Latest / Speaking of Supply Chain / Why Your Planning System Is Not the Problem

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Why Your Planning System Is Not the Problem · Speaking of Supply Chain

0:00
Speaker 1: Going back to people running around with their hair on fire,
0:03
Speaker 1: why aren't these fundamentals already addressed? And I think in
0:06
Speaker 1: the large organizations that you and I work with, these
0:09
Speaker 1: seemingly simple things require the effort of a Middle Eastern
0:13
Speaker 1: peace treaty to try to get consensus between sales and
0:16
Speaker 1: supply chain on service levels, or between supply.
0:19
Speaker 2: Chain and manufacturing on batch sizes.
0:22
Speaker 1: And because they're difficult to change, nobody's going to take
0:25
Speaker 1: the initiative to do it, and they're ignored.
0:30
Speaker 3: Welcome to speaking of supply chain. I'm Christine Barnhardt, head
0:33
Speaker 3: of Industry Engagement and Alliances at MEBACH, and I am
0:37
Speaker 3: your host. Today. This is where we go beyond the
0:40
Speaker 3: buzzwords to unpack what actually drives performance in supply chain.
0:46
Speaker 3: Today we're going to talk about planning and why despite
0:49
Speaker 3: all the investments in system data and new AI, it
0:55
Speaker 3: still is not delivering consistent results. So most organizations, in
1:00
Speaker 3: my opinion, do have a planning problem. But what we're
1:04
Speaker 3: seeing is that, in my opinion as well, they're trying
1:07
Speaker 3: to solve it in the wrong way. So they're chasing
1:10
Speaker 3: the next shiny object, new platforms, advanced capabilities AI without
1:16
Speaker 3: fixing what is fundamentally wrong, you know, be in their
1:20
Speaker 3: architecture and underneath their planning organizations. As a result, planning
1:26
Speaker 3: is not translating into performance. So I'm super excited to
1:30
Speaker 3: have a very special guest today, which is Dan Cogan
1:34
Speaker 3: from Solventure. He is an industry leader in supply chain. Dan, welcome,
1:39
Speaker 3: so happy to have you. Would love for you to
1:43
Speaker 3: introduce yourself to the audience.
1:45
Speaker 1: Yeah, well, first of all, thanks Christine for having me
1:47
Speaker 1: on the podcast. We've probably known each other for about
1:49
Speaker 1: six months now, and maybe it's to the benefit of
1:52
Speaker 1: your audience that we bring some of our otherwise private
1:55
Speaker 1: conversations out from behind closed doors. I know it sounds
1:59
Speaker 1: like a spicy episode already. That's my hook, so keep
2:03
Speaker 1: listening everyone.
2:04
Speaker 3: I love it. I love it. So you had lost
2:07
Speaker 3: your background and what you're doing these days?
2:10
Speaker 2: Yeah, so really quickly.
2:12
Speaker 1: I've got about two decades of experience across industry, consulting technology,
2:18
Speaker 1: all of that time in supply chain and even dabbling
2:21
Speaker 1: a little bit in academia these days as well. Today,
2:24
Speaker 1: in my role at soul Venture, I'm responsible for developing
2:27
Speaker 1: our solutions portfolio, and that includes things like expanding and
2:31
Speaker 1: maturing our service offerings, maintaining key partnerships like the one
2:35
Speaker 1: between our companies, and also occasionally rolling up my sleeves
2:39
Speaker 1: and getting my hands dirty on some of our key engagements.
2:42
Speaker 1: So I'm really it's a combination of working in the
2:45
Speaker 1: business and also on the business, and I wouldn't want
2:48
Speaker 1: it any other way.
2:50
Speaker 3: I love it. Dan and I have kind of similar
2:53
Speaker 3: similar roles to some extent, but I think similar mindset.
2:57
Speaker 3: We're both Midwesterners and so that you just never know
3:02
Speaker 3: where this is.
