Data is not garbage.  Could it be better?  Could you get more insights from it?  Absolutely. That is the opportunity lurking within the data.  As data leaders, we should push forward the idea about unleashing the potential within your data versus disparaging it.   This mindset shift enables the ability to see past the immediate imperfections and into potential for refinement and discovery.

A real-world example of the impact of the different approaches is two separate clients that had significant duplicate and disjointed supplier data.  One client framed the issue as having crap data that needed to be cleaned up and the other framed the issue as the opportunity to gain a 15% reduction in their raw material cost.  The difference in how this situation was framed directly impacted the engagement, the energy at every interaction, and effectiveness of the initiatives.  Nobody wants to work in crap, but everyone wants to be part of something that will have significant impact.

Understanding the Value in All Data

The term “garbage data” inherently suggests that certain datasets are, from the outset, of no value. This is a misconception. All data, when approached with the right tools and mindset, holds potential insights. The challenge often lies not in the data itself but in our methods and perspectives towards analyzing it.

When we label data as “garbage,” we risk overlooking opportunities for learning and growth. Instead, viewing all data as a resource waiting to be properly tapped encourages a culture of innovation and problem-solving.

The Growth Mindset and Data Analysis

Carol Dweck’s concept of the “growth mindset” – the belief that our basic qualities are things we can cultivate through our efforts – applies perfectly here. Viewing “garbage” data through the lens of a growth mindset enables data professionals to see past the immediate imperfections and towards the potential for refinement and discovery.

Here are a few strategies to reframe how we approach less-than-perfect datasets:

  • Focus On the Strategic Objectives: Focus on what can be achieved to drive engagement and funding.  Executives don’t want to fund consolidating supplier data, but they do want to fund ways to reduce raw material spend.
  • Recognize Quality Requirements Differ:   Data might be fit for purpose for one aspect of the business, might not be the case for another.  The operational side of the house has different data requirements than the analytics group.
  • Identify Opportunities for Improvement: What can “garbage” data teach us about our data collection processes, and how can we improve?
  • Foster a Collaborative Approach: Engage with your team in brainstorming sessions on how to tackle challenging datasets and the potential that is contained within.
  • Data is Ongoing:  Data is a product that can always be improved. Adopting a Plan, Do, Check, Act process fosters a growth mindset.  

Concluding Thoughts

Let’s retire the term “garbage data” from our professional vocabulary. Let’s view every dataset as a stepping stone toward deeper insights and knowledge. By adopting a growth mindset towards data, we empower ourselves and our organizations to explore, innovate, and achieve our goals.

By reconsidering how we refer to and think about our data, we open up new avenues of opportunity and learning. The next time you’re tempted to label a data as “garbage”, pause and reconsider. What additional opportunity might you find with a change in perspective?