Information overload: it’s a malady peculiar to our times. 80% of us experience information overload, while 36% of managers reported poor health due to the amount of information they process. All this data is stressing us out.
For product managers, the problem is more pernicious - information and data are the lifeblood of effective product management. They come from a variety of sources - user feedback, analytics dashboards, stakeholder opinions, market data and more - and they inform every phase of the product lifecycle, from discovery through delivery and beyond. They’re used to turn intuition into evidence, align stakeholders, and drive continuous improvement.
For product managers, information overload can and does stymie progress, and it can manifest in a number of different ways. Do any of the following strike a chord with you?
Too many inputs (user requests, stakeholder opinions, metrics) makes it hard for you to judge what to act on first. It can lead to analysis-by-committee and delayed roadmaps. We’ve all probably heard of the famous jam study in which Sheena Iyengar and Mark Lepper demonstrated that while a large display of 24 different jams attracted more customers, those who saw the smaller display (with only six jams) were significantly more likely to purchase a jar. An apt demonstration of how too much choice can lead to inaction.
Maybe it’s difficult to focus for any length of time and you jump between emails, Slack, dashboards and so on without actually achieving much progress. The human brain can only process a limited amount of information at once. When we’re faced with a deluge of information, our brain struggles to focus and prioritise, and we tend to jump between tasks and mental states,
If everything feels urgent, maybe you lose sight of your north star or the features that really drive customer and business value. There are several famous and tragic examples of information overload leading to a failure to prioritise - in the 2008 financial crisis, for example, complex financial instruments and vast amounts of data contributed to a lack of understanding and poor risk assessment. And critical information that was overlooked amid a flood of data contributed to the Challenger space shuttle disaster.
You’re on the receiving end of too many requests, comments and criticisms from sales, marketing, engineering or whoever. Stakeholder noise can drown out the voice of the user, leading to a product that doesn't address their actual needs and pain points. Anyone who’s ever studied for a business exam will have come across the failure of New Coke in the 1980s. Coca Cola chose to ignore consumer feedback in favour of a pre-determined formula change, leading to negative public reaction and a quick reversal.
How does a product person successfully navigate the daily flood of data, feedback, and inputs from multiple channels they need to manage? Mind the Product has addressed this topic many times and in many ways, so here’s a distillation of our best advice.
Fundamentally, you need to bring structure to the data and information that’s overwhelming you and then structure to the decisions you make with the data and information at your disposal. There are lots of methods and suggestions of best practice to help you achieve this so pick the ones that suit your ways of working, that of your teams and your organisation.
Establishing a single source of truth is widely considered best practice in product development and decision-making, if implemented thoughtfully. If everyone is working from the same source data, then the data owner is known, metrics are consistent, and assumptions are documented, and decision-making can speed up. But don’t fall into the trap of assuming that it gives you all the data you need - there will always be qualitative insights and market signals that need to be incorporated into decision making.
In this evergreen article, Why you need quantitative AND qualitative data, Glenn Block and Timo Hilhorst focus on the differences and respective merits of quantitative and qualitative data and why it’s important for product managers to gather both types.
And this ProductTank San Francisco talk, Make better product decisions by using quantitative and qualitative data, Brian Tran shows us how we can become better product people by supercharging our data with human insights. He says that data collected qualitatively and quantitatively should be able to tell you what job needs to be done and if the problem is currently being solved by a product on the market.
A North Star metric should always help you to understand what data to prioritise and what to ignore. As Sebastian Straube points out in this article, Measuring the right North Star metric, not everything that we can measure matters. Sebastian’s article runs through the North Star framework and looks at how it might be applied to Netflix.
A prioritisation framework is a crucial tool for dealing with information overload. It provides a structured approach to managing information, and breaks down large tasks into manageable pieces that don’t overwhelm. Another evergreen article, Four questions that will lead to better prioritisation, by Lisa Long, is a good starting point. As Lisa says: “The path to success in the complex environment that is product management is to learn as fast as possible. Prioritisation is a way to help you find the one thing to work on, and focus on that.”
Prioritisation frameworks abound and different frameworks will be appropriate in different circumstances. The framework you choose depends on factors like your project's goals, the complexity of the product, the team's expertise, and the available data. This article, Prioritisation: Bringing order out of chaos, offers case studies on how prioritisation is managed at Yelp and Shipt, while this ProductTank talk, Embracing the art of prioritisation by Emily Tate, gives valuable and practical guidance on dos and don’ts. This article, 20 Product Prioritization Techniques: A Map and Guided Tour offers an overview of 20 prioritisation techniques.
Jeff Bezos’s management style has had a profound influence on modern business and has shaped how many companies operate today. At Amazon, documentation isn’t only about record-keeping, it’s used to refine thinking, clarify assumptions and test logic. Techniques that Bezos has popularised - like the Amazon six-page memo or the Type 1, Type 2 decision framework - can really help product people to promote clarity, critical thinking, and a shared understanding.
Equally there are other techniques like one-pagers that offer a concise way to communicate information and force you to clarify your thinking, prioritise key information and present it in a clear and concise manner. Whatever techniques you choose to use, it’s important to eliminate unnecessary details and focus on your core message so that you enable decision makers to grasp your key points quickly and easily.
These are an essential part of any product management practice. Reflection allows product people to analyse their past experience, identify patterns, and adapt strategies, while rituals like daily check-ins and retrospectives create a structured environment for team collaboration, feedback, and iterative improvement.
Remember that a structured approach goes a long way. By structuring how you collect, prioritise, and share information, and by protecting your focused time, you can turn the tide on information overload.
Decision supervision - Structured thinking for product people by Lucy Spence
Analysis paralysis and how to avoid it
Avoiding product management whiplash
The Decision Stack is Martin Eriksson's mental model for strategic alignment so that everyone in a company can make better decisions, faster.