3:02
Speaker 1: I'm gonna transplants. I just want to just want to
3:04
Speaker 1: caveat that.
3:06
Speaker 3: Really, where are you from? Originally?
3:08
Speaker 1: I grew up in Northern Virginia Washington, DC area, but
3:11
Speaker 1: I had to get away from the politics.
3:13
Speaker 2: You know me, I don't like politics.
3:15
Speaker 3: I love it.
3:15
Speaker 2: I love it.
3:17
Speaker 3: Just this past week we published a blog on your
3:22
Speaker 3: behalf through through Me Bach that I think was titled
3:27
Speaker 3: do you really want an APS upgrade? Tell me about
3:31
Speaker 3: the blog and why do organizations instinctively say yes to
3:37
Speaker 3: an APS upgrade?
3:39
Speaker 2: Yeah, this one's a fun one.
3:40
Speaker 1: I think I really wore my heart on my sleeve
3:42
Speaker 1: when I was writing that blog.
3:44
Speaker 2: I think I just look at it.
3:46
Speaker 1: It's so cliche to complain about your your advanced planning system,
3:50
Speaker 1: your APS, right. The user is never going to blame
3:54
Speaker 1: themselves for lack of knowledge, The IT team is never
3:57
Speaker 1: going to self implicate for poor data integration. The management
4:01
Speaker 1: team is never going to point the finger at themselves
4:03
Speaker 1: or broken processes. So it must be the APS right.
4:07
Speaker 1: And it's super easy to lump everything under this umbrella
4:11
Speaker 1: of technology and just push that easy button. But I
4:14
Speaker 1: think that's when we really need to have a hard
4:16
Speaker 1: look in the mirror, if you will. There's definitely some
4:20
Speaker 1: outperforming vendors in the technology landscape, but if you look
4:25
Speaker 1: at what's really happening, it's quite commoditized. I think that
4:30
Speaker 1: probably there are some vendors that offer specialized features that
4:33
Speaker 1: speak to a certain percentage of their users, but eighty
4:36
Speaker 1: percent of the functionality is going to be common across
4:39
Speaker 1: all the vendors and effectively works for anybody who's manufacturing.
4:43
Speaker 2: Right.
4:43
Speaker 3: Yeah, No, I mean I think I'm seeing the same thing.
4:46
Speaker 3: So the issue isn't that companies don't have a planning system.
4:49
Speaker 3: It's that those systems and the processes around those systems
4:55
Speaker 3: aren't driving decisions that either are being executed or can
5:00
Speaker 3: be executed, right, So it like the plans don't reflect
5:04
Speaker 3: what's actually executable, what the operational reality is, or the
5:10
Speaker 3: data is not very great, right, and there's like this
5:14
Speaker 3: lack of trust and ownership. Is that Is that really
5:18
Speaker 3: what you're what you're talking about here? Yeah?
5:20
Speaker 1: I think there's so many things to unpack there, you know,
5:24
Speaker 1: do the plans match operational reality? I think just thinking back,
5:28
Speaker 1: like until port congestion during COVID, when was the last
5:31
Speaker 1: time anyone reviewed their their sourcing lead times? And how
5:34
Speaker 1: many times has it been done since then? And uh,
5:38
Speaker 1: I'm an academic, I already admitted that, So I think
5:40
Speaker 1: it just an example is anytime there's a company that's
5:43
Speaker 1: struggling to balance their production efficiency with inventory, I always
5:47
Speaker 1: bring the model of economic order quantity and the general
5:51
Speaker 1: response is, oh, yeah, EOQ. That's a that's a cute theory,
5:54
Speaker 1: but it's just a theory. You're like, well, correct, it
5:57
Speaker 1: is a framework, But let me ask you, how are
5:59
Speaker 1: you setting lot sizes today? And there's a lot of well,
6:03
Speaker 1: our plant manager did that unilaterally back in nineteen ninety five.
