Episode 413: 🏭🧱 Inventory Stock, Planning Strategies, and Cost Savings: From Supply Chain to SciFi

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Welcome everyone to another episode of Dynamics Corner Brad.

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What's demand?

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Planning, planning, preparation, are they all the same?

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I'm your co-host, chris.

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And this is Brad.

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This episode was recorded on February 28th, 2025.

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Chris, chris, chris, last day of February, did you know that it's not a leap year?

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Not leap year.

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And what is demand planning, what is forecasting and how do we predict the future?

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With us today, we learned all about that Not leap year.

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And what is demand planning, what is forecasting and how do we predict the future?

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With us today.

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We learned all about that with Lon Porter and Sam Bush yeah, morning, why?

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Did?

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I just jump in?

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You scared me who just jumped in I just jumped out of my skin because it was like silent.

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I was waiting to come and then all of a sudden I just heard Vaughn say something and it was like really loud.

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Listen, we come in with a bang.

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So, vaughn, you scared her, vaughn, you scared me to death.

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How can Vaughn come in so loud?

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He's probably one of the most soft-spoken people I know.

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He's got it.

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I would call him a gentle quiet soul.

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He didn, I would call him a gentle, quiet soul.

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I wouldn't even say anything.

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How did I come in so loudly?

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We don't know.

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I was just thinking to myself.

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I'm looking at this background and I'm like man, I've got the most un-podcastable background ever right.

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Is that a real background or is that?

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a fake background yeah check.

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Oh okay.

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It's bland.

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You need color there, man.

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You look like you're in an asylum.

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You do, you do.

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I usually always have a background, so I don't even notice what's behind me, and when I switched this on I was like, wow, that's.

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I like it.

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I've got like a TV stand at the back over there with no TV on it and some medals from years ago that I don't want to let go of, like holding on to my youth, and then a whole bunch of like.

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There's just nothing interesting.

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No, it's okay, Put a picture behind you in a plant.

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Just something.

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I told my kids that they needed to paint me something that I could hang up behind you, because it will also be better for for sound and stuff to absorb the sound.

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But I can draw you a picture if you'd like and I'll send it to you.

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I'll wait till I die no, I, I do like it would have been better if you had your white robe or your white uh coat, your white doctor coat.

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Oh wow, yeah, that would have been.

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Yeah, you're actually.

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Then it would have looked like you probably had a head floating in the middle.

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Or you could have really looked like you belong in an asylum.

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I remember doing weird things.

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And now I feel like I'm watching Silo because Vaughn's wiping off the camera like he's doing the cleaning.

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That's right.

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Why have I got this line down the middle of my?

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cleaning.

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Why am I got this line down the middle of my?

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It's so weird what's going on, so you sam sam, you've watched sila too?

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yeah, I just started watching it.

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I'm almost done with season one, okay I'm not gonna say anything.

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I'm not gonna say all I'll have to say is it is amazing.

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I started watching it.

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I binged season one in a day, been season two in a day.

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It was when I was sick, so it was very easy to do.

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And now I'm halfway through book two because as soon as I finished the series I started reading the books.

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There's three books.

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There's Wool, shift and Dust the stories.

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The books are just as good as the show.

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If not better Adding to my Libby app right now.

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Excellent, excellent.

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Let me know what you think of them.

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What did you say?

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Silo.

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Silo, it's on Apple TV, okay.

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Oh it's it's it's a true, plausible, sci-fi, dystopia movie series, excuse me, so what?

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I like about.

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I don't like movies or shows that are so outlandish that they can't be real, like the way I said this on another episode, where that one guy runs into 40 000 guys with machine guns, tanks and and airplanes and he kills them all but with silo it's so plausible and you can see it happening and it's just mind-blowing yeah, oh yeah I'm on the severance train right now as well oh, I finished that same episode came out last night instead of tonight, so it's already out there okay

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I'm on the seven train severance is really good, but it's slow, like it's very slow, but it still keeps you drawn in and it's good uh-huh oh yeah, I'm a big, I love sci-fi, anything at all like read it, watch it into it.

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But this I'm like oh, severing your brain from the workday Sounds interesting.

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That is.

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I was thinking about it and it didn't really hit me until they did one of the scenes.

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I'm not going to spoil it, because it's the plot of the show.

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If you read it you can see it, but when the woman was on the elevator and she got on the elevator, then got off the elevator, then I'm like they have no memory other than getting onto an elevator and getting off of an elevator and they have no recollection of sleep or time outside of work.

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And they could be in there for days and they don't even realize, they don't notice it.

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That is so good.

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I'm glad that the episode came out last night so I can watch it tonight, because I have to go to bed early, but I appreciate that With that we didn't look to speak with you because we wanted to talk about books and movies, which we could do all day, or Dr Vaughn's wonderful background.

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We wanted to talk to you about I love this and then, with him wiping it, now I'm just.

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I just it's fitting Vaughn, you need to watch Silo, because it's fitting with your background and you wiping the camera, it just fits right in.

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I thought you were doing it on purpose, to be honest with you.

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So, but before we get into the conversation, would you mind telling us a little bit about yourself?

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We can start with Sam.

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Yes, hello, hello, I'm Sam Bush.

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I feel like I have a rehearsed like.

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This is me, this is what I do, but I need to update it.

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It's been a minute since I've updated.

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Okay, so I am a partner marketing manager for NetStock.

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Been at NetStock about three months.

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Three months, yeah, three months Feels like I just started, but also like I've been there forever, so that's a good feeling.

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And then I am a podcast host of Ambush on Air, which you can see back there if you're watching this.

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I should have said that to do my shameless plug.

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Plug away.

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I know right to do my shameless plug, plug away.

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I know right Where's my light Better when it's on right, okay.

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I have a podcast light that has like 50 settings and it's the most hilarious thing on earth.

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That's pretty cool, that's awesome.

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Based in Columbus, ohio, been in marketing about 15 years, not California.

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Not California.

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Not California as much as you would think.

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I am a Midwesterner, that's me.

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Oh, excellent, dr Vaughn.

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Dr Vaughn, I'm a channel account manager at NetStock.

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I said yesterday to somebody that I was talking to I've been with NetStock since God was a child.

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I think I was employee number seven and we're probably around about 300 employees now worldwide.

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So I've been in the business for a long time.

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That is nuts, yeah, like 11 years.

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And I've had different roles in the business for a long time.

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That is nuts, yeah, like 11 years.

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And I've had different roles in the business as I was going along from channel management to kind of start off with sales solution consultant.

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I ran a sales team in South Africa while I was there and I've moved into the US business about two years ago that I started in this region.

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So I've come here as a channel manager and we're focusing on building the channel and reviving the existing channel that we had and building better channel relationships with our partners.

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So that's kind of why I came across and we have started building a team uh here in the us to do that and and internationally, actually don martin, who heads up the channel uh in the us, has been well worldwide, has been building, um, building a channel team in all of those regions that we're at.

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So, yeah, I'm I'm kind of one of those guys when you start off with a bootstrapped startup, it startup and everybody's doing everything, to get into a point where we have to, kind of like, try and specialize in certain areas where we can add value rather than do everything like we used to.

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So it's been quite a journey with NetStock everything like we used to.

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So it's been.

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It's been quite a journey with net stock.

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It's now owned by an investment business in in the U S and that's, you know, the reason for the expansion over the last couple of years, maybe since 2020, last five years or so.

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The investments Wonderful.

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And I have one question for you Cuanto tiempo has vivido en Mexico?

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Cuanto.

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Cuanto tiempo has vivido en México?

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¿Cuánto, ¿cuánto tiempo has vivido en México?

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¿Cuánto tiempo?

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My Spanish is very bad sir.

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Oh, whoa, okay, we won't say that.

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Lento lento I have no idea what you said.

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I did speak Spanish, but that was a long time ago.

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It's okay.

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Me vivo en Merida para dos años.

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Okay, you answered the question.

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Me vivo en Merida para dos años.

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sí, Thank you, thank you.

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A bit slow, but.

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I'll get there.

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Well, if you immerse yourself in.

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I'm assuming they speak Spanish in Madagascar.

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Well, you know, that's really been the problem.

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I'm probably I'm on 502 days on Duolingo, so my vocab's good, I understand the way the language is put together and I'm learning that pretty well, but I'm not immersed in speaking and that's why, like, if I take what you said and I break it down or you write it down, I'll like if I take what you said and I break it down or you write it down, I'll be able to answer it straight away.

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But I have to try and process that in my head as we're going along.

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So that's what?

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That?

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That's what takes so long.

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Right, and it's all because I'm not speaking spanish to people.

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So, um, you know, I don't pick up the words.

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If I read, I'm fine.

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If I listen and do lingo, I'm fine.

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But when I speak to people, I start missing things because I'm not used to hearing it.

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It's strange how that works sometimes, but I thought you'd be immersed in it in your day-to-day.

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but I guess, if you're like me, you never leave the house either.

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It's the other world.

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That's what I say.

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I met my neighbor the other day.

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He said to me.

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I hear you're always in america.

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I was like no, actually I'm up in my room most of the time.

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I maybe travel once a once a month, um, but he knows my he's, you know, my wife is chatting in in spanish to him and and, uh, he, you know he sees her all the time and the kids, but he, he doesn't think I exist or he thinks that I'm in the us all the time, right?

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No, I spend most of my time here.

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I'm just just in a room speaking to partners and working right.

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I know that life.

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I always tell myself I could just get a small one room place and I'd be fine because, I spend most of my time sitting at my desk.

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I'm either at my desk sleeping, or in the kitchen.

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And the office has 90% of the time, the 10% of the time is in the kitchen and the.

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The office has 90 of the time, the 10 of the times in the other places.

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So so, netstock, can you tell us a little bit about netstock?

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so well.

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I'll go back in history again because I've been around for so long.

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Um, but netstock, the the founders of netstock and one of them was a friend of mine, that's how I was employed.

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He was kind of like the brains behind developing the software.

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They had built businesses doing inventory planning and optimization for many years before that for big corporate, multinational businesses big corporate, multinational businesses and they had like a team of consultants that they would then deploy into these businesses and they would spend years there helping them optimize their inventory with whatever the methodology was that they were selling.

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And this went on for many years.

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Our CEO at that point our CEO was in Chicago, the developer was in south africa and there was an engineer in the in australia.

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They had all worked together previously in the businesses and they'd split up over that period of time and, uh, they decided to start this business called net stock and the idea was really to take the methodology that they were using and the consultants that you and the consulting businesses that they were running and taking the functionality and the methodology and building that into the software and then taking that software to small and medium-sized businesses rather than working with the big multinationals only.

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And the idea really was to get away from that whole consulting, but it was also to be cloud first, remote first, which was unheard of in 2010 when they started and yeah, that's that's how we started we built software, started selling it to some of the businesses in South Africa.

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They obviously had a lot of contacts in South Africa with businesses that they've been working with.

