Latest / Speaking of Supply Chain / Real-Time Inventory Visibility Is the New Standard

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Real-Time Inventory Visibility Is the New Standard · Speaking of Supply Chain

• 0:06
  Speaker 1: You're listening to Speaking of Supply Chain, a meeboch podcast.
• 0:10
  Speaker 1: This is a show for logistics professionals looking to learn
• 0:13
  Speaker 1: more about the latest innovations in supply chain.
• 0:16
  Speaker 2: Each episode will.
• 0:17
  Speaker 1: Feature a conversation on topics such as mitigating supply chain
• 0:20
  Speaker 1: disruption and reducing risk, current automation trends, sustainability initiatives, and more.
• 0:26
  Speaker 1: Let's dive right in.
• 0:30
  Speaker 3: Hello, and welcome to Speaking of Supply Chain, where we
• 0:33
  Speaker 3: explore trends, current events, and innovations impacting the logistics and
• 0:36
  Speaker 3: supply chain industries. I'm your host, Ellen Wood. The CpG
• 0:40
  Speaker 3: industry faces increasingly unpredictable demand patterns, complex inventory management challenges,
• 0:46
  Speaker 3: and heightened expectations for agility and responsiveness. Traditional forecasting tools
• 0:51
  Speaker 3: often fall short, leaving companies vulnerable to costly stockouts or
• 0:55
  Speaker 3: excess inventory. In today's discussion, Joel beieal CEO and co
• 0:59
  Speaker 3: founder of alloy AI and I are going to explore
• 1:02
  Speaker 3: how their tool leverages advanced AI and real time analytics
• 1:06
  Speaker 3: to tackle these pressing issues, optimizing demand planning and inventory
• 1:10
  Speaker 3: decisions for a rapidly changing market.
• 1:12
  Speaker 2: Welcome Joel, Thank you, Ellen.
• 1:14
  Speaker 3: Excited to be here, Excited to have you here. We're
• 1:17
  Speaker 3: going to have a great conversation. I can tell because
• 1:19
  Speaker 3: this is such a huge topic right now. Planning is
• 1:23
  Speaker 3: the buzzword on everyone's mind. But before we get started,
• 1:26
  Speaker 3: let's do our ice break really quick. And the question
• 1:29
  Speaker 3: that you chose for today is what book are you
• 1:31
  Speaker 3: currently reading?
• 1:32
  Speaker 2: Well, I'm going to give I'm going to give two
• 1:34
  Speaker 2: answers because I actually just finished a book and I'm
• 1:36
  Speaker 2: starting a new one. So I just finished Demon Copperhead, okay,
• 1:42
  Speaker 2: Barbara King Solver, which is a tough one. It's it's
• 1:45
  Speaker 2: pretty sad, sad book. So I need a little bit
• 1:49
  Speaker 2: of lighter fair after that, and I actually started reaching
• 1:52
  Speaker 2: reading Jack Reacher of All Oh, of all Things. So
• 1:56
  Speaker 2: i'd seen the show. I mean, i've seen the movie,
• 1:58
  Speaker 2: I guess years ago. Tom Cruise he's not a very
• 2:00
  Speaker 2: good Jack Reacher. He's a little too short. Back Reacher
• 2:03
  Speaker 2: is six'. Five i'm not Sure Tom cruise is five.
• 2:06
  Speaker 2: Eight but, YEAH i DECIDED i needed something a little more.
• 2:10
  Speaker 2: Lighthearted SO i actually just finished the first book AND
• 2:13
  Speaker 2: i was, Like i'll read the second because you can
• 2:14
  Speaker 2: get through them in a couple of.
• 2:15
  Speaker 3: DAYS i am also a fan of, novels AND i
• 2:20
  Speaker 3: belong to a couple different book, clubs AND i love to.
• 2:23
  Speaker 3: Read but there is one series AND i read reread
• 2:27
  Speaker 3: the series every, year and it's The outlander. Series, yep
• 2:31
  Speaker 3: so made into THE tv. Show it's huge on multiple platforms.
• 2:35
  Speaker 3: Now for a while it was only on the one streaming.
• 2:38
  Speaker 3: Platform AND i am on book number four for this.
• 2:41
  Speaker 3: Year and each of the books is about a thousand.
• 2:44
  Speaker 3: PAGES i, mean they're heavy duty. Novels AND i remember
• 2:47
  Speaker 3: the first TIME i was reading through. It my brother
• 2:49
  Speaker 3: in law saw it on my coffee table and he was,
• 2:52
  Speaker 3: like are you actually reading that? BOOK i was, like,
• 2:54
  Speaker 3: yeah it's one of like. Eight he was, like why
• 2:56
  Speaker 3: would you do that to? YOURSELF i, thought what kind
• 2:59
  Speaker 3: of question is that readers read? Books and sometimes when
• 3:03
  Speaker 3: we read the bigger, ones.
• 3:05
  Speaker 2: Yeah and so are you reading them all in a
• 3:07
  Speaker 2: row or do you break it up with Other?
• 3:09
  Speaker 3: Okay SO i will, well, OKAY i don't read just
• 3:13
  Speaker 3: one book at a time most of the.
• 3:15
  Speaker 2: Time so this is my two. THREE i, MEAN i
• 3:19
  Speaker 2: know the.
• 3:20
  Speaker 3: Three, YEAH i will read two to three at a.
• 3:23
  Speaker 3: Time in, fact the other book That i'm reading right
• 3:25
  Speaker 3: now is a book about marketing Video marketing For marketers
• 3:28
  Speaker 3: is the name of the. Book and Because i'm a,
• 3:30
  Speaker 3: marketer and So i've always got something that i'm reading
• 3:33
  Speaker 3: for like personal or professional. Development i've always got something
• 3:37
  Speaker 3: that i'm reading just BECAUSE i want to read something
• 3:39
  Speaker 3: AND i need something to call my brain down at.
• 3:41
  Speaker 3: Night and Then i'm usually reading something that someone suggested
• 3:44
  Speaker 3: to me OR i got at the. LIBRARY i, mean
• 3:47
  Speaker 3: on my vacation a couple of weeks, AGO i read
• 3:49
  Speaker 3: seven books in five.
• 3:50
  Speaker 2: Days, okay, well YOU i can appreciate. THAT i grew
• 3:55
  Speaker 2: up in a. Family i'm the youngest of six, kids
• 3:58
  Speaker 2: and we did not have A tv girl. Up that
• 4:00
  Speaker 2: was a decision my parents. Made, okay it was very.
• 4:04
  Speaker 2: UNUSUAL i think everyone was. Confused but as a, result
• 4:08
  Speaker 2: we're all big readers and we've Been that's All i've
• 4:12
  Speaker 2: been doing most of my. LIFE i do get distracted
• 4:14
  Speaker 2: now more BY tv shows THAN i probably used, to
• 4:17
  Speaker 2: but uh, yeah and stilled the love of. Reading and
• 4:20
  Speaker 2: my brother ended up being involved with one of the
• 4:23
  Speaker 2: largest online used booksellers in the. World so he ended
• 4:27
  Speaker 2: up running that business called Thrift. BOOKS i have used
• 4:32
  Speaker 2: you probably used. Them, Yeah so, yeah so reading is
• 4:36
  Speaker 2: SOMETHING i can tell you you deeply care, about and
• 4:38
  Speaker 2: SOMETHING i love to. DO i don't read a lot of,
• 4:41
  Speaker 2: fiction THOUGH i FIND i need it to just decompress
• 4:43
  Speaker 2: at the end of the. Day SO i LIKE i
• 4:46
  Speaker 2: generally again switch between more, serious sad and. Fair as
• 4:51
  Speaker 2: my wife will often, say she's and then and Then
• 4:53
  Speaker 2: i'll pick something that's kind of a throwaway but just.
• 4:55
  Speaker 3: FUN i love to throw away fun ones, there they're
• 4:59
  Speaker 3: just lighthearted something to, do all, Right, well books is
• 5:03
  Speaker 3: not what we're talking about. Today we are talking about
• 5:07
  Speaker 3: THE CpG industry and stock and planning and.
• 5:13
  Speaker 2: This is a big.
• 5:13
  Speaker 3: One this is a big. Topic it's the. Novel this
• 5:16
  Speaker 3: is the missioner of situations right. Now so let's talk
• 5:21
  Speaker 3: a little. Bit starting at the. Beginning what was the
• 5:24
  Speaker 3: original inspiration behind Alloy. Ai what were you trying to?
• 5:28
  Speaker 3: Solve what was the big problem in the marketplace that
• 5:32
  Speaker 3: really drew you into this particular.
