[Music intro]
MICHAEL SCHRAGE: This is Michael Schrage.
I am the MIT Sloan Management Review guest
editor for a very interesting series
on strategic measurement.
It is my good fortune to have as our guest Andrew Low Ah
Kee, who is the chief revenue officer for GoDaddy, one
of the most interesting and innovative internet companies
here in Silicon Valley.
And we’re here to discuss how Andrew and GoDaddy use KPIs
and analytics, not just to manage day-to-day performance
but to manage the strategic transformation of the company
in a very, very competitive global environment.
Thank you so much for being here, Andrew.
ANDREW LOW AH KEE: Thanks for having me.
It’s great to be here with you.
SCHRAGE: I’d like to begin by asking you a straightforward
question for the audience.
What’s the most important thing our viewers should understand
about GoDaddy?
LOW AH KEE: It’s really pretty simple.
We have a singular purpose.
And that’s to help anyone, anywhere in the world,
who has an idea turn it into a reality.
And we do that by giving them all the tools and help
they need to have their ideas start, grow, and thrive online.
SCHRAGE: You’ve been with the company for a long time running
the operations.
What’s been the evolution of your key performance
indicators?
LOW AH KEE: Before we talk about how it’s evolved,
I think it’s important to talk about where we started.
This business, when I first got involved with back in 2011,
was one of the most analytical, data-rich environments
that I had ever had the privilege of working with.
As we’ve grown and evolved the business,
what we’re focused on is how did the different metrics numbers
drive changes in our customers’ success?
Because the core premise that we run our business on here
at GoDaddy is, when our customers succeed,
good things happen for us.
SCHRAGE: How do you make the leap from what are the KPIs
associated with closing a sale — you know, reach, penetration,
frequency, all the classic ways of assessing sales
and marketing — to moving the levers on customer behavior,
influencing change?
LOW AH KEE: Financial metrics are inherently
rearward looking, right?
Dollars show up not as a leading indicator, but they’re lagging.
And so your ability to actually get to leading indicators that
tell you “if I do x, y, and z, and if I move performance along
a measure, how does that turn into financial outcomes?”,
your ability to drive linkage and real tight-coupled
understanding of how operational changes turn into financial
changes, that’s a powerful thing.
There’s a set of measures you use to understand the sales
funnel.
Great.
Those are well understood; it’s a sales funnel.
But then, once they own it, what now?
Because in an internet business, where we have a recurring,
ongoing relationship with our customers,
it’s not about a point-in-time transaction.
It’s actually about a relationship that spans years,
if not decades.
SCHRAGE: When you first began looking at the company,
was LTV a present KPI?
LOW AH KEE: It was something that people were aware of.
And in our case, one of the interesting things
is, we always understate the lifetime value.
What we see is the longer customers stay with us,
they actually — the probability that they churn goes down,
which is really an interesting dynamic because it always means
that you’re actually getting a little bit better over time.
And so we’ve seen actually our LTVs grow and rise during that
time period we’ve been around the business.
And what that’s let us do is spend more money to acquire
those customers.
We absolutely seek to understand everything as fine-grained
as we can.
That said, we balance that against our obligation
as operators to go take action, right?
It’s easy to get trapped in analysis paralysis.
You hear that phrase a lot.
And we never want to wait for perfected data
before we take action.
SCHRAGE: Right.
LOW AH KEE: We want to be moving forward, advancing the cause,
because that way, you’re actually maximizing the rate
of learning, and pace, and delivery for both
your customers and the business.
SCHRAGE: How have — organizationally,
and culturally, and operationally — you shifted
from descriptive statistical strength to predictive slash
prescriptive data capabilities?
LOW AH KEE: That has long been an attribute of GoDaddy.
And then, once you layer on some of the newer capabilities —
whether we talk about machine learning, or data science,
where you’re using models to make a prediction based on data
— OK, now you’re just making a decision with a prescriptive
set of data.
SCHRAGE: Here you are, you say from the day it was born,
there was quantitative literacy, there was a data-driven ethos
there.
What do you say to your counterparts in companies
and in industries where intuition rules?
Where qualitative gut feel rather than “get me better
numbers” is the imperative?
LOW AH KEE: At an executive level,
you have to decide what kind of business do you want to run?
Do you want to run a business that’s data-driven and is using
data — and gut and intuition, where the data may not tell
the story perfectly?
Data doesn’t mean there’s an absence of subjective feel
and guidance, because not everything can be quantified.
I think there’s a decision around what is the culture
and the environment that you want to use to make decisions?
Here at GoDaddy, one of the simple tactics we use to know
that is every business review starts with a scorecard
because it defines and it forces alignment around “here’s
the strategy.
Here are the things we say matter.
Here’s how we’re going to know whether we’re succeeding
against them.
Are we delivering or aren’t we delivering?”
SCHRAGE: I want to use that to shift to a capability that is
pretty much transforming data and analytics worldwide —
and that is machine learning.
Now we have all manner of algorithms emerging, where
in fact those algorithms are capable of, if you give them
the right data, optimizing certain kinds of outcomes
that you care about.
What’s the most important thing our viewers should understand
about how you’re trying to strike this balance between
KPIs for people and KPIs for machines and machine learning?
LOW AH KEE: I think about KPIs for machines
really as decisions you can automate, right?
Because the fun part is when you not only have a decision
or a prediction, but then you actually have the ability to go
implement that and then get that feedback loop all
in an automated fashion so that you’re getting better
and better and better and better.
And obviously, the cases and the scenarios that lend themselves
really well to that — because it’s just a tool — are places
where you’ve got a lot of data and you’ve got a high-frequency
decision.
Places where you make infrequent decisions,
once-a-year types of calls, those aren’t going to lend
themselves as well to that sort of environment.
Certainly, there may be value in some of the predictions
you get.
But your ability — and frankly, even the value of automating
an infrequent, occasional decision,
which probably has a lot of subjective factors around it
as well — that probably lends itself less well to that tool.
SCHRAGE: What are the three next steps,
or organizing principles, or insights that you feel people
need to take more seriously if they’re going to take advantage
of the data, think through their strategies more rigorously,
and have metrics and KPIs that reinforce that strategic intent
and that desired strategic outcome?
LOW AH KEE: I think the first is,
you’ve got to be clear on your strategy.
Preferably, write it down.
Doing that is actually where all of this starts.
The second is, get really clear on what you’re going to do
to measure success, right?
And that can’t be two dozen things,
because it’s just too many.
And so you’ve got to distill it down to a manageable list.
And then, get really granular, as granular as you can,
on what drives those measures of success.
The more you can actually mathematically link something
together, the stronger your ability to actually know,
wait a second — if I apply effort on this one lever
in my business, I know how that’s going to ripple and flow
through the system.
But the best way to do it is just start.
And never, ever, ever prioritize just
more analytics, more analysis, over taking action.
SCHRAGE: Couldn’t have ended better.
It’s been a terrific pleasure.
I’ve learned a lot, and I hope the audience has as well.
LOW AH KEE: Thanks so much for having me.
It was really great to get to chat.
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