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I've got few customers then reached out to contacts that they had in.

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Sage in South Africa was introduced to Sage in North America and a couple of years in roundabout, when I was employed, had signed an agreement with Sage in North America to white label a product called Sage Inventory Advisor and that was our first kind of channel to market with that product.

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So I was employed at that point to look after Sage in Africa and the Middle East and some of the guys came over to the US and started working with Sage here in the US and that was our, you know, when we originally started building the business.

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Since then we built obviously in Australia where the engineer was.

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They started building a business there, the US was going, I was looking after South Africa with our CEO and we eventually then also employed people in the UK and so we kind of got to the point where we were covering all territories across the world and then, around about maybe seven years ago or so, we thought the business through Sage was starting to slow down and we felt like we weren't growing at the pace that we needed to.

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We were looking for investment, obviously as a tech startup, that's what we were hoping for and we decided to go directly digital marketing.

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We built a whole digital marketing.

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Part of the business went direct to try and get more customers integrated with 45 different ERPs and systems that we could get to try and kind of diversify.

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And we did pretty well at that for a while.

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And then, I think maybe two or three years ago, we started thinking a bit more about getting back into channel and how we because in the end, specifically for an application like ours, it's ERP dependent, so the best way to market really is channel.

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So in the last couple of years there's been this kind of swing to get back into channel and build maybe not over 45 different erps, but at least the top kind of uh vendors in in the us and internationally and then grow from, grow from.

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There, as I said, we finally got.

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We were kind of one of those success stories that came out of covert um we.

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We had a a number of investors that were looking at us before COVID hit and, as it hit, most of them disappeared.

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In 2019, there was one business, an investment business in Texas, that kind of either came back or stuck around and said listen, let's just see what's happening in the world and how you guys, how resilient you are to this, and let's see what happens.

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And then, kind of like the perfect storm, we had a couple of months where business was very slow and then suddenly everybody was at home.

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They couldn't get any of the information from their on-prem ERPs and all the stuff that was sitting in the office.

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The supply chain was a mess.

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So they needed something to be able to plan better and try and figure out what was going on with the supply chain.

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And here was NetStock.

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We could deploy this product remotely through the cloud.

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They could interact with it anywhere, anytime.

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It was just sort of like one of those success stories that came out of COVID and sales started increasing.

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There was a huge demand for our product and in October 2020, we got the investment and, yeah, since then we've been a really incredible investment business that worked with us.

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We were really really lucky to get such great people and our business is really focused on our culture and we try to keep.

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I mean, we always say we try to keep the culture.

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It's impossible to keep that small business culture, but we try for the most part to do that in the businesses be as transparent as possible, be as flat as possible and be as supportive as possible to everybody in the business.

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So it's still got that feel and we were lucky enough to get an investment investment company that was, you know, exactly like that.

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They didn't want to come in and change the way that we wanted to do things.

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They would advise us from the board, they would let us, you know, give us matrix that we didn't have, that we needed to try and adhere to so that we could become a better business.

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But they let us run the business and do what we needed to do.

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And you know, that's kind of the philosophy to this day we hire on culture.

00:19:01.923 --> 00:19:14.090
It's a very big thing in the business to make sure that we keep that culture because that's been, I think, or we believe that's been the reason for our success over all these years and hopefully that's what will carry on the success into the future.

00:19:14.090 --> 00:19:21.915
So there's a very long story that I put out there, but that kind of gives you the outline of how we got from 2010 to where we are now.

00:19:22.736 --> 00:19:23.876
Yeah, it was a good story.

00:19:23.876 --> 00:19:25.357
I appreciate the story.

00:19:25.357 --> 00:19:39.086
Culture is extremely important within an organization and individuals often forget that because it's the people that make up the organization and also follows through or flows through to the product as well.

00:19:39.086 --> 00:19:42.307
With Netsoc, you mentioned Sage.

00:19:42.307 --> 00:19:48.026
What are some of the other products that it works with and that I want to dive into?

00:19:48.026 --> 00:19:50.347
I have a million questions on what it does.

00:19:51.461 --> 00:19:55.332
Well, the big ones really that we're focusing on.

00:19:55.332 --> 00:19:56.824
Sorry, sam, am I taking up too much?

00:19:57.125 --> 00:19:57.928
You're good.

00:19:57.928 --> 00:20:01.088
You're good, I'm like you can talk this whole time, I'm just listening.

00:20:02.680 --> 00:20:08.605
Obviously Sage, all of the products that they, that they supply, and we've been partners with them for a long time.

00:20:08.605 --> 00:20:17.387
Um, akumatica, we went into akumatica and and uh, joined the fulfilled by akumatica and we're on their price list.

00:20:17.387 --> 00:20:18.851
A lot of the.

00:20:18.851 --> 00:20:30.972
We knew a lot of the partners there because originally a lot of the sage partners took on Acumatica because they needed a cloud, some kind of a cloud application for their customers.

00:20:30.972 --> 00:20:35.090
Now Sage has got Intact, so that gap's closed a little bit.

00:20:35.090 --> 00:20:49.249
And then NetSuite was always around, so that's been a big one for us, especially in the last year we did integrations with netsuite and then microsoft was probably the newest one that we've done.

00:20:49.249 --> 00:20:52.826
Um, those, those are kind of like the four that we're focusing on now.

00:20:52.826 --> 00:20:59.426
So we, we um did official integrations on app suite with business central.

00:20:59.969 --> 00:21:04.765
uh, we've actually got two products, because one of the things that we did was we acquired another business called Demandworks.

00:21:04.765 --> 00:21:26.255
It was also around 2020 after it was one of the things that the investment business said that we needed to do, and that's more of a kind of starts punching towards that enterprise level with their sales and operations planning and that type of stuff.

00:21:26.255 --> 00:21:31.092
And we've got a demand planning module that has integration with F&O as well.

00:21:31.092 --> 00:21:35.970
So from a demand planning point of view, we're able to connect to F&O with that product as well.

00:21:35.970 --> 00:21:47.134
So, yeah, depending on the product, depending on the customer and depending on the requirements we could deploy on both those Dynamics applications.

00:21:48.019 --> 00:21:50.173
So you, get F&O and Business Central.

00:21:51.179 --> 00:22:01.260
Yeah Well, I mean, we've got on-prem integration with Great Planes and obviously all the on-prem products.

00:22:02.263 --> 00:22:15.509
Nav AX, I think they would have to create I don't think we've got scripts for those but people would just create files and we would consume those and do the work that we need to do.

00:22:15.660 --> 00:22:19.330
So throughout the Microsoft stack as well, we could connect.

00:22:19.330 --> 00:22:37.192
And one of the great things about that is that when there's sort of a migration path for any of those to any of those other products, they can kind of take net stock along, so you can start off at gp and eventually get onto, you know, I don't know dynamics or whatever the other product is.

00:22:37.192 --> 00:22:38.502
They can take net stock along.

00:22:38.502 --> 00:22:53.643
We retain all of the historical data in net stock and one of the big things that when you move from one erp to the next is that you know people think that you can take all your historical stuff along or they end up accessing both ERPs to get that information.

00:22:53.643 --> 00:23:12.704
We retain all that historical data because we use that in our forecasting engine to do the demand planning and you know purchase order history and that type of stuff to measure supplier reliability and all of that remains in NetStock when they move from one application to the next, so you're ERP agnostic.

00:23:14.930 --> 00:23:15.731
Pretty much.

00:23:15.731 --> 00:23:16.413
That's excellent.

00:23:16.413 --> 00:23:22.287
And for Business Central you had mentioned, you work with both the cloud version or the online version of Business Central.

00:23:22.287 --> 00:23:26.095
Netstock itself is a cloud-based product and you can also work with the on-premises versions of Business Central.

00:23:26.095 --> 00:23:29.181
Netstock itself is a cloud-based product and you can also work with the on-premises versions of Business Central.

00:23:29.181 --> 00:23:36.847
How far back can someone work with Business Central, dynamic Nav or Navision in NetStock?

00:23:36.847 --> 00:23:39.166
Which versions do you support in essence?

00:23:39.602 --> 00:23:42.384
I don't know the version numbers but I can tell you.

00:23:42.384 --> 00:23:48.046
I mean, I'm trying to think about how far back we integrated with that.

00:23:48.046 --> 00:23:51.210
It was many, many years ago that we integrated with Nav and GP.

00:23:51.210 --> 00:24:08.032
So you know, and it's a pretty simple integration, we just, you know, read information from the database, create flat files in a folder and then send that up via security Ppt to our site and then consume it that way.

00:24:08.032 --> 00:24:21.027
So it's a very simple kind of integration and we can change those scripts if required if there was changes to the database.

00:24:21.027 --> 00:24:32.380
But I don't know if there'd been major changes to the stocking information that we require in the databases for NAV or GP through those versions.

00:24:32.380 --> 00:24:40.114
But I know we've got some really old NAV customers and old versions that we can integrate with.

00:24:40.114 --> 00:24:41.364
So I don't think that should be an issue.

00:24:42.950 --> 00:24:43.290
Excellent.

00:24:43.290 --> 00:24:48.690
But as far as NetStock is concerned, I like the integration because then you can have integration with anything.

00:24:48.690 --> 00:24:53.686
If you're importing the files, I could have some other system, so there's a lot of flexibility there, which is nice.

00:24:53.686 --> 00:25:01.426
Who or what type of business is the target for using a product such as NetStock?

00:25:01.426 --> 00:25:03.229
What you have in your offerings?

00:25:06.375 --> 00:25:09.701
Well, I think originally it started off being the really small businesses.

00:25:09.701 --> 00:25:22.417
We started off wanting to kind of be the spreadsheet replacement and saying that I mean, everybody kind of says that, but there's some really big businesses that are still using spreadsheets to do their planning, which is pretty scary.

00:25:22.417 --> 00:25:42.686
So the idea really was to create a purpose-built application that would automate a lot of the processes and a lot of things that people were doing in spreadsheets to try and calculate, you know, forecasts or classifications or you know whatever they needed or what the order should be, when they should order all that type of stuff.

00:25:42.686 --> 00:25:53.419
And that was really the driver, because in small businesses a lot of the time the owner is the planner, is the marketer, you know, is everything.

00:25:53.419 --> 00:26:12.500
So having an application that would do all the heavy lifting for them and then just give them the answers and let them go okay, I'm okay with this, or I need to fix this and let me have a look at that, try and make it quicker for them or make them more agile in the business, in those small businesses, that was really the initial kind of focus.

00:26:12.500 --> 00:26:34.413
Obviously, we built the application a lot since then and the functionality has now grown into kind of bigger businesses and then with the addition of that demand with business, which we call NetStock, ibp, that now basically closes that gap from medium-sized business to enterprise as well.

00:26:34.433 --> 00:26:36.438
There's overlap between those products.

00:26:36.438 --> 00:26:51.480
So really anything from small mom-and-pop business I think complexity really starts coming in when there's manufacturing involved or there's distribution involved.