• 5:35
  Speaker 2: Venture, Yeah i'll not bore you with the full. Story
• 5:38
  Speaker 2: but WHEN i dropped out of a PhD program in
• 5:43
  Speaker 2: economics AND i started working in, software AND i worked
• 5:47
  Speaker 2: for a company that primarily did analytics for, retailers and
• 5:51
  Speaker 2: SO i got very experienced working with point of, sale inventory,
• 5:56
  Speaker 2: data things of that, nature but all provided by the
• 5:59
  Speaker 2: re tailor so the retailer could optimize its own. Business
• 6:03
  Speaker 2: and we struggled to sell to CPGs because they didn't
• 6:07
  Speaker 2: have the same. Data so that was kind of my
• 6:09
  Speaker 2: intro to the. Space BUT i saw, that you, know
• 6:12
  Speaker 2: and we were working with some of the largest CPGs
• 6:14
  Speaker 2: in the world and they would, wait you, know a
• 6:17
  Speaker 2: month after the fact they get some data From, nielsen
• 6:19
  Speaker 2: these syndicated data. Providers it wasn't super, granular it's very.
• 6:23
  Speaker 2: Expensive SO i just kind of filed that, away did
• 6:27
  Speaker 2: some other things for a number of years and financial,
• 6:29
  Speaker 2: technology but always liked the. Space and then AS i
• 6:33
  Speaker 2: started to talk to people i'd known from before more
• 6:38
  Speaker 2: on THE CpG, side they started to, say you, know
• 6:40
  Speaker 2: actually there is data that's. Available retailers share a lot
• 6:44
  Speaker 2: of data back with. Us it's just too hard to
• 6:46
  Speaker 2: work with because every retailer has their own mechanism for sharing.
• 6:50
  Speaker 2: It so that's HOW i came about the, problem AND i, said,
• 6:53
  Speaker 2: OKAY i had no idea that data was even. There
• 6:56
  Speaker 2: in many cases it was, free but it turns out
• 6:59
  Speaker 2: that every single retailer they don't coordinate to make it
• 7:02
  Speaker 2: easy for their. Suppliers they all know a different, solution
• 7:06
  Speaker 2: they provide different. Data so Really alloy was born out
• 7:10
  Speaker 2: of the FRUSTRATION i heard from those, companies and there
• 7:12
  Speaker 2: was SOMETHING i heard over and over, again as people would,
• 7:15
  Speaker 2: say we're blind once we ship out, products we ship
• 7:18
  Speaker 2: product out to our retail, partners and then we wait
• 7:22
  Speaker 2: for the next, week and then we get more orders
• 7:25
  Speaker 2: and we don't really know what's going. On we're talking to,
• 7:28
  Speaker 2: them you, know we'll anecdotally get. Data and so that
• 7:31
  Speaker 2: was really the problem that we set out to solve
• 7:34
  Speaker 2: at the, beginning is the data is, There it's just,
• 7:37
  Speaker 2: unwieldy it's hard to. Use AND i happen to have
• 7:43
  Speaker 2: a lot of experience at that point building out data,
• 7:45
  Speaker 2: platforms being able to collect a lot of disparate data,
• 7:47
  Speaker 2: sets and SO i kind of took that experience AND
• 7:50
  Speaker 2: i started to apply it to the.
• 7:51
  Speaker 3: Space, WELL i, mean and as you point, out being you,
• 7:56
  Speaker 3: know a software, engineer there's a lot of analytics tools out.
• 8:00
  Speaker 3: There there are tons on the. Market what makes this
• 8:03
  Speaker 3: one different from the other traditional tools that already.
• 8:07
  Speaker 2: Exist, yeah SO i think the key thing is to
• 8:10
  Speaker 2: understand While alloy does a lot of, analytics And i'm
• 8:14
  Speaker 2: sure we'll talk about. That at our, core we're really
• 8:17
  Speaker 2: a data. Platform and you, know most, tools you, know
• 8:22
  Speaker 2: the ones that most people are going to be familiar,
• 8:24
  Speaker 2: with the, tableaus the lookers and the, clicks the you,
• 8:28
  Speaker 2: know tools like, that they really don't help you collect the.
• 8:32
  Speaker 2: Data they're just they're good. Visualization they're they're kind of
• 8:36
  Speaker 2: good analytics layer on top of. It and the problem
• 8:39
  Speaker 2: that we saw is people couldn't even get the data
• 8:42
  Speaker 2: to start doing the. Analytics and so that's really where
• 8:47
  Speaker 2: we start as we, say, okay, brand who do you sell?
• 8:50
  Speaker 2: Through what are your major sales? Channels which, retailers, distributors you,
• 8:54
  Speaker 2: know e commerce. Platforms we're going to go get that
• 8:58
  Speaker 2: data for. You we're going to get the most there's
• 9:00
  Speaker 2: granular data that's available in a way that a computer
• 9:02
  Speaker 2: can do that a human might struggle with because you're
• 9:07
  Speaker 2: as you every single day, exactly you, know nobody wants
• 9:10
  Speaker 2: to sit there and click that. Button and that's how
• 9:12
  Speaker 2: by the, way these companies have been operating for. DECADES
• 9:14
  Speaker 2: i mean they have people manually downloading that data On
• 9:17
  Speaker 2: monday mornings and so so that is really Where alloy
• 9:23
  Speaker 2: starts is we collect all this, data we normalize, it
• 9:26
  Speaker 2: and so you can, compare you, know and see how
• 9:29
  Speaker 2: you're doing In, amazon you, know how you're doing In,
• 9:32
  Speaker 2: kroger how you're doing In, walmart et, cetera and really
• 9:36
  Speaker 2: understand your business. Holistically so that's really where we differentiate.
• 9:41
  Speaker 2: We you, know our business business model is such that we're.
• 9:45
  Speaker 2: Fine we play nice with all the other bi. Tools
• 9:47
  Speaker 2: if you want to Use, tableau we'll put the data
• 9:50
  Speaker 2: in there and you can do a lot of things
• 9:52
  Speaker 2: that you can't do an alloy or and that's. Great
• 9:56
  Speaker 2: but of, course because we have domain, experience we've also
• 9:58
  Speaker 2: been able to build a lot of analytics and workflows
• 10:01
  Speaker 2: that are very specific to this, space and we find
• 10:04
  Speaker 2: that that saves people a lot of, time and so
• 10:06
  Speaker 2: they tend to like to use our. Analytics but we're
• 10:09
  Speaker 2: fine if they have another solution that works for, them well.
• 10:12
  Speaker 1: Too.
• 10:12
  Speaker 3: Sure all, right so now we've got the, data it's all,
• 10:16
  Speaker 3: clean it's all, normalized as you, said and we've we've
• 10:19
  Speaker 3: got a ton of.
• 10:20
  Speaker 2: It what is?
• 10:22
  Speaker 3: It how does it? Forecast how does it handle those
• 10:25
  Speaker 3: sudden shifts in consumer, behaviors unexpected, trends viral. TRENDS i
• 10:31
  Speaker 3: know they're you know that you hear the stories about
• 10:33
  Speaker 3: someone going On Shark tank and all of a, sudden you,
• 10:35
  Speaker 3: know all of their inventory is gone because it's it's
• 10:38
  Speaker 3: gotten its, publicity those types of market. Disruptions can It
• 10:43
  Speaker 3: can it handle those volatile changes and.
• 10:46
  Speaker 2: Shifts, yeah it's a great question and something THAT i
• 10:49
  Speaker 2: think is somewhat unique TO. CpG i, mean there's a
• 10:53
  Speaker 2: lot of other industries that tend to be a little more.
• 10:54
  Speaker 2: Stable you, know when you're in consumer, Products you're. Right
• 10:59
  Speaker 2: you can have a famous influencer goes on and posts
• 11:02
  Speaker 2: about a beauty brand and they're going to see a
• 11:04
  Speaker 2: twenty x spike in. Sales, SURE i can't predict when
• 11:08
  Speaker 2: that's going to. Happen that would be amazing IF i.
• 11:10
  Speaker 2: Could so the short answer is we can't predict the,
• 11:15
  Speaker 2: unexpected and that's not what we what we try to,
• 11:18
  Speaker 2: do AND i don't think that's. Possible if you look
• 11:21
  Speaker 2: at how does forecasting, work you, know whether you're using
• 11:25
  Speaker 2: more traditional statistical, models whether you're using kind of newer
• 11:29
  Speaker 2: machine learning, models all of them are just taking historical
• 11:34
  Speaker 2: data and you're fitting to. That and you, know, generally
• 11:39
  Speaker 2: as models have gotten more. Sophisticated you can you can
• 11:41
  Speaker 2: look at a lot more different. Factors you can try
• 11:43
  Speaker 2: to understand. Causality you can, Say, okay, yes if somebody posts,
• 11:48
  Speaker 2: online this is WHAT i think the impact is going to.
