IT Best Practices

An Introduction to Data-Driven Decisions for Managers Who Don’t Like Math

Using data effectively, companies can learn about their consumers, make better business decisions and continually steer the company to prosper. Data can give businesses a competitive advantage and help in finding new business opportunities. Walter Frick of Harvard Business Review shares advice for those who want to understand and improve the use of data in their business.

Why We Should Use Data

Companies are vacuuming up data to make better decisions about everything from product development and advertising to hiring. In their 2012 feature on big data, Andrew McAfee and Erik Brynjolfsson describe the opportunity and report that “companies in the top third of their industry in the use of data-driven decision making were, on average, 5% more productive and 6% more profitable than their competitors” even after accounting for several confounding factors.

A Few Tips For Those Who Don’t Like Math

  • Pick the right metrics

There is a lot of data. The important part is distinguishing between which data is useful and which data isn’t.

  • Know the difference between analytics and experiments

Analytics provide data on how a business is performing and experiments “test out different approaches with different consumer or employee segments and measure the difference in response.”

  • Ask the right questions of data
  1. What was your source of data?
  2. How well do the sample data represent the population?
  3. Does your data distribution include outliers?
  4. How did they affect the results?
  5. What assumptions are behind your analysis?
  6. Might certain conditions render your assumptions and your model invalid?
  7. Why did you decide on that particular analytical approach?
  8. What alternatives did you consider?
  9. How likely is it that the independent variables are actually causing the changes in the dependent variable?
  10. Might other analyses establish casualty more clearly?

  • Correlation vs. cause-and-effect

One thing you should understand is the difference between correlation and cause-and-effect. When two variables correlate, it does not imply that one causes the other.  

  • Know the basics of data visualization

How you present your data is a biggie. Accurately display your data with the right kinds of charts and tables. Make sure the content is compelling and gets the message across.

  • Learn statistics

This does not mean going back to school, but grasping the basics of statistics should suffice in helping you understand data.

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