00:26:51.480 --> 00:26:52.654
There's more than one location.

00:26:52.654 --> 00:27:09.605
Trying to plan, let's say, 100 items in one location might not be that difficult to do and we can do that in a spreadsheet, but when you multiply that by 10 locations and you're trying to manage those items differently in 10 different locations, things start becoming a bit more complex, right?

00:27:09.605 --> 00:27:17.944
So that's really where you need to start having some kind of a tool to help manage that inventory better.

00:27:19.010 --> 00:28:00.721
So, from those businesses right up to really enterprise businesses that want to be able to forecast at a channel level or break the forecast up at a customer level to see which customers are affecting that forecast in what way, or make adjustments at different levels, whether it be top down or bottom up or middle out Very mature demand planning teams and then right down to the owner run owner run business that does everything we, you know we try and cover everything yeah, and I'll give you like the marketing answer, because that's, that's obviously the answer, but this is like a written one, you know?

00:28:01.324 --> 00:28:04.653
uh, basically, it's anybody marketing.

00:28:04.834 --> 00:28:20.178
Answer to everything there is, there's always a marketing answer um, but this is like the the most simple way that I've learned to describe it and that's like anybody who has around 250 SKUs or more are like our ideal customer.

00:28:20.178 --> 00:28:22.162
We'll do anybody, but that's ideal.

00:28:22.162 --> 00:28:26.414
And then people have inventory value of like at least 200k.

00:28:26.414 --> 00:28:28.338
It's like a sweet spot for us.

00:28:28.338 --> 00:28:35.394
So manufacturers, distributors, wholesalers, e-commerce businesses those kind of people are what we talk to the most.

00:28:35.394 --> 00:28:43.035
But again, like Vaughn said, we can do the smallest of small to that mid-market size business how we kind of classify it.

00:28:43.035 --> 00:28:52.661
So business from 10 to 200 million in annual revenue is usually like our best fit for, kind of our average deal.

00:28:53.422 --> 00:28:54.203
Excellent, Excellent.

00:28:54.203 --> 00:29:00.470
So with small to medium sized businesses or enterprise business, your SMB and enterprise market you can cover, which is good.

00:29:00.470 --> 00:29:07.803
It's good to have a wide range, and I'm assuming there's different functionality that you utilize based upon your scale of use.

00:29:07.803 --> 00:29:18.298
And thank you for putting in an ideal number of SKUs Understanding there can be some variability in there as well, too, depending upon how you need to plan, which is good.

00:29:18.298 --> 00:29:19.842
So with it.

00:29:19.842 --> 00:29:22.137
So how does it work?

00:29:22.137 --> 00:29:23.976
How does it plan?

00:29:23.976 --> 00:29:34.961
So it's a business, an SMB or enterprise business that needs to plan its inventory and you're planning procurement, planning and forecasting sales.

00:29:34.961 --> 00:29:38.900
And what else is going on under the hood in there?

00:29:39.391 --> 00:29:44.542
Or what is it trying to solve exactly for small businesses, smbs?

00:29:46.510 --> 00:30:10.559
Typically in that space, what we're trying to solve is optimizing their inventory, you know, making them more efficient at controlling their inventory, because you know the big pain points there really are that either they're holding too much inventory and they're tying up cash and that's affecting cash flow, or they're stocking out of items and that's affecting sales and profits, and you know.

00:30:10.559 --> 00:30:14.458
So that's really the two major kind of like pain points.

00:30:14.458 --> 00:30:23.333
And then the other one is really just the the time that it takes to get to a point where they can calculate what they should be buying and when they should be buying it.

00:30:23.333 --> 00:30:37.417
And that's usually, you know, like we said, the forecasting and a spreadsheet trying to figure out what the min maxmax level should be on the items, trying to know when to trigger an order to make sure that you buy in time, you don't buy too much or you don't buy too little.

00:30:37.417 --> 00:30:58.075
Most people are trying to either do with some functionality native functionality in an ERP or in combination with spreadsheets and things like that, because you know ERPs aren't built to plan on inventory.

00:30:58.296 --> 00:30:59.679
You know we always say this thing about.

00:30:59.679 --> 00:31:04.574
You know when we talk to customers how much inventory do you have?

00:31:04.574 --> 00:31:05.496
So I have this widget.

00:31:05.496 --> 00:31:07.140
How many of that widget do I have?

00:31:07.140 --> 00:31:07.840
I've got 10.

00:31:07.840 --> 00:31:19.862
Now if you look at the ERP, you know exactly why you have 10, because we can see when it arrived, how much of it was sold, how much of it is inbound, where it is in which location.

00:31:19.862 --> 00:31:27.817
That's what an ERP does it gives you the factual information about that item and it tells you what you've got and where it is right.

00:31:27.817 --> 00:31:28.539
So now you know that.

00:31:29.020 --> 00:31:30.113
But how much should you have?

00:31:30.113 --> 00:31:32.260
And that's that's really the trick.

00:31:32.260 --> 00:31:33.384
Should it be 10?

00:31:33.384 --> 00:31:34.509
Should it be 20?

00:31:34.509 --> 00:31:35.392
Should it be 5?

00:31:35.392 --> 00:31:44.260
What's the optimal amount of inventory that you should be holding today to make sure that your customers get what they want and that you're not tying up too much cash?

00:31:44.320 --> 00:31:48.378
And that's really what we calculate for for customers in theP.

00:31:49.060 --> 00:32:12.596
And then what we do is we project that day by day, 365 days, into the future to say, well, this is what you should have today and this is how it compares to what you have in your ERP, and this is what you should have tomorrow and that's how we think it's going to compare to what you will have in your inventory tomorrow, taking the forecast or sales orders that are due or whatever it is into consideration, or inbound purchase orders.

00:32:12.635 --> 00:32:20.021
This is what we think your level is going to be based on what we see in the erp, and this is what it should be tomorrow, the next day, and so on and so on.

00:32:20.021 --> 00:32:52.617
And then we plan against that to say how do we get from where you are to where you should be, and we create a purchase order plan for that, saying well, if you order on this time and we take the lead time into consideration and all your policies and what you want to achieve with the business, this is what you should buy and this is when you should buy it, or this is what you should manufacture, and then this is when you should manufacture it, or even this is what you should distribute to your network at what time, to make sure that that network also has optimal inventory in each of those locations.

00:32:53.582 --> 00:33:14.998
Okay, yeah, so I think that's one of the biggest challenges for SMBs, where they're coming from an ERP, moving to Business Central and everything's brand new to them and, like as you said, a lot of them do all of the forecasting, typically in a spreadsheet or based on emotions or maybe experience.

00:33:14.998 --> 00:33:24.455
Right, how do you manage, for an organization has never had any proper forecasting and remember some of these.

00:33:24.455 --> 00:33:27.780
Sometimes you work with individuals in the organization.

00:33:27.780 --> 00:33:34.579
Where I've been with a company for 20 plus years, I know when or when I should order.

00:33:34.579 --> 00:33:38.018
That's a challenge in itself.

00:33:38.018 --> 00:33:46.720
So how do you navigate around that and consider these data points?

00:33:46.720 --> 00:34:07.919
When we consider these data points, when we calculate forecasting versus, hey, I've been here for 20 plus years, I know I should order 20 of these because it's seasonal or Christmas is coming around, right, so how do you handle those challenges?

00:34:11.829 --> 00:34:11.989
right.

00:34:11.989 --> 00:34:12.150
So what?

00:34:12.150 --> 00:34:12.911
How do you handle those challenges?

00:34:12.911 --> 00:34:15.336
Well, those people in a business either make or break an implementation with us, right?

00:34:15.336 --> 00:34:18.443
I'm sure there's a lot of that in in all implementations.

00:34:19.170 --> 00:34:23.960
But um and you, you touched on it exactly trust.

00:34:23.960 --> 00:34:48.257
Trust the calculations, right, and that's what we need to get to, and it's a process that we need to go through in the onboarding to get those people to understand the calculations and trust the calculations, so that when we spit out a recommended order and say this is what we think you should order today, they can look at that and say I trust that because I understand how the inputs and the calculations work.

00:34:48.257 --> 00:34:53.820
To give me that and it's going to give me a better result than my gut feel.

00:34:53.820 --> 00:35:11.039
We call them the spreadsheet slaves because they have a spreadsheet called master inventory, something, something that only they know how to use probably has more errors than they wish to admit, because it's been around for 10 years.

00:35:11.039 --> 00:35:14.958
That and how they feel about the business.

00:35:16.032 --> 00:35:19.579
And, yeah, it's a process really, and those are the people that we need to convince.

00:35:19.579 --> 00:35:32.657
But I tell you that those people could be your biggest ally and your worst enemy, because once they do understand the calculations and they realize that this is going to do all of that stuff better than what they can.

00:35:32.657 --> 00:35:38.405
You know if they can get past the ego of, like, I know better than the application does.

00:35:38.405 --> 00:35:44.583
But you know, that really is just a process of understanding the calculations and building trust with those people.

00:35:44.583 --> 00:35:49.079
So, yeah, you're right, and we run into those people.

00:35:49.079 --> 00:35:50.708
So, yeah, you're right, uh, and, and we run into those people, uh, a lot.

00:35:50.708 --> 00:36:18.512
I mean, we, we went into a meeting with the guy asked us to sign an nda, uh, before he showed us his spreadsheet, because I've never heard of that before I've come across and and you know I mean we laugh, but he, he spent, you know, years perfecting this, the spreadsheet.

00:36:18.552 --> 00:36:20.315
So it is difficult letting go of that.

00:36:20.315 --> 00:36:22.541
It is difficult, you know, going.

00:36:22.541 --> 00:36:31.869
Hey, you know there's an application out there that might do this better than than I do, even though I've been in this business for so long and I've been building and I've been buying for this business for so long.

00:36:31.989 --> 00:36:35.798
So, yeah, it's a challenge it is, chris hits the good point.

00:36:35.798 --> 00:36:42.059
He was talking about the trust factor of it and, chris, we run across this for eip implementations all the time.

00:36:42.059 --> 00:36:43.882
It's knowledge in someone's head.

00:36:43.882 --> 00:36:45.413
They have a gut feel.

00:36:45.413 --> 00:36:50.403
They don't want to let it go, but they could also be oh, this doesn't work or this doesn't make it.

00:36:50.403 --> 00:37:13.139
But a lot of businesses don't understand the risk of having everything relying on one person or this one person spreadsheet to run a business because, oh, chris understands how to calculate and forecast and we just trust Chris, when Chris could be over ordering, under ordering or even inhibiting growth of the business because of the way that he's doing it.

00:37:13.139 --> 00:37:16.800
Not to pick on you, chris, I'm just using you as an example but it's.

00:37:16.940 --> 00:37:17.061
It's.

00:37:17.061 --> 00:37:21.856
It is a challenge and you had mentioned also, like the letting go, because there is the.