6:07
Speaker 1: We haven't really adjusted it since. And so yes, this
6:10
Speaker 1: EOQ is a cute theory, but maybe theory is a
6:13
Speaker 1: good starting point there.
6:15
Speaker 3: Right, No, No, it's funny. And I think one of
6:17
Speaker 3: the things you said in your blog was something to
6:19
Speaker 3: the effect of you're not running on your planning system,
6:23
Speaker 3: you're running around it. And honestly, that image of people
6:27
Speaker 3: kind of with their hair on fire, I can say
6:29
Speaker 3: that because that a redhead right where you know, you're
6:33
Speaker 3: you're utilizing spreadsheets, you're jumping from meeting to meeting because
6:38
Speaker 3: everything is broken, right, So I think that that is
6:42
Speaker 3: that's the reality that people are living with today.
6:46
Speaker 2: I think it's more companies than not just going back.
6:49
Speaker 1: It's fashionable to complain about your aps and you go
6:52
Speaker 1: back to that easy button. And I think savvy executives
6:56
Speaker 1: do it intentionally, and I think there's also less than
6:58
Speaker 1: savvy executives that kind of do it unwittingly. But there
7:02
Speaker 1: is a hidden benefit to lumping everything under that easy
7:05
Speaker 1: button of technology, and that's what the blog was about.
7:09
Speaker 1: I mean, And the benefit is twofold one is you
7:11
Speaker 1: have this easy button sitting in front of you, and
7:14
Speaker 1: maybe it doesn't get pushed because it's lack of funding
7:16
Speaker 1: or lack of buying for an APS system, and then
7:19
Speaker 1: you have an excuse to continue with your poor performance.
7:22
Speaker 2: Right.
7:23
Speaker 1: But I think then the other thing is that if
7:24
Speaker 1: the easy button does get pushed, the APS implementation is
7:29
Speaker 1: going to act as a forcing function to clean up
7:31
Speaker 1: all of the issues that were truly the root cause.
7:33
Speaker 1: And in that latter case, the ends justify the means.
7:37
Speaker 3: Well, I think it can act as a catalyst to
7:40
Speaker 3: clean up the things that we're wrong. I think often
7:43
Speaker 3: it doesn't, unfortunately, because we buy a new tool, but
7:47
Speaker 3: we still don't fix the foundational issues and the process issues.
7:51
Speaker 3: And I see a ton of companies they recognize that
7:55
Speaker 3: they have a problem, right, and then they're jumping straight
7:59
Speaker 3: to I need a new platform or I need some
8:02
Speaker 3: fancy AI tool. And I've said this repeatedly. One of
8:08
Speaker 3: the things that I think is happening is technology is
8:11
Speaker 3: delivering on its promise to make decisions faster. Unfortunately, we
8:18
Speaker 3: have the wrong data, we have the wrong processes, so
8:21
Speaker 3: we're just driving to a wrong answer faster than what
8:25
Speaker 3: we drove to a wrong answer maybe five to ten
8:28
Speaker 3: years ago. I mean, is that consistent.
8:31
Speaker 2: Doing dumber things faster? Right?
8:34
Speaker 1: I think it's it's always about chasing the bright, shiny
8:38
Speaker 1: new object and it's going to be the next savior
8:41
Speaker 1: so that we don't have to roll up our sleeves
8:43
Speaker 1: and do any real work. Right, everybody's always chasing that.
