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How to Ask Data Science Questions

Published August 8, 2021
Doug Rose
Author | Agility | Artificial Intelligence | Data Ethics

Many organizations that try to implement machine learning are guilty of putting the cart before the horse. They build a machine learning team before they have any idea of what they will actually do with machine learning. They have no specific problems to solve or questions to answer that they cannot already solve or answer with their existing tools — their business intelligence software or spreadsheet application. They end up building a knowledgeable data science team, but all the team ends up doing is playing with the technology. Nobody on the team knows enough about the organization to identify areas in which machine learning could be of practical use. They need to start to ask data science questions.

How Not to Launch a Machine Learning Initiative

I once worked for an organization whose leadership was committed to machine learning and made a considerable investment in it. They assembled a team of machine learning experts from a local university and provided them access to the organization’s data warehouse. The team built the infrastructure it needed to implement machine learning, but it quickly reached a dead end. Nobody in the organization had given much thought to how this amazing new technology would benefit the organization.

When the team began to ask, “What questions do you need answered?,” “What problems do you need to solve?,” and “What insights gained would help drive business?,” nobody had an answer. In fact, nobody in the organization ever imagined asking such questions. The organization had a strong control culture in place, so employees generally did what they were told. They were not rewarded for asking interesting questions and often felt discouraged from doing so. When they did ask a question, it was something like, "What type of promotions do our customers like?," which is something that could be solved with traditional database or spreadsheet tools.

The members of the machine learning team felt as though they had built a Formula One race car that was just sitting in a garage.

Nurturing a Culture of Curiosity

Whether you have a data science team in place or are planning to create such a team, the first step is to build a culture of curiosity. Start by educating everyone in the organization about machine learning, so that, at the very least, they can recognize various ways it can be applied. Next, encourage everyone in the organization to start asking questions, looking for problems to solve, and sharing their ideas. Machine learning can benefit every team in your organization — including research and development, manufacturing, shipping and receiving, marketing, sales, and customer service. Have each department maintain a list of problems, questions, and desired insights; prioritize the items on the list; and then consider which technology would be the most effective for addressing each item. Keep in mind that the best technology isn't necessarily machine learning; sometimes, all you need is a data warehouse and business intelligence software.

Of course, questions, problems, and desired insights vary depending on the organization, but here are a few sample questions to get you thinking:

  • What can we do to market more effectively to our customers and prospective customers?
  • How likely is it that a user will click on this ad?
  • Are there any processes or procedures that could benefit from greater levels of automation?
  • Who are our best customers?
  • If we could predict the future, which predictions would be most valuable to our organization?
  • How could we use machine learning to optimize preventive machine maintenance?
  • How can we use machine learning to identify the best qualified candidates to fill our current openings?

Here are a couple concrete ways to encourage people in your organization to start asking interesting questions:

  • Conduct question meetings. The sole purpose of the question meeting is to ask interesting and relevant questions and call attention to problems. Do not try to answer questions or solve problems during the meeting. Ban all cell phones and other electronic devices, and have your research lead conduct the meeting.
  • Place a question board in a well-trafficked area. A question board invites people to post questions and problems and provides inspiration for additional questions. In large organizations, consider posting multiple question boards, so everyone can participate.

Asking questions and calling attention to problems seems like a no-brainer. For any organization to survive and thrive, innovation is essential, and what sparks innovation are compelling questions and difficult problems. Unfortunately, many organizations have a strong control culture in which people are not rewarded and are often punished for asking questions and challenging the status quo. If that sounds like your organization, you need to find a way to break it free from its control culture and make everyone in the organization feel free to share their ideas and concerns.

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