00:37:21.856 --> 00:37:23.320
I created this.

00:37:23.320 --> 00:37:24.603
I do this all the time.

00:37:24.603 --> 00:37:30.311
I know what I'm doing and oh, now that they have another tool, I'm not going to be needed.

00:37:30.311 --> 00:37:47.657
Instead of taking a look back and I can use my time and be a little more valuable with my time or have more value in my time I can't even talk today have a little more value in my time to be able to do other things than just plugging numbers into a spreadsheet.

00:37:47.657 --> 00:37:56.059
I can actually look at a forecast, look at a plan and then review that plan to make sure that it fits with it as well.

00:37:56.059 --> 00:38:01.795
I have a question with forecasts and, chris, I know you have a bunch of them.

00:38:01.795 --> 00:38:02.858
I'll mute myself.

00:38:02.898 --> 00:38:03.701
No, it's all good.

00:38:04.431 --> 00:38:16.324
When calculating forecasts for different types of businesses, is it possible to calculate seasonality and weather into it?

00:38:16.324 --> 00:38:24.282
I've always wondered about that, thinking how weather could impact planning and forecasting, as well as other trends.

00:38:24.282 --> 00:38:31.889
Because just go back to COVID, which never existed at this point, because I think we all forgot about it as we all lived through it for many years.

00:38:31.889 --> 00:38:42.418
But doing a forecast during COVID time or doing forecast versus other times may be different, so is there a way to put in variable factors?

00:38:42.418 --> 00:38:46.878
And then also wintertime the shipping may take longer than during the summertime.

00:38:46.878 --> 00:38:55.018
I'm just trying to throw out some ideas and I've always had these questions, as if there was a way that that gets accounted for in a forecast.

00:38:55.760 --> 00:39:15.144
Yeah, you know, it's things that we've been discussing and wanting to do, for, you know, discussing for as long as I remember about forecasting is how do we get the forecast more accurate and how do we look at other factors that might influence the forecast outside of the internal information and things that we have.

00:39:15.144 --> 00:39:25.264
And you know, I think the way that AI is going at the moment, that's going to be the next step.

00:39:25.664 --> 00:39:28.617
Right, I wanted an episode without that being mentioned.

00:39:29.018 --> 00:39:31.434
I guess we can't do it.

00:39:31.454 --> 00:39:36.809
No, it's okay, I was going to say at the end is this is the nose most non-ai episode.

00:39:37.351 --> 00:39:40.016
Well, well, look at it this way let's not, let's not bring ai in.

00:39:40.016 --> 00:39:42.322
How do we take uh?

00:39:42.402 --> 00:39:43.831
you can't, by the way, I was joking.

00:39:44.311 --> 00:39:51.403
How do we take information from sources outside of the ERP, which is what we rely on and market knowledge?

00:39:51.403 --> 00:40:14.184
Because obviously we allow the customer to override forecasts or input promotions and we have these smoothing algorithms in the forecast to try and get the best fit forecast or the most accurate forecast we possibly can right, because forecasting is not an exact science.

00:40:14.184 --> 00:40:16.090
It never has been, probably never will be.

00:40:16.090 --> 00:40:19.099
So what other factors might influence that forecast?

00:40:19.099 --> 00:40:27.293
And that seasonality that you're talking about is actually something that we've, you know, not struggled with, but it's been challenges that we've had with some customers as well.

00:40:27.293 --> 00:40:41.677
So, for instance, a customer that sells seed and the rains start a month earlier and suddenly the seasonality is moved from one month to the next, and how do you adjust for it?

00:40:41.677 --> 00:40:59.916
Now, there are ways that we can adjust that in the forecasting engine, but it's a manual intervention, usually from the customer understanding their market, understanding what effect that weather has on them, and they can make adjustments pretty easily in the forecasting engine.

00:40:59.916 --> 00:41:08.338
But can we get to a point where we can read other data and then use that data to predict?

00:41:08.338 --> 00:41:27.697
Because this really gets to a point where we start predicting more rather than relying on on market knowledge to be able to do that, and that's really, for me, the exciting part of being able to to, not only because the the challenge with that again is now what data do you use, right, right.

00:41:28.318 --> 00:41:36.737
So I think with AI, the nice thing about that is that you can test different data sets and also with machine learning and the way that AI is going.

00:41:36.737 --> 00:41:40.436
Now you know there's more probability and you can see.

00:41:40.436 --> 00:41:48.503
You can then track those forecasts and see how well the forecast is doing against your sales.

00:41:48.503 --> 00:41:51.456
But yeah, it's not something that.

00:41:51.456 --> 00:41:58.257
It's something that we've been discussing for a long time and I'm quite excited about being able to get that into the forecasting.

00:41:58.257 --> 00:42:05.541
But yeah, it's still a long road to go, because you know what information is actually valuable.

00:42:05.541 --> 00:42:10.077
What's the right data for your business, is the right information to be looking at?

00:42:10.077 --> 00:42:17.101
I mean, weather's quite an interesting one, probably a good example of where we can get the most value out pretty quickly.

00:42:19.110 --> 00:42:22.797
But you know, weather forecast is as reliable, right yeah?

00:42:22.976 --> 00:42:23.197
yeah.

00:42:27.250 --> 00:42:33.396
The other thing that comes to mind right now is all the tariffs, so all the discussion of tariffs across the market.

00:42:33.396 --> 00:42:43.876
We're getting a little bit of conversations in our sales cycle just about maybe like let's look at this in a couple of months, once some of the conversations around tariffs tariffs have settled.

00:42:43.876 --> 00:43:02.623
So one thing that this is again a little marketing plug we're doing a webinar about tariffs and how our AI tool can kind of help you adjust quickly, whether it's, you know, in the moment of a big crazy change or you know, managing the manual side of it now.

00:43:02.623 --> 00:43:14.706
Um, but our CTO and one of our customers are doing just his use case on some of the seasonality and flow and change of how he's used our AI tools on March 27th.

00:43:14.706 --> 00:43:16.818
So if anybody's interested, it's on the website.

00:43:16.818 --> 00:43:26.802
But that's a good like conversation that we're starting to have more and more openly about some of those additional prediction data sets that we could use.

00:43:27.503 --> 00:43:27.684
Yeah.

00:43:28.251 --> 00:43:29.014
So you could have to meet.

00:43:29.014 --> 00:43:33.556
Go ahead ben I'll stop after this.

00:43:33.697 --> 00:43:41.679
I promise so you can have variable suppliers to take into some of those considerations such as tariffs from the again.

00:43:41.679 --> 00:43:50.684
Nobody knows what will happen, but just say there's tariffs, the variable rates across different regions or even limitations on shipping from different regions.

00:43:50.684 --> 00:43:52.951
I think of when ports close.

00:43:52.951 --> 00:44:03.856
The port gets backed up to be able to demand or forecast or predict or plan for other suppliers who may come in from different channels, so that you can keep up with your demand from your customer.

00:44:05.336 --> 00:44:08.657
Yeah, yeah, Just like for forecasting in itself.

00:44:08.657 --> 00:44:14.021
I've done a lot of forecasting tool implementation in my career.

00:44:14.021 --> 00:44:28.567
What I always find challenging is that forecasting, depending on the data points that you get, you're very, very limited and it's always very difficult to get 100% accuracy.

00:44:28.567 --> 00:44:30.708
You can get there fairly close.

00:44:30.708 --> 00:44:41.998
Do you find in the near future if the data is available for your application to use when you're forecasting?

00:44:41.998 --> 00:44:44.244
Do you find that it'll improve eventually?

00:44:44.244 --> 00:45:14.836
You know again and I've been implementing ERP for roughly, roughly two decades, almost two decades here and that's always been a challenge for me of trying to not only convince users to trust the data because they know it's like, oh, it's just based on my history, but it doesn't consider all the other data points, and some of those data points or data sources that they get to help calculate this also may not be accurate as well.

00:45:14.836 --> 00:45:18.521
Like you said, weather forecast is never always accurate.

00:45:18.521 --> 00:45:29.362
Do you find that that eventually will change, as long as data sources are made available for it to consider?

00:45:31.050 --> 00:45:31.795
Yeah, I think so.

00:45:31.795 --> 00:45:34.259
I mean, I think forecasting will improve.

00:45:34.259 --> 00:45:39.681
How much it will improve is kind of left to be seen.

00:45:39.681 --> 00:45:44.822
But I think you know there's so much more to consider.

00:45:44.822 --> 00:45:50.496
Like forecasting has never been, you know, 100% accurate ever and I don't think it's ever going to be.

00:45:51.297 --> 00:45:54.123
It's what you do with that forecast and how you manage that.

00:45:54.123 --> 00:45:59.380
Are we managing the forecast errors?

00:45:59.380 --> 00:46:24.273
Are we looking at that and saying in the application, what we do is we look at the average error over a period of time and we look at things like whether that error is over forecasting or under forecasting and then we use that in a calculation to allocate a risk to the forecast, because there's a lot more things that affect that forecast.

00:46:24.273 --> 00:46:33.126
It might be an erratic sales item, it might not be seasonal, you know, or it might be seasonal but there's not enough information to see the seasonality.

00:46:33.126 --> 00:46:43.083
There's all these things that could help make that forecast better, but it's in being able to understand how risky it is to forecast that item.

00:46:43.083 --> 00:46:48.567
And then what we do is take that risk and we use that risk to calculate optimal safety stock.

00:46:48.567 --> 00:46:53.161
So if we see that you're over forecasting and that means you're probably buying more than what you.

00:46:53.161 --> 00:46:58.353
You know we're doing as well as we came with the forecasting, but we're still over forecasting and buying more than what we should.

00:46:58.353 --> 00:47:02.331
We're probably holding more inventory than we should be, than we need to.

00:47:02.331 --> 00:47:08.221
We're probably not going to stock out, so we automatically decrease your safety stock calculation based on that.

00:47:08.221 --> 00:47:11.085
So we look at inbound and outbound risk all the time.

00:47:11.085 --> 00:47:15.561
So forecasting is just one part of it to get to that optimal inventory level.

00:47:15.561 --> 00:47:18.719
Yes, we want the forecast to be as accurate as possible.

00:47:18.719 --> 00:47:24.389
We work really hard at getting our forecasting engine and all the settings to make it as accurate as possible, but we know it's never going to be 100%.

00:47:24.389 --> 00:47:29.139
So now we take the error and we say what's the risk of us getting this right?

00:47:30.041 --> 00:47:31.552
And based on that, what?

00:47:31.552 --> 00:47:35.688
How much do we need to up the safety stock or or drop the safety stock?

00:47:35.688 --> 00:47:38.996
So if we're under forecasting, we're going to be a risk of stocking out.

00:47:38.996 --> 00:47:41.653
We increase the safety stock to try and overcome that risk.

00:47:41.653 --> 00:47:43.742
And then the same with your supply risk.

