Internal paradigm shifts are never easy in a corporate setting, but sometimes they are the only way to point the company in a direction that will help its products and services better satisfy customer needs.
“In recent years, we’ve made great strides at building software tools in a more agile manner, but we saw an opportunity to develop products that are richer and more useful to our customers,” explained Kenya Oduor, Ph.D., director of the user experience team at LexisNexis. “This required putting in place a new process to frame product deliverables more effectively around direct value to users.”
Oduor stressed the importance of technology teams building “empathy” for their customers so they can better understand whom they’re designing products for and what those users are trying to accomplish with the products.
“It’s important to define in advance what success looks like for your customer so that every step you take in software design and development is aligned with what that customer values,” she said.
Oduor explained that LexisNexis is now using a “design thinking framework” that brings together professionals from its product management, user experience, and engineering teams, as well as input from customers within various types of organizations. This is an approach that has been slow to emerge in the corporate IT world, but is now gaining traction in the development of business software applications.
“In the past we were focused on faster and more efficient execution in software development, but with this paradigm shift we’re trying to ensure that design thinking complements agile development,” said Oduor. “The key difference is we’re no longer building product features based on a list of requirements that a product manager hands to us. We’re now collaborating with our colleagues to understand our customers’ challenges and needs, then we go out and design tools that meet those needs.”
A recent example involved the development of Lexis DiscoveryIQ, a new enterprise eDiscovery software platform that leverages the power of machine learning to help litigation professions predict relevance of documents in the early stages of the eDiscovery workflow.
“When we met with colleagues and prospective customers to discuss their specific pain points, it was clear that users of the software really needed more transparency into how our product’s ‘brain’ was making relevance predictions,” said Oduor. “We used that input to design the software in a way that allowed users to feel more comfortable with the use of machine learning and the outcomes they obtained from the engine. In fact, we’re continuing to work on ways to increase the transparency in machine learning so that users have more control over how the software is put to work for them and ultimately improves outcomes.”
Oduor advised that it’s essential to have both “bottom-up” and “top-down” buy-in to the design thinking framework in order for the paradigm shift to happen. “After all, it’s important to make sure that your new software development processes fit together in a complimentary fashion, without negatively impacting your existing business operations,” she said.
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