Blog post outline
1. What is data-informed product management, and why is it important?
2. How can you use data to improve your product's design and development process?
3. What are some of the benefits of data-informed product management?
4. How can you get started with data-informed product management?
5. What are some of the challenges you may face when implementing data-informed product management?
Data-informed product management might be the sexiest thing since sliced bread. OK, that might be a bit of an exaggeration, but it's still pretty darn exciting! 🚀✨
If you're like most people, you're probably wondering what all the hype is about and how you can get in on the action.
In order to be an effective product manager, you need to be able to use data to inform your decisions.
Too often, we see products fail because the product manager was not able to get buy-in from stakeholders or customers.
By using data, you can back up your decisions with evidence and show that you are making the best choices for the company and its customers. In this blog post, we'll break down what data-informed product management is, why it's important, how you can start using data to improve your own product management skills and, last but not least, we will explore some of the ways that you can use data in your product management career. 💸💸
Good product design and development don't happen by accident. They are the result of a deliberate, data-driven process.
In other words, data-informed product management.
Sounds complicated, right? Don't worry, I am here to break it down for you.
What is data-informed product management?
Data-informed product management is using data to guide your product design and development decisions.
This means basing your decisions on evidence, rather than assumptions or gut feelings.
Why is data-informed product management important?
There are a few reasons why data-informed product management is so important.
First, it helps you avoid making costly mistakes.
Second, it allows you to move beyond assumptions and Guess Work to make informed decisions that are backed by evidence.
And third, it gives you a competitive edge by helping you develop products that are better tailored to your customers' needs. 📈
How can you use data to improve your product's design and development process?
There are a few different ways you can use data to inform your product development process:
1) Use customer feedback to drive decision making: Customer feedback is essential for understanding what people want and need from your product. Use surveys, interviews, reviews , and other customer feedback channels to collect this information and use it to inform your decision making.
2) Test new features before launch: launching a new feature without first testing it is a recipe for disaster. Use A/B testing or beta testing to test new features with a small group of users before rolling them out to everyone. This will help you catch any potential problems and make sure the feature is actually beneficial for users.
3) Analyze user behavior after launch: Once a new feature or version of your product is launched, keep track of how users are using it. This will help you understand what's working well and what needs improvement. User analytics tools like Google Analytics can be helpful for tracking this information.
Of course, there are also challenges associated with being data-informed.
One of the biggest challenges is ensuring that you have access to accurate and timely data.
Another challenge is making sure that you have the right team in place to effectively make use of the data available to you.
Finally, you need to be careful not to get too bogged down in the data - remember that at the end of the day, your product needs to meet the needs of your customers, not just the numbers. 🥳😇
Business case of the "HT" data incident
Julie is Director of Product Management at a health tech company called "HT". She is responsible for the software piece of the existing medical devices. Doctors are primary users of the output patients' information.
Julie was in her office, looking over some data pipelines she had built with her engineering team. She and her team had been working hard to improve the product, based on feedback from doctors. She was feeling good about their progress, when she received a call from one of the doctors. 🔔🩺
He told her that he had been using the device and that he had found a bug. Julie was surprised; she had just run those same reports two days ago and they were perfect.
She asked him to send her some more information so that she could take a closer look and narrow the search scope. A few hours later, Julie's phone rang again. 🚨🚨 This time it was another doctor on the team. He told her that he had also found a bug and that it was causing problems with his patients' treatments schedule. 🌡💉
Julie started to get worried; if there were two bugs, there might be more. When she looked at the data, she could see that there was definitely a problem:
One parameter was wrong; instead of normal deviation of 1% between the tests, they increased to 5%, which is 5X in this case.
She quickly put together a plan to fix the issue and called the doctor back to let him know what was going on. Then she contacted engineering to let them know what was happening.
Fortunately, engineering was able to fix the bugs relatively quickly and everything went back to normal. 🎉
But Julie learned an important lesson from all of this: even though she had tested the reports herself, she needed to be sure to test them against how doctors were actually using the reports from medical devices.
Otherwise, she might have missed something important and caused real problems for patients.
Conclusion
Data-informed product management is a process of using data to inform your decisions about product design, development, and marketing.
There are a number of benefits that come with being data-informed, including avoiding costly mistakes, tracking progress, and maintaining objectivity.⚖⚖
However, there are also challenges associated with being data-informed - namely, access to accurate and timely data as well as ensuring that you have the right team in place.
Despite these challenges, I believe that the benefits of being data-informed far outweigh the challenges - after all, making decisions based on hard evidence is always going to be better than making them based on gut feeling alone.
