By Craig Stephen, Senior Vice President, Research & Development at Oracle Labs and for Java Platform Group and Oracle Digital Assistant
There are plenty of ideas floating around to spur innovation. The challenge is selecting the ones with the potential to increase profits, reduce costs, and improve customer experience. At Oracle Labs, we’ve developed a technique for addressing this challenge. At the start of every new project, we connect the work we are doing to a specific business problem—some real-world pain that we or our customers are experiencing, including all its hard-to-solve realities.
That effort is difficult, and it takes a lot of management support. But it forces researchers to collaborate closely with business stakeholders, who, in turn, must clearly articulate their challenges and requirements. The work pays off: It helps us discover problems worth solving.
Yet even with that pragmatic approach to pursuing big ideas, organizations will face multiple challenges. One hurdle is figuring out how to scale innovation so breakthroughs don’t benefit a single department or business unit but can instead be applied across a broad range of a company’s interests.
We at Oracle Labs found a way to achieve this goal years ago, when we realized that machine learning (ML) and artificial intelligence (AI) have the potential to address scores of business problems and opportunities.
At the start of every new project, we connect the work we are doing to a specific business problem.”
For example, Oracle Digital Assistant combines speech recognition and natural-language processing so that customers can engage with Oracle’s applications by asking questions, issuing commands, or engaging in complex dialogues. The question for us was: How can we take advantage of these techniques across Oracle’s broad technology portfolio? After all, understanding and answering questions from database administrators is quite different from, say, responding to HR professionals involved in the hiring process.
Our solution: Rather than creating agents for each Oracle application, the Oracle Digital Assistant team developed a common toolbox with core intelligent agent technology. Development teams across Oracle can now easily use that toolbox to build a foundation for new capabilities tailored to the unique needs of individual markets. Oracle is the steward of its customers’ most precious asset: their data. We’re continuously searching for ways our customers can use ML to derive ever greater value from their data.
This highlights a second question faced by enterprise executives when applying breakthrough technologies such as ML and AI to real-world business goals: how to quickly embrace new features as the technologies continue their rapid evolution. We’re solving that by embedding people from Oracle Labs in product development teams. The technical people and businesspeople come together to discuss how image recognition and natural-language understanding, for example, open up new enterprise use cases. Together they explore ideas and build proofs of concept for those use cases with the highest potential.
My staff members make fun of me, because every time I speak to them as a group, I remind them of our mission: to find answers for the biggest real-world problems and opportunities businesses face. But I’ll continue to laugh right along with them if it focuses us on developing game-changing solutions that have positive impacts on enterprises. You never know where the next innovation will come from, but focusing on actual customer needs makes the search much easier.
Photography by Bob Adler/Getty Images