Beyond the Metrics: How Collaborative Insights Drive Success

So, what does smart data usage look like? How does an organization create an environment of strategic, data-driven decision making across teams, all focused on shared business goals? The answer is most often not that teams need more data. Instead, what they need is better data—and the ability to utilize it in a business-relevant, user-centric context. But, maybe most importantly, this responsibility cannot fall to data teams alone. Multidisciplinary collaboration is crucial in determining what data your organization should collect—and how it informs your decisions and processes.

First, ensure your organization’s various goals are aligned.

Data can help organizations understand the market, opportunity areas, and how they are trending toward business goals. These high-level goals are typically made up of smaller team projects and KPIs. Although often aligned to a larger, unified objective, these smaller goals have unique requirements. For example, imagine a B2B retailer is looking to grow its digital presence. The high-level KPIs might include total traffic to the store page and online revenue. But, different teams, including Technology, Marketing, on-ground channel partners, and more, will have to work together to move those metrics. Technology might be focused on ensuring site availability and reduced lag time as users navigate the site, while marketing might focus on retargeting users who abandon their carts and increasing traffic from social media.

Once goals are aligned, collaboration provides key context for impactful data.

To ensure individual teams’ data and goals ladder up to the overall business goals, contextual data is critical to success. Data must be determined in the context of business decision-making and operations; otherwise, it will not be influential. Getting that context requires collaboration. Data specialists are not always embedded in business processes and user experience activities. This is where multidisciplinary collaboration shines—a force that combines multiple knowledge bases to bring the best human-centric solution.

For example, Alex Sher, Senior CX Strategist and a co-author of this article, was once involved in an effort to improve a coaching application for sales representatives and their managers. The goal was to increase their sales effectiveness. The client initially wanted to streamline the process of submitting a coaching form while the sales rep and their manager were together. However, during UX research, it was found that managers preferred to submit their coaching forms on Fridays, when they had more time to reflect in their home offices. The team was then able to validate this finding with the data team, learning that about 80 percent of the coaching forms were submitted on Fridays.

Those numbers convinced the team to prioritize a note-taking feature, aligning the app with the users’ behavior and helping the coaching session stay fresh when managers wrote up the reports at the end of the week. The collaboration between UX and data teams revealed new opportunities for a design that matched users’ behaviors.

Assemble the right team for the job.

Combining different expertise allows the team to get more out of their data and provide a robust view of their experiences, informing more user-centric thinking and leading to smarter success metrics.

When considering your metrics, make sure the right people are involved in the process. The data team will undoubtedly help determine what can be measured and how, but the outcomes of any data project will be improved through support from other teams. Technology should be included to determine technical limitations and features to consider. Business and Product teams will be able to represent business goals. Design and UX can ensure the data is presented in a usable way and consider how it will fit into the team’s processes.

Additionally, any teams that will be using the data should be included in the process. A Fortune 500 client of One North, focused on driving innovation and efficiency for their employee experience,​ found success when the research group was expanded to include strategy, design, experience, and technology. They were able to identify the scale of operations and current-state limitations and approach and product catering to the needs of end users and requirements of business stakeholders.

Set your team up for success—Time and transparency

You can’t bring various stakeholders together for an hour at the beginning and end of a project and expect them to contribute fully to a data project. Teams must be aligned on the project’s goals upfront and have the chance for regular collaboration throughout the project. This will ensure that teams remain aligned and that feedback is gathered at key stages, including when determining what to measure, how to present data, and any changes to your business processes that may occur.

You should also consider how these teams will be asked to work together. A multidisciplinary effort is an excellent opportunity to increase transparency and democratization in your organization. Using a RACI matrix identifies your project teams’ roles and responsibilities for any task or milestones. This will help ensure that someone is responsible for thoughtful facilitation and that all the teams involved effectively contribute. It also will ensure the team has a shared understanding of who needs access to what information.

Effective collaboration can take many forms in one of these projects. For instance, working with end users can be a form of co-design, where designers lead creation sessions with those who will ultimately use the end product. Various teams might be interviewed independently to determine their goals for the project. Methodologies across teams can vary; however, maintaining a multidisciplinary approach can ensure that all activities have a thorough line connecting to an overarching goal. This will help break down workstream silos and empower teams to build solutions that successfully meet user needs.

Collaboration in action

We’ve seen this collaboration result in huge strides for our clients. For example, we partnered with leading international law firm Mayer Brown on a website redesign launched earlier this year. Within a few months, Living Ratings of Law Firms 2024 ranked their website #4. This was a 90 percent increase from their 2023 ranking (#40). They were categorized as ‘Determined,’ implying they possess all the attributes required to maximize the effectiveness of digital and social media channels and content. Multidisciplinary collaboration was the backbone of this project. Utilization benchmarking was done early to contribute to the design and content discovery process. Stakeholder interviews ensured the new look and feel aligned with the company’s outlook. Close collaboration between user research, brand and content strategy, and technical explorations combined user desires, brand expectations, and technical architecture to ensure a seamless experience.

Data-driven decision-making is more than just providing teams with data. It’s about creating an environment where data can drive informed decisions. Organizations can unlock the true potential of their data by fostering multidisciplinary collaboration, setting clear goals, involving teams throughout the process, and democratizing tools and results. With the right approach, data can transform decisions, leading to greater success and innovation.

Photo Credit: Markus Spiske | Unsplash