00:47:43.762 --> 00:47:45.971
So we look at your purchase order history.

00:47:45.971 --> 00:47:51.311
We say, okay, you know, on average, um, you know, we look at all the purchase order history.

00:47:51.311 --> 00:48:02.153
We do some calculations to see if they're like blanket orders and, uh, you know, orders that are completely out of scope and a whole bunch of stuff to to get that as, as you know, accurate as you possibly can.

00:48:02.153 --> 00:48:05.862
And then we look at your, your average lead time to get an item.

00:48:05.862 --> 00:48:12.523
So, yes, you know we're going to get this item in three weeks, but on average we can see with the purchase order history that it's coming in four weeks.

00:48:12.523 --> 00:48:16.101
So you're at risk for late delivery on average by a week.

00:48:16.101 --> 00:48:18.751
We'll increase the safety stock based on that risk.

00:48:18.751 --> 00:48:29.722
So we're not fixing the problem with the supplier and maybe that's up to the customer to go now speak to the supplier and say, hey, is this lead time supposed to be four weeks?

00:48:29.722 --> 00:48:32.456
Should I go to another supplier and manage that supply risk?

00:48:32.456 --> 00:48:34.614
And the same on the forecast.

00:48:34.655 --> 00:48:35.639
Can we better forecast?

00:48:35.639 --> 00:48:41.956
Do you know something about this item that you can input on market knowledge or, like you said, weather or that type of stuff to try and get this more accurate?

00:48:41.956 --> 00:48:59.007
But getting a forecast one percentage more accurate than it was I don revolutionary in the planning kind of realm.

00:48:59.007 --> 00:49:09.295
It's what you do with information and how you get to a point where you're calculating optimal stock levels, you know, and making sure that they don't stock out and making sure that they don't, you know.

00:49:09.295 --> 00:49:10.521
The other thing is classification.

00:49:10.521 --> 00:49:13.744
So now you've got an item and you know you it's a.

00:49:14.775 --> 00:49:21.447
You're really struggling with the forecast, but it's a low volume, low value item that's not really contributing much to the business.

00:49:21.447 --> 00:49:32.376
How much time do you want to spend getting that absolutely accurate right, Whereas if it's one of the most important items in your business that's running your business you want to be investing your time and your money there to make sure you get that right.

00:49:32.376 --> 00:49:38.146
So you know there's so many sort of aspects to getting to that point, not just the forecast.

00:49:38.146 --> 00:49:48.384
The forecast is just the initial input and, yes, the more accurate the forecast, the better the planning is going to be, because the better we can plan again, If we know what we're going to be selling, obviously we can plan better.

00:49:48.384 --> 00:49:55.487
But there are things that we do to kind of mitigate the risks of that forecast not being 100%.

00:49:56.579 --> 00:50:07.628
Yeah, those are great points and I appreciate you sharing that, because it's always been a struggle, even with my conversation with clients, where they're asking you know, how can I trust this is going to be 100% accurate?

00:50:07.628 --> 00:50:10.061
And I'm like, well, I can't really tell you.

00:50:10.061 --> 00:50:11.306
It's going to be 100% accurate.

00:50:11.306 --> 00:50:13.295
It'll get you really really close right.

00:50:13.295 --> 00:50:22.329
It gets you where you can just decide what you want to do without you having to do all the manual work, all the forecasting.

00:50:22.329 --> 00:50:23.476
This tool will do that for you.

00:50:23.476 --> 00:50:50.228
Which kind of leads me to the next question that you need to have a proper calculation of forecasting, and how long of a history do you need us to get you the most out of it?

00:50:52.757 --> 00:50:56.887
I would say three years would probably be optimal.

00:50:56.887 --> 00:51:03.465
Three years would probably be optimal, you know, because if there is seasonality over we could 24 months.

00:51:03.465 --> 00:51:05.175
We could get seasonality because obviously we can see year on year what's going on.

00:51:05.175 --> 00:51:11.585
With three years we've got some really solid seasonality because we now have checked over three years where how seasonal that really is right.

00:51:11.585 --> 00:51:13.614
So I would say three years would be optimal.

00:51:13.614 --> 00:51:15.679
Um, but we do.

00:51:16.061 --> 00:51:18.867
You know, our forecasting engine takes into consideration new items.

00:51:18.867 --> 00:51:23.306
So if they've just come in and you've input a forecast, we treat those items differently.

00:51:23.306 --> 00:51:29.038
We treat items, young items that have, you know, been around for maybe three or four months differently.

00:51:29.038 --> 00:51:31.826
So the forecasting engine takes those things into consideration.

00:51:31.826 --> 00:51:33.898
We can also do things like supersede.

00:51:33.898 --> 00:51:44.027
So if you have replacement items, we supersede historical data from one item onto the new item and it will use that historical data to create a forecast for the new item.

00:51:44.027 --> 00:51:47.059
We can do group seasonal forecasting.

00:51:47.059 --> 00:51:58.242
So if you have some items that have been around for two years and you add a new item to that group, it can use the seasonal trend of that group to predict what the seasonality is going to be for that item.

00:51:58.262 --> 00:52:01.708
So there's tricks that we have in the forecasting engine.

00:52:01.708 --> 00:52:02.769
That will look at that.

00:52:02.769 --> 00:52:10.148
But yeah, if it's a seasonal business, we'd need at least two years to find that seasonal pattern.

00:52:10.148 --> 00:52:15.045
Otherwise, you know, we could start with three months worth of historical data.

00:52:15.045 --> 00:52:18.784
Also, we can import data.

00:52:18.784 --> 00:52:38.425
So if that data is sitting in a spreadsheet somewhere or if it's in your previous ERP, like I said, we probably have a connector or we could probably take that information it's just sales by month, really information into a spreadsheet and we can upload that to NetStock and we've got the information to run the forecasting engine.

00:52:38.425 --> 00:52:49.416
The only things that you'd be missing there are things like your purchase orders, historical purchase orders for the for the um supply performance, uh calculations and things like that.

00:52:49.416 --> 00:52:56.199
But we could start off with just um sales information out of a, out of a spreadsheet no, that's wonderful.

00:52:56.219 --> 00:53:21.246
So you can add additional historical information for, especially for new items, maybe it's substitute or maybe a variant that's no longer available, because one of the common things that I see too are when someone implements or migrate to business central, they have different item numbers for different colors, when in reality in business central those are sort of variants or versions of the same product.00:53:21.246 --> 00:53:25.400


So it sounds like you're able to calculate those as well, or at least combine them.00:53:25.400 --> 00:53:28.184


So, which kind of leads me to my next question.00:53:28.184 --> 00:53:45.940


So how long does it take for an organization to fully trust the application that's going to forecast for you, so that people like Sam can go on vacation right, be sitting at the beach and say, yeah, it's going to forecast for you, so that people like Sam can go on vacation right, be sitting on the beach and say, ah, it's going to work, I trust that it's forecasting properly, I have orders coming in.00:53:48.416 --> 00:53:50.222


Sam, did you do anything while you were on the beach?00:53:50.222 --> 00:53:52.081


Did you log into NetStock?00:53:54.077 --> 00:53:55.623


I did not do a single thing.00:53:55.623 --> 00:53:59.125


I had my phone in my car most of the time.00:54:01.115 --> 00:54:04.465


I told her not to check Slack while she was on holiday on the beach.00:54:04.465 --> 00:54:05.047


I did.00:54:05.047 --> 00:54:09.061


Yeah, it's a bit of a how long.00:54:09.061 --> 00:54:11.027


You know we speak about implementations.00:54:11.027 --> 00:54:22.481


On average, we'd say probably like 14 to 16 weeks, you know, maybe a couple hours a week to get there, so it's not like a full-time job.00:54:22.481 --> 00:54:23.619


You could do it really quickly.00:54:23.619 --> 00:54:32.927


We've had, you know, people get into it and small businesses that we're really eager to go and, you know, do it in like a month.00:54:32.927 --> 00:54:52.251


But it really depends again on things like data, the people that you're working with and how well they can adapt to change and how eager they are to embrace technology to kind of fix the things or do the things that they were doing manually.00:54:52.251 --> 00:54:58.847


But yeah, that's kind of like our average is around 12 to 16 weeks.00:54:59.396 --> 00:55:00.541


Of course, it's an ongoing thing.00:55:00.541 --> 00:55:23.097


We've got a learning academy built into the application, because one of the things that we wanted to do with, as I said with NetStock when we started with those small businesses, is we wanted to educate them on inventory methodology methodology, right.00:55:23.097 --> 00:55:29.590


So built into the application, apart from having tutorial videos and blogs and, and you know, tours and things in the application, and also we've got in-app support through a chat.00:55:29.590 --> 00:55:43.623


There's the learning paths that you can go on to understand more about inventory planning and you can even certify as a net stock inventory specialist through our learning academy.00:55:43.623 --> 00:55:46.664


So it's really about ongoing.00:55:47.856 --> 00:55:50.324


We want our customers to get better and better at what they do.00:55:51.882 --> 00:55:57.065


We're one of those businesses where we're quite lucky because the ROI is in your face every single day.00:55:57.065 --> 00:56:08.541


Every single day, we're telling you where your inventory is, how much of it is tied up, how much of your cash is tied up, what your service levels are, where you're stocking out, where you're holding too much excess.00:56:08.541 --> 00:56:09.706


Every single day.00:56:09.706 --> 00:56:14.003


So if you see an improvement on those dashboards, you can see straight away what the ROI is.00:56:14.003 --> 00:56:22.389


So it's kind of in your face and we want people to get better and better and improve their inventory planning, you know, so that they can they sort of become.00:56:22.389 --> 00:56:29.251


We want those spreadsheet slaves to kind of become the heroes of inventory management in their business.00:56:29.251 --> 00:56:36.920


You know, by using the tool rather than you know the spreadsheet that they've been working on for you know so many years and kind of trust.00:56:36.920 --> 00:56:48.362


Um, you know so I wouldn't say blindly, but but have so much faith and and trust that right and that, yeah, we try to achieve a lot of people don't realize that.00:56:48.643 --> 00:57:07.432


uh, especially for organizations where they have high volume of inventory or high moving inventory, where a lot of their cash really is held up in inventory, and so if they don't get a handle of that, that becomes detrimental, because all it takes is for one bad season.00:57:07.432 --> 00:57:11.646


Now you have all this inventory sitting there not knowing what to do with it.00:57:13.635 --> 00:57:23.250


So we actually we did and we've been looking at ways that we because we have we've got about 2,500 customers worldwide.00:57:23.250 --> 00:57:26.963


There's always been this discussion about what could we do with.00:57:26.963 --> 00:57:38.769


You know, we have a lot of data from small, medium-sized businesses and what can we do with this data to help our customers or gain insights on, you know what they're doing and how they should be doing it.00:57:38.769 --> 00:57:49.987


