Innovation thrives at the intersection of data, design, and development. Removing the barriers separating these areas requires leaders, agents, or freelancers who wear "many hats” – orchestrators who align strategy, creativity, and execution. These orchestrators must be fluent in data, empathetic in design, and technically adept in development.

On their own, data, design, and development each bring immense value, but true value exists where they converge. Without someone to bridge them, projects remain fragmented, and missed opportunities abound. Data without design yields confusion. Design without data results in misguided judgements. Development without data and design fosters ineffective solutions.

Whereas skilled specialists deliver depth in their respective area, interdisciplinary orchestrators, well-equipped with multidisciplinary skills, drive integration. They are fluent enough in data to uncover insights, empathetic enough in design to create human-centric solutions, and technically adept enough in development to build, deploy, and scale. Moreover, they are able to converse intersectionality with specialists because they have a degree of fluency in area-specific “lingo”. This makes them uniquely positioned to orchestrate collaboration across teams and stakeholders.

Research highlights the value of integrating data, design, and development. McKinsey notes that companies that break silos with integrated, cross-functional, multi-disciplinary collaboration achieve up to 30% better performance across metrics of innovation and efficiency. Notably, 60% of companies that successfully scaled analytics did so through the use of cross-functional teams - what McKinsey called “squads” .¹

When Disciplines Intersect

• Uncovering Hidden Insights: At one bank, placing data analysts and designers into a single team uncovered a hidden customer pattern, saving the company tens of thousands of staff time. A data scientist noticed an odd pattern – many customers were coming into branches only to check their account balance, contrary to assumptions that most would use ATMs or online banking. Rather than dismissing it as a data anomaly, he alerted the design researchers on the team. Those UX researchers went out to interview and observe users, confirming the trend was real. The insight led the bank to redesign its service delivery, such as by improving mobile banking features and in-branch kiosks, ultimately migrating simple balance inquiries to digital channels. The result: tellers were freed up for more valuable interactions, and customers gained a faster way to get what they needed. Without the combined lens of data and design, this opportunity might have been missed.
• Scaling UX Personalization: Under Armour acquired several fitness and nutrition apps and integrated them into a single platform (UA Record) with 175 million+ users in 2016.² In 2020, Under Armour furthered its digital consolidation through their MapMyFitness app. By synchronizing data from workouts, health stats, purchase history, and more, they gained a 360° view of each customer – insights no competitor had at the time. In one instance, the app could recommend the perfect running shoes to a user at just the right moment in her fitness journey.
• Accelerating Innovation: One auto manufacturer found that weaving together data analytics and design thinking not only helped create a “killer, user-centric” product, but also uncovered efficiencies in their production process they hadn’t seen before [^3]. By mapping out the end-to-end journey of a part through the factory (a very design-informed exercise) and analyzing performance data at each step, a cross-functional team identified several bottlenecks. Instead of just building a fancy new AI tool in isolation, they convened over 20 people from data, design, and business in one room to reframe the problem together. This holistic exploration shifted the solution focus entirely and even simplified the technical approach needed. The initial plan – an algorithm for a handful of engineers – evolved into a user-friendly tool for the two frontline operators who made key decisions daily. By iterating with both data modeling and human-centered design in parallel, the company deployed a solution faster, with less complexity, and with higher user adoption among the operators. The lesson was clear: when you put interdisciplinary minds together on a problem, you often solve the right problem and build the solution that actually gets used.

As these case studies make evident, the integration of design, data, and development results in outcomes that none of them could achieve alone. Their convergence is greater than the sum of their parts.

Orchestrators: Turning Data into Decisions, Design into Direction, and Development into Delivery

Cross-functional teams work most optimally when led by multi-disciplinary leaders. Professionals with knowledge and experience spanning all three domains are best suited for driving convergence and collaboration. This orchestrator role reduces wasted effort, accelerates time-to-market, and prevents the classic pitfalls of siloed work (e.g., designs that can’t be built, or data models that don’t address real user problems). Whether embedded in a cross-functional team or hired as a freelancer, these leaders offer what every client wants: data-informed decisions, beautifully-designed products, and expertly-built solutions.