As the technology industry continues to evolve and advance, utilising data in product management decisions has become increasingly critical for optimising the achievement of business goals and revenue targets. However, for many companies, data is often an afterthought in the product management process. This results in suboptimal decision-making and missed growth opportunities.
In conversation on The Product Edge podcast, we recently had the opportunity to sit with Frank McKenna, Chief Product Officer at CreditorWatch with 20 years of experience in product management across many industries evaluating the importance of using data to make the most informed product decisions.
As the technology industry continues to evolve and advance, utilising data in product management decisions has become increasingly critical for optimising the achievement of business goals and revenue targets. However, for many companies, data is often an afterthought in the product management process. This results in suboptimal decision-making and missed growth opportunities.
So, Frank helped us understand what a Data-Led Product Manager Looks Like.
A data-led product manager puts data at the forefront of all their decision-making. They focus on the best quality data available to make objective and systematic product decisions. The majority of product managers fall into the category of being “data-informed,” meaning they rely on the data that is available while understanding that it is imperfect and allows for some error and testing.
To become more data-led, product managers should:
- Focus on data-informed decision-making: Start closer to the gut instinct end of the spectrum and work hard to improve the collection of data and refine it. Rely on this data and analytics to drive decision-making, and as more data is gathered, the decision-making process becomes more mature and leads to better results.
- Utilise various data sources: Often, the challenge for product managers is finding the data. However, there are several sources available, including metadata (data derived from the usage of the product), financial data (linked to customer dollars), and secondary data (information on competitors).
- Manage data complexities: To avoid getting intimidated by the data itself, keep the process simple and have a clear objective of what you are looking forward to. Utilising available data sources will help to achieve the objective.
- Evaluate the quality of data: Remember for every key metric, it’s important to have a counter metric to validate the accuracy of the first metric.
Final thoughts…
In today’s dynamic and fast-paced technology industry, the pressure on product managers to make the right decisions is only increasing. By becoming more data-led, product managers can empower themselves to make better decisions and drive growth for their companies.
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