So last year, for the first time and we're gonna be doing this every year we released a benchmark report where we went and anonymized all the information.00:57:49.987 --> 00:57:57.565


We did some interviews with, like, I think, 300 customers, a whole bunch of information that came out in that benchmark report.00:57:57.565 --> 00:58:07.923


One of the things that came out in that was that around was it 38, I stand corrected I think it was 38% of small, medium-sized business.00:58:07.923 --> 00:58:10.889


38% of their inventory was excess.00:58:11.894 --> 00:58:17.387


If you think that you could A lot of cash, yeah, you could take that's a lot of cash, that's a lot.00:58:17.387 --> 00:58:33.257


And the bigger the business has got, the worse it got, so at the more kind of like, uh, enterprise levels, it was as much as 42 percent, right, and if you think about the cost of cash now, which never used to be an issue, but now it's a pretty big issue, right?00:58:33.257 --> 00:58:40.608


Um, and warehouse space, labor, all all of the costs that go into holding too much inventory.00:58:40.608 --> 00:58:41.570


It's a big problem.00:58:41.570 --> 00:58:52.043


Even though they've been better at and we've seen that they've actually been better at managing inventory and managing the demand side of things, there's still 38% excess.00:58:52.043 --> 00:59:10.206


Now that alone, if we could take 10% out of that 38%, if we take 10% of your that 30%, 38%, right, if we take 10% of your inventory and reduce your inventory by 10%, I mean you'd be the hero of your business for sure, like your financial director would just absolutely love you, right?00:59:10.206 --> 00:59:11.820


And that's kind of what we're trying to do.00:59:11.820 --> 00:59:18.766


We're trying to get those planners to be able to do those type of things in their business, really make a difference, really.00:59:19.114 --> 00:59:24.081


Because, you know, we were a small, we were a tech startup, we were a small and medium-sized business.00:59:24.081 --> 00:59:25.420


We understood those businesses.00:59:25.420 --> 00:59:39.543


We were also all trying to do everything we could with very limited resources, right, and you know, look where we've gone, you know, and we want to be able to support those small, medium-sized businesses to do that as well.00:59:39.543 --> 00:59:40.907


And how are they going to grow?00:59:40.907 --> 00:59:44.943


They're going to grow and inventory is the biggest thing in an inventory business.00:59:44.943 --> 00:59:48.012


Right, that is your like.00:59:48.012 --> 00:59:54.628


They say it's either your asset or or uh, it's a liability and depending on how you manage it right.00:59:54.628 --> 00:59:59.320


So is it an asset or is it a liability, but it is the biggest, biggest part of your business.00:59:59.320 --> 00:59:59.875


You need to, you need to manage it right.00:59:59.875 --> 01:00:00.880


So is it an asset, or is it a liability, but it is the biggest part of your business.01:00:00.880 --> 01:00:03.443


You need to manage it as well as you possibly can.01:00:03.463 --> 01:00:04.065


That's important.01:00:04.065 --> 01:00:10.403


The cost of inventory sitting on the shelf is expensive and it's not only because of the cost of the product, but it's also the shelf space.01:00:10.403 --> 01:00:17.577


A lot of individuals don't realize that, if you can again, as everyone had alluded to or mentioned forecasting is not 100%.01:00:17.577 --> 01:00:25.650


If forecasting it's not, even just with inventory forecasting anything Chris talked about the weather you can forecast anything that's not accurate.01:00:25.650 --> 01:00:49.130


It can't be 100% accurate because there's always external view, which is important to take into consideration as well as having dead inventory or inventory that's not turning.01:00:49.731 --> 01:00:49.932


Yeah.01:00:50.956 --> 01:00:51.579


That's extremely important.01:00:51.994 --> 01:00:54.083


Sam, how do you market all of that?01:00:54.083 --> 01:01:07.496


How do you convince your new buyers of why they need as young entrepreneurs they're running businesses to use an application like this where you know well, you know, you know how that goes right.01:01:07.496 --> 01:01:13.077


They could research themselves like I can use this tool yep, yep, I think it's interesting.01:01:13.177 --> 01:01:15.851


So I actually don't sit on the marketing team.01:01:15.851 --> 01:01:17.978


A lot of people don't realize that it's new for me.01:01:17.978 --> 01:01:24.534


I sit under, so we have a whole marketing team that focuses on most of those challenges.01:01:24.534 --> 01:01:52.427


But I think that the sweet spot for me is making sure that most of our content out in the ether is very self-service driven and very like millennial, focused and ready, because we're seeing a big shift in our target buyer, just like everybody, where our buying committee is becoming younger and younger and we have less of those people that are I've been doing this 20 years and it's in my head.01:01:52.655 --> 01:02:03.860


Therefore, I'm good you have this like new, young blood coming in and saying I don't want to spend my vacation looking at my demand plan, so I need a tool like this so that my life is easier, right?01:02:03.860 --> 01:02:14.268


So those are the conversations we're starting to have on, like how do we shift our go to market for that more driven focus and less of the?01:02:14.268 --> 01:02:25.896


We've been on GP for, you know, 30 years and now we're looking to move to business central, but Bob doesn't want to change his mind about his spreadsheet because he's going to retire on the spreadsheet.01:02:25.896 --> 01:02:28.864


Right, he's ready to retire in a year.01:02:28.864 --> 01:02:38.262


He's just buying time, but you're getting that new person come in, regardless of age, regardless of whatever, with that change management spirit.01:02:38.724 --> 01:02:57.739


So we're seeing a lot of that shift, which is the highlight of my marketing career for sure it's a big shift and it's important to realize that, generationally, the generation that grew up with the cell phones, that grew up with the internet, that grew up with the searching, is now the ones that are primarily making decisions.01:02:58.320 --> 01:03:01.382


I say primarily there's different businesses at different stages.01:03:02.778 --> 01:03:03.943


Every business is different.01:03:03.943 --> 01:03:07.079


So it is a challenge not to turn it into marketing from a marketing point of view.01:03:07.079 --> 01:03:20.268


To go back to Bob, like you said, who has that spreadsheet, who is like me, who remembers the cell phone being invented, who remembers the Netscape and Internet Explorer war of a browser where everybody else just grows up?01:03:20.268 --> 01:03:30.065


And now, well, now, if children are being born and they come out with cell phones in their hands, so it's, it's a big change and a big shift.01:03:30.065 --> 01:03:46.708


Look at the challenges of not progressing with the technology and how they may be holding themselves back because they're afraid or they don't know or don't understand and may not trust.01:03:46.708 --> 01:03:48.679


I think you said who'd you say Bob?01:03:49.139 --> 01:03:50.202


Bob, I named you Bob.01:03:50.623 --> 01:03:56.079


I don't know who you said but all the Bobs in the world listening to this right now, they probably like that's me.01:03:56.581 --> 01:03:58.382


I'm gonna retire my spreadsheet.01:03:58.882 --> 01:04:18.262


I've been in businesses before where we're so focused on talking about bringing the person from gp into the bc world, and I think the shift that I'm really focused on and something we're doing at netstock is we're actually not really trying to sell to.01:04:18.262 --> 01:04:21.143


Focused on and something we're doing at NetStock is we're actually not really trying to sell to that person right now.01:04:21.143 --> 01:04:30.115


We're happy if they come to us, but that sales cycle is a lot harder than someone who is coming in trying to make change in their business as a newcomer.01:04:30.115 --> 01:04:37.445


Right, that, like entrepreneurial spirit that Vaughn talked about with kind of our culture, plays into how we sell as well.01:04:37.445 --> 01:04:43.923


We're looking for the similar spirit in our customer profile as we are ourselves.01:04:43.923 --> 01:05:02.340


Right, I'm like it's a lot easier to sell optimization and forecasting and that you know, trust the system and train the system to someone who's ready for that instead of someone who's like I like my basic stuff, I like it the way it is.01:05:02.340 --> 01:05:04.061


This is easy, right?01:05:04.061 --> 01:05:07.786


So that's what I see from a shift for us.01:05:08.295 --> 01:05:15.804


I have a saying for that as well, because those sales are difficult and they're challenging and your probability of success go down.01:05:15.804 --> 01:05:21.764


But I say to everybody, sometimes no business is better than bad business.01:05:21.764 --> 01:05:41.846


Agreed, Because that is something that I learned very early on in my career that sometimes walking away from those types of deals now that we're shifting from I don't mean to shift from the demand planning point of view, but it's important to realize that sometimes walking away from a deal or a transaction, it doesn't even have to be ERP implementation, it can be anything.01:05:41.846 --> 01:05:43.675


It could be cutting someone's lawn, for example.01:05:43.675 --> 01:06:02.125


If it's a challenging task or a challenging deal, it's better to walk away than have it go sour or have issues or contention issues or challenges, Because the other thing that follows up with that a happy customer tells one person, an unhappy customer tells 10.01:06:03.166 --> 01:06:03.648


The internet.01:06:03.648 --> 01:06:04.548


They tell the internet.01:06:04.548 --> 01:06:06.110


Yes, that's a good one.01:06:06.110 --> 01:06:08.295


All of the self-service people like me Listen.01:06:08.697 --> 01:06:13.432


I heard that saying, or I had that saying, long before the internet, by the way.01:06:13.432 --> 01:06:13.673


Oh, wow.01:06:14.476 --> 01:06:15.197


This was back when.01:06:15.217 --> 01:06:19.027


Young Brad started out when we used to literally have to put stuff on a cd.01:06:19.027 --> 01:06:22.063


I'm not even going to tell you I'm dating.01:06:22.063 --> 01:06:23.467


We used to use floppy disks.01:06:23.467 --> 01:06:50.706


I remember when we used to install the vision on a floppy disk wow, so but it's, it goes it goes to the point that, like you just said, sam, it's that's where I take all that into consideration, because happy people just are happy, and miserable people want everyone else to hear and share their misery, so everyone should also take that into consideration when they see some of this stuff.01:06:51.195 --> 01:06:57.630


I just want to say that that version that you installed with the floppy disk, we probably don't support that version, unless you have the spiritual datapy disk.01:06:57.650 --> 01:07:01.443


We probably don't support that version, unless you have the critical data in there that we could control.01:07:03.918 --> 01:07:12.755


I'm almost certain the data has changed since then, If somebody's still running that you probably don't want to work with them anymore.01:07:12.795 --> 01:07:14.121


Yeah, you don't want to be in business.01:07:15.335 --> 01:07:16.681


They're not on our list of target.01:07:16.681 --> 01:07:18.342


That's definitely not, actually, which leads me to a question that Brad had mentioned about in business.01:07:18.342 --> 01:07:18.664


They're not on our list of target.01:07:18.664 --> 01:07:18.860


That's definitely not.01:07:18.791 --> 01:07:31.027


Definitely not, actually, which leads me to a question that Brad had mentioned about, you know, happy and unhappy in users that are using the product where you're providing them.01:07:31.027 --> 01:07:34.300