• 11:51
  Speaker 2: Be BUT i don't necessarily know when someone is going
• 11:53
  Speaker 2: to post, online and so you know what we. Do
• 11:58
  Speaker 2: of course we're building those. Models we have the same
• 12:01
  Speaker 2: limitations as everybody, does and that we only have historical
• 12:04
  Speaker 2: the data and none of us have a crystal ball
• 12:06
  Speaker 2: about what's going to happen in the. FUTURE i don't
• 12:08
  Speaker 2: know the weather next, week, RIGHT i don't demand. Exactly amazingly,
• 12:14
  Speaker 2: enough weather forecasting has gotten so much better if you
• 12:18
  Speaker 2: actually look at it over. Time so sometimes you even
• 12:20
  Speaker 2: have models that are inputs into other. Models. Right If
• 12:23
  Speaker 2: i'm trying if weather is highly, impactful you, KNOW i
• 12:25
  Speaker 2: sell ice cream or. Pizzas pizzas are highly dependent on,
• 12:29
  Speaker 2: weather you, know then you're actually using a forecast for
• 12:33
  Speaker 2: what you think the weather is going to. Be that's
• 12:35
  Speaker 2: an input into your, forecast your demand. Forecast, Right BUT
• 12:39
  Speaker 2: i think what how we approach this problem is we
• 12:42
  Speaker 2: say one of the limiting factors is, again what historical
• 12:46
  Speaker 2: data you're putting in how how granular is? It how
• 12:50
  Speaker 2: much data DO i have to feed in these? Models
• 12:52
  Speaker 2: and what's the frequency of? It and oftentimes if we're
• 12:56
  Speaker 2: talking about these consumer, brands they forecast they have you,
• 13:00
  Speaker 2: know they don't have super dense data. SETS i mean
• 13:03
  Speaker 2: most of them forecast using what they're shipping out to the,
• 13:06
  Speaker 2: retailers you. Know and again those shipments may maybe they're,
• 13:10
  Speaker 2: daily maybe they're, weekly they're they're, infrequent you, know they're
• 13:13
  Speaker 2: they're in, bulk and we're bringing what is the actual
• 13:17
  Speaker 2: consumption by you AND? I how much are people actually
• 13:21
  Speaker 2: buying day, in day, out and.
• 13:25
  Speaker 3: How much is sitting in that retailer's back room store
• 13:28
  Speaker 3: room right?
• 13:30
  Speaker 2: Right you, know we actually have that information. Too we
• 13:32
  Speaker 2: have the, invagory, right but it's a much more granular
• 13:36
  Speaker 2: and it's it's usually down to the. Location you, know
• 13:39
  Speaker 2: we can go to a specific store fulfillment CENTER dc
• 13:43
  Speaker 2: and and so you're getting a very rapid response Of,
• 13:48
  Speaker 2: hey when let's say that social media post happens And
• 13:51
  Speaker 2: i'm a beauty brand And i'm seeing that mascara shoot
• 13:54
  Speaker 2: through the, Roof we're going to see it instantly or
• 13:58
  Speaker 2: or as close to instantly as the data as, possible
• 14:01
  Speaker 2: and we're often seeing that days or a week. Before
• 14:05
  Speaker 2: kind of traditional planning systems will because they're relying on
• 14:09
  Speaker 2: a again often weekly data at its. Cores so that's
• 14:13
  Speaker 2: really how we differentiate is it's around how real time
• 14:17
  Speaker 2: can we see those? Signals so when things, deviate our
• 14:21
  Speaker 2: models can adjust and they can, SAY, whoa why are
• 14:25
  Speaker 2: we seeing this? Spike MAYBE i don't know why, yet
• 14:27
  Speaker 2: But i'm seeing, it and so both your forecast is
• 14:33
  Speaker 2: going to adjust for. That but we also you, know
• 14:36
  Speaker 2: usually there's if your sales are twenty, xing you're going
• 14:39
  Speaker 2: to be in crisis. Mode to take advantage of, that
• 14:42
  Speaker 2: there's gonna be lots of. Things you're gonna be expediting,
• 14:44
  Speaker 2: shipments you're going to be, saying hey DO i need
• 14:46
  Speaker 2: to adjust. Production you're going to be moving inventory, around
• 14:50
  Speaker 2: and we give you you, know at our, core, well
• 14:52
  Speaker 2: forecasting is an element of what we. Do it's this
• 14:55
  Speaker 2: kind of you, know sense and response system of you're
• 14:58
  Speaker 2: seeing what's happening in real. Time i'm it's never according to.
• 15:02
  Speaker 2: Plan nothing ever works according to. Plan it's just a
• 15:05
  Speaker 2: question of how far off you. Are and we're going
• 15:08
  Speaker 2: to tell you that sooner than you'd otherwise.
• 15:10
  Speaker 3: Know, Okay, NO i loved your analogy with pizza depending
• 15:15
  Speaker 3: on the, weather because in my previous, LIFE i was
• 15:19
  Speaker 3: the restaurant manager for a pizza, place and sure, enough
• 15:23
  Speaker 3: if it was raining that, day it didn't matter what
• 15:25
  Speaker 3: the forecast, said we were going to sell out a.
• 15:27
  Speaker 3: Pizzas so you'd have to adjust for that on the,
• 15:30
  Speaker 3: fly knowing, that you, know whatever that historical data said
• 15:34
  Speaker 3: doesn't matter anymore because this new piece of information is
• 15:39
  Speaker 3: going to completely change the. Game and so What i'm
• 15:43
  Speaker 3: hearing is that this tool gives that information a lot,
• 15:46
  Speaker 3: faster so that that person you, know who knows what that,
• 15:49
  Speaker 3: means or who can at least give a more educated
• 15:52
  Speaker 3: guess as to what that's going what impact that's going to,
• 15:55
  Speaker 3: have can make those adjustments on the, fly redeploying in
• 16:00
  Speaker 3: or ramping up.
• 16:02
  Speaker 2: Production, Right that's exactly. It and to use that, EXAMPLE
• 16:05
  Speaker 2: i love that you worked in, pizza because, YES i
• 16:07
  Speaker 2: don't think most people understand how much rain impacts the
• 16:10
  Speaker 2: sale of. Pizza THEY i worked with a pizza restaurant
• 16:15
  Speaker 2: chain years. Ago that's WHY i know the same. Thing
• 16:17
  Speaker 2: but you, know, yeah if you're managing the pizza. Joint you,
• 16:21
  Speaker 2: know you see the rain. CLOUDS i guess come and it's, like,
• 16:24
  Speaker 2: okay we're gonna get slammed, here yeah for. Dinner, well
• 16:29
  Speaker 2: if you're supplying the pizza, joint, right you're not gonna
• 16:33
  Speaker 2: you're not going to feel that impact until all of
• 16:36
  Speaker 2: a sudden you're than you. Had, yeah because the inventory
• 16:40
  Speaker 2: is running. Out you, know there's a big there's a bigger,
• 16:42
  Speaker 2: order and so that's the. Difference, again the retailers see
• 16:46
  Speaker 2: this and they can respond more. Quickly their suppliers are
• 16:49
  Speaker 2: all more blind and they're just waiting for that. Lag
• 16:52
  Speaker 2: and that's why you, have you, know the bull whip
• 16:54
  Speaker 2: effect and supply chain is because that signal, starts and
• 16:59
  Speaker 2: yet as you go further back in the supply, chain
• 17:02
  Speaker 2: other people aren't aware that things haven't gotten. It, yeah
• 17:05
  Speaker 2: exactly about the second that information has propagated up the supply,
• 17:09
  Speaker 2: chain well it's back to being, sunny and pizza demands
• 17:12
  Speaker 2: fallen and everyone's tired of eating pizza after the rainy,
• 17:14
  Speaker 2: week and you, know all of a sudden you have
• 17:17
  Speaker 2: an excess of of you, know pizza supplies that are
• 17:20
  Speaker 2: that are piling up the, suppliers so you can really think,
• 17:23
  Speaker 2: of you, know the starting point for everything we do
• 17:27
  Speaker 2: is how do we how do we propagate that demand
• 17:30
  Speaker 2: signal more quickly up the supply chain so the suppliers can.
• 17:34
  Speaker 2: Respond and obviously that benefits the retailers or in our
• 17:38
  Speaker 2: analogy the pizza you, know place where they can, say, okay,
• 17:41
  Speaker 2: Great i'm going to have the right WHEN i order,
• 17:44
  Speaker 2: Something i'm going to be able to get it at
• 17:46
  Speaker 2: the time and the place THAT i want. It mm.
• 17:48
  Speaker 3: Hmm so it it feels, like as we're talking about
• 17:54
  Speaker 3: this chaos is just the new. NORMAL i, mean polatility
• 17:59
  Speaker 3: and that, complexity it's just expected now in retail because
• 18:03
  Speaker 3: retail has taken. It it's a growing monster between e
• 18:07
  Speaker 3: commerce and brick and mortar stores and you, know all
• 18:11
  Speaker 3: of the distribution that happens behind the scenes and trying
• 18:14
  Speaker 3: to keep up with. It we've got the clearinghouses Like
• 18:18
  Speaker 3: amazon or Even walmart dot. COM i, mean they sell
• 18:21
  Speaker 3: things that you don't get.
• 18:22
  Speaker 2: In A walmart.