8:47
Speaker 1: But I think that most of the value actually comes
8:50
Speaker 1: in doubling down on fundamentals. Again, just examples, Hey, do
8:55
Speaker 1: we need to reconsider our service levels? Do we need
8:58
Speaker 1: to review our batch sizes? And I'm not just talking
9:00
Speaker 1: about does the data exist, but actually scrutinizing whether those
9:04
Speaker 1: parameters reflect what needs to be happening to drive the
9:07
Speaker 1: performance of your business. And I think, maybe going back
9:11
Speaker 1: to people running around with their hair on fire, why
9:14
Speaker 1: aren't these fundamentals already addressed? And I think in the
9:17
Speaker 1: large organizations that you and I work with, these seemingly
9:21
Speaker 1: simple things require the effort of a Middle Eastern peace
9:25
Speaker 1: treaty to try to get consensus between sales and supply
9:29
Speaker 1: chain on service levels, or between supply chain and manufacturing
9:32
Speaker 1: on batch sizes. And because they're difficult to change, nobody's
9:37
Speaker 1: going to take the initiative to do it, and they're ignored,
9:39
Speaker 1: and often ignoring them for one or two years becomes
9:42
Speaker 1: five or ten years. But again, these are the parameters
9:45
Speaker 1: that are really driving your business performance.
9:49
Speaker 3: Right, If you order too much, you carry too much inventory.
9:51
Speaker 3: Finance is complaining at you that you have too much inventory.
9:57
Speaker 3: If you order too little, are you doing order frequently enough?
10:01
Speaker 3: Then you're expediting or you have out of stocks. And
10:05
Speaker 3: I think that fundamentally, there's a lot of people running
10:09
Speaker 3: supply chains these days that don't understand how those dots
10:13
Speaker 3: all connect. Right. They don't understand that how often I
10:18
Speaker 3: order and the size of the material that I order
10:22
Speaker 3: has an impact on my inventory and my service. And
10:25
Speaker 3: beyond that, I think we have a lot of really
10:27
Speaker 3: crappy data, right, and I think operational data is actually
10:32
Speaker 3: pretty good. Right. We're recording, you know, where an order
10:35
Speaker 3: goes and how long it took to get there, But
10:38
Speaker 3: then it's not getting back into master data. And so
10:42
Speaker 3: when you talked in your blog about the swamp, right,
10:47
Speaker 3: were you thinking more master data or more operational data? Uh?
10:51
Speaker 2: Yeah, it can be both. It can be both.
10:53
Speaker 1: So the swamp analogy was about the APS implementation, because
10:57
Speaker 1: again it might seem like this so called easy button,
11:01
Speaker 1: but you and I know and others that have been
11:03
Speaker 1: through it before, No it's anything but an easy button
11:05
Speaker 1: when you start to consider, okay, all of the tribal
11:08
Speaker 1: knowledge or processes that need to be defined and and
11:12
Speaker 1: also agreed cross functionally, all of the parameters that need
11:16
Speaker 1: to be reviewed or captured if they don't exist. You're
11:19
Speaker 1: telling me I have to go out to all of
11:20
Speaker 1: my suppliers and get lead times for all of them.
11:22
Speaker 2: I've never had to do that before.
11:25
Speaker 1: All of the data capture and integration flows, the configuration
11:28
Speaker 1: of the system, the testing, the training, the change management.
11:31
Speaker 1: It's really it's a swamp. It's not an easy button
11:34
Speaker 1: at all. But again, it's an effective forcing function that
11:39
Speaker 1: organizations can leverage to transform their planning.
11:42
Speaker 3: I was gonna say, I'm going to be a little
11:44
Speaker 3: provocative switch gears here, but I'm talking to you and
11:47
Speaker 3: you're way more provocative than I am most of the time.
11:50
Speaker 3: So from my perspective, and I say this as somebody
11:56
Speaker 3: that I sol helped design and sell software and now
12:00
Speaker 3: work for a consultant. Right, I don't think that what's
12:03
Speaker 3: missing is capability oriented. I think it's this concept of
12:08
Speaker 3: orchestration and that and I'm going to define it and
12:12
Speaker 3: then I'm going to let you tell me where I'm
12:14
Speaker 3: right or wrong and help the audience understand it better.