Here's the forecast, here's what we think it's going to.01:07:34.300 --> 01:07:36.166


What you need for your inventory.01:07:36.166 --> 01:07:40.221


You should start ordering these to make it on time or to get here on time.01:07:40.221 --> 01:07:49.403


Do you find and I don't know if you have this data do you find that people tend to make changes to what you've given them?01:07:49.403 --> 01:07:56.679


Like what is the percentage of users changing the data because they I don't trust it.01:07:56.679 --> 01:07:57.664


I'm going to change it.01:07:57.664 --> 01:07:58.309


Maybe a couple here.01:07:58.309 --> 01:07:58.954


There's a few percentage here versus we're like don't trust it, I'm going to change it.01:07:58.954 --> 01:07:58.931


Maybe a couple here.01:07:58.931 --> 01:08:02.264


There's a few percentage here versus we're like I trust it.01:08:02.264 --> 01:08:04.900


I'm just going to go ahead and release those purchase orders.01:08:06.704 --> 01:08:09.400


Yeah, so we, we track that in the application as well.01:08:09.400 --> 01:08:15.760


Just to make it worse, on our executive dashboard the executives can see, you know, how many orders are being placed.01:08:15.760 --> 01:08:20.708


So for us those are markers of success with implementation, with the customer.01:08:20.708 --> 01:08:31.203


If they're downloading our recommended orders as they are and making very few changes to those recommended orders, then we know that that's successful.01:08:31.203 --> 01:08:44.966


If we see that they stop downloading orders, which means they're creating orders themselves in the ERP or they're changing orders quite a lot before they send it through to the ERP, then there's a problem.01:08:44.966 --> 01:08:48.003


You know, we always say there are three things.01:08:48.003 --> 01:08:55.090


It's not the order that needs to be changed, it's either the forecast or the policies or the data.01:08:55.090 --> 01:09:02.798


Right, and if those things are managed properly, properly, then you're going to get a really good recommended order.01:09:02.798 --> 01:09:05.836


Right, because we're going to take everything into consideration and calculate.01:09:05.836 --> 01:09:06.457


That's what we do.01:09:06.457 --> 01:09:08.362


Right, we calculate an optimal order.01:09:08.362 --> 01:09:15.654


But if those three things aren't in place, like if we're not managing, so you know we're looking with all those risk calculations and everything.01:09:15.675 --> 01:09:26.190


We're still also on the dashboards bringing up all the top over and under forecast items, you know, so that they can see those things and say you know, is there something that can you intervene?01:09:26.190 --> 01:09:31.067


Is there something that you know about this item or about the market that we cannot see with all the information that we have?01:09:31.067 --> 01:09:32.195


And can you intervene?01:09:32.195 --> 01:09:44.016


Right these exception lists everywhere in the application, because we're always trying to, again with these small and medium-sized businesses, trying to make them as effective as possible in as little time as possible, right?01:09:44.016 --> 01:09:46.865


So where are the top problems that you need to deal with with your forecast?01:09:46.865 --> 01:10:00.944


You know, make sure your policies are set up and we've got a data purity dashboard that tells you, you know, these items aren't connected to a supplier, these purchase orders are overdue from two years ago, or sales orders are overdue from two years ago.01:10:00.944 --> 01:10:02.761


Clean the data.01:10:02.761 --> 01:10:07.742


So we're constantly looking at those things and if you manage those things, it's just a calculator in the end.01:10:07.742 --> 01:10:12.143


Right, it's going to take all of that information and it's going to spit out an answer, like a calculator does.01:10:12.143 --> 01:10:20.484


But if the inputs aren't right and the settings aren't right, it's not going to give you as accurate an answer, and that's really what you have to manage.01:10:20.484 --> 01:10:25.945


But you know, again, this is the process of teaching people to trust the application.01:10:25.945 --> 01:10:26.868


The nice thing about it is.01:10:26.868 --> 01:10:37.319


You know it's so visual that you could go down step by step and see every single part of the calculation and how we got there and why it's doing this and you this.01:10:37.319 --> 01:10:40.587


So it starts becoming so easy to interact with the application.01:10:41.234 --> 01:10:46.686


If there's something that's wrong on the purchase order, go into the item and have a look at that item.01:10:46.686 --> 01:10:53.621


We've now got AI capability that actually when you go into the item you hit analyze and it'll give you a whole breakdown of that item.01:10:53.621 --> 01:10:59.988


It'll basically analyze that item and come back and say to you this item is overstocked.01:10:59.988 --> 01:11:07.106


You have two purchase orders on the way that's going to increase that overstock.01:11:07.106 --> 01:11:09.020


Can you cancel those orders?01:11:09.020 --> 01:11:11.990


Or this item is going to stock out in two weeks' time.01:11:11.990 --> 01:11:15.078


You've got a delivery due for three weeks.01:11:15.078 --> 01:11:21.984


So you've got a week that you're potentially going to be out of stock and because of that you might lose X amount of sales.01:11:22.435 --> 01:11:35.481


This is a really important item in your business so you might want to expedite the order or even buy from another supplier source locally to mitigate that risk of that stock out right or the potential stock out in the future.01:11:36.296 --> 01:11:41.028


So it gives you the ability to very quickly get to the problem areas.01:11:41.028 --> 01:11:55.485


We even have with the AI Assistant and Opportunity Engine, which now goes and looks for the biggest problems in the business and then puts them on a dashboard for you and says, hey, these are the 15 biggest problems we see in your business today.01:11:55.485 --> 01:12:00.038


Can you, you know, go deal with five of those biggest problems we see in your business today?01:12:00.038 --> 01:12:01.101


Can you, you know, go deal with five of those?01:12:01.101 --> 01:12:25.945


And you know, it's about these incremental things that we do to to better the business so that again, eventually, your inventory reduces to to what that optimal, as close to that optimal level as possible, and at the same time, we increase the availability to make sure in the stock turns, to make sure that you're turning that cash faster and that you're servicing your customers with the items that they actually want to buy and not tying up your cash in items that are not important to the business.01:12:26.676 --> 01:12:30.047


This is why you're the doctor I have one more question for you.01:12:31.051 --> 01:12:34.042


I don't know if this comes into play, but I've worked on implementations.01:12:34.042 --> 01:12:35.246


I was thinking you're talking about the orders.01:12:35.246 --> 01:12:46.015


I've dealt with individuals that had orders 10, 15 years old and they tried to use it to manage customer forecasts.01:12:46.015 --> 01:12:48.201


I've worked with several implementations that receive forecasts.01:12:48.201 --> 01:12:53.359


Everyone's talking about forecasting here, so we're forecasting our product, but also our customers may also have a forecast that they send to us so that we can.01:12:53.359 --> 01:13:04.970


If it's a manufacturer or a supplier, a wholesaler that's selling to a retailer, for example, oftentimes retailers will send forecasts for their seasons to make sure that they have enough inventory so that they can sell to their customers.01:13:04.970 --> 01:13:11.127


Where would the customer forecast reside in the forecast process?01:13:11.127 --> 01:13:14.143


Does it reside in the ERP system or is it something that you would put in NetStock?01:13:14.685 --> 01:13:18.724


We put it in NetStock, so we have tools to collaborate.01:13:18.724 --> 01:13:35.068


So you know, whether it's customers, whether it's product owners, whether it's salespeople for different regions, they're able to input their forecasts and we're able to plan against that.01:13:35.068 --> 01:13:43.404


So you know, it could be budgets, it could be anything, any forecast that you want to import, and we can have that all on the same screen and the planners can then work.01:13:43.404 --> 01:13:48.327


This is where this S&OP kind of integrated business planning and all that type of stuff comes in.01:13:48.327 --> 01:13:49.976


This kind of takes it to the next level.01:13:49.976 --> 01:13:52.340


Now, where finance is going.01:13:52.340 --> 01:14:13.283


Oh, you know, we need to increase our top line by X amount or margins or whatever it is, and then input all of this information, marketing information, customer forecasts that are coming in, and then decide on a consensus forecast at the end Based on all of these forecasts.01:14:13.283 --> 01:14:23.710


This is the final forecast that we're deciding on and then let that then drive the supply plan and the inventory optimization from there.01:14:23.710 --> 01:14:32.780


So, yeah, that's really, and, as I said with the IBP product, there's a demand planning product there called Pivot Forecasting, and that's exactly what it does.01:14:32.780 --> 01:14:49.969


There's collaboration, there's scenario planning, which you alluded to before and saying you know if the tariffs hit, you know, or the port closes and we can't get items from that port, what other scenarios can we build just in case?01:14:49.969 --> 01:14:58.378


And then let's action that scenario if it happens, or we stick with this plan that we have right now.01:14:58.378 --> 01:15:07.207


So you can do different scenarios as well in that planning application and then you know, depending on what you you know what the situation is or what happens.01:15:07.207 --> 01:15:09.101


You can then action different plans.01:15:09.101 --> 01:15:11.320


We're looking at doing that.01:15:11.320 --> 01:15:27.506


You can do that with the demand planning, the IBP product, and we're looking at a digital twin for the well, I said the low-end product, but the original inventory advisor product, the net stock product that we have.01:15:27.506 --> 01:15:40.279


So, yeah, all of those things we want to be able to take and the more information we can bring in for people to do better demand planning and sales and operations planning, the better for us.01:15:41.756 --> 01:15:47.001


We're seeing a big trend with people wanting to forecast by customer and by channel as well.01:15:47.001 --> 01:15:50.505


Like you said, whether it's big box retail or whether it's online.01:15:50.505 --> 01:16:05.515


There's different behaviors, different strategies in each of those and then also different inputs, depending on whether customers are giving you uh forecasts or not and, on the other side, being able to give your supplier a forecast right.01:16:05.515 --> 01:16:06.636


Can we plan?01:16:06.636 --> 01:16:11.387


We can predict or plan what we're going to be purchasing for the next 12 months.01:16:11.387 --> 01:16:26.167


We can put that into a format that that you can then give to your supplier and say you know, because it's all about that, then that that collaboration starts getting really, really good, because now you're collaborating with your customers and you're getting the demand plan as accurate as possible.01:16:26.814 --> 01:16:32.414


You know, we always say demand planning is a process, it's not just a forecast algorithm.01:16:32.414 --> 01:16:37.338


You know and I think that's what we've been talking to all this time Like we're trying to get the forecast as accurate as possible.01:16:37.338 --> 01:16:42.189


But that's just one step in the demand plan is getting that base statistical forecast going.01:16:42.189 --> 01:16:43.939


Now how do we intervene?01:16:43.939 --> 01:16:49.805


How do we plan better against that base forecast to get to a forecast that's right for our business?01:16:49.805 --> 01:17:01.314


And then that's going to drive the inventory planning right through to the supplier, where now we're planning with the supplier and we're saying this is our forecast for the next 12 months of what our offtake is going to be from you.01:17:01.314 --> 01:17:07.305


