Fee, J.P. Morgan Asset Management’s Danius Giedraitis, and Microsoft’s Gaby Marano discussed how asset managers can turn data into sales.
Jon Fee kicked off the virtual event with brief remarks on the value of data and introduced his co-panelists. Fee said, “Data used wisely can make your organization so much more effective and efficient at the same time.”
Marano and Giedraitis introduced themselves and shared their data “a-ha” moments. “When I first started in the industry, data was a foreign language,” Giedraitis said, sharing how it later became the driving force behind the firm’s distribution strategy.
Gut decisions or decisions based on optics have their place, but Fee noted information stored in someone’s “gut” can’t be shared across a team, whereas data can.
Financial services lags when it comes to using data to drive distribution and growth. Yet organizations that leverage customer behavioral data outperform peers by 95% in sales growth and more than 25% in gross margin, according to McKinsey & Co.
Giedraitis commented, “There are probably some things that are far along relative to other industries, but there’s a lot of opportunity to do things more thoughtfully.” Though the finance industry has come a long way in regard to data, Giedraitis sees plenty of room for improvement and innovation.
In contrast, Marano noted GPS apps and even food service apps are quite advanced in their data usage and deployment, saying, “I think that sets the bar really high on the consumer side.” In other words, there are industries that are further along in their data maturity journey, and those industries know when to use data to push their consumers to make a purchase. Uber Eats or Seamless will ping consumers when their usual go to restaurants are having a special deal at a time when the data says the customer could be most eager to purchase, as an example. Looking at finance, she added, “Those using AI are closing 10% more pipeline.” Marano continued, “The numbers are there.”
Fee offered that there are misconceptions that hijack effective data usage in asset management. The first misconception was “more data equals better outcomes.” Other myths included, “Having data means you are data driven,” and “AI will replace human decision making.”
Speaking to the first myth, Marano agreed. “Getting your data sets to talk to each other is a prerequisite for getting the results you are seeking to drive,” she said. “[If] I had to add one more [myth] I’d say, ‘Data isn’t just numbers, it's text too.’” Language can be data too, and conversations that sales teams have matter.
“Data teams feel like every number, attribute, or field they can report on they should,” Giedraitis said. “With respect to all other metrics, a few metrics matter more.” Finding the metrics that drive the most important signals is critical, and it is easy to get lost in the weeds if you over-engineer. Speaking to AI misconceptions, Giedraitis said “The biggest misconception is people think it will cure all their problems. It won’t.”
Fee shared that the relationship between different pools of data is critical in making informed decisions. “It's never going to be a singular data point, it's going to be multiple data points you are triangulating that give you the trendline that helps you course correct.” When working with clients, he frequently asks what people do when a metric is positive or negative. Many don’t have an answer. “I typically encourage folks to go back and rethink the data that they are pulling.”
Organizations move through multiple phases in their data deployment evolution. Starting from an underdeveloped place, the initial integration of data can provide information from which they can make ad-hoc reactions. At this stage they have no data-specific roles, but they are beginning to see the value of data. From here, companies evolve into being proactive. Proactive companies start thinking about data quality and metrics, eventually becoming “optimized companies” that have data professionals on staff and implement procedures.
Sharing a graphic about the process of becoming an underdeveloped organization when it comes to data use, Marano said, “The message here is it's a journey, but it requires many foundational pieces to get there.”
Giedraitis added, “You can’t jump from undeveloped to optimized, because that scares people.” It requires a slow articulation toward being optimized. “Crawl before you walk before you run,” he said, sharing the old adage.
“The most important thing is the level of trust in data,” Fee said. When firms, enterprise wide, buy into and trust the data, that leads to success. “There’s a caveat to this — nobody trusts data until they're knowledgeable on what that data means.”
Driving impact demands organizations to buy-in. Giedraitis shared, “What works well is finding the power users, the more data-literate individuals across teams.” These individuals can articulate the value of data from within and help build trust. “Doing that from just a small, centralized group is very hard.”
“Innovation is inherently uncomfortable. In disruptive times, trust is more important than ever,” Marano said. Building trust, camaraderie, and joint visions is crucial to getting an organization on board with building data practices.
Within organizations, some people are “super users,” some are “data explorers,” and some are “time-constrained decision makers.” Each will have a different relationship with data. Super users will try new things and be a champion for new technologies and ideas. But some folks are busy. The time-constrained decision maker isn’t interested in experimenting. “Eventually we try to look and empower each of these people differently.”
There are clearly other personas than these, and unpacking where the individuals in a firm are on their own journey and relationship with data can help firms evolve their organizational thinking and data practices.
Clients engage in products and services in a variety of ways. “Being able to see someone from all angles is paramount,” Marano said. “AI is only as good as the information it has.” Clients and customers are more than just purchases. What events do they attend? How do they behave digitally?
“One of the things that’s important to think about,” Giedraitis said, “is to connect the engagement across these often fragmented systems.”
Marano also noted that sometimes organizations try to measure everything and flip what they are prioritizing frequently. Less can be more, and every decision requires time to pan out. Teams need the right data delivered in the right way to truly drive impact. Answering an audience question, the group agreed that six to eight key metrics is a healthy number. More can be too much, while less can limit the full 360 view.
Mapping out a work system can be helpful for organizations. Fee compared growth to a baton, noting that teams have to pass opportunities to one another and everyone needs to be prepared to give it their all. Automating these systems and being able to pass data around easily and coherently can be a difference maker for an organization.
Within the space of distribution, technology is constantly changing the landscape. Phones, social media, and AI are all big things that have changed the way distribution happens.
Marano said, “I still think we’re in very early innings.” Having machines handle administrative tasks, like taking meeting notes, can help free up time for employees to do what’s most important and interesting about their job. Done well, AI could improve productivity and help manage risk and compliance.
“Doing more with the same is how we’ve been framing it,” Giedraitis said. Transforming client experience and modernizing market and data platforms are green spaces where the tech can improve, but Giedraitis agreed that taking out the “no joy” parts of work can be hugely beneficial.
“I think the AI era is here, and it's here to stay,” Marano said.
Giedraitis added, “Every minute that you wait is a minute that someone else is moving forward.”
