Keeping the Peace Between Data and Product Teams

Since the dawn of the interwebs, product teams and data teams have locked horns. Product teams want data fast, and they want it neatly organized in order to make data-backed decisions. Data teams argue that quality data requires time and consideration.

Overcoming this conflict leads to the holy grail of data democratization where everyone within an organization can access and interpret data with confidence. When product and data teams come together, ownership of data quality is distributed throughout the organization. To get there, however, data teams need to centralize and start treating internal teams like customers. Data democratization requires a culture change that puts everyone on the same page. To achieve nirvana and keep the peace between data and product teams, leaders must get to the core of the conflict, resolve conflict through centralization, and encourage empathic mindset shifts.

Understanding the data-product conflict

The ongoing conflict between product and data teams is a blocker to data democratization and the symptoms are numerous:

• Siloed teams. When siloing occurs in an organization, each team dedicates their energy solely to their own respective tasks and goals rather than to the company’s goals. This results in a situation where collaboration and information-sharing are reduced, ultimately lowering the quality of the product and user experience.
• Data chaos. Large volumes of data spread out across different systems and departments with no standardization or taxonomy mean that no one department has a clear understanding of the actual situation, and there is minimal trust in the data.
• Lack of trust in data. Leaders need a single source of truth where they can reliably retrieve accurate data. With warring parties, leadership is forced to choose one over the other and data teams—backed by analysts and scientists—typically win. Unfortunately, this is to their own detriment; they become the single point of failure for analysis delivery and accuracy.
• Limited data accessibility and visibility. Since data is spread across multiple systems, centralized data can only be accessed and understood by highly skilled data analysts.
• More money spent on contracting data analysts. Without data democratization, organizations are left with little choice but to hire costly data analysts to make sense of their data chaos and burn out is real.

To get to data democratization, a significant amount of time and energy needs to be spent on developing norms (and eventually habits) on how you collect, shape, and transform data. These are norms that will allow product teams to be more self-serving. This recipe requires one part software and two parts culture shift.

Resolving conflict part 1: software centralization

The responsibility for establishing these norms falls on a centralized data team and requires a learning period. While this is critical, it heaps significant pressure on data teams, and this is where the conflict starts.

The following scenario might sound familiar: The product team is on a tight deadline to hit user, customer, and company goals. They need fast access to the data and the knowledge on how to use it properly so that they can achieve success in a highly competitive market. The data team argues that if you need this data to make business decisions, it is of the utmost importance that the data is accurate. Product teams then get upset when the data that they’re trying to use is messy. They don’t understand what events they need to use when presented with a number of different purchase events. Product teams lose trust in the data, and data teams are frustrated because this is a result of the latter not following instructions or naming conventions.

So how can companies solve this part of the conflict? The key is a centralized, unified tool. Organizations should seek out an analytics platform that is easy enough for product teams to use but comes with strong governance capabilities and collaboration tools to keep the data clean and accessible. A centralized tool allows teams to speak a common language, easily share insights and jointly own the data upkeep responsibility—resolving a major piece of the data-product conflict.

Resolving conflict part 2: cultural shift

To achieve data democratization, your company won’t need anything as drastic as an uprising, but the journey will be preceded by a process of dismantling and rebuilding. This is the two part culture shift.

First, centralize before you democratize.Think of centralization as the early stages of democracy. First, a centralized data team establishes a set of norms and rules on the data processes that provides the foundation for how the company as a whole will function. This includes things like agreeing on naming conventions and identifying metrics to be measured. It is important that these rules are then accepted by the rest of the organization if democratization is to be achieved. It ensures that all teams are on the same page when it comes to the analysis and use of data.

Product, data, marketing, and sales teams all operate under this set of laws or norms, but they eventually start to function like states. They realize that they need to do some things slightly differently in a way that works for their particular situation, but within the constraints of agreed upon norms.

Next, think of a product mindset shift as a final step towards democratization. This culture shift from centralization to democratization is a vital process that companies have to go through. It starts with people understanding and agreeing on shared norms, understanding the value of following those norms, and then getting to a place where they want to do it themselves. This cultural shift, or revolution, has to happen to achieve democratization.

In a recent article, Benn Stancil wrote about how data teams can overcome their struggles by starting to treat internal teams like customers. With this mindset shift, data teams start to think about how they build out their product and, with it, their customer service and onboarding process. By viewing data with a go-to-market lens, data teams can see how they play a role in finding problem-solution fit and product-market fit. If the successful adoption of a software solution grows from one product team to 10, they know they have found some initial success and can move to general availability.

The key to this success, as any product manager will tell you, is empathy. By viewing internal teams with empathy, data teams will get a better understanding of:

• The outcomes their customers want to achieve
• How to build systems and processes that will help them achieve their goals
• Their pain points and obstacles
• The right solutions shapes for the right problem holes

Many companies fail on their journey to data democratization. As their data and product teams lock horns, the conditions needed to get to democratization are not available, and data teams tend to retreat and entrench. By going through an initial centralization process followed by a cultural shift, product and data teams can empower their entire organization to leverage data. In a fully democratized organization, employees feel comfortable asking data-related questions, teams have the right tools in place to enable self-serve use, and the understanding that data democratization is an ongoing process. The companies that are able to make this shift will not only keep the peace between their data and product teams, but will also be able to build better products with their data.

Amplitude as a tool for democratization

Amplitude provides data teams and organizations with all the tools needed to help spark that cultural revolution that will lead to a healthy data democracy. We offer unique value due to our experience in the industry. Our customer support and professional services teams can help organizations figure out which stage they are at in the data democratization process and create a clear plan for getting there.

Get started with Amplitude for free.

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