Working cross-functionally
The journey to Adobe Analytics starts with a good implementation. We all know the saying of “garbage in, garbage out”. To eliminate a “garbage out” implementation, Admins must monitor every detail of the data put into the system. That said, the data collection strategy is influenced by many stakeholders in the organization whom an admin will have to work with day-in and day-out.
As an owner of the tool, you must work with business teams to understand their requirements and KPIs, work with IT and design partners to understand the data flow and work with reporting stakeholders to help them understand implemented variables and values for reporting. Furthermore, we also must work with EDW teams to ingest data into their systems to be widely used across the company. To add on, there are other teams who are dependent on Analytics data like Adobe Target, media campaigns, and other vendor partners.
As you can see (and already know), as an admin of Adobe Analytics, you are consistently working across organizations and teams. To maintain efficient cross-functional relationships, admins need to put on a “product manager” hat. Instead of only thinking about your own reporting/data collection needs, you must consider the product needs of the entire organization. Being an admin is not an easy role but can be made much easier with collaboration across teams.
These are some of the skills needed to work well cross-functionally:
- Technical foundation: An Admin should have a solid understanding of the technical implementation of Adobe Analytics. Admins are the middle-man between business owners and technical resources, bridging the gap of “what to measure” vs. “how to measure”. Admins need to be an active part in the solution design, based on their knowledge of the organization’s KPIs and KBOs. In order to be efficient in cross-functional collaboration, admins need to be able to converse on a deep level with engineers to establish expectations of the implementation. Based on the solution design, the admin can implement and manage the appropriate variable settings and taxonomy required. There are hundreds of details in every project and admins should be able to understand how their data set will fit into the grand scheme of things.
- Leadership: A skilled admin should have the ability to inspire confidence in the quality of their dataset. This is accomplished by implementing and maintaining Adobe best practices. Adobe best practices ensure accuracy of data collection, the usability of collected data, and ensuring actionable insights from the collected data. Additionally, passing implementation knowledge and training new users is an integral part of leading within Adobe Analytics. Admins should look to increase adoption of the tool by leading enablement and training sessions to showcase the usefulness of Adobe Analytics.
- Customer-driven mindset: An admin must have a sense of how to make the user experience better. As admins of Adobe Analytics, your customers are the stakeholders and users of Adobe Analytics. In order to create a better experience for them, ensuring cross-functional teams have appropriate access is critical. Understanding their roles and needs, you can preemptively overcome roadblocks by provisioning appropriate access from the beginning. Moreover, Admins should implement and maintain appropriate taxonomy and documentation of components and variables within Adobe Analytics. This will provide clear documentation for your cross-functional teams to review.
- Communication: Effective cross-functional collaboration requires expert communication skills. An admin must clearly articulate business questions and how they are trying to answer them. Admins should frequently request feedback from the cross-functional team and implement necessary changes to facilitate effective collaboration. Changes to the implementation can have rippling effects throughout the data flow and reporting processes. For example, a variable collection change can impact the results of a segment, which in turn can impact a report summary that is used by a business stakeholder to make a business decision. Documenting and communicating any changes made to components or variables ensures transparency of reporting impacts and helps facilitate implementation troubleshooting.