Pedram Navid is a consultant, data scientist, and owner of West Marin Data, where he helps startups accelerate their growth by advising on product strategy, marketing, community, and data. He’s worked as a senior data engineer, a data scientist, a performance analyst, and he’s here today to talk about measuring the value of a marketing data team.
Pedram Navid’s journey with data science started with a circuitous path, winding its way from tech support to data engineering with each step along the way exposing the need to better manage the data his clients and co-workers were requesting.
“As the data needs started to increase in my previous roles,” explains Pedram, “I began working with Python out of necessity and slowly realized the importance of data science. Everyone needed data to perform their jobs, but there wasn’t a defined protocol on how that data would be managed or valued.”
When it comes to defining the value of a data team, Pedram is upfront about the difficulty associated with such a task. Pedram recently posted a question about how orgs determined the value of their data teams on Twitter, and the responses were not as revelatory as he hoped.
“I posted the question because it’s a perennial concern with qualitative reviews and appropriate budgeting,” says Pedram, “Data teams need to buy tools, hire support, but they’re unprepared to illustrate how they are providing value. You need actual data to prove effectiveness.”
Pedram believes a naive way to determine the value of a data team would be productivity; ‘how many tables or dashboards did the data team build?’ but this measures outputs, not outcomes, which is where the true determination of the value of a data team would most likely come from.
“Data teams should be aligned with business values and goals, like revenue and retention. However, while data may be the underpinning mechanism that powers a company’s ability to increase revenue and retention, these things aren’t necessarily driven by data teams.”
If you really want to prove the value of data within an organization, it’s important to always have a seat at the table with the C-Suite, that way, you can let the stakeholders do the talking and let data provide context.
“If I work with a marketing team,” explains Pedram, “I may not be directly driving the results, but I believe my role as a data scientist is to help that team understand how data is assisting them in hitting their goals. Great data teams provide context.”
Since data flows through every part of a business, Pedram feels that data teams have the unique ability to remain neutral, which allows them to present their findings and apply their insights in a holistic, unbiased fashion that provides value for the entire organization.
“Ideally, data teams aren’t aligned with any specific silo,” says Pedram, “and since data has no bias, it can provide an organization with an unvarnished look at what might need to change or improve. Data should be the basis for hard conversations.”
When it comes to managing the sea changes and sweeping evolution of tools available to data teams, Pedram has a solution; keep it simple.
“It’s difficult to keep up with data,” admits Pedram, “That’s why it’s important to focus on problems and solutions that align with business goals. Data teams are not lacking access to tools but what they may be lacking is an engrained data management culture. I go back and forth on offering broader access to data across an organization. It’s nice to provide access to data, but there can be danger when people make their own versions of data or don’t adhere to database protocols designed at the outset. My advice is to keep things as simple as possible, for as long as possible.”
For a Cinderella story about data management gone amazing, and some horror stories on it gone awry, and to find out how you can better define the value of your data team, listen to our full interview with Pedram at the links provided above and below.