>> Narrator: From the SiliconANGLE Media office
in Boston, Massachusetts, it's theCUBE.
Now here's your host, Dave Vellante.
>> Hello, everyone and welcome to this week's episode
of theCUBE InsightsPpowered by ETR.
In this Breaking Analysis, I want to do some explanation.
For the past four months, I've been sharing data
from a company called Enterprise Technology Research, ETR.
I've worked with the SiliconANGLE team
to create a pure editorial product
that blends the ETR dataset
with insights that we've gleaned from theCUBE.
We've been getting great engagement and I've been getting
some questions that I wanted to address in today's episode.
Let me first say that as a long time industry analyst,
I've always valued data-based opinions,
so when I met the folks at ETR,
I became really intrigued and I thought working with them
might be a good way to share some really awesome survey data
and then blend it with context
from theCUBE's huge observation space
where we do, you know, 100 shows per year.
Today I want to cover six things.
The first thing I want to do is answer the question
that I get most often which is who the heck are these guys?
And I think it's really important to understand
how and where ETR gets its data
so I want to spend a little time on their methodology
and dig into that a bit.
And then next, I want to talk about
this thing called net score.
I refer to net score all the time.
It's one of my favorite metrics and I'll show some examples
and explain what it means and how I use it
and I'll use real and current data on containers,
VMware, I got some data on Oracle, AWS and HPE
who just announced its earning.
So there's actually content in this episode.
It's not just a tutorial so stick with me here.
And then I want to talk about the term market share
and what that means in the parlance of ETR.
I'm often asked what is the relationship
between ETR and theCUBE so I obviously want to address that
and if that doesn't answer all your questions,
I can give you some ways to get more information.
So first, who is ETR?
Well ETR is a research company.
Actually, it's a platform or a product
that was built by a company called Aptiviti.
The key advantage is they do primary market research,
first party data, and they have a community
of survey respondents that give them
spending intentions data and they survey this base
on a fairly regular basis.
Currently, there are about 4,500 buyers
in this survey base and in my experience,
each quarter, about 1,000 or so respond
to their requests for spending data.
This group collectively represents nearly a trillion dollars
in annual IT spending on enterprise tech
and you can see here there's a nice mix of C-level execs,
VPs, IT Management, but the respondents,
they like to participate because those that do,
well, they get access to the data
in exchange for their information.
Now there's no incentive for them
to exaggerate their spending intentions.
I mean it's not like, remember the old days
of computer pubs where if you spend over a threshold,
you get a free magazine?
This is legit spending data,
spending patterns that ETR vets with historical data.
They also pay close attention to the income statements
of public companies, attune their data and forecasts
in a way that I'll address later and you can also see here
that the data is global and it comprises a very strong mix
of large organizations across
virtually all industries and geographies.
I mean it's North America heavy,
but they've got representation all over the world
and these guys have been at it for 10 years
and they're serious data geeks.
They have a team of stats folk, aka data scientists
in today's terms who do some really cool things
with the data like using regression analysis
to compare their spending data with Wall Street consensus.
Now they primarily, ETR serves Wall Street customers
who are trying to gain an advantage, you know,
ahead of earnings news coming out
and they want to squint through the noise
which is kind of what I'm trying to do here.
ETR's founder, his name is Thomas Delvecchio
and he's essentially created a survey panel on steroids.
You know, when I worked at IDC, our Holy Grail
was to create a panel and use it to track spending data.
We never got there.
It was too hard so what we did was
we did spot surveys on hot topics like you know,
data duplication last decade,
to see where all the action was and then periodically,
we do broader spending intention surveys.
You know, but they weren't conducted on
a formal quarterly cadence and what Delvecchio did
is he flipped this model on its head.
What I mean by that is ETR does
regular quarterly broad-based spending surveys
and then periodically, they drill down into the hot areas.
The great thing about this model from my perspective
is that you can run the analytics
and do time series across the data.
It's a way, way more powerful approach.
Now there are other panels out there that you can tap into,
but ETR's built a platform on top of what in my opinion
is the best spending intentions data that I've ever seen
and they've got a really nice SaaS product
that allows me to cut the data by size of company,
geography, market segment and I can answer questions like
are containers killing VMware?
And I can answer that question
by slicing and dicing the data
rather than having to field a completely separate survey.
So what I want to do here is I want to take that example
and drill into a key TR, key ETR metric
that I use a lot which is called net score.
Now net score represents
the intensity of spend for a company.
Higher net scores indicate a positive spend trajectory,
and a lower net score indicates
a flat or negative spend trajectory.
So what I'm showing here is a cut from the ETR dataset
and what I'm actually doing to answer that question
that I just proposed, look at,
so you see number one in the red,
I'm filtering the ETR data by container platforms.
So this is organizations that are spending on containers
and you can see the number two there,
the N is 541 organizations spending on containers
and then number three, I cut the sample by VMware mentions.
So out of the folks answering the survey for a given period,
I want to isolate on those doing business with VMware
and evaluate their spending.
Notice number four, which is the net score.
That's what I want you to focus on.
Net score's a measure of spending momentum, as I said.
So specifically for each ETR survey,
ETR asks about spending.
Are you adopting the platform as new?
Are you spending more, spending the same or spending less?
Or are you leaving the platform?
And they essentially subtract the spending less
from the spending more and calculate a net score
and you can see in number five, the net score's over time
and I superimpose these numbers with shared accounts
that are mentioning VMware.