• 18:23
  Speaker 3: Store so it's it's technically one of those those types
• 18:26
  Speaker 3: of sites and so brands that are trying to sell
• 18:30
  Speaker 3: into these these retail companies and they're trying to get
• 18:34
  Speaker 3: their products. Listed how are they responding to a lot
• 18:39
  Speaker 3: of that volatility and just not really knowing what's going
• 18:45
  Speaker 3: to influence the market in, retail, Right, so.
• 18:51
  Speaker 2: You, know the volatility supply chains have been in the
• 18:53
  Speaker 2: news more the last couple of, years more on the supply, disruptions,
• 18:57
  Speaker 2: right everything that happened DURING, covid the so wes. Canal you,
• 19:01
  Speaker 2: know in the last couple of, months it's been all about.
• 19:03
  Speaker 2: Tariffs SO i think everyone's starting to be, like, oh,
• 19:05
  Speaker 2: yeah things don't just magically appear on the. Shelves you,
• 19:08
  Speaker 2: know there's a very communicated system system behind. IT i,
• 19:14
  Speaker 2: think you, know when we look in at our, customers
• 19:19
  Speaker 2: the companies we work, WITH i think the huge shift
• 19:22
  Speaker 2: THAT i see is there's so much more. Competition that's.
• 19:27
  Speaker 2: True there are just so many brands out there competing
• 19:32
  Speaker 2: for your, attention and it's global in. Nature. NOW i
• 19:37
  Speaker 2: actually saw a chart you were mentioning walmart dot com
• 19:40
  Speaker 2: and it was showing the growth Of walmart's marketplace and
• 19:44
  Speaker 2: how that's kind of taken off over the past five.
• 19:46
  Speaker 2: Years and there was a second chart and it showed
• 19:49
  Speaker 2: what percentage of those sellers Are american companies Versus chinese,
• 19:53
  Speaker 2: companies and you were just seeing you, know when they'd started,
• 19:58
  Speaker 2: out it was primarily you, Know american suppliers who are providing,
• 20:02
  Speaker 2: that and it still is a, majority but that you,
• 20:05
  Speaker 2: know those lines are going to, cross it looks like
• 20:08
  Speaker 2: and then not too distant. FUTURE i think you've already
• 20:10
  Speaker 2: seen that happen On amazon's, marketplace which obviously is bigger
• 20:13
  Speaker 2: and it's been around. Longer and so you're competing globally
• 20:18
  Speaker 2: with you, know brands around the world that are you,
• 20:22
  Speaker 2: know aggressively trying to undercut you on. Price they're, trying you,
• 20:26
  Speaker 2: know different ways of marketing getting access all, that and
• 20:30
  Speaker 2: SO i think that's just the nature of a. Brand
• 20:33
  Speaker 2: it also means there's a bigger, opportunity there's more way
• 20:35
  Speaker 2: to sell your. Product you can also sell your product internationally,
• 20:38
  Speaker 2: more you, know the distribution is just easier than it
• 20:41
  Speaker 2: used to. Be what does that. Mean so one of
• 20:45
  Speaker 2: the things that we've, seen and OBVIOUSLY i have a
• 20:48
  Speaker 2: biased view Because i've been looking at this, problem you
• 20:51
  Speaker 2: know from a certain, way is WHEN i started alloy
• 20:58
  Speaker 2: again this pre. Pandemic often the feedback we would get
• 21:03
  Speaker 2: as people would say that is really. Cool that's amazing
• 21:07
  Speaker 2: THAT i could drill into an individual store and see
• 21:10
  Speaker 2: a specific skew and how much inventory is sitting there
• 21:12
  Speaker 2: and how MUCH i sold over the past week and
• 21:15
  Speaker 2: my returns and all. THAT i wouldn't even know what
• 21:17
  Speaker 2: to do with that. Data and that was often the.
• 21:20
  Speaker 2: Feeling i'd be, like that is an overwhelming amount of.
• 21:24
  Speaker 2: Detail it is very, Neat but that's not the WAY i.
• 21:28
  Speaker 2: OPERATE i MEAN i, AGAIN i operate On i'm waiting
• 21:32
  Speaker 2: for my orders that come in from RETAILER x On
• 21:34
  Speaker 2: tuesday and filling. Those AND i think the thing that
• 21:39
  Speaker 2: we've seen is it really the pandemic accelerated this to
• 21:43
  Speaker 2: an understanding that the world is more competitive. Now there
• 21:47
  Speaker 2: are both more disruptions on the supply chain that have been,
• 21:50
  Speaker 2: happening AND i think everyone assumes those are going to.
• 21:52
  Speaker 2: Continue just kind of, geopolitically it's a little more complex
• 21:56
  Speaker 2: than it used to. Be but again there's also just
• 21:58
  Speaker 2: so much more competition on the demand. Side and so the,
• 22:02
  Speaker 2: speed again going back to the earlier example we're using
• 22:05
  Speaker 2: around a social media, post how fast CAN i respond to?
• 22:08
  Speaker 1: That?
• 22:09
  Speaker 2: Right AM i understanding that's happening within hours and doing
• 22:13
  Speaker 2: WHAT i can to you, know capture as much demand as,
• 22:17
  Speaker 2: possible or AM i just on my back foot and.
• 22:19
  Speaker 2: Waiting AND i think for for, decades you, know brands
• 22:22
  Speaker 2: didn't have the ability both technologically or the data wasn't,
• 22:27
  Speaker 2: there and they also didn't have the mindset to be
• 22:29
  Speaker 2: able to respond that that. Fast AND i think that
• 22:32
  Speaker 2: is the shift you're seeing is you, know again we're
• 22:34
  Speaker 2: just in a, digital always on, world AND i think e,
• 22:38
  Speaker 2: commerce of, course massively accelerated this because you can see
• 22:41
  Speaker 2: your sales. Live you, know you can see who's on your.
• 22:45
  Speaker 2: Website so that to me is really the shift that
• 22:48
  Speaker 2: we're seeing right.
• 22:48
  Speaker 3: NOW i agree absolutely the demand is obviously bigger with
• 22:55
  Speaker 3: e commerce just because of the convenience of. It but,
• 22:57
  Speaker 3: ALSO i mean to your point, point and this is
• 23:01
  Speaker 3: me coming from a marketing perspective and not necessarily you,
• 23:05
  Speaker 3: know a management. Perspective but IF i have the data
• 23:07
  Speaker 3: to be able to show me on these e commerce
• 23:10
  Speaker 3: sites what times people are buying what you, know what
• 23:14
  Speaker 3: sites they're coming, from you, know where that that attribution
• 23:17
  Speaker 3: is coming, from then that gives me the ability to
• 23:20
  Speaker 3: then kind of control that or at least have some
• 23:24
  Speaker 3: sense Of, okay this is this is, working this is.
• 23:27
  Speaker 3: Not and you, know from from a marketing, perspective SO
• 23:31
  Speaker 3: i think that that granularity of the data is a
• 23:35
  Speaker 3: huge thing for. Companies i'm really surprised, that you, know
• 23:39
  Speaker 3: the marketers aren't banging on THE ceo s door saying
• 23:41
  Speaker 3: you need to get this data so that we know
• 23:43
  Speaker 3: what we're doing and we know when to sell and
• 23:46
  Speaker 3: where to, sell and when to push and when to pull.
• 23:49
  Speaker 2: Back, yeah and there's a huge. DIVIDE i, mean as you,
• 23:52
  Speaker 2: said you're looking at website analytics right and you're trying
• 23:56
  Speaker 2: to understand you, Attribute, okay who's coming in From? Google
• 23:58
  Speaker 2: who's COMING i mean we're looking today on our site
• 24:02
  Speaker 2: how much traffic is starting to be driven through LIKE,
• 24:04
  Speaker 2: chatgbt people do searches and you, know so a whole
• 24:08
  Speaker 2: new channel right with with a total different way of.
• 24:11
  Speaker 2: Optimization and and SO i think that has trained people
• 24:15
  Speaker 2: for this just instant, this you, know expectation for instant
• 24:20
  Speaker 2: understanding of what's going, on and then what CAN i
• 24:23
  Speaker 2: do about? It physical world's a little. Slower you, KNOW
• 24:27
  Speaker 2: i can't unfortunately magically transport, uh you, know inventory across the.
• 24:32
  Speaker 2: Country you, know it takes a little, longer but again
• 24:35
  Speaker 2: they're getting a lot faster there, too and that's just
• 24:37
  Speaker 2: going to. Continue BUT i think e commerce has been
• 24:40
  Speaker 2: such a powerful catalyst for showing people what's possible, absolutely
• 24:45
  Speaker 2: and then it's, Like, okay how how close to that
• 24:47
  Speaker 2: real time uh decision making can we get in the physical.
• 24:53
  Speaker 3: World SO i know that we were talking about, retailers
• 24:56
  Speaker 3: but also consumer. Goods their their supply chain often rely
• 25:02
  Speaker 3: on older legacy systems that maybe don't play nice with other.
