Best practices

Building Analytics? Time to Start Thinking Like a Product Manager

When it comes to solving a problem in product development, taking stock of the situation at hand is one of the first steps you should take. In this article, Matthew Halliday gives some advice on how to think like a product manager. Get a few steps closer to a thoughtful analytics design with these informative tips.

Analytics that empower users is nothing more than great user experience design. For those tasked with building analytics, that means you have to think and operate like a product manager (PM). You are now in charge of a product that has a user experience (UX)—and as any great PM will tell you, the better the UX, the more successful your product will be.

Where do you start? The good news is that there are plenty of established and well-defined product management best practices you can follow. Here’s how to put them to work for thoughtful analytics design:

Take stock of the situation

The first step in product development is taking stock of the situation at hand. That starts with asking the big questions: What are we doing? Why are we doing it? How will it be done? Who will be involved?

Next, dive deep. Don’t just stop at the first answer—for each, keep asking “why” until you get to the root of why the analytics you are building matter and the business impact you want it to have. In my experience, it usually takes five to seven consecutive “whys” to pull back the layers and get to the most useful insights about the business challenges you are looking to solve.

Third, explore historical data to understand the impact of existing workflows and decision making. In particular, look for examples of missed opportunities or other bad outcomes. This will help you identify areas to examine more closely.

Identify & connect with users

Once you have a clear read on the business challenge, the next step is identifying and connecting with the users of your future product. In the case of analytics, it’s the people who are going to start making better decisions with data.

This sounds simple, but it’s really easy to mess up. That’s because the people who ask for an analytics dashboard are often one step (or more) removed from the people who will actually be using it. They will say, “I need to know who my top performers are—give me a dashboard that tracks individuals on X, Y, and Z.” But don’t just go with what they tell you—dig deeper. Managers may have existing relationships with users, but that doesn’t mean they truly understand their workflows. Building analytics without understanding how they will actually be used is a surefire way to build the wrong thing.

The best way to get up to speed on the decision-making process that’s currently in place at your organization—and where it’s falling short—is by connecting with users directly. Take the time to learn about what they are doing today, how they are doing it, and why they are doing it that way. Throughout the process, keep in mind that your ultimate goal is to empower them. Nobody wants to be a machine that spends all day churning out requests. People are creative—they like to explore and come up with ideas. You have the power to help them do it.

Define the behavior change you want

People who are tasked with developing new products will often say, “I connected with my users and they want X,” and then go off and start building without giving it further thought. That’s a mistake.

Any time you develop a product—regardless of what it is—you are bound to make limiting assumptions about the user and the product they need. Left unchecked, these assumptions can have a major impact on the user experience and therefore the overall success of the project. Building 1:1 relationships with end users is one way to avoid unintentional design flaws, but that alone won’t do it. You also have to define the behavior change you want.

Here’s a highly useful framework from the Circles Method that I encourage anyone building analytics to follow when defining the project’s goals and objectives: Step into your users’ shoes and think through the following statement, “As [X user], I want to [do Y], so that [Z happens].” For example, let’s say you are building analytics for a warehousing and logistics manager: As [the person in charge of ensuring orders get filled], I want to [understand how many days worth of product we have on hand], so that [I can order enough new product to meet demand without overloading the warehouse].

The “so that” is critical. I cannot stress enough how important this is to great product design. Imagine trying to build Lyft or Uber without having any clue about why people hail cars. If you don’t understand the “so that,” you’d probably come up with something like a transportation logistics management software for cab companies—not a killer app where you can order a car simply by typing an address into your phone and clicking a button.

Einstein was onto something when he remarked that if he had an hour to solve a problem, he’d spend 55 minutes defining the problem and the remaining 5 minutes solving it. When it comes to thoughtful analytics design, no truer words have ever been said.

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