But supply chain expenses can be expensive.
And on certain items, when shipping costs are high,
it may not make sense to ship that thing online.
It may make sense to make that buy line "pickup in-store only,"
or only sell it in-stores.
And so, we provide visibility into that level of detail
from a financial perspective as well.
Hi folks, I'm Daniel Myers, developer relations here at Snowflake.
On today's episode of "Powered By,"
I'm talking with James Sutton,
co-founder and CTO of Elevate,
a retail operations platform for data insights
built on Snowflake.
James, how are you?
- I'm good, happy to be here. Thanks for having me on.
- Yeah, yeah.
I'm really excited to have you here today.
So to kick this off,
can you tell me a little bit about yourself, your background
and why did you start this company?
- Yeah, so my name is James.
I've been working in retail and supply chain
for up to 10 years now. More on the client side.
I've been working for retailers or for manufacturers,
trying to use data to make better decisions.
And really over this past couple years,
really the past decade,
since I've been working in the industry
omni channel has really changed the game.
Customers expect things fast, they expect things on time,
they expect their orders not to be canceled,
and really, there's just a lot of systems and processes
that are required in order to enable that experience.
And so for retailers specifically,
you have to get the goods into your warehouse.
You have to process things.
You have a system for that.
You have order management system that handles orders
and puts things into stores for in-store pickup.
And there's ERP systems for financial reconciliation.
And as employees of those retailers,
all that data is really not brought together
in a way to make actionable decisions
and understand your performance
and understand really your exceptions,
because that's what you're trying to manage to.
And so about a year ago, me and a couple co-founders
also working in this space, started Elevate.
And really what we've been developing since then
is what we wish we had when we were on the client side.
Analytics as a service offering,
to have all the insights that we need
and we think our customers need
in order to make the right decisions
and get products to their customers on time
and not cancel it.
So excited to talk to you more about Elevate today
and what our offering is and why Snowflake
is such a big part of it.
- That is exciting.
So tell me a little bit more about
the solution that you're building
and a little bit on how Snowflake fits into it.
- Yeah, for sure.
Our analytics platform is a combination
of really an end-to-end service for our customers.
There's a lot of great data applications out there,
and most of them are focusing on marketing efforts
and acquiring new customers
and enabling a great digital experience.
But many of them are not focusing on supply chain.
And so the whole supply chain industry
is kind of lagging in this space
and they still live off of weekly Excel-based reports
or static reports that give you,
maybe, the summary details you need
but you can't really drill into the details
as to exactly what order
and what time or what package is an exception.
And so we've been building this Elevate analytics platform
to answer those questions.
And so what you're looking at on this slide is,
Snowflake sits right in the middle of that.
We've leveraged Snowflake for all of our data storage
from a data lake, and then transform that data
into Elevate data models that has everything
about a particular order or shipment
or transaction that you may need to know.
And then we expose that
through our front end BI interface.
So Elevate as an offering,
is a combination of all the integration
from all these different systems
that I had talked about previously,
getting all that data into Snowflake,
transforming those many, many tables
into something that's actually digestible and usable.
And then pre-built business logic to enable retail leaders
with the insights they need
in order to run a successful warehouse
or run a successful program
or track their packages on delivery to customer.
So we handle this both from a technical approach
but also we act as consultants
and meet with our customers regularly.
Since we have all their data,
and we come from that industry,
we meet with our customers
to give them the information they need
and make recommendations
as to the things that they should be looking at
in order to better their experience.
- That's great, that's great.
I mean, it seems like a pretty powerful platform
that you're building out on top of Snowflake there.
Can you tell me a little bit about,
the history of the company.
What's the status of it today?
How many employees do you have
and what's the funding status?
- We are definitely doing a different startup path
than I think a lot of people do.
So we've chosen to be self-funded at this point.
And we're fortunate
that this is our second or third career opportunity.
So we're fortunate to be able to do that.
We currently have seven employees working on the platform
but we are growing exponentially.
So if any of you are interested
in coming on as a data engineer, reach out to us.
We have a good amount of clients
both in warehouse operations and omni channel.
And we're growing both as far as our breadth
that we want to provide analytics for but also our depth,
as far as the different systems that we support.
So we really feel like
this company is going to grow exponentially,
especially as a lot of these operational systems
move into cloud and the integrations become more seamless
and the schemas become more standardized.
It's a lot easier for some of these analytical solutions
to sit on top of them and have pre-built insights
compared to historical legacy applications.
A warehouse management system
between customer 1, 2, 3, 4 are going to be very different
from each other.
So it takes a little bit longer
to integrate and build this out.
- I agree wholeheartedly.
I think that as a lot of these other platforms
and solutions move to the cloud,
I think an analytics platform,
like the one that you're building,
will be even more and more important.
So I guess from here, let's see a demo of it.
- Yeah, for sure.
