The Crucial Role of Contextual Data in Decision-Making
I am a fan of Data driven decisions. As a person who is somewhat risk averse, I like to see data that allows me to understand the risks I am taking and make the best decisions possible. However, not all data in all situations are great data. Context is critical in accumulating data.
Allow me to provide an example.
An Example from Fleet Maintenance
Consider a company looking to optimize its motor vehicle fleet maintenance. Despite having an abundance of data, it is easy to fall into a classic pitfall: correlation doesn’t imply causation. This principle is humorously illustrated by spurious correlations, such as the relationship between science technology degrees and avocado toast Google searches.
The Missing Link: Data Input Processes
Our client had extensive data on parts replacements, vehicles, timing, and costs. However, they lacked crucial context due to some incomplete data input processes:
Categorization – New parts were not properly categorized, making it difficult to track similar components across different vehicle models.
Inconsistency – The process for recording parts used in repairs was inconsistent, complicating things like tracking warranty.
The Impact of Contextual Data
When part categories are introduced, trends started to emerge. For instance, grouping all transmission-related data revealed an unusually high replacement rate, which then led to some important questions:
· Are these specific transmissions problematic?
· Are the vehicles appropriately specified for their tasks?
· Are operator behaviors contributing to transmission failures?
Until then a high transmission replacement rate was only tribal knowledge.
With consistent data entry for parts related to work orders, it became easier to identify work efforts that were most likely able to be completed under warranty.
Key Takeaway
“The more data the better” is often the refrain, but more data without context doesn’t deliver better information. In that case, less is often more. Proper processes to capture contextual data lead to asking the right questions and making informed decisions that drive business improvements. This approach transforms raw data into actionable insights, enabling truly data-driven decision-making.
Contact us and we would love to have a discussion with you about your data, and what it’s telling you.