A little bit of statistical background on, on idea filters.

It is true that depending on how you set up your scoring and

your weight factors, and your hurdles, things might change a little bit.

And I just want to point out that that's rather advanced statistics not that

critical if you're, but if you are in the long term over years setting up

these systems and using these systems to manage your portfolio of ideas then,

then you might want to consider some of these factors so

a couple things to point out, one you might want to accentuate the weights.

So, rather than going to 150% maximum, you'd say no this,

this factor is really important.

We're going to make that 300%.

So we're going to, we're going to triple any score on that factor right?

You could also go to negative ratings.

Some, some teams like to think of it in negative terms or par.

Zero is a, is an okay score.

And if it's.

If a certain factor is bad, if an idea scores poorly on a certain factor,

we should actually subtract points.

So let's do minus two or minus five.

Right, and if,

if an idea is good on a certain factor then let's give positive points.

These are nice ways to statistically tweak things if you're

doing this over years you can build up a more, your system's going to get more and

more intelligence into it.

I just want to point out that it's, it's not making a lot of difference.

The 80-20 rule,

you've got 80% of the value by not spending a lot of time tweaking this.

And also, no matter how you do it,

it tends to make the same relative difference.

Between ideas.

So, remember that's one of the key reasons we're having an idea filter.

We're going to look at multiple ideas, and

we want to see the difference among those ideas.

That's the more important thing to take away than the exact score in any one

of these ideas.