I love it.
So I'm going to start with delivery performance.
And so delivery performance is key to my heart
as a customer because I track things on my phone,
and with push notifications,
you know exactly when things are supposed to get there.
If you told me five days, I want it in three days.
But if you don't deliver it in five days
I'm calling customer service.
I'm seeing where my stuff is.
And what we realize
is that a lot of customers don't measure that internally.
So they use solutions like Narvar or other competitors,
After Ship, to communicate with customers.
And the customers know what's going on with the package,
but internally they may not know, of the 25,000 packages
they shipped last week,
how many of those are delivering on time?
And so what we do with Elevate
is we compare what was promised to a customer
to all the delivery events of what got delivered on time.
And so what you're looking at here
is an overview of that performance.
So within this dummy data,
90% of my packages were delivered on time.
I can see exactly where in the country
I'm performing or not performing.
Our customers are leveraging this information
to really diversify their carrier networks.
So, if they're not performing well in certain areas,
maybe they need to choose a different carrier
that delivers faster there.
Or maybe they need to open up a new fulfillment center
or leverage their stores differently.
Just really understanding the geographics
of your performance can really start some good conversations
about what your supply chain should look like.
But this goes into a lot of detail.
So one of the things that we we find pretty quickly
is that when you have more aggressive timelines,
typically our retailers don't hit them as often.
And so if you go on the website and you order next-day air,
and you want it delivered tomorrow,
that's a really tight time window
that a retailer has to achieve
to get that package to you on time.
They've got to pack and
ship it in like three hours to get it into UPS's network.
And then UPS needs to deliver it on time.
And so we provide all that information
as to how those handoffs are occurring.
And not just the summary level information
but really drilling down into the details.
And so this is where Snowflake and the cloud platform
becomes really powerful,
is because everything is built at a granular level.
It's not just your summary information.
I know exactly what carton didn't get delivered on time.
I know all the time stamps throughout the journey
of when it got ordered,
when it got allocated, when it got shipped,
when it got origin scanned, when it got delivered.
We can identify why things are late.
And then if we have gaps in our processes,
like, we're not shipping things on time
in order meet these SLAs,
then we can go and work with our operations teams
to solve those.
So this is more of a omni channel use case.
Also within omni channel,
we look at things in terms of financial performance as well.
So, you wanna deliver on time,
but you also wanna make money on what what you're selling.
And most retailers measure gross margin
which is just your revenue minus your costs against sold,
but supply chain expenses can be expensive.
And on certain items, when shipping costs are high,
it may not make sense to ship that thing online.
It may make sense
to make that "buy-online, pickup-in-store-only,"
or only sell it in stores.
And so we provide visibility into that level
of detail from a financial perspective as well.
And the example I like to use
in this kind of dummy data,
is, I've got this item number four here
that I made gross margin on.
I made $1,400, but after my shipping costs were taken out,
and my supplies costs
and my labor costs for fulfilling those goods,
I lost 14.9%.
So just having visibility to this level of data
through the Elevate data model powered by Snowflake
and then through Elevate,
we're enabling operational leaders to be more profitable,
manage operation, and understand exceptions,
so that they can really perform better.
We also have a lot of other content
in the warehouse operations space that I can jump to.
But do you have any questions about what I've shown so far?
- I mean, this is awesome.
I love how actionable this information is
and how easily digestible by the person viewing it.
It's pretty cool to see.
As you were building out this platform
especially as the CTO,
what was some of the considerations
that you had regarding the tech stack
that you had for this solution,
and how did you decide to use and leverage Snowflake
as part of your platform?
- Yeah, I mean, that's a great question.
Since we've been founded this
a little over a year ago,
and as a startup, we really had
like the whole data landscape like to choose from.
And that's great, right?
Like working for an organization
there's a whole RFP process,
and you have to get all these approvals,
and it can be pretty lengthy.
But when you start your own company
and you're paying the bills
you can go and pick whatever you want.
And so that's been kind of fun,
to really be able to try and leverage
all the different technologies are out there
and figure out what is right for Elevate.
And some of the things we really liked about Snowflake
and why we continue to leverage Snowflake
as our core data store
is it's really easy to integrate data with Snowflake.
And since we're combining data
from multiple different systems,
we have to use many different integration patterns
in order to get in there.
Whether it is Python through Dags, or using STK,
or using cloud storage and leveraging Snowpipe,
which has been great, or leveraging a managed service
like Stitch or Fivetran or Airbyte,
all of these different options
to get data into Snowflake, they just work.
And so our speed to value of getting data
from all the different applications we're tying to
and into our data model,
has been really a key benefit for us.
The second thing that people talk about all the time
is the difference between compute and storage,
and separating that out,
that has been really beneficial for us.
Both from a security standpoint,
we can set up databases that are isolated
and have object-level security
so that all of our customers data lives in isolation.
