Datadoodle

Home » Uncategorized » Page 30

Uncategorized

Pulling on the root of bad business writing

by

In his fine weblog Startup Diaries, David Silverman takes a good stab at answering the eternal question: Why is most business writing so bad?

He writes, for example, “I blame this on an educational system that rewards length over clarity. When you get tick marks for bulls’ eyes — and no demerits for the number of darts used — the student learns to overwrite in hopes that at least some of their sentences hit the mark.”

I once experimented with that theory. For one class in graduate business school, I had to write two book reviews. The first one got a bad grade despite concise, well thought out points.… Read the rest “Pulling on the root of bad business writing”

Rejecting stale tech marketing words

by

Read a pile of technology marketing and you quickly assume that you alone despise many of the words you keep hearing. They’re words like optimize, leverage, synergy, and utilize. People in this industry don’t really talk like that, do they?

Many don’t, at least not in private, and they don’t tweet like that, either. One tweet trail at Gartner BI Summit complained about exactly this kind of word — these miserable words with all the wild flavor bred out of them like factory-farm tomatoes.

On the list of suggested extinction, Jill Dychè listed optimize and fact-based. Scott Davis listed leverage, co-optition, and dot-bomb.… Read the rest “Rejecting stale tech marketing words”

Don’t call me “non-technical”

by

When I’ve referred to “non-technical” users, I’ve always meant just about anyone working far away IT. Well, based on research by Lyzasoft’s CEO Scott Davis, I think I’d better be careful with that definition.

My concern is not for IT people. It’s for the “quants” in finance, marketing, accounting and operations who may not write code or maintain computer networks but do go deep into math, data and logic most work days. These “quants” resent being called “non-technical” by the IT types. The quants shoot back: knowing SQL, they might point out, is easy compared with modeling demand elasticity.

The mutual disrespect is too bad, especially since the two technical types have more in common than those who rely on “guts.”