Your Data Reports are a Tamagotchi

Tali Fulman
Tali Fulman
·
Feb 17, 2025

Remember those tiny virtual pets we used to carry around in the 90s? If you’re ol-, I mean, veteran enough, you probably had an electronic pet fish, gorilla or alien. If you have no idea what I’m talking about, go look it up - you’re in for a surprise. In any case these digital creatures demanded constant attention. Feed them, clean up after them, play with them – neglect any of these tasks, and your virtual pet would suffer the consequences. And by “suffer the consequences” I mean they’d die. Or, you know, go up in their spaceship and leave you alone. Like I said - the 90’s were weird.

In my years of consulting with organizations on their data strategy, I've noticed a striking parallel: Your data reports and dashboards are just as demanding as those nostalgic digital pets. They require regular maintenance, updates, and care to remain valuable and relevant to your business.

The Hidden Costs of Neglected Reports: A Real-World Case Study

Last year, I worked with a mid-sized e-commerce company that had invested heavily in their data infrastructure. They had beautiful dashboards, comprehensive reports, and even a dedicated BI team. Yet, when we conducted an audit, we discovered that:

  • Almost 50% of their reports hadn't been accessed in the past three months
  • Key stakeholders were maintaining their own "shadow" Excel sheets because they didn't trust the “official” dashboards
  • Different departments were making conflicting decisions based on inconsistent data sources
  • The BI team was spending 60% of their time maintaining legacy reports instead of driving new insights

This scenario isn't unique. In my experience, the root cause of these issues is consistently the same: treating data infra and products as a static asset rather than a living system, or as a product - just like the ones your friendly product manager next door is responsible for.

Be careful of what you wish for

Early in my career, I learned a lesson I'll never forget about the gap between feedback and actual usage. We had just launched what we thought was a game-changing operational dashboard for managers overseeing global teams. Following what we believed was best practice, we sent detailed release notes to all stakeholders, explaining the features and requesting feedback.

The response was overwhelming - our inbox flooded with 'Reply All' emails praising the dashboard as revolutionary and life-changing. We were ecstatic. Finally, we'd created something truly valuable!

Or so we thought.

A few weeks later, we noticed usage declining. The mystery was only solved when some of these same managers visited our office. Sitting beside them and watching them work revealed the harsh truth: the dashboard wasn't actually meeting their needs. Features we thought were intuitive weren't. Critical functionalities were missing. Users were supplementing our "revolutionary" dashboard with manual work and other reports.

This moment was transformative for me. It showed that positive feedback - even enthusiastic praise - isn't enough. Real product management requires getting close to your users, observing how they actually work, and understanding their true needs.

This experience shaped my entire approach to data products.

Here's how we can apply proven product management methods to make our data work truly valuable:

Bringing Product Management Methods to Your Data Work

Working with data teams across various organizations - from nimble startups to large enterprises - I've noticed a pattern: the most successful teams are those who treat their data assets with the same rigor and methodology as product teams treat their products. Here's how you can apply proven product management methods to your data work:

1. Usability Testing for Data Products

Just like product teams conduct user testing sessions, your data work needs regular user feedback:

  • Run periodic sessions with report users to observe how they interact with dashboards
  • Collect feedback on pain points and missing functionalities
  • Test new report layouts or metrics with a small group before wide release
  • Document common usage patterns and user needs

2. Product Lifecycle Management

Different reports are at different stages in their lifecycle, requiring different approaches:

  • Launch Phase: Heavy monitoring and quick iterations based on initial user feedback
  • Growth Phase: Focus on scalability and adding features requested by users
  • Maturity Phase: Optimize performance and maintain reliability
  • Decline Phase: Decide whether to sunset or revamp based on usage patterns

3. Agile Development Methods

Apply agile principles to your data work:

  • Work in short iterations to deliver value quickly
  • Hold regular "sprint reviews" with stakeholders
  • Maintain a backlog of requested features and improvements
  • Prioritize based on business impact and effort required

4. User Experience (UX) Design

  • Design intuitive layouts that guide users to key insights
  • Create clear hierarchies of information
  • Ensure consistent styling and terminology
  • Make it easy to explore and drill down into data

5. Feature Prioritization

Use product management prioritization techniques:

  • Apply frameworks like RICE (Reach, Impact, Confidence, Effort)
  • Gather and prioritize "feature requests" from users
  • Balance quick wins with strategic improvements
  • Focus on delivering maximum value with minimum effort

The Results? This approach helps you:

  • Avoid building reports nobody uses
  • Deliver insights faster to stakeholders
  • Prevent the accumulation of stale, broken reports
  • Maintain high-quality, relevant data products

And remember - just like a product manager regularly checks in with users and maintains their product, don't forget to regularly check in with your data products. Sometimes they just need a small update (or a cookie 🍪) to keep running smoothly.

The Power of Paying Attention

Looking back at that early experience with the operational dashboard, I realize now that what we were missing wasn't just better testing - it was a whole product mindset. Just like you wouldn't launch a product without understanding your users, you can't launch a successful data product without truly understanding how it fits into your stakeholders' daily work.

Years after that eye-opening experience with the operational dashboard, I found myself staring at my kid's new Tamagotchi (that I got at a data conference!) while cleaning out a drawer. It hit me - those little virtual pets were actually teaching us something profound about responsibility and attention. They didn't need complicated care routines; they just needed consistent attention and someone to notice when something wasn't quite right. And also batteries, occasionally.

And just like a Tamagotchi, your data products will tell you when they need attention - through declining usage, user complaints, or manual workarounds. The key is to listen to these signals and respond with the right product management tools at the right time.
It's about developing that sixth sense for when your dashboards need attention, building genuine relationships with your users, and understanding that sometimes the simplest solution - like sitting next to someone for an hour - can provide the most valuable insights.

After all, at the heart of product thinking isn't fancy frameworks or methodologies - it's about caring enough to pay attention.

Want to share your data product stories or challenges? Let's connect!

Tali Fulman
DATA CONSULTANT, MENTOR AND LECTURER
A Data Artisan for over 13 years. As a data leader in some of the most successful companies in Israel, Wix and Simply, my personal mission is to help companies and individuals grow and develop.