• 25:06
  Speaker 3: Systems so are there any practical limitations that you've encountered
• 25:10
  Speaker 3: when trying to deploy or integrate with their inventory systems? ERPs?
• 25:17
  Speaker 3: MANY i, mean that's just the nature of.
• 25:22
  Speaker 2: Software but so there's something that's a little probably surprising
• 25:27
  Speaker 2: when people talk to. Us there's broadly, speaking you can
• 25:30
  Speaker 2: bucket a company's data into internal data and external. Data
• 25:34
  Speaker 2: so internal generally being what's in YOUR, erp what's in
• 25:38
  Speaker 2: that inventory management, system all the things THAT i, control
• 25:41
  Speaker 2: and then the external data being all the other data
• 25:44
  Speaker 2: points that are available from partners or other data. Sources,
• 25:48
  Speaker 2: okay we play with. Both, okay so we but our you,
• 25:54
  Speaker 2: know our genesis was really around the external. Data but,
• 25:58
  Speaker 2: naturally once you start to, see, well what's happening across
• 26:01
  Speaker 2: all my different retailers and e commerce, platforms people want
• 26:04
  Speaker 2: to marry that together with well how much inventory DO i?
• 26:07
  Speaker 2: Have where's my own? Inventory because you, know they have
• 26:10
  Speaker 2: more direct control over. That it is much easier for
• 26:15
  Speaker 2: us to connect with external data sources than it is
• 26:18
  Speaker 2: with internal. Ones, well now that's, surprising, right you, know seem.
• 26:23
  Speaker 2: Counterintuitive you're, like, well the brand already controls this. Data
• 26:27
  Speaker 2: why is that? Harder and it's, because, well brands go
• 26:30
  Speaker 2: and buy THEIR erp and they heavily customize it and
• 26:34
  Speaker 2: they change, it and they have their own very specific
• 26:36
  Speaker 2: way of looking at the, world and every single one
• 26:39
  Speaker 2: as their own. Way, well the nice thing Is target
• 26:44
  Speaker 2: has one system that is shared by every single. Supplier
• 26:47
  Speaker 2: it has the same data, watch it has the same data.
• 26:50
  Speaker 2: Points so it only requires a single integration for, us
• 26:54
  Speaker 2: and you can flip a switch and it doesn't matter
• 26:56
  Speaker 2: if you're selling tires or ice, cream it's the. Same,
• 27:00
  Speaker 2: yeah the skews are, different and they have different season
• 27:03
  Speaker 2: out you, know there's all the analytics what you're looking
• 27:05
  Speaker 2: at might be very, different but the data itself is the.
• 27:08
  Speaker 2: Same so we can we can turn on these external
• 27:13
  Speaker 2: parties or partners extremely. Quickly it usually takes a little
• 27:18
  Speaker 2: bit of work with it to make sure that we
• 27:20
  Speaker 2: can marry that nicely with internal data. Sets when people want.
• 27:22
  Speaker 3: To bring that, in that's that's surprising but interesting and
• 27:26
  Speaker 3: it makes perfect. Sense so what kind of internal resources
• 27:31
  Speaker 3: are realistically needed for these types of. Deployments let's say
• 27:35
  Speaker 3: a mid sized consumer goods. Company you, know there's, personnel there's,
• 27:40
  Speaker 3: time there's, infrastructure there's mapping all of those data. Points
• 27:47
  Speaker 3: what's the typical timeline look.
• 27:48
  Speaker 2: Like, yeah so the usually we're we're getting some kind
• 27:53
  Speaker 2: of it. Resource we try to keep it as lightweight as,
• 27:56
  Speaker 2: possible and so we have a very specific set of
• 27:59
  Speaker 2: data that we're using looking for and for the for
• 28:02
  Speaker 2: the main, eerps we've integrated with them many, times we
• 28:05
  Speaker 2: know which tables we want access, to et. Cetera so
• 28:07
  Speaker 2: it can be pretty, straightforward but you're, right there's almost
• 28:10
  Speaker 2: always some mapping that needs to be. Done and, again funny,
• 28:17
  Speaker 2: enough we can do a lot of this in a
• 28:18
  Speaker 2: very automated way for the external data sets that we,
• 28:22
  Speaker 2: get but we're going to need to bring in all
• 28:23
  Speaker 2: of your you know master. Data, okay what give me
• 28:26
  Speaker 2: your full product master you know what are all the
• 28:29
  Speaker 2: different the hierarchies you, use et cetera For it really
• 28:34
  Speaker 2: depends on how deep you want to. Go we, have you,
• 28:37
  Speaker 2: know some customers they want to connect their entire supply.
• 28:39
  Speaker 2: Chain they're, like, LOOK i want to understand. MANUFACTURING i
• 28:42
  Speaker 2: want to see all the. LOGISTICS i want to see
• 28:44
  Speaker 2: it from you, know raw or or finished goods rolling
• 28:48
  Speaker 2: off that manufacturing. LINE i want to be able to
• 28:50
  Speaker 2: track that all the way to the point of. Consumption
• 28:55
  Speaker 2: that's going to be a bigger. Exercise there's a lot
• 28:57
  Speaker 2: of mapping to kind of map out what that full
• 28:59
  Speaker 2: supply chain looks, like and those are going to take.
• 29:00
  Speaker 2: Months in other, cases people are happier more With, LOOK
• 29:05
  Speaker 2: i just want to bring in my inventory at my you,
• 29:09
  Speaker 2: know main. Warehouses let me connect that into my orders and,
• 29:12
  Speaker 2: shipments and then again connect that into the consumption and
• 29:15
  Speaker 2: that can happen much more, quickly usually a matter of.
• 29:17
  Speaker 2: Weeks so to give you an idea connecting into the
• 29:20
  Speaker 2: external data, SOURCES i mean usually data is blowing in.
• 29:24
  Speaker 2: HOURS i mean it's it's a extreamly. Fast for how
• 29:30
  Speaker 2: how quickly we can do it, now depending on data,
• 29:32
  Speaker 2: sizes and usually we're pulling a couple of years of
• 29:34
  Speaker 2: history that can take. Longer but one of the big
• 29:37
  Speaker 2: areas we've focused on is just that time to value, saying,
• 29:40
  Speaker 2: hey we can we can be showing you your data
• 29:43
  Speaker 2: the day after you engage with, us and you can
• 29:46
  Speaker 2: kind of you can kind of get a taste for
• 29:48
  Speaker 2: what's going to become, possible and then you decide how
• 29:51
  Speaker 2: deep you want to. Go and often for our, customer you,
• 29:53
  Speaker 2: know you start. Basic we're, bigger big believers in, crawl, walk. Run,
• 29:57
  Speaker 2: hey let's start with your main. Retailers, right let's just
• 29:59
  Speaker 2: do that for. Now let's make let's show you some
• 30:01
  Speaker 2: recommended order some of the things that we can. Do
• 30:04
  Speaker 2: once that looks, good, well, hey let's bring on a
• 30:06
  Speaker 2: couple more. Retailers let's start plugging into your earp and
• 30:08
  Speaker 2: you kind of build out from. There rather than signing
• 30:11
  Speaker 2: up for some huge project with you, know unclear timelines AND,
• 30:15
  Speaker 2: roi you, know it's, like let's let's build you, know
• 30:19
  Speaker 2: kind of step by.
• 30:19
  Speaker 3: Step, yeah and develop a really robust case for this
• 30:23
  Speaker 3: business case before we spend all of the time and
• 30:27
  Speaker 3: effort to map all of that. Data so you MENTIONED,
• 30:31
  Speaker 3: roi can you quantify what that return looks like or
• 30:35
  Speaker 3: even the timeframe of getting THE roi for those those. Clients,
• 30:40
  Speaker 3: yeah and what makes a difference in getting a BETTER
• 30:44
  Speaker 3: roi versus not achieving?
• 30:46
  Speaker 2: One, yeah so many points to that. QUESTION i will
• 30:50
  Speaker 2: say we target we're usually shooting for kind of a
• 30:54
  Speaker 2: payback period of six to eight. Months that's our. Goal, okay,
• 30:58
  Speaker 2: OKAY i mean doesn't mean we always get, it but
• 31:01
  Speaker 2: that is that's what what kind of the target. Is
• 31:05
  Speaker 2: and again we can implement pretty, quickly which which helps
• 31:08
  Speaker 2: a lot for that because you're not signing up necessarily for,
• 31:11
  Speaker 2: hey the next six. Months we're just an implementation. Mode
• 31:14
  Speaker 2: sure THAT roi can come from a lot of different.