12:17
Speaker 3: But I think it's aligning for me. Orchestration is aligning
12:21
Speaker 3: decisions around demand, supply, finance, customer and ensuring that the
12:28
Speaker 3: data is unified and continuously managed. Meaning the data that
12:34
Speaker 3: I have in the ERP versus the APS versus maybe
12:38
Speaker 3: some customer fulfillment solution, that's the same data. It means
12:43
Speaker 3: the same thing in all of the various systems, and
12:47
Speaker 3: it's continuously being reviewed, managed updated. It's good. It's healthy data, right,
12:55
Speaker 3: and that we're connecting then these processes and these decisions
13:00
Speaker 3: across multiple horizons, and we're really linking planning to execution.
13:06
Speaker 3: So that's like four bullets, but really lofty. I think
13:10
Speaker 3: this definition of orchestration, So like, what's your definition of orchestration,
13:16
Speaker 3: and like, where have I missed the mark?
13:18
Speaker 1: Now? I like yours quite a bit. I think it's
13:22
Speaker 1: interesting when you talk about integrating the different planning horizons.
13:27
Speaker 1: I just spoke last week with a five billion dollar
13:30
Speaker 1: manufacture and they have a demand forecasting system that's already
13:34
Speaker 1: in place, and that forecast flows into a rough cut
13:39
Speaker 1: capacity plan. It happens to be a spreadsheet. Okay, that's
13:42
Speaker 1: all right, but it dead ends there. So they have
13:45
Speaker 1: long term capacity planning, but it doesn't translate to a
13:48
Speaker 1: master production schedule. It doesn't translate to material requirements plan.
13:52
Speaker 1: It's just orders coming in and being shipped out without
13:55
Speaker 1: any planning on a tactical horizon. So you like to say, yeah,
13:58
Speaker 1: every company is going to have els and operations execution.
14:01
Speaker 2: Right.
14:01
Speaker 1: If you don't do that, you're you're not in business.
14:04
Speaker 1: But I think a lot of companies have trouble looking
14:07
Speaker 1: beyond the end of their the end of their nose,
14:10
Speaker 1: to have a true S and P process or supply
14:13
Speaker 1: chain planning process that looks beyond the tactical horizon. And
14:17
Speaker 1: I think, okay, we can give it a bunch of
14:19
Speaker 1: different definitions. I think about like what you said about customers, suppliers, finance.
14:26
Speaker 2: Right.
14:27
Speaker 1: You can also think about it maybe from an internal view.
14:29
Speaker 1: People processes, tools and data. But the purpose of a
14:33
Speaker 1: system is what it does. And if you're not getting
14:36
Speaker 1: the performance you want, you need to change the system.
14:39
Speaker 1: And in a successful transformation, all of those dimensions have
14:42
Speaker 1: to be reviewed and they have to be aligned and integrated.
14:45
Speaker 3: Exactly exactly, and you know, from my perspective, it's it's
14:49
Speaker 3: kind of this four step process, if you will. I
14:53
Speaker 3: have to have data right, and I have to trust
14:55
Speaker 3: the data so that the data can give me insights
14:58
Speaker 3: into what's happening in my business. And then once I
15:00
Speaker 3: have insights, I need to make a decision about how
15:04
Speaker 3: to react to those insights, and then I need to
15:08
Speaker 3: take action. And I think a lot of times what
15:11
Speaker 3: I'm at least seeing in terms of planning is we'll
15:16
Speaker 3: do a planning implementation, we clean the data. It's a
15:19
Speaker 3: big part of the process. At the beginning. We got
15:23
Speaker 3: to get the data, so they've got the data piece,
15:26
Speaker 3: but then we leave the data and it gets bad
15:28
Speaker 3: over time. And then we have the action piece, which
15:31
Speaker 3: is the push of a button that says, okay, we're
15:34
Speaker 3: going to take this action. But the insights and the
15:37
Speaker 3: decisions in between these are like completely disconnected and siloed.
15:41
Speaker 2: Yeah, I mean, you're right.
15:43
Speaker 1: The goal isn't isn't better data. The goal isn't more training.
