4 best-kept secrets for optimizing the Data Analyst<>Product Manager relationship
Our high-paced environment is constantly changing and floods us with a world of complex data every second. In this reality, our role as data analysts is crucial in transforming information into valuable insights, by quantifying its business impact and helping companies achieve their goals.
At Melio, where the product takes a central spot in the company, a key step for this journey is an effective collaboration between us, the data analysts (DAs), and the product managers (PMs).
While being a good data analyst involves reading and interpreting data to drive business opportunities, what truly sets apart a great analyst? How can we maximize our collaboration with product managers and become indispensable in the decision-making process?
The PM <> DA relationship
To understand the dynamics of a common relationship between a data analyst (DA) and a product manager (PM), let’s break it down:
The PM acts as the visionary driving force behind the product’s development and success. They have a deep knowledge of what customers want, what the market needs, and the main objectives of the company.
On the other hand, the DA’s primary responsibility is to investigate the data, extract meaningful insights, and offer strategic guidance. Communicating these findings in a clear and comprehensive manner ensures the team can work cohesively towards achieving their goals.
This collaboration leads to a better understanding of the product strategies and helps validate hypotheses based on data, ensuring that the product evolves in harmony with both market demands and data-driven opportunities.
However, to rise from being merely good to truly exceptional, we must possess certain key capabilities that increase our effectiveness. Let’s delve into four little-known secrets that differentiate an average data analyst from an awesome one:
#1 Understand the PM’s real intention
The ability to grasp the genuine intentions of the product manager is a fundamental step that sets the tone for a smooth and efficient process. However, comprehending the true essence of the PM’s vision is not always a straightforward task, as the language used in product discussions may not always align with the one used in the data discussions. It may require concerted efforts to bridge the gap and translate the “product language” into the “data language”.
Yet, once achieved, this understanding becomes instrumental in selecting the most relevant KPIs and preemptively making changes during the planning and development phases. As a result, the analysis can proceed uninterrupted and stay firmly on course toward delivering impactful results.
#2 Present multiple possible scenarios
In the dynamic landscape of product development, the word “estimation” takes center stage, especially when contemplating new features or changes. Understanding the potential business impact of such alterations — like adjusting pricing policies within the product — becomes paramount in determining the course of action.
At this point, the data analyst should play a pivotal role in creating multiple scenarios that simulate various behaviors, ranging from optimistic to pessimistic outcomes. By presenting decision-makers with more choices and possibilities, they gain a better representation of potential outcomes, as well as a more accurate idea of resource allocation where the company will have the most significant and positive impact.
Consequently, through data-driven insights and comprehensive scenario planning, data analysts enable prudent decision-making, fostering a pathway to success in the ever-evolving business landscape.
#3 Master the data visualization
Beyond presenting data in standard formats, exceptional data analysts excel in creating compelling visualizations that breathe life into numbers. The secret is to evaluate what is the most suitable visualization chart for each case, taking into consideration the type of measure (continuous or discrete), the granularity and aggregation, and the number of dimensions to be presented.
The visualization tool used is also fundamental to telling the story in a clear and concise way, and its choice should be made wisely. That’s can be done by comparing possible visualization styles and chart types. My personal tip is: further explore the advantages of stacked bars — regular and normalized — and the dual-axis charts. They aren’t used as often as they should.
By leveraging advanced visualization tools and techniques, they can effectively convey complex information to non-technical stakeholders, empowering them to grasp insights quickly and make informed decisions.
#4 Be part of the process
The sooner you know the plan, the better your performance will be. This concept is valid for basically every function in a company, and it summarizes the ideal workflow that should happen in every team.
By being involved from the very beginning, the data analyst not only facilitates their analysis planning and execution but also becomes the essential link between data knowledge and the product vision. In the data environment, this becomes even more crucial for us, since most of the high-tech companies are always aiming to rely their decisions on data.
Including the data analyst as part of the product team and sprint planning is one of the most effective ways to achieve a broader perspective of the entire process.
Better collaboration = better product
This sense of collaboration between the data analyst and the product manager is key to improving the performance of any product development and optimization process: less friction, less iterations at later stages, and more alignment during the development phase.
This collaboration thrives when the roles are divided, but not separated.
Our success as data analysts lies in comprehending the product context, which enables us to apply the appropriate statistical techniques and create relevant insights for the business needs. A product manager should possess data analysis skills to perform ad hoc analysis and the ability to read and translate the analysis results into actionable items. They see the importance and power of the data even before it is shared.
Excelling in those roles is not always an easy task. It requires efforts beyond the average in every step of the process, aiming for a better connection and communication between the stakeholders. As a result, a synergy between these roles becomes a vital component of success.
And what about you? Want to be a merely good or a truly exceptional analyst?