But then separating out compute
so that we can have the right compute instances
and the right size based off of the jobs
that we're doing within Elevate
has been really beneficial for us.
So, I mean, I think that for most companies within data
there's a lot of great options
and none of them are really wrong.
But Snowflake was really just the easiest
and it just works and it continues to work.
And there's not really a lot of reasons
why not to leverage it right now.
- Well, I love to hear it when people say
that it's easy and just works.
That is music to my ears.
So, with that said,
it seems like the number of integrations that you have
would still be...
that is still a challenge
just to work with all of these different systems
and get that data.
Talk to me a little bit about
some of those integrations that you've done.
How has the idea of semi-structured data,
alongside structured data in Snowflake,
how has that impacted
some of the integrations that you've built?
Do any of the integrations today, for example, leverage JSON
or any others of these semi-structured formats?
- Yeah, that's a great question.
And honestly, we're getting data in many different formats
to get into this state.
A lot of the operational systems that we're hitting
whether it's order management systems,
or warehouse management systems are not semi-structured,
it's very columnar based.
And so that is just like very straightforward
about getting into Snowflake.
I think semi-structured data,
for example, all the delivery data that we get,
we leverage EasyPost, we have a partnership with them,
to get all the transactional events
about--after a company ships an item
what happens throughout each step of that journey.
And all of that lives in a semi-structured schema.
And pulling that into Snowflake is really easy
because it just handles it so naturally.
But we get everything into a uniform data set,
transform the data set into our data model
within Snowflake, and those Elevate data models
are the final product
that we sit these type of insights on top of.
And I think that's a ton of value, right?
It's hard to go and build integrations
with all these different systems.
But then, even if you have all the systems,
what are the 30, 40, 50 tables mean?
And what do the relationships between shipments and orders and LPNs,
what does all that mean?
And I think that that's where we're trying be that differentiator in the market,
is that we have experience with those systems,
both on a technology side.
And so we go and build those connectors into an IBM product
or a Manhattan product,
and now we have that answer of what we're looking for
as to how to bring it into our data model,
through Snowflake and through the front end insights
that are more actionable.
Because the operational systems are great
and they serve their purpose
but they're not really reporting systems.
You may be able to get summary reporting out of them
through some tool that they have.
You can go and get details.
Like I can look at a particular order,
but I can't see like great summary level reporting
and then drill into details to take action.
And even if I could,
really all the actions are between systems.
Like, what does my warehouse management system say
compared to my order management system.
or my partial carrier that's delivering it.
By really connecting those dots
is where Elevate and Snowflake really thrive,
because we pull everything all together
so that it's more actionable.
- That's awesome, that's awesome.
So, what's next for Elevate?
Over the next six months to three years,
what's on the horizon?
- Yeah, that's a great question.
We're actively growing our teams
so we can support more customers and support our growth.
We want to both grow deep first and then kind of wide.
So we want to support more customers
that are leveraging common systems in this space.
And we want to get both within omni channel
and warehouse operations.
And so we already have connectors built
for some of the more common applications
that we see are being utilized in this space
but we want to continue to support more,
and get all of those to come into our data model
so that this can be leveraged across customers.
I think that the hot word in industry
and all these companies that are getting funded
are all about applying machine learning
and applying artificial intelligence
on top of products like this.
And I think at some point we'll get there,
but my personal opinion is that
you have to know what you're looking at.
You have to be able to measure your performance first
and then you can start kind of using that technology
to get better.
And so we're trying to solve the visibility problem
which is pretty big in the supply chain industry.
We're going to solve visibility first.
So then talk to me again in one to two years
and maybe we'll talk about machine learning.
But we just wanna get make this data
and make these insights actionable.
And in the right business user's hands
that can actually track down this order,
contact the customer and apologize for a bad experience,
if they missed a Mother's Day cutoff
or missed a Christmas delivery,
and then go and make the right operational decisions
to make sure that doesn't happen again.
- Makes sense, makes sense.
And so if one of our viewers today
wants to get in touch with you or with Elevate,
to learn more, where should they go?
- Yeah, so our website is elevate.dev.
We have a contact pattern on there.
We also have a LinkedIn page you can follow us on.
So yeah... looking forward to ... for anyone to reach out,
we're happy to talk about what we've built.
If this is a great option for you.
If you're a data engineer and you like this space,
reach out to me,
we're looking for good talent. .
And also reach out if you just have any retail
or supply chain questions.
We also do a lot of consulting in this space
with large retailers
and happy to help on a strategic basis if we can.
- Well, that's awesome.
That's awesome.
And as we wrap up today for our viewers,
my name is Daniel Myers,
developer relations here at Snowflake.
And if you're looking to build
your business or application on Snowflake,
check out developers.snowflake.com.
With that, I'll see you next time.
Thanks.
(energetic music)