• 31:18
  Speaker 2: Things so there's no of, course perfect example of. This
• 31:22
  Speaker 2: some of that is just going to be time. SAVING i,
• 31:24
  Speaker 2: mean at this, point every company is out there collecting this,
• 31:28
  Speaker 2: data doing reporting on, it and so there is certainly
• 31:31
  Speaker 2: just a you, know a time savings you, know kind
• 31:35
  Speaker 2: of manpower element of, hey we're going to save you
• 31:39
  Speaker 2: a couple of people's, time, Right but obviously that's not
• 31:43
  Speaker 2: usually the exciting part of. It you, know people are more, Like,
• 31:47
  Speaker 2: okay how DO i sell? More that's the number one
• 31:49
  Speaker 2: question we're to. Get and one of the things that
• 31:52
  Speaker 2: we do is we make recommendations of where retailers aren't
• 31:57
  Speaker 2: ordering enough from. You so and it's very. Specific this
• 32:03
  Speaker 2: is not, like, hey you're undersupplied here you, know this is,
• 32:10
  Speaker 2: hey for this, retailer this is exactly how much inventory
• 32:14
  Speaker 2: you should send on this given day to each of
• 32:17
  Speaker 2: their distribution. Centers and here is all the justification for
• 32:20
  Speaker 2: why that inventory is, needed because generally you can't initiate
• 32:26
  Speaker 2: that order. Yourself you have to go convince the retailer to, say,
• 32:28
  Speaker 2: hey you've purchased by a million. Dollars of Course i'm
• 32:33
  Speaker 2: biased in, THIS i want to sell more, product but
• 32:35
  Speaker 2: here is the justification for WHY i think this is
• 32:37
  Speaker 2: going to make sense for both of. Us, so those
• 32:41
  Speaker 2: those are the, Things those are the sweet. Spots so
• 32:43
  Speaker 2: if you want to talk, about you, know when you
• 32:45
  Speaker 2: have you, know quickly replenishing, items we can almost always
• 32:50
  Speaker 2: find lots of opportunities where you can make incremental. Orders
• 32:54
  Speaker 2: and that's a very very CLEAR. Roi so that's kind
• 32:57
  Speaker 2: of one of our favorite things to focus, on and
• 33:00
  Speaker 2: it's usually a little bit of a wow moment when
• 33:01
  Speaker 2: people are, like oh my, GOSH i found we had
• 33:04
  Speaker 2: a customer the other, day or it wasn't the other.
• 33:07
  Speaker 2: Day NOW i guess this is you, know back to
• 33:08
  Speaker 2: school last, year you know brand everybody would. Know AND
• 33:12
  Speaker 2: i mean they got millions of dollars in incremental orders
• 33:15
  Speaker 2: during back to school because they could just look through. That,
• 33:18
  Speaker 2: again it's huge seasonal period for. Them they do a
• 33:21
  Speaker 2: massive amount of. Sales you missed that, Window you're not
• 33:24
  Speaker 2: going to sell that, product, RIGHT i, mean this is
• 33:26
  Speaker 2: a this is a window you need to. Hit and
• 33:29
  Speaker 2: and we could start seeing where the out of stocks
• 33:31
  Speaker 2: were about to start. Happening you, know you could you
• 33:34
  Speaker 2: could see the sales start to. Spike you can see
• 33:36
  Speaker 2: the weeks of supplies start to. Drop we can give.
• 33:39
  Speaker 2: Justification we were all to selling that to some of
• 33:40
  Speaker 2: the largest. Retailers AND i mean they got millions of
• 33:43
  Speaker 2: dollars in incremental. Orders so those are those are kind
• 33:46
  Speaker 2: of our, favorite uh you, know ones to. Have but
• 33:49
  Speaker 2: but it's always a mix OF i think very you,
• 33:52
  Speaker 2: know specific things people can, do some cost, savings and
• 33:55
  Speaker 2: then you get you, know canidly you get a bunch
• 33:57
  Speaker 2: of stuff that's probably somewhere in the. Middle it's the insights, that,
• 34:00
  Speaker 2: hey you're going to better understand your. Business how do
• 34:03
  Speaker 2: you quantify? That i'd be lying IF i SAID i,
• 34:05
  Speaker 2: Knew but it's it's clearly. VALUABLE i, mean that's why
• 34:09
  Speaker 2: people pay for a lot of, this and you, know
• 34:11
  Speaker 2: just having a better pulse of your business is worth,
• 34:13
  Speaker 2: something even if it's hard to put an exact number against.
• 34:16
  Speaker 3: IT i would think that having the knowledge of stockouts
• 34:19
  Speaker 3: in you, know individual retail locations or individual retailers just
• 34:24
  Speaker 3: in general would be huge information to, say you, know
• 34:27
  Speaker 3: when we send our, inventory when they order, it they sell,
• 34:31
  Speaker 3: it and it's it's a quick. Mover and if we
• 34:34
  Speaker 3: can get that information faster that you, know they just
• 34:36
  Speaker 3: ordered and now all of a sudden they're out of
• 34:38
  Speaker 3: stock three days later and it's four days until their next,
• 34:41
  Speaker 3: order maybe we need to have a discussion about how
• 34:43
  Speaker 3: much they're. Ordering SO i mean that that's huge, intelligence
• 34:48
  Speaker 3: especially for you, know the sales, teams but just also you, know,
• 34:52
  Speaker 3: operationally trying to figure out which channels are driving the
• 34:56
  Speaker 3: revenue for your.
• 34:57
  Speaker 2: Business, well so let's let's use that, example because we
• 35:02
  Speaker 2: can break it up into a couple different pieces and
• 35:04
  Speaker 2: in kind of levels of maturity as an. Organization, sure
• 35:08
  Speaker 2: because you're absolutely. RIGHT i, MEAN i think hopefully everybody
• 35:11
  Speaker 2: listening could, say understanding Where i'm out of, stock there's
• 35:14
  Speaker 2: a clear value to, that, Right i'm missing a sale.
• 35:18
  Speaker 2: Exactly that's kind of everybody's worse. Nightmare so the first
• 35:23
  Speaker 2: step of that is SAYING i have an out of.
• 35:25
  Speaker 2: Stock you get some kind of report or alert you
• 35:30
  Speaker 2: are out of stock OF x. Item and this is
• 35:33
  Speaker 2: where the next, question though someone may, have is, WELL
• 35:38
  Speaker 2: i have a lot of out of. STOCKS i, mean
• 35:39
  Speaker 2: for the AVERAGE CpG five percent ish is often the, stock,
• 35:43
  Speaker 2: right sure can you quantify those for? Me? Right which
• 35:48
  Speaker 2: out of stocks are bigger problems than? Others and so
• 35:52
  Speaker 2: you know we started with out of stocks years. Ago
• 35:55
  Speaker 2: and then the next thing we just said is, well
• 35:56
  Speaker 2: really what we want to do is we want to
• 35:58
  Speaker 2: have a weighted measure that we call lost. Sales how
• 36:01
  Speaker 2: much are you actually losing losing because not all out
• 36:06
  Speaker 2: of stocks are. EQUAL i could be out of stock
• 36:08
  Speaker 2: in one store and it's LIKE i don't really. CARE
• 36:11
  Speaker 2: i don't do a lot of volume. There, yeah it's,
• 36:12
  Speaker 2: unfortunate you, KNOW i WISH i had, zero but that's
• 36:15
  Speaker 2: NOT i don't want one hundred percent service. LEVEL i
• 36:17
  Speaker 2: can't have, one and it would be incredibly, expensive, Right
• 36:21
  Speaker 2: so there's that trade. Off so WHAT i want to
• 36:23
  Speaker 2: understand is where are the biggest? Issues where are the
• 36:28
  Speaker 2: ones Where i'm going on a stock WHERE i do
• 36:29
  Speaker 2: a ton of? Volume right the vo you.
• 36:33
  Speaker 3: Start, hire you know that it's it's the it's the
• 36:36
  Speaker 3: revenue stream you want to, chase.
• 36:38
  Speaker 2: Exactly, right eighty twenty rule applies and everything in, life
• 36:41
  Speaker 2: it seems. Like, so so that's kind of that next.
• 36:43
  Speaker 2: Step and then and then the next thing people will
• 36:46
  Speaker 2: say is so what DO i do about? It that's
• 36:48
  Speaker 2: great that you told me THAT i lost a million
• 36:51
  Speaker 2: dollars last week at this. Retailer where AM i going
• 36:55
  Speaker 2: to lose a million dollars next week or two weeks from,
• 36:58
  Speaker 2: now depending on what my lead time and all that
• 37:01
  Speaker 2: THAT i can get ahead. Of and that's where WHEN
• 37:03
  Speaker 2: i was talking about those recommended, orders that's actually the
• 37:06
  Speaker 2: culmination of years of work that started with the very
• 37:08
  Speaker 2: simple question you had and then worked up to lost,
• 37:11
  Speaker 2: sales and then it would start to be, like, well in,
• 37:14
  Speaker 2: aggregate this is how much they should order To, no
• 37:18
  Speaker 2: we need to be extremely precise so that literally someone
• 37:21
  Speaker 2: can take this data and turn it into an order
• 37:23
  Speaker 2: and SAY i need ten thousand units, HERE i need
• 37:26
  Speaker 2: twenty thousand units. Here this is WHEN i need them
• 37:29
  Speaker 2: buy and so you can actually act on. Them and
• 37:32
  Speaker 2: so that's you, know but, again we have we have
• 37:36
  Speaker 2: companies that are still in like stage. One they're, Like
• 37:38
  Speaker 2: i'm just excited IF i can see out of socks
• 37:40
  Speaker 2: and others every single, week you, know or out there
• 37:43
  Speaker 2: banging on the doors their sales, teams their you, know
• 37:46
  Speaker 2: customer supply chain teams talking to those retailers saying this
• 37:50
  Speaker 2: is where we're going to have. Issues let's get aheut
• 37:52
  Speaker 2: of it.
