The design stage of the software development lifecycle has never been more important. But getting design ‘right’ is much easier said than done. Views on an ‘optimal design’ will likely vary among IT, finance, operations and sales-and-marketing teams, for example. Being as data-driven as possible to identify both problems and solutions is critical. Advanced telemetry and statistical analysis can be harnessed to identify points of user friction and user actions that work against the success of the enterprise.

Data can play a critical role in solving some of today’s design challenges by helping organizations identify and understand precisely how users prefer to interact with system capabilities and features. Timely insights and feedback based on customer and employee data can reveal existing pain points and how to enrich design to make it truly user-centered.

Ecommerce firms are especially good at this, often using insights from psychology and behavioral economics to discover problems that users aren’t even consciously aware of. For example, an e-commerce business could discover that a particular shade of orange prompted customers to buy more, act more quickly and abandon less often.

They could use data to surface and isolate the problem (button color), and experimental design techniques such as A/B testing and randomized control trials to land on a solution. The only thing stopping enterprises from yielding similar insights from their users is the limiting belief that such things have only isolated applications.

Beyond the critical need to focus on customer data, data-based employee insights can position businesses to engage with and enable employees in powerful new ways that enhance productivity and efficiency. This is particularly significant as businesses everywhere work hard to recruit and retain critical skills amid ongoing labor shortages in today’s hypercompetitive global job market.

Digital twinning is also being used effectively to create digital business models that demonstrate what organizations can do to enhance processes, applications and user experiences, analyzing data from various sources to reveal specific and timely opportunities for improvement.