Now remember, ETR allows for multiple responses
of various VMware solutions so again,
there are multiple responses in that shared end,
but you can see that VMware's net score has hailed up
around 33-34% over you know, a two-year period.
So there's zero evidence
that containers are hurting VMware today in this data.
Now prior to 2018, by the way,
I kind of ignore those spikes
because the shared end is too low.
It's like 12 mentions,
but the rising number of shared accounts over time
is yet another clear indicator of adoption
between those container costumers and VMware spend.
Now I can cut this by size of company, industry,
a zillion different ways, but this is everyone
in the dataset for the October survey.
What I want to do now is take a look at
what ETR calls market share.
Market share in ETR language is a measure of pervasiveness.
So they calculate this by taking the number of mentions
of a vendor within a sector,
they exclude replacements and they divide by the number
of respondents within that sector.
So what I'm showing here is an example
using market share data for analytic databases.
So focus on number one which takes the entire sample
from the October survey and then number two
and an N of 1,336 respondents.
So we choose in number three,
the data warehousing software segment
and then select from the pull down AWS Redshift
and compare that with Oracle within that sector.
So you can see in the last two years
that AWS has rapidly gained share.
You can see in number four that the net scores
where AWS has a way stronger spending momentum
with 62% and negative 3% for Oracle.
What I love about this dataset is the ease
with which I can either call BS or validate a vendor's claim
and get ahead of the market by combining the data
that we collect on theCUBE and that we hear all the time
with the ETR survey data.
And remember, in last week's Breaking Analysis,
I put up a view showing Snowflake
which claims it continues to do well
despite its apparent overlap with AWS Redshift
and as you may recall, the ETR data clearly confirmed
that Snowflake was thriving along with Redshift
and eating away at Teradata's business.
So it confirms their narrative.
Let me share another example of how I use ETR market share.
HPE just reported earnings yesterday
and it missed its revenue targets and here's a chart
that HPE presented as part of its earning package.
Now at the highest level,
HPE reports revenue across three major lines:
intelligent edge, hybrid IT and financial services.
Not picking on HPE, but you know, I can make this argument
with pretty much any legacy computer company
or any hardware company and now the narrative
from these companies is we're investing in the new hot areas
like edge and the world is hybrid and that's our opportunity
and we are uniquely positioned
and we see lots of repatriation from the cloud
where people have moved to the cloud
but have sort of cloud regrets
and now are moving back to us.
You hear this all the time from execs at these companies,
but you sure don't see it in numbers.
Look at the growth rate year over year in HPE's business.
Edge and Hybrid IT are both shrinking in this example.
Even when you adjust for currency
and take out what HPE refers to as tier one sales
to the big hyperscalers
which is a business that HPE exited last year.
Meanwhile, when you watch
and you're looking at AWS and Azure numbers,
they're growing at 35% for AWS,
59% year over year for Azure last quarter.
Now the HPE narrative is we're focusing on margins
and exiting low-value businesses and to be fair, that's true
and it shows up in HPE's gross margins
and operating profit and free cash flow.
But I have an addition to the narrative:
which is the cloud is eating away at that business
and while repatriation most certainly happens,
it's a figure that's not showing up on the income statement.
So I look at the ETR data to answer the question
how is the cloud impacting HPE's market share?
So here's what I do.
To answer that question, I filter the data,
that I'm showing on this chart,
and I select the cloud computing filter
in the upper left from the pull down.
I do a second filter right below,
pulling down and selecting AWS, Azure
and Google Cloud Platform.
So there's 818 respondents in the ETR October survey
that fit that criteria, cloud spenders,
and then I click on the market share radio button
and pull data in from January 2010
to the October '19 survey.
In the October 2019 survey, you can see that the shared end
shows 495 respondents that are also spending on HPE.
So nearly 500 HPE responses within 800 cloud accounts.
Look at the story.
Like many, HPE came out of the downturn
with a pent up demand.
It announced the public cloud in 2011
which froze the market a little bit and by late 2014,
the market clearly understood that that offering
was a fail and HP exited the business in 2015
and you can see how the cloud is eating away
at spending on HPE's products and you can see
the net score of 10.9% in the red underscoring the headwinds
that HPE is facing.
Now of course, Antonio Neri, who's HP's CEO,
he's doing what he has to do:
cutting costs, focusing on higher margin opportunities,
adopting an Azure service model, doing stock buy backs,
but as I like to say, the data does not lie.
Now where it really gets mind-blowing
is when ETR runs regression models
using Wall Street's estimates for a public company
as an outcome variable and test that
against the covariates
and independent variables in its dataset.
Now these act as predictors so not only using the data
that tell the story of what happened in the past,
but using it as a forecasting tool.
Okay, so that's most of what
I wanted to share with you today.
There's a lot more, but let's leave it there for now.
I want to address a relationship between theCUBE and ETR.
We're essentially just friendlies.
We currently have no commercial relationship.
There's no money exchanging hands.
There's no other incentives other than
we're birds of a feather, so to speak.
They give me access to their data and I use it weekly
in these Breaking Analysis segments
and we co-brand the content,
theCUBE Insights Powered by ETR.
So it's a beautiful fit between what we learn in theCUBE
and this awesome dataset.
Look, if you find this stuff useful,
I encourage you, reach out to ETR.
Their website is ETR.plus
or just Google Enterprise Technology Research
or you can hit me up on LinkedIn or Twitter.
I'm @dvellante and I'd be happy to put you in touch.
This is Dave Vellante signing out
from this episode of Cube Insights Powered by ETR.
Thanks for watching, everybody, and we'll see you next time.
(upbeat music)