• 37:53
  Speaker 3: NOW i, mean and that's a win win for the
• 37:56
  Speaker 3: retailers and the. SUPPLIERS i, mean, no one doesn't want
• 38:00
  Speaker 3: to make the, sale.
• 38:01
  Speaker 2: Yes and out of stock is not good for.
• 38:04
  Speaker 3: Anyone, so speaking of failing or, underperforming what are some
• 38:11
  Speaker 3: examples of customers or a type of client or company
• 38:17
  Speaker 3: where your tool is not a great, fit where it
• 38:20
  Speaker 3: doesn't work as. WELL i, MEAN CpG covers a lot
• 38:24
  Speaker 3: of different, potential different. Products are there some that do
• 38:28
  Speaker 3: better than?
• 38:28
  Speaker 2: Others? ABSOLUTELY i WISH i could say that every single
• 38:34
  Speaker 2: company we talked to or a perfect. Fit generally, speaking
• 38:41
  Speaker 2: we we've had quite a bit of success across a
• 38:43
  Speaker 2: lot of different. Verticals so there are some verticals where
• 38:47
  Speaker 2: we've probably had. More we've done more IN, CpG we've
• 38:51
  Speaker 2: done more in consumer, Electronics health and beauty is a
• 38:53
  Speaker 2: big vertical for. Us, historically we've done probably a little
• 38:57
  Speaker 2: less in, apparel although we've gotten a number of brands
• 39:00
  Speaker 2: on that side. Too LIKE i, said the, data it doesn't.
• 39:04
  Speaker 2: Matter the data is it's pretty agnostic as to what
• 39:10
  Speaker 2: the type of product. Is but the types of problems
• 39:13
  Speaker 2: that companies have and what they're trying to solve does.
• 39:17
  Speaker 2: VARY i, mean apparel companies extremely. Seasonal they generally have
• 39:23
  Speaker 2: products that you know they are shipping in for the,
• 39:26
  Speaker 2: season and then it's about how DO i sell through that? Inventory?
• 39:29
  Speaker 2: Right what do those sell through rates look? Like when
• 39:31
  Speaker 2: DO i what's a markdown? Schedule you know that's very
• 39:34
  Speaker 2: different than you, know selling toothpaste or there's a real
• 39:39
  Speaker 2: concept to. That you, know we'll call it kind of
• 39:41
  Speaker 2: an evergreen. Product the product doesn't change very. Often it's
• 39:45
  Speaker 2: just in regular replenishment. Mode and so you. Know as a,
• 39:49
  Speaker 2: result you, know people will use it very. DIFFERENTLY i
• 39:54
  Speaker 2: think we tend to often do better with replenishment items because,
• 39:59
  Speaker 2: again a lot of what we're doing is looking for
• 40:02
  Speaker 2: where can you replenish more versus if it's something where
• 40:04
  Speaker 2: you're just selling in for the. Season you, know there's
• 40:08
  Speaker 2: not really opportunities in some cases for, replenishment but there's
• 40:12
  Speaker 2: opportunities to optimize in other. Ways, right you can change
• 40:14
  Speaker 2: that markdown, schedule you can do other things the other.
• 40:18
  Speaker 2: Thing SO i would say it it, matters but we've
• 40:21
  Speaker 2: been successful across all of. Those the bigger thing that
• 40:25
  Speaker 2: comes down is change management at these. Companies and this
• 40:29
  Speaker 2: is going to be. True i'm sure it's true for your. Business,
• 40:30
  Speaker 2: true everybody's how much do they really want to? Change
• 40:34
  Speaker 2: not at.
• 40:34
  Speaker 3: All everybody wants to. Change no one wants to do the.
• 40:38
  Speaker 2: Change, yeah you, know and you have you know where
• 40:41
  Speaker 2: where do? Where does it not? Work, well it doesn't.
• 40:44
  Speaker 2: Work when you have a. Buyer it brings you in
• 40:48
  Speaker 2: and then you have the support to make the hard.
• 40:50
  Speaker 2: Changes and you, KNOW i WISH i could say we
• 40:53
  Speaker 2: try to make it and this is a huge focus for.
• 40:55
  Speaker 2: Us how can we make it as easy and simple
• 40:58
  Speaker 2: again to get, implemented to do it, quickly to make
• 41:02
  Speaker 2: alloy as simple as. Possible but it still requires somebody
• 41:06
  Speaker 2: on the other side who's, LIKE i WANT i want this.
• 41:10
  Speaker 2: CHANGE i want more visibility into our data by the
• 41:13
  Speaker 2: way we we air dirty laundry a little.
• 41:15
  Speaker 3: Bit, yeah because.
• 41:18
  Speaker 2: All of a sudden you start seeing that channel where
• 41:21
  Speaker 2: you perpetually have too much. Inventory, Yeah we've had that
• 41:25
  Speaker 2: happen many. Times people don't like to see. It you're
• 41:27
  Speaker 2: in a meeting and it's awkward when all of a, sudden, like,
• 41:29
  Speaker 2: wait why is there twice as much inventory in this
• 41:33
  Speaker 2: channel as this? One what is going? On and you,
• 41:37
  Speaker 2: know so you need to have an organization where we
• 41:39
  Speaker 2: see a lot between sales teams and supply chain. Teams,
• 41:43
  Speaker 2: right sales teams will be, HEY i need, THIS i need,
• 41:46
  Speaker 2: this you, know supply channel will be like do You
• 41:51
  Speaker 2: and all of a, sudden you have alloy and they
• 41:53
  Speaker 2: have visibility and they can, SAY i don't think you
• 41:55
  Speaker 2: do need. That you got money inventory, Already so SO
• 42:01
  Speaker 2: i think that is that's where you, know there have
• 42:05
  Speaker 2: been a couple of times WHERE i look back AND i, say,
• 42:07
  Speaker 2: yeah that deal didn't work because for the most, part
• 42:10
  Speaker 2: there wasn't THE i think the organizational desire for the.
• 42:15
  Speaker 2: Change but the flip, side of, course you see the
• 42:17
  Speaker 2: companies that do, change and it's so. Neat it's so
• 42:21
  Speaker 2: cool to, see you, know and it's not. Easy it's never. Easy,
• 42:26
  Speaker 2: AGAIN i WISH i could tell people it. Was but
• 42:28
  Speaker 2: companies that are just, like we're going to, reorient we're
• 42:30
  Speaker 2: going to think on a different, timeframe we're going to
• 42:32
  Speaker 2: be that much, faster we're going to use this extra,
• 42:34
  Speaker 2: data and and that's that's really fun to see.
• 42:38
  Speaker 3: Too, yeah it is really fun to see organizations who
• 42:40
  Speaker 3: who want the, change who are excited, about you, know
• 42:43
  Speaker 3: whatever implementation it. Is you, know for me at me,
• 42:47
  Speaker 3: back we see lots of different implementations of different softwares
• 42:50
  Speaker 3: or or you, know new facilities or new production. Flows
• 42:55
  Speaker 3: and it's it's fun when they're engaged and excited about
• 43:00
  Speaker 3: it and they want to see their company succeed in
• 43:04
  Speaker 3: a new. Way and SO i totally get that where
• 43:06
  Speaker 3: you're able to show them something new that they can
• 43:09
  Speaker 3: do with this information that they've had sitting there this whole,
• 43:12
  Speaker 3: time and they just didn't understand what it meant and
• 43:15
  Speaker 3: now they're able to see it clearly for what it
• 43:17
  Speaker 3: is and adapt and grow and thrive in the. Marketplace
• 43:24
  Speaker 3: what would be your favorite customer success? Story and you
• 43:29
  Speaker 3: don't have to list a client name if they want
• 43:32
  Speaker 3: to stay, anonymous but, like what's that one time that
• 43:35
  Speaker 3: you made that biggest change or the biggest aha moment
• 43:39
  Speaker 3: and the client was just blown, away super. Excited tell
• 43:43
  Speaker 3: us about.
