From Bottlenecks to Breakthroughs: Making Your Product Data Accessible

Data cleanliness and effective data infrastructure are vital challenges faced by modern teams. In our latest session with Nate Sooter, the Senior Business Operations Manager at Smartsheet, we explored the importance of data accuracy and the role of a centralized data team in overcoming these hurdles. Nate’s experience highlights how a deep understanding of the business domain and strategic data partnerships can empower analysts to provide actionable insights, making a meaningful impact on the organization. 

Overcoming Challenges in Building Data Infrastructure

Data cleanliness is one of the most significant issues plaguing modern teams. Sometimes calculating the value of an opportunity may even be too complicated (it was for Nate early on!). Teams struggle with finding the right data format, turning it into usable information, and gathering business logic to create valuable reports for stakeholders.

As a data analyst, you have to have a solid understanding of the business context to get past this. Excellent data workers distinguish themselves by having a deep understanding of the business domain they serve. Without this context, data analysts may struggle to become strategic partners, relegated to mundane tasks and without the ability to give actionable insights. This business-facing expertise, particularly crucial for small teams like Nate’s at Insightly, propels careers and enables data workers to make a meaningful impact on the organization.

Data team roles can often be ambiguous, and small teams may not have dedicated people just to data and analysis. These responsibilities may be filled by data engineers, analytics engineers, data analysts, data scientists, machine learning engineers, and even individual contributors in each business unit. Each role can play a distinct part in the data flow, from data warehousing to enriching and modeling data for business consumption.

Ultimately, most teams use dashboards to enable business users with data. Nate cautioned against the overuse of dashboards, as they often become static reports. Rather than static displays of data; they should guide users to take specific actions based. By creating dashboards that prompt actions, data analysts can effectively empower business users to make informed decisions.

Justifying ROI in Data Investments

Nate has used two primary approaches to justify ROI. The first is identifying wasted time and inefficiencies within the organization. Data teams can analyze how much time analysts and stakeholders spend on data preparation, cleaning, and munging tasks. By quantifying the time saved through better data infrastructure and tools, those cost savings can be passed back to the bottom line.

The second approach involves understanding the pain points experienced by stakeholders on the business side. By addressing the specific pain points and delivering actionable insights, data teams gain credibility and trust, leading to increased investment in data-related efforts. Like a good salesperson or marketer, you have to understand your customers (in this case, your internal GTM team). 

Empowering Analysts with Centralized Data Infrastructure

At a certain scale, a centralized data team will empower analysts across different business organizations. Centralized data teams excel in managing the infrastructure required for effective data analysis. They handle tasks such as setting up ETL pipelines, managing permissions, and ensuring data reliability and governance. This frees up analysts to focus on their core responsibilities without being burdened by technical complexities.

A key aspect of the centralized data team’s role is standardizing and defining data models. The central team works closely with various business units to understand their requirements for data modeling. Everyone has to be on the same page for this to work, so communication is important. Through partnerships with business teams, the central data team ensures that data models align with the needs of different departments, such as sales, marketing, and finance. All the while maintaining enough flexibility to grow without too many problems. 

Nate shared a few specific examples of this work at Smarsheet. The first involved building functional territories for sales representatives. This required balancing the growth potential of accounts while ensuring fairness for the reps. 

The second challenge was consolidating and centralizing data about accounts. By creating comprehensive dashboards and providing access to account-specific data in one place, they streamlined the data analysis process for field organizations.

To Wrap It All Up

Nate Sooter’s experience shows us that a centralized data team can help tackle these obstacles by handling technical tasks and providing analysts with the right tools. By understanding the business needs and communicating clearly, those analysts create dashboards that guide users towards making smart decisions. Justifying investments in data infrastructure becomes easier when we can save time and solve real problems for the business.