A recent HBR piece sheds light on the challenges most companies face in their quest to create a data-driven culture and how to help overcome them. Whether your company is well on its way to being data driven or just getting started at building a data culture, you’re likely to benefit from the 10 steps outlined in the article, including:

  1. Data-driven culture starts at the (very) top. Top management at companies with data-driven cultures typically require that decisions be “anchored in data.” According to the article, “The example set by a few at the top can catalyze substantial shifts in company-wide norms.”
  2. Choose metrics with care—and cunning. Managers should choose metrics that matter for their business—and be able to effectively measure them. By setting clear expectations by setting the metric employees are expected to use, managers can “exert a powerful effect” on employee behavior.
  3. Don’t pigeonhole your data scientists. Breakdown the boundaries between data scientists and the business. Moving staff from centers of excellence to line positions and requiring all employees to be “code-literate” are examples of how companies are overcoming this challenge.
  4. Fix basic data-access issues quickly. According to the HBR article, even the most basic data is inaccessible across the company. One strategy to help overcome this problem is to provide broader employee access to a limited number of data sets and metrics at a time, ensuring people have a clear understanding of its value and why it’s important for the business.
  5. Quantify uncertainty. Requiring employees to understand and quantify uncertainty helps ensure the use of reliable and broad data sets for better accuracy. This also forces employees to experiment more and leads to smarter decisions.
  6. Make proofs of concept simple and robust, not fancy and brittle. To separate promising ideas from more practical ones, companies should employ proof of concepts that include viability in production to ensure success. One way to do this is to start simple and increase sophistication over time.
  7. Specialized training should be offered just in time. According to the article, “Many companies invest in ‘big bang’ training efforts, only for employees to rapidly forget what they’ve learned if they haven’t put it to use right away.” Rather, companies should focus on training that is needed now and can be applied immediately to advance a data culture.
  8. Use analytics to help employees, not just customers. Apply data analytics in ways that benefit employees, not just customers. According to the article, this can be achieved by looking for ways to revamp work, saving time, helping avoid rework, or getting frequently-needed information.
  9. Be willing to trade flexibility for consistency—at least in the short term. Companies can waste countless hours trying to rationalize inconsistent data, different metrics, and favorite programming languages. To overcome this and contribute to consistency of data usage and metrics across the business, executives can mandate the usage of specific metrics and programming languages.
  10. Get in the habit of explaining analytical choices. Since they may be several solutions to a single problem, it’s important for employees to be able to clearly communicate and make tradeoffs. According to the article, “It’s a good idea to ask teams how they approached a problem, what alternatives they considered, what they understood the tradeoffs to be, and why they chose one approach over another.” 

To learn more, including examples from across industries, read the complete HBR article.