Project Management: Asking the Right Questions of your Data
Today, for employees of all backgrounds, data has become an essential part of their jobs in ways that we have never seen before. This includes everything from engineers tracking roadmap progress and bug fixes to recruiting and HR tracking how benefits affect retention. With so many people living and working in data, it has become essential to make sure that the correct data is not only being captured and analyzed but that we are asking the right questions of the data and of those who analyze it.
Why data is ubiquitous
Data is not just for the data analyst anymore. The number of people working in data has grown tremendously and now encompasses nearly every department. Product managers are living in data to understand all aspects of what their team is building - both what’s working and what’s not. Marketers are using data to fully analyze their funnels for optimizing spend to ensure that they are using the highest performing creative in the markets that provide the most return. Sales managers are using data to get a complete view of their pipeline, including what makes a rep successful and identifying strategic opportunities in new segments and regions.
Technology alone can’t change things; people are needed as well
The result of this new wave of data workers is a shift in the day-to-day tasks of the data analyst. Traditionally, data analysts are trained to be service providers, but with more employees self-serving with their data, data analysts are becoming more strategic in their role. Thus, data analysts have to start shifting from providing service to driving conversations around how we need to be analyzing the data.
How to approach data to find the right answer
When looking for a solution, rather than starting with the data, it’s essential to think about the business problem you’re trying to solve first. If you start with the data, you’re likely to end up spending time chasing “answers” that won’t make your business more productive. We must go into the data with a clear directive of what we are looking for, or else we will end up in a state of chaos digging through massive amounts of data to try to find trends and patterns that often lead to dead ends as a result of unclear objectives.
A great example of this can be found in marketing. It is essential to have a thorough understanding of each step in the funnel, and the tactics that have been effective for moving people from each stage of the funnel to the next. Data can help you identify the exact place where you are losing the customer in the funnel and subsequently, how that impacts every stage after, which is crucial for businesses. If you identify that people are getting stuck because they can’t find the sign-up button, putting in that fix is going to impact your conversation rate and overall revenue significantly.
Again, you mustn’t send your data analysts into a rabbit hole, where they’re likely to get stuck. It’s business owners’ job to find an experiment or a business question that can impact the bottom line and send their analysts after that first. If you do that, you will get more value quickly, and it will get you the buy-in and the resources to do the next thing. Chasing something that is exciting but won’t make a difference to the business is not going to move the needle. You have to find what is going to make a tangible and immediate difference so you can keep going.
Into the crystal ball
Newer, better, and faster technology always arrive with time, but the fundamentals remain the same: focus on answering business questions. Technology alone can’t change things; people are needed as well. The ways we answer questions and the technical processes with which we tackle them will change over time, but the core learning about how to improve your business will remain the same.
Daniel Mintz’s background is in music and political science, but somehow, he ended up working with technology - and data products. He has been working as a data evangelist for fifteen years and has watched that space evolve quite rapidly over the last five to ten years. He has overseen data analytics operations at large political organizations and publishers. He stepped into his role as Chief Product Evangelist at Looker three years ago. At Looker, he spends a lot of his time talking to customers hearing about what they’re up to, what they’re trying to do, and coming up with ways to help tackle their hardest challenges.
Looker is a unified data platform that delivers actionable business insights to employees at the point of decision. Looker integrates data into the daily workflows of users to allow organizations to extract value from data at web-scale. Over 1700 industry-leading and innovative companies such as Sony, Amazon, The Economist, IBM, Spotify, Etsy, Lyft, and Kickstarter have trusted Looker to power their data-driven cultures.