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How I Reduced a Client's Daily Process from 4 Hours to 10 Minutes

· workflow, efficiency, bloomberg

One of the most rewarding projects I worked on at Bloomberg started with a simple observation: a client was spending 3–4 hours every morning on a repetitive data-gathering process before they could even start their actual analysis.

Spotting the Problem

The client — an equity analyst at a mid-sized fund — had built their daily workflow around manually pulling data from multiple Bloomberg Terminal functions, copying it into Excel, and running a series of calculations. Every morning, the same routine. Three to four hours. Before they’d made a single investment decision.

When I sat with them to understand their process, a few things stood out:

  1. Repetition. They were pulling the same data points every day from the same securities.
  2. Manual steps. Cut-and-paste between Terminal and Excel, with no automation.
  3. Error risk. Manual data entry meant occasional mistakes that took time to catch and correct.

The Approach

I didn’t start with technology. I started with questions:

  • What decision are you trying to make with this data?
  • Which steps add value, and which are just preparation?
  • What would your ideal morning look like?

The answers revealed that roughly 80% of the time was spent on data collection and formatting — steps that added zero analytical value.

Building the Solution

Using Bloomberg API and BQL (Bloomberg Query Language), I built an Excel-based solution that:

  1. Automated data retrieval — BQL queries pulled all required data points directly into Excel with a single refresh
  2. Standardised calculations — Pre-built formulas replaced manual computation
  3. Added validation checks — Automatic flags for data anomalies or missing values

The technical side took about a week of iterative development, with the client testing each version and providing feedback.

The Result

The daily process went from 3–4 hours to approximately 10 minutes — a ~95% efficiency gain. But the real win wasn’t the time saved. It was what the analyst could now do with those freed-up hours: actual analysis, idea generation, and better-informed investment decisions.

What I Learned

This project reinforced something I believe deeply: the best technology solutions start with understanding the human workflow. The Bloomberg Terminal is powerful, but power without usability is just complexity. The job isn’t to show clients every function — it’s to find the specific combination that makes their job easier.

That approach — listen first, build second — has shaped every client engagement I’ve had since.