Is this industry still worth entering? Three scores give the answer

What this is

One of our published methods, written in plain language: what it can do, when to use it, what goes in and what comes out.

Why it matters

Most methods are published as papers or code. This one is written so you can decide whether it fits your problem before you invest time in it.

How to use it

Read the page top to bottom. If it matches your question, use the online tool - or subscribe and run it on your own data.

What you get

A clear answer on what the method does and does not do, plus a live curve from our own demand series. Free to read.

Free to readOnline tools from $5 per runSee it →

Demand curve read by this method — A live reading from our own demand series - the shape of the signal this method works on. 570 industries are tracked daily; this is one of them.

Our own data: 75 industries with benchmark scores, and 213,208 city x industry records behind them (lifechain, 2026-10-08).
Data base: InfoGap own records - 391 Chinese cities x 8 dimensions, 213,208 city-industry rows, 40,499 POIs (central / lifechain, 2026-10-08).

InfoGap Algorithm Handbook · one algorithm per page · plain language

1In one sentence: what it does

Scores an industry from three angles — does it decide on data, will new technology replace it, how high is the barrier.

2When to use it

You are most likely in one of these three situations:

You want to open a shop, and the industry comes first.

What people usually do: see whether peers are making money, and follow whoever is.

With this: score each of the three angles once, land on one of three conclusions, and pick against that conclusion.

The shop has been open two years, and you feel customers getting fewer.

What people usually do: add services, add promotions.

With this: look at the vitality grade of the industry first. If the industry itself is heading down, that is the industry's problem, not your service's — promotions will not pull it back.

You are looking at a city opportunity table: Beijing, Shanghai, Shenzhen and Chongqing each have a batch of industries marked "rising", and you don't know which one to go after.

What people usually do: pick whichever scores highest.

With this: use it to see whether the industry itself holds up in a downturn, then decide whether to take that city dividend. The city table only says where somebody wants something, not whether this line can take a hit.

3What goes in · what comes out

Input: a score for each of the three angles (0–100 each) plus two supporting numbers (this is the set used for the real run)

Does it decide on data — 62
Will new technology replace it (the higher, the safer) — 45
How high the barrier is (the moat) — 58
Data quality — 62
How digital it is — 55

What comes out

Output: the raw run, as it came out (not a character changed)

The three angles:
  Data-driven   62 points (weight 0.4)
  Replaceability 45 points (weight 0.3)
  Entry barrier  58 points (weight 0.3)
Total (weighted): 55.7
Conclusion: 🟡 Data-replaceable — an industry in digital transition, facing replacement risk, needs to transform
Vitality: medium

How to read it: 55.7 sits in the middle band. It means the line can still be worked now, but it is stuck right in the window of being reworked by digital tools, and the old ways will get harder and harder. The other two conclusions are 🟢 data-driven (strong) and 🔴 not replaceable (it lives off craft / licence / location and nobody can take it away).

📈One picture: is this industry still worth entering

Three angles scored; see whether you can enter, need to change, or should stay away.

4How to use it

There is no public calculator for this yet — the method above is the whole procedure; on this site the inputs have to be keyed in by hand.

Score each of the three angles (0–100)
Work the weighted total out with the weights above
Read the total score, the conclusion colour, and the vitality grade

5Who it is for

People about to enter an industry; people who have worked in one for a few years and feel it changing lately; people who look at projects for other people.

6Common questions

Q: I scored it myself — won't that be off?

A: It will. It works out your judgement as it stands, not objective fact. Only honest scoring is useful — treat it as a mirror, not a ruler.

Q: If it comes out in the middle band, is it hopeless?

A: It is not a death sentence, it is "needs changing". Either move toward data, or make the barrier thicker — pick one.

Q: How does it relate to the city opportunity table?

A: Use them together. The city table answers "where is the demand"; this one answers "can this line take a hit".

7Related algorithms

traffic-target · who should you be talking to demand-verify · is the demand real curve-generation · is it rising or falling ← Back to the Algorithm Handbook

✓Why this scenario exists (the evidence)

Why this scenario exists:

The site has a city × industry opportunity-gap table produced by a real run: 50 rows, running down from a score of 120.22 (Beijing, 13 industries) to 112.66 (Chongqing), every row marked "industry direction = rising".

But that table only says "where the demand is", not "whether this industry can take a hit itself" — which is why this algorithm exists, to supply the other half.

Source: the site's city × industry opportunity-gap table.