Can we ensure that we have this stuff on time for these amounts of items at this time?01:17:07.305 --> 01:17:11.743


And that'll help them with their manufacturing and their planning from their side as well.01:17:11.743 --> 01:17:18.645


So giving a forecast or receiving a customer forecast is kind of essential to that sales and operations planning process.01:17:19.314 --> 01:17:31.010


Sounds like a lot of planning, which kind of leads me to my next question about you know for an organization to get the most out of their business central and you know utilizing those tools.01:17:31.010 --> 01:17:42.797


What is your advice for a company or organization that's ready to jump into bringing in a demand planning tool?01:17:42.797 --> 01:17:47.466


What is your advice to get prepared or to start planning?01:17:47.466 --> 01:17:53.323


What should they be doing now, before even getting into the demand planning?01:17:53.323 --> 01:18:15.168


Because again in the past, sometimes actually, brad alluded to this where when you have bad data or maybe it was Yvonne you have bad data and your forecasting is inaccurate because you're feeding it with the wrong information and then you got to go back and then massage the data that you got and then send it out and see what comes out.01:18:15.168 --> 01:18:21.766


What's your advice for an organization about to invest in a demand planning tool?01:18:21.766 --> 01:18:22.868


What should they do now?01:18:23.976 --> 01:18:31.344


Well, I think data is probably and this is during that 12 to 14 week process or however long it takes like I said, how long is a piece of string?01:18:31.344 --> 01:18:51.163


The biggest part of that is data right, because for us to be able to help you understand how the calculation works and produce a recommended order that you trust, we need to have, like I said, the right data, the right policy settings and the most accurate forecasting we can get.01:18:51.163 --> 01:18:55.099


So the forecasting engine does a lot of that kind of heavy lifting itself.01:18:55.099 --> 01:19:02.945


It even has the ability to do things like smooth out peaks in your historical data and um troughs.01:19:02.945 --> 01:19:12.278


You know, if you were stocked out for 15 days of of the month, there were no sales during those 15 days, your forecast is going to be understated, you know.01:19:12.278 --> 01:19:14.682


So we need to be able to and we can.01:19:14.682 --> 01:19:18.176


We can automatically make adjustments for those things to get as accurate a forecast.01:19:18.176 --> 01:19:28.048


So I'm quite confident that we're getting as accurate a forecast as we possibly can with the forecasting engine if you set it up right and you do all the rest.01:19:28.069 --> 01:19:29.171


The next thing is the policies.01:19:29.171 --> 01:19:34.037


Now the policies.01:19:34.037 --> 01:19:37.006


We're going to sit and discuss that with you and you're going to decide.01:19:37.006 --> 01:19:39.515


Those policies are usually set on how important the items are.01:19:39.515 --> 01:19:50.750


So we want to invest more in items that are high value, fast moving items, less in items that are not, so we can get that balance of inventory and we're investing in the right items, which turning the inventory faster and we're making more profit right that, and we set policies against that.01:19:50.750 --> 01:20:03.532


So once we've sat and done that and and aligned those policies with what the business is trying to achieve, that again those are those two inputs um to the application are now there, what the business is trying to achieve, that again, those two inputs to the application are now there and the calculator is working right.01:20:04.132 --> 01:20:06.016


And then the last part is the data right.01:20:06.016 --> 01:20:08.082


And I think that would be the biggest thing.01:20:08.082 --> 01:20:17.527


And I actually had a conversation with a partner about this and we were talking about how do we better prepare a customer for what's going to be required from a data point of view.01:20:17.527 --> 01:20:36.018


Right now we have a data purity dashboard that picks up all the things that that's qr and that also, again, it's one of those things that are never going to be 100 we know data is never 100 and I would say to the customer go and clean your data before you input this, this application, but then you'd never see them again, right.01:20:36.559 --> 01:21:01.090


So we have very specific things that we, that we that we look at, and I mean there's a whole lot of touch points, but I can tell you the three most important things in that overdue sales orders, overdue purchase orders okay, and items connected to a supplier right, because if you have an overdue purchase order, we think that there is stock arriving today.01:21:01.090 --> 01:21:14.360


It's overdue from two weeks ago, so we're expecting it and tomorrow we'll expect it, and tomorrow we'll expect it, unless that purchase order disappears or it arrives and we are now stocked and we can carry on with the planning.01:21:14.360 --> 01:21:38.588


If there's sales orders, we see that there's firm demand and we're saying, hey, we've got these sales orders that need to go out to the customer, so we need to purchase more inventory because we've got firm demand, right, so we're buying more than what we need and those things will skew what that purchase order looks like and then, when they get to that, we can't really train people to trust that process if the order is coming out wrong.01:21:38.588 --> 01:21:43.908


So those are two things that are really important when it comes to the way that we calculate to get to that order.01:21:43.908 --> 01:21:50.702


And the third thing, obviously, is we don't know which supplier to plan against if you don't have an item connected to a supplier.01:21:50.702 --> 01:22:01.963


So I would say off the bat those three things if we could have that as clean as possible when we pull in your data, that process would go a lot quicker.01:22:02.506 --> 01:22:06.880


And then, from an internal point of view, from a process point of view, that's just change management.01:22:06.880 --> 01:22:21.807


And I'm sure you guys deal with this all the time in ERP, probably more than what we do, because we're really only touching one kind of department, which is your purchasing and planning department, because you guys are touching every single part of that business when you roll out an ERP.01:22:21.807 --> 01:22:25.159


Right, but it's change management.01:22:25.159 --> 01:22:27.144


We're 100% going to take this on.01:22:27.144 --> 01:22:28.887


This is what we want to do in the business.01:22:28.927 --> 01:22:37.545


And you need buying from the execs to drive it down and say, hey guys, this is the tool that we invested in this tool, we trust that this is going to work.01:22:37.545 --> 01:22:43.747


Net stock's done a great job on selling to us um and we need to implement this in the, in the application.01:22:43.747 --> 01:22:59.164


And then we need somebody to drive the process, what we call the net stock champion, which is going to be the person that takes responsibility for that project working and then, at a lower level, the people that we need to work with, the people that are on day-to-day basis, are going to interact with the, with the application, and that's just.01:22:59.164 --> 01:23:01.108


You know, the usual project stuff.01:23:01.108 --> 01:23:09.796


It's like we need buy-in, we need commitment to to get it done, we need the data as clean as possible and we need to engage.01:23:09.796 --> 01:23:18.225


We need people to engage with us and train and learn, but you know, those are kind of like the, the usual suspects when it comes to implementations, right?01:23:20.975 --> 01:23:22.238


Does it forecast?01:23:22.278 --> 01:23:23.380


people going on vacation.01:23:23.380 --> 01:23:25.944


Well, people can go on more vacations if they have the forecast Exactly.01:23:32.595 --> 01:23:35.335


So we used to have this picture of when we first started with, with a little picture of the dashboard on an iPad.01:23:35.335 --> 01:23:51.318


I remember Barry, who's his friend of mine, that was one of the founders um, he said that they came to a a conference I think it was one of the big sage conferences when they first started off, way back when, and he had net stock on an ipad and nobody even had ipads.01:23:51.318 --> 01:23:59.021


Then, you know, and maybe we were a little bit ahead of time, we had this picture of an ipad with a little dashboard on this person sitting on the beach.01:23:59.021 --> 01:24:01.265


You know, and that was kind of like.01:24:01.265 --> 01:24:06.301


The selling point is that you know you could do this from anywhere anytime.01:24:06.301 --> 01:24:15.078


Of course, that didn't make sense until COVID came around, but you know, back then it did look nice that they could sit on your beach and sit on the beach and do your inventory planning.01:24:15.140 --> 01:24:18.247


It's still nice in something to do.01:24:18.247 --> 01:24:20.823


Well, vaughn Sam, sam Bush, I get it.01:24:20.823 --> 01:24:21.877


Ambush, sam Bush.01:24:21.877 --> 01:24:23.804


Sam Bush, you say it fast, I like it.01:24:23.804 --> 01:24:25.926


I got it, vaughn Sam.01:24:25.926 --> 01:24:27.979


Thank you for taking the time to speak with us today.01:24:27.979 --> 01:24:33.363


We really appreciate your time and sharing all the information that you shared about NetStock, as well as other things.01:24:33.363 --> 01:24:44.347


If anybody has any additional questions or would like more information on NetStock or they would like to see some of the other I'm all tongue-tied today see some of the other great things that you do.01:24:44.347 --> 01:24:48.076


What's the best way to get in contact with you, sam?01:24:48.076 --> 01:24:49.221


We'll start with you, sam Bush.01:24:50.016 --> 01:24:51.021


For me it's LinkedIn.01:24:51.021 --> 01:24:59.386


You can find me Sam Bush or Ambush on Air is my podcast, or you can email me at sambush at netstockcom.01:25:01.256 --> 01:25:01.859


Mr Vaughn sir.01:25:02.375 --> 01:25:03.560


Yeah, I would say the same thing.01:25:03.560 --> 01:25:08.440


Reach out to me on LinkedIn Because I'm from the old school.01:25:08.440 --> 01:25:10.077


I don't have my surname, but it's Vaughn.01:25:10.077 --> 01:25:19.820


At netstockco we had too few people in our business to worry about name and surname.01:25:19.820 --> 01:25:21.326


That's good.01:25:21.326 --> 01:25:23.310


That's how you know you're an OG.01:25:23.310 --> 01:25:25.601


I guess the single names.01:25:25.601 --> 01:25:26.024


You're an OG.01:25:26.295 --> 01:25:31.695


Well, thank you very much again for taking the time to speak with us and sharing us about NetStock, and we look forward to speaking with you again soon.01:25:32.277 --> 01:25:35.078


Thanks for having us, I really appreciate it All right, ciao, ciao.01:25:35.779 --> 01:25:36.319


Thanks guys.01:25:37.461 --> 01:25:44.546


Thank you, Chris, for your time for another episode of In the Dynamics Corner Chair and thank you to our guests for participating.01:25:44.845 --> 01:25:46.386


Thank you, brad, for your time.01:25:46.386 --> 01:25:49.890


It is a wonderful episode of Dynamics Corner Chair.01:25:49.890 --> 01:25:53.351


I would also like to thank our guests for joining us.01:25:53.351 --> 01:25:59.086


Thank you for all of our listeners tuning in as well.01:25:59.086 --> 01:26:10.887


You can find Brad at developerlifecom, that is D-V-L-P-R-L-I-F-E dot com, and you can interact with them via Twitter D-V-L-P-R-L-I-F-E.01:26:10.887 --> 01:26:24.251


You can also find me at matalinoio, m-a-t-a-l-i-n-o dot I-O, and my Twitter handle is matalino16.01:26:24.251 --> 01:26:27.943


And you can see those links down below in the show notes.01:26:27.943 --> 01:26:29.306


Again, thank you everyone.01:26:29.306 --> 01:26:30.860


Thank you and take care.