Day 5 · 14:00 · 90 min

The executive playbook

What you take back on Monday

Day 5 · 14:00

The course ends. The pack on Monday does not. This is the one-page operating system you take back to the function.

You will leave able to

  • Leave with a checklist for every chart that will see EXCO.
  • Know which tool does which job (Excel, R, Quarto, Shiny, AI).
  • Name the 30-day habit that keeps the craft from rotting.

Everyone can be a data scientist. Not everyone should publish a mean.

Faculty, Hack Your Data · Lagos Business School

The chart checklist

  1. Tidy: one variable per column, one observation per row.
  2. Unit of observation named in the subtitle.
  3. Distribution shown when a mean would hide a tail.
  4. Colour maps a variable, not a decoration.
  5. Title is a description; any claim lives in the prose, with a caveat.
  6. Source file and extract date in the caption.
  7. The pipeline that built it lives in a repo, not in a sent folder.

Which tool, on purpose

JobDefault toolNot this
Ad-hoc cut, n small, you are aloneExcel / Power QueryA Shiny app
Repeatable weekly briefQuarto + tidyverseA new workbook each Monday
24/7 operations pulseShiny / Posit Connect / BIA PDF from last Thursday
Draft the dplyr you cannot rememberbongo.ai / approved copilotPaste the customer file into a consumer model
Publish the pack of recordWebsite on mainEmail attachments named FINAL_v9

The 30-day habit

  • Week 1. Recreate one chart from your last EXCO pack in ggplot. Hang both. Ask which one you would sign.
  • Week 2. Move the source CSV into a project folder. Knit a one-page Quarto. Send the HTML, not a screenshot.
  • Week 3. Add a stop-word list to one qualitative extract (VoC or exit comments).
  • Week 4. Put the project on an internal Git host. Invite one colleague. The craft becomes a function’s, not a person’s.

What we did not cover — on purpose

Causal inference beyond the warning. Production machine learning. Credit-risk models. Geospatial. Those are other LBS rooms. This room was communication under uncertainty: tidy data, honest charts, reproducible packs, a copilot you do not blindly trust.

Community

Stay on the alumni channel. Share pipelines, not confidential extracts. If you hire analysts, ask to see a repo. If you *are* the analyst, ask for time to knit rather than time to beautify a slide.