• 43:43
  Speaker 2: THAT i think the first one that comes to, mind
• 43:46
  Speaker 2: and this will be a little, general but it gets
• 43:48
  Speaker 2: to that theme around change. Management this was a customer
• 43:52
  Speaker 2: who had in the very early. Days there's still a
• 43:53
  Speaker 2: customer so they've been with us for many. Years and
• 43:58
  Speaker 2: so this is when we were very. Small we didn't
• 44:00
  Speaker 2: even have a fully formed product at the. Time we
• 44:02
  Speaker 2: were still figuring it. Out and, uh it was a
• 44:07
  Speaker 2: it was a smaller company actually mostly in, apparel so
• 44:13
  Speaker 2: AND i think they were just kind of confused by
• 44:16
  Speaker 2: what we were. DOING i think a lot of it was, Like,
• 44:18
  Speaker 2: okay this sounds kind of. Neat you, know they had
• 44:23
  Speaker 2: they'd had a lot of. Success it had kind of
• 44:27
  Speaker 2: been a company that had just taken off and you,
• 44:31
  Speaker 2: know mid size company they, were they were a huge.
• 44:33
  Speaker 2: Company but, uh but they were willing to take a
• 44:38
  Speaker 2: bet on. Us and so this is probably why it
• 44:40
  Speaker 2: kind of feels close to my heart BECAUSE i was,
• 44:42
  Speaker 2: like they bet on me when we didn't have. Much
• 44:47
  Speaker 2: but if you want to talk about a company that,
• 44:49
  Speaker 2: changed you, know and again it started at the. Top
• 44:53
  Speaker 2: it was like their leadership, saying we need to become
• 44:58
  Speaker 2: a data driven organization and we. Don't we don't want
• 45:03
  Speaker 2: to be that kind of traditional. Company AND i, Again
• 45:06
  Speaker 2: i've seen it now for, years And i've seen how
• 45:10
  Speaker 2: they today in many ways are more sophisticated than companies
• 45:14
  Speaker 2: that are, many many times their, size just because it's
• 45:18
  Speaker 2: been a part of THEIR dna and it's it's just
• 45:20
  Speaker 2: like not even a question of is this data that
• 45:23
  Speaker 2: you look? AT i, mean they live and they breathe
• 45:25
  Speaker 2: it every single, day and when when new employees, join
• 45:29
  Speaker 2: it's just, like this is what you. Do this is
• 45:31
  Speaker 2: how you do your. Job if you're a salesperson and
• 45:34
  Speaker 2: you don't intimately understand you know what is happening and
• 45:40
  Speaker 2: are super. Honest one of the other Things i'm good
• 45:43
  Speaker 2: friends with THE, ceo and he'll talk about it's like
• 45:46
  Speaker 2: you've got to you've got to be honest when you're
• 45:49
  Speaker 2: dealing these are relationships and saying this is, working this
• 45:52
  Speaker 2: isn't even when the things that aren't working aren't to
• 45:54
  Speaker 2: your own personal. Advantage you, know that's what really build that.
• 45:57
  Speaker 2: Trust SO i think again that's a very general. ONE
• 46:02
  Speaker 2: i think there's lots of other examples that have, that
• 46:04
  Speaker 2: Like War. Concrete, hey they came in and they immediately
• 46:08
  Speaker 2: were able to turn it. Around they had this problem
• 46:10
  Speaker 2: with overstocks and they were able to figure it. Out
• 46:13
  Speaker 2: but this is one THAT i guess is just kind
• 46:16
  Speaker 2: of close to my heart because, Again i've just seen
• 46:18
  Speaker 2: that over the years and it's just been so cool
• 46:20
  Speaker 2: to say this is a very different organization than the
• 46:22
  Speaker 2: one THAT i met. You that's.
• 46:24
  Speaker 3: Awesome, no and that's exactly what you set out to
• 46:27
  Speaker 3: do was to change these organizations and the way that
• 46:31
  Speaker 3: they approached this problem and help them through. That so
• 46:37
  Speaker 3: that's got to be incredibly. Gratifying SO i would, say
• 46:43
  Speaker 3: from my last, question what do you see next For? Alloy,
• 46:46
  Speaker 3: like what are you guys working? On what are you
• 46:49
  Speaker 3: trying to?
• 46:49
  Speaker 2: Do? Extra, yeah, well is this going to shock? You
• 46:57
  Speaker 2: it's not going to shock you at, all because it's
• 46:58
  Speaker 2: what everybody's talking about so IF i look at what
• 47:01
  Speaker 2: do we have that's, Unique we've got a very unique
• 47:05
  Speaker 2: data set that we collect on behalf of our. Customers
• 47:10
  Speaker 2: we have a very deep understanding of the types of
• 47:14
  Speaker 2: problems that our customers are, solving right because we see
• 47:18
  Speaker 2: it across hundreds and hundreds of different. Companies we have
• 47:24
  Speaker 2: a new technology out there WITH. Lllms, okay RIGHT, Ai
• 47:30
  Speaker 2: and you, KNOW i, think to, me what gets me
• 47:33
  Speaker 2: the most exciting or excited is there are so many
• 47:38
  Speaker 2: of these use cases WHERE i, say we can really
• 47:42
  Speaker 2: train you, know AN ai to do these M AND
• 47:48
  Speaker 2: i know that seems kind of scary to some people
• 47:50
  Speaker 2: because they're, like wait a, minute or we just training
• 47:52
  Speaker 2: away our. Jobs and the short answer, is in some, ways,
• 47:53
  Speaker 2: YES i mean all of our jobs are but we're
• 47:58
  Speaker 2: not going. Anywhere we're, Gonna we're, Gonna we're we're pretty.
• 48:03
  Speaker 2: Adaptive but that to me is. Fascinating and as we've
• 48:08
  Speaker 2: started to play with you know, again we've also got
• 48:12
  Speaker 2: all the, tools, Right we've got all the models and
• 48:15
  Speaker 2: all the, analytics and you, know instead of training an,
• 48:19
  Speaker 2: analyst you train AN ai to be, like, well how
• 48:22
  Speaker 2: do you do this? Job what tools can you? Request
• 48:25
  Speaker 2: what data do you ask? For and it's it's fascinating
• 48:29
  Speaker 2: seeing if if you follow kind of the chain of
• 48:31
  Speaker 2: thought of these lms as you train, them you can
• 48:33
  Speaker 2: be like, hey at each step like ask for data
• 48:36
  Speaker 2: or ask to use this, tool and then you, know
• 48:39
  Speaker 2: our platform will give them that response and they have
• 48:42
  Speaker 2: to kind of digest the information that's provided and decide
• 48:45
  Speaker 2: the next step of what they want to. Do it's.
• 48:48
  Speaker 2: INCREDIBLE i mean they're in the speed at which they're getting.
• 48:51
  Speaker 2: BETTER i mean it's just looking this. MORNING i mean
• 48:53
  Speaker 2: it's like they get, better you, know every three, months
• 48:55
  Speaker 2: they like double and. Capabilities it seems. Like SO i
• 49:00
  Speaker 2: think that to me is going to be a fascinating.
• 49:03
  Speaker 2: Change is how do you, know get to a world
• 49:07
  Speaker 2: THAT i don't think that's is that far away where
• 49:09
  Speaker 2: we're essentially all going to have our own team of
• 49:12
  Speaker 2: analysts of these agents that are, out you, know operating relatively. Autonomously,
• 49:17
  Speaker 2: again they're not going to be doing everything on their,
• 49:18
  Speaker 2: own but they go out and do, things they come back, Report,
• 49:22
  Speaker 2: hey this is WHAT i. Found you give them some,
• 49:25
  Speaker 2: direction they go off and do that. Again so that's you,
• 49:29
  Speaker 2: know we as a company are really. Focused we don't
• 49:34
  Speaker 2: we try to avoid getting into the MARKETING ai hype
• 49:37
  Speaker 2: because it's. Insane i'm sure you, see it is. Insane,
• 49:42
  Speaker 2: yeah we just had our team came back from you,
• 49:44
  Speaker 2: know one of the big supply chain, conferences and they're
• 49:46
  Speaker 2: like every single company that's all it, was you, know
• 49:50
  Speaker 2: and then you go talk to companies like who's using?
• 49:52
  Speaker 2: WHAT i, mean almost everybody's using almost nothing at this.
• 49:56
  Speaker 2: POINT i think it's it's a lot of. Dabbling so you,
• 49:59
  Speaker 2: know we're we're taking maybe the slower, approach but one
• 50:03
  Speaker 2: of saying we want to put something out there that
• 50:05
  Speaker 2: really works and has a CLEAR roi and all. That
• 50:09
  Speaker 2: but i'd say the things that we're working on right,
• 50:12
  Speaker 2: now you certainly AGAIN i don't know are they going
• 50:14
  Speaker 2: to be ready three months from? Now is it a
• 50:15
  Speaker 2: year from? Now but you can see the promise and
• 50:18
  Speaker 2: that's pretty darn. Exciting that is.
• 50:20
  Speaker 3: Exciting SO i think that brings us to the end
• 50:25
  Speaker 3: of our. Episode to our, listeners if you found today's episode,
• 50:28
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• 51:01
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