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Planning for future development by identifying factors leading to high-growth

Editorial Staff

It all sounds as if it's tailor made for cynics: a government looks at high-growth companies using what it terms "non-traditional data" (which turns out to be social media comment about and by the company and the companies's own websites) and uses it to predict what industries and what regions may thrive. And cynics would be right: social media comment tends to be polarised and out of balance and websites are, of course, the bearers of good tidings. So what's going on?

The UK's Office for National Statistics (ONS) undertook research as part of a project by the Department for Business, Energy and Industrial Strategy (BEIS) (don't worry if you can't keep up with UK government acronyms: there's always a department lined up for renaming to keep people busy on pointless tasks so there's not much point in trying to remember department names, etc.).

That project used tax data from HM Revenue and Customs (HMRC) .

Interestingly, "it was observed that high growth companies tend to discuss general overview terms such as team and management more than specific terms like tax, law and manufacturing." Hm.. companies that grow fastest tend to not disclose factual information. However, the conclusion seems to be at least an unsupported assumption if not a downright non sequiter: "This is an interesting first insight into the language used by businesses in their websites, and could suggest that high growth companies are more interested in people and processes rather than specific tools or terms."

Then there is a startling (can you feel the cutting sarcasm) finding that urban retail businesses tend to grow faster than rural retail businesses. That is remarkably like "why rob banks?" "Because it's where the money is."

Then, we get "Our analysis has confirmed existing research that it’s difficult to predict high growth firms, and that both clustering effects and being well networked are weakly associated to high growth firms."

That translates to "we learned nothing new, including that this research "is difficult. Then it says " We have, nevertheless, uncovered some interesting relationships which might bear further investigation."

That translates to "but we are going to continue to spend public money on this proven failure just in case we happen to find something that someone else hasn't already found.

If you want to read the entire report, you can find it here: https://datasciencecampus.ons....

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