The State Of Data Driven Decision Making In Product Management

Source: Data Driven Decision Making in Product Management

By Aaron Eden on March 14, 2016

A recent study by Harvard Business Review analyzed the utilization of competitive intelligence and market insights within large corporations. They found that an astonishing 45% of analysts’ input had no impact on decision making within the company. The primary reason, suggests HBR, is that “many executives decide on a course of action and then use competitive intelligence to ratify their choice.”

However, the study found that analysts who worked specifically to provide insight for product launches generally found their input to be impactful. When it comes to product management, corporations by and large recognize the value of research. That’s because, according to HBR, a “lack of insightful anticipation…leads to many more failures than there should be.”

We surveyed more than 150 product managers about their perceptions and practices regarding data-driven decision-making. You can download the full report here, but we’ve outlined three interesting findings and implications below:

1. There’s a language barrier.

There are a lot of buzzwords flying around in product management right now, and that’s a problem particularly when they mean different things to different people. For example, Wikipedia defines ‘data science’ as the “interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured.” And yet, while that sounds a lot like ‘data driven decision making’, product managers beg to differ: Personal_Aptitude_for_data-01.png

Twice as many product managers felt they are excellent (a 9 or 10 out of 10) at data driven decision making than data science, while less than half as many felt they were weak at it. We need to be careful when discussing the desired practices and outcomes so as not to conflate phrases.

2. Product managers are often the resident experts.

As you’ll read in the report, only 21% of product managers have access to a data scientist in the organization, although, as we now know, that might not be the capability they think they need. By and large, product managers felt that their own aptitude for data driven decision making was superior to their team’s effectiveness at actually executing it. It’s critical for product managers to take training and education seriously when it comes to this topic, as they’ll likely be the expert on hand.

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Nevertheless, more than 40% of product managers felt their teams were generally effective (7 or above out of 10).

3. Large enterprises are on the cutting-edge.

For the most part, product managers from large organizations were the most likely to adopt best practices for capturing data. This was true for using business intelligence tools, social listening, and running surveys. However, they were behind when it comes to running in-person interviews and online user tests.

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There is still considerable room for improvement across the board, but generally speaking product teams are using a variety of channels to collect data and effectively make decisions. Learn more about their practices in our full report.

Data driven report by Moves the Needle: Download Here Data-Driven Product Management Practices