Ask a data engineer why they got into the field, and they’ll likely share how they looked forward to bringing concepts to life or solving complex challenges; or they wanted to share their expertise in a collaborative, agile environment; or they simply wanted to provide better visibility into the way products work for end users—and how it could be improved.
They’re unlikely to tell you that they got into engineering to sit in meetings, align teams, set expectations, and debate timelines with product and marketing stakeholders. But for many, that’s the reality—and during the pandemic, these challenges intensified as the pace of change accelerated, driven by shifting business models and rapid product evolution to meet digital-first demands.
“Data democracy” has been heralded as the answer to this rapid cycle of innovation—but it is not enough. These initiatives have noble intentions: Sharing data and information about how users interact with products widely should, in theory, help groups across the business—from marketing to IT—operate from the same source of truth to stimulate better insights and better results faster.
In reality, however, data democracy fails to yield those conclusive answers and shared goals. Too much raw data is difficult and time-consuming for teams to interpret, especially as the flow of digital signals has surged, and lacks the context needed to draw conclusions about the best path forward.
Instead, the data is so oppressively overwhelming to manage that departments either give up or derive inaccurate conclusions—neither of which helps drive sound decisions and productive partnerships. Rather, these conditions create a new source of frustration and inefficiency for many engineering teams: the entire organization has access to information ripe for misinterpretation, even as expectations for results grow more urgent.
Moving forward decisively, confidently, and in step with other functions requires a new relationship with data that goes beyond access to action. To succeed on their own terms—with opportunities for the early input, collaboration, and problem solving that can prevent constant crisis management—engineering teams need to move from a focus on data democracy to a practice of data stewardship.
Data stewardship is the act of providing quality data paired with meaningful context in a format that’s easy to comprehend. Unlike data democracy, which focuses on shared data access, data stewardship is grounded in a shared understanding of the end user. It is fueled by digital experience intelligence (DXI) tools that provide insight and empathy into the customer experience and enable meaningful collaboration around quantitative insights.
Armed with the latest DXI tools and a commitment to a better, more efficient way of working, data engineers can serve as data ambassadors, helping colleagues identify and proactively surface the most impactful information to achieve alignment, drive decisions, and accurately track results. To achieve this cultural shift, leaders must take three crucial steps:
- Understand how data is being used across the organization.
Before embarking on transformational change, data ambassadors should understand what data sources already exist and how the information is being used within individual teams, while spotting barriers to data access and any gaps between information and action. It’s also crucial to identify the ways individual teams incorporate data into their decision processes and which tools they use to share actionable insights.
For example, as a first step toward data stewardship, user review pioneer Bazaarvoice implemented a DXI platform to gain a complete picture of its digital experience and how it could be improved. The company then recruited “Observability Champions” within each team who could help integrate DXI processes and findings into daily operations within their part of the organization. With this approach, Bazaarvoice now empowers teams to discover the insights that are most meaningful for their individual needs. When teams test new features by launching internally, they can instantly monitor results and make iterative changes, improving the eventual external rollout.
Thanks to integrations with other internal tools and built-in DXI dashboards, Bazaarvoice avoids data silos. Cross-functional teams review dashboards together and collaborate around solutions.
- Bring empathy and flexibility to data interpretation.
Data ambassadors also need to approach the results of data inquiries with an open mind. Identifying colleagues who are eager to learn and passionate about using data to improve experiences is crucial. By developing empathy toward other team members and their priorities —and tackling problems with a desire to learn rather than to dictate solutions—data and BI engineers can help colleagues unlock ground-breaking insights.
Younique is a multi-level marketing cosmetics company with a digital-first approach when it comes to promotions, selling tools, and the eCommerce shopping experience. The emphasis on digital experience has driven strong growth and a $1 billion valuation. But internally, Younique struggled with communication and information gaps between product and customer service teams, slowing the process of identifying and resolving customer pain points.
To shed new light on persistent problems, Younique turned to DXI to understand not only what was happening, but why, for its customers. Younique’s product team was aware that one element on their shopping cart page—an unclickable bar labeled “Update” that looked like a button—was causing confusion, but they’d previously been unable to quantify the problem. New DXI tools revealed this “Update” bar was one of the elements that received the most “rage clicks,” with customers repeatedly clicking or tapping in frustration. This insight helped product teams align quickly to prioritize removal of the element; overall, shoppers’ time to checkout has dropped 14%.
Younique has continued to evolve its data processes and culture to tighten alignment between customer care and engineering, enlisting dedicated customer service “tech leads” to use FullStory to assess customer issues before they’re passed along to the tech team. These tech-savvy customer care reps ensure that issues are shared with engineering with context, summary, and multiple examples so that dev can move immediately on solving the problem, not figuring out what it is. The result is a savings of hundreds of hours a week for both teams and a decrease in average time from support ticket submission to fix from days to minutes.
- Align individual strategies to business goals.
While successful data stewardship hinges on building trust within individual teams, their experiences with DXI should support organization-wide initiatives and objectives. Especially as change accelerates, the ability to share common goals and the data to support decisions becomes even more important. Using DXI to illuminate key customer interactions and quantify the impact of individual site features eases this alignment, helping cross-functional teams prioritize together and act decisively.
Data and BI engineers face myriad challenges as companies innovate quickly amidst digital transformation—but also have a unique opportunity to help navigate toward more sustainable processes. By shifting company practices to support data stewardship, teams can help proactively shape the conversations that guide sound decisions.