Using Machine Learning in Smart Business Apps: GoodData’s New Strategy
By integrating data and analyzing it with machine learning, smart business apps can automate some business decisions, according to GoodData.
“By embedding analytics in an application,” the report states, “users will have the correct information put into context for them to access automatically. […] A key differentiator for GoodData’s platform is that it provides a closed loop system integrating data to insight to action.”
GoodData says it sees strong potential for smart business applications is a variety of sectors, including the financial services, retail, healthcare, and accounting industries.
“The applications are limitless,” said Roman Stanek, CEO of GoodData. “By offering insights at the point of work and automating routine decisions, smart business applications enable any organization in any industry to leverage the power of data in streamlining processes, improving business decisions, and accelerating action.”
Use cases include automating claims processing in retail and insurance using machine learning, as well as loan decisions in banking, Stanek said in an interview with RTInsights. “Every time you submit a claim, someone looks at it. Someone is looking at your history and similar cases, and that can be fully automated,” he said.
While formerly such decisions might be subject to rules-based processing, the innnovation is that “the machine is learning from past examples. So it is almost the opposite of a rules-based decision,” Stanek said.
According to a post on their website, GoodData says smart business apps can join business intelligence tools, day-to-day apps, and workflows. Data can be accessible to business users as well as the “data elite”–data scientists and BI teams. The smart business apps are touted as making decision-making easier and faster but not requiring going to another app to check data.
“Smart Business Applications represent the culmination of all we’ve been doing since the company was founded,” Zdenek Svoboda, GoodData’s vice president of platform, said in a release. “Thanks to advances in artificial intelligence and machine learning, we’re able to introduce business users to a whole new analytics experience that’s built around their needs and outcomes, not [just] around the data.”
The post stated that some benefits of embedding actionable insights into Smart Business Applications include:
- Eliminating any bias or irrelevant details (“noise”)
- Making complex machine learning models — the ones that were formerly reserved for analytical elites — available across the organization so that everyone can put data to work for them
- Making incremental improvements to decision-making processes that can lead to substantial bottom-line benefits over time
The company stated that it believes that integration is key to making analytics more user friendly.
“We don’t want people to know that they are using analytics per se; it’s a part of their daily workflow. By building analytics and machine learning into the apps they already use, we not only offer data-driven insights where they’re needed — at the point of work — we can also automate repetitive, low-level decisions, freeing users to focus on more complex problems,” said Stanek.