The Product Design Process and Data
Product design is a constant process of iteration. No product is developed off the first design, making collaboration and teamwork crucial to successfully navigating the design process. What turns a design team into a data-driven team is when analytics is used to boost team-driven systems and workflows. A data-driven design process doesn't seek to replace teamwork with data, rather it uses data to supplement and improve existing capabilities.
Data within Design
Implementing data analytics into product design is not a new concept. However, the difficulties and obstacles associated with this are often underestimated and misunderstood. Adding new technologies or platforms without a corresponding emphasis on qualitative judgements can lead to designers overlooking product flaws if, for example, those issues do not have a corresponding effect on quantitative data.
In data-driven design processes, data cannot supplant qualitative judgements. Qualitative processes and workflows, such as visiting and speaking directly with customers; provides valuable insights that cannot be substituted with data visualizations or analytical reporting.
It can also be helpful to think of data as being more than simply reactive analysis. Data can be used to generate ideas for the design process. For example, using analytics to understand customer concerns or needs can help teams scope out and anticipate customer frustrations and pain points before the product goes to market.
Data is at its most valuable when it is used proactively to shape the customer experience. Anticipating customer needs, wants and concerns can be difficult to perform on scale. Teams can only meet and speak to a limited number of customers each day. However, when customer concerns are recorded and compared through analytics, wider trends can be discovered.
Data is also invaluable in helping designers specify when updates are necessary to a product line. Many updates require the tracking of users through workflows to be accurate. This tracking and measurement of users would be near impossible without the help of product analytics. The impact of updates can then also be measured quantitatively, giving designers insight into the expected and actual effectiveness of product updates. This data can also give designers a view into whether updates should be rolled out across entire product lines or specific models.
Your Data-Driven Team
Of course, when using data, it is important to keep in mind that culture and fit are equally important to design teams. A company culture that respects arguments supported by data, seeks to include data as evidence and respects quantitative trends will find much more success with product analytics than one that doesn't. Organizations that also encourage experimentation and collaboration between teams will find more success with implementing data-driven processes and workflows in their teams.
This of course comes back to the original ideal that data-driven design processes can only augment human capabilities and culture, not replace them. Design is uniquely collaborative, and team cultures that allow for this will be much better at implementing data-driven strategies than teams with poor culture. Data and analytics cannot replace a team with great culture, processes and fit.