data-driven decision-making

USAGE SUMMARY

"data-driven decision-making" is correct and commonly used in written English.
It is typically used to describe the process of making decisions based on data and analysis, rather than intuition or personal opinions. Example: "Our company's success is a result of our strong commitment to data-driven decision-making. We thoroughly analyze sales data and customer feedback before making any major business decisions."

✓ Grammatically correct

News & Media

Science

Formal & Business

Human-verified examples from authoritative sources

Exact Expressions

32 human-written examples

Getting them to adopt technology for data-driven decision-making is often the largest obstacle".

The Guardian

Our culture is taken up with an all-pervasive pretence at rational, data-driven decision-making.

The Guardian

His compelling research resonates in another era of budget-cutting and data-driven decision-making.

The New York Times

Reading assignment In last month's class, the topic was "data-driven decision-making".

The New York Times

Google, not surprisingly, is committed to applying data-driven decision-making to human resource management.

The New York Times - Tech

We live in an age of data-driven decision-making: decisions that impact every aspect of our lives.

The Guardian

Human-verified similar examples from authoritative sources

Similar Expressions

28 human-written examples

Ms. Spellings praised No Child Left Behind for "shining a spotlight" on what works and what does not, and said its focus on data-driven decision making was a sea change in Education Department practice.

The New York Times

Pragmatism and data-driven decision making rule the company.

TechCrunch

A glaring example of the perils of data-driven decision making still haunts Ebay.

Forbes

Data-driven decision making (DDDM) ALL STUDY PERIODS All EPIS STAGES Interagency workgroups  6.

Health & Justice

"Data-driven decision making and intelligence is becoming critical for all businesses.

TechCrunch

Expert writing Tips

Best practice

When advocating for "data-driven decision-making", ensure the data is relevant, accurate, and properly analyzed to avoid flawed conclusions. Always validate your data sources and analytical methods.

Common error

Avoid relying solely on data without considering the broader context or qualitative factors. "Data-driven decision-making" should be balanced with human judgment and practical insights to prevent skewed or impractical outcomes.

Linguistic Context

The phrase "data-driven decision-making" functions as an adjective phrase modifying the noun 'decision-making'. It describes a process or approach to making choices that are heavily influenced by data analysis and insights. As Ludwig AI explains, it means basing decisions on data and analysis rather than intuition.

Expression frequency: Common

Frequent in

News & Media

33%

Science

48%

Formal & Business

11%

Less common in

Encyclopedias

0%

Wiki

0%

Reference

0%

Ludwig's WRAP-UP

In summary, "data-driven decision-making" is a common and grammatically correct phrase used to describe a systematic approach where data informs choices. As Ludwig AI confirms, it's about making decisions based on data and analysis, not just intuition. Predominantly found in News & Media and Science contexts, it conveys a professional and rational tone. While emphasizing the importance of data, remember to balance it with contextual understanding and human judgment. Consider alternatives like "evidence-based decision-making" or "analytics-driven decision-making" to vary your language.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

evidence-based decision-making

Emphasizes the use of empirical evidence to inform decisions, akin to using data as a primary driver.

analytics-driven decision-making

Highlights the role of analytics and statistical methods in the decision-making process.

fact-based decision-making

Stresses reliance on verifiable facts and objective information rather than subjective opinions.

informed decision-making

Focuses on the aspect of being well-informed through data and analysis before making a decision.

data-informed decision process

Highlights the impact of data in shaping the decision-making process rather than being the sole driver.

quantitatively driven decisions

Uses measurable, numerical data as the primary basis for decisions.

insights-driven strategy

Shifts the focus from the decision itself to the overall strategy guided by data insights.

metrics-based approach to decisions

Highlights the utilization of performance metrics in evaluating alternatives and choosing the best option.

statistically validated choices

Highlights that the decisions were backed by statistical evaluation.

algorithm-guided decision

Emphasizes the use of algorithms and automated processes in making decisions.

FAQs

How can I effectively implement "data-driven decision-making" in my organization?

Start by identifying key performance indicators (KPIs), investing in data analytics tools, training employees on data interpretation, and fostering a culture that values evidence-based insights. Regularly review and refine your processes to ensure data is accurately informing decisions.

What are some alternatives to "data-driven decision-making"?

You can use alternatives like "evidence-based decision-making", "analytics-driven decision-making", or "fact-based decision-making" depending on the context.

What are the potential pitfalls of relying solely on "data-driven decision-making"?

Over-reliance on data can lead to neglecting qualitative insights, overlooking ethical considerations, and failing to adapt to rapidly changing circumstances. It's crucial to balance data with human judgment and contextual awareness.

How does "data-driven decision-making" differ from traditional decision-making approaches?

"Data-driven decision-making" emphasizes the use of empirical evidence and analytical insights to inform choices, whereas traditional approaches often rely on intuition, experience, or personal opinions. The key difference lies in the objectivity and verifiability of the information used.