15:47
Speaker 1: Those are the means. The goal is better decisions and
15:50
Speaker 1: making sure that those are executed accordingly. And I think
15:54
Speaker 1: there have to be processes set up around the data,
15:56
Speaker 1: and they have to be institutionalized. I think a lot
15:59
Speaker 1: of time people that are in planning roles have grown
16:03
Speaker 1: up through those roles. Maybe they grew up on the
16:04
Speaker 1: manufacturing floor and then became a supply planner. Maybe they
16:08
Speaker 1: were in sales became a demand planner. Maybe they're fresh
16:11
Speaker 1: out of fresh out of college. But I see a
16:14
Speaker 1: lack of systems thinking about about the supply chain, and
16:18
Speaker 1: if I think if everybody had just a little bit
16:20
Speaker 1: more knowledge or perspective from that angle, that we'd be
16:24
Speaker 1: better off.
16:25
Speaker 3: So I mean, for the audience and people listening, you know,
16:28
Speaker 3: we've kind of poopooed on you know, don't don't do
16:31
Speaker 3: an APS upgrade, And I don't think that's really what
16:34
Speaker 3: we're saying. I think I would challenge you to say,
16:37
Speaker 3: give some guidance. When can an upgrade or a new
16:42
Speaker 3: implementation create value.
16:45
Speaker 2: Yeah, it's interesting.
16:47
Speaker 1: So at soul Venture, we work with clients that have
16:50
Speaker 1: their own homegrown systems and are ready to move to
16:53
Speaker 1: a more off the shelf system. We have clients that
16:58
Speaker 1: are looking to upgrade. It depends on the industry that
17:01
Speaker 1: you're in and the circumstances, and sometimes these decisions take
17:04
Speaker 1: a long time to materialize. You know again, I think
17:06
Speaker 1: we're now in twenty twenty six, we're still dealing with
17:09
Speaker 1: decisions that were made post COVID when things got volatile
17:13
Speaker 1: and people said, oh, I can no.
17:14
Speaker 2: Longer be backwards looking. I need to before it's looking.
17:17
Speaker 1: I need a better demand forecasting process, I need better
17:20
Speaker 1: supply planning system. So some of those decisions are now
17:23
Speaker 1: just coming to fruition five and six years later, just
17:28
Speaker 1: because of the sales cycles and the budget required. But
17:31
Speaker 1: I think we can acknowledge it that things are becoming
17:35
Speaker 1: more volatile. It's not just because of call it to
17:39
Speaker 1: exogenous events that are happening in our global geopolitical systems
17:44
Speaker 1: and things like that. But a lot of times consumer
17:47
Speaker 1: companies are having proliferation of their product portfolios. So there's
17:51
Speaker 1: a lot more mixed variability, there's a lot more volume variability.
17:55
Speaker 1: So if there are changes in your business, either because
17:57
Speaker 1: of external events or because your product and your business
18:01
Speaker 1: model is changing, again, think about omni channel as well
18:04
Speaker 1: as as a catalyst. These are triggers that maybe you
18:08
Speaker 1: need to make sure that you have the right process
18:10
Speaker 1: in place and that they're supported by the right tooling
18:13
Speaker 1: and the right data.
18:14
Speaker 3: You know, it's so funny to me again, I'm going
18:17
Speaker 3: to push a button here. I think I've seen so
18:20
Speaker 3: many companies, so many people jump to demand. I just
18:24
Speaker 3: if I could just predict demands better, right, And they've
18:28
Speaker 3: made huge investments, often with a lack of thinking about
18:33
Speaker 3: the supply side. And on the supply side, if I
18:37
Speaker 3: could just cut a day or two out of my
18:40
Speaker 3: decision process, if I could just you know, trim the
18:44
Speaker 3: lead time, if I could get it to market more reliably,
18:48
Speaker 3: I don't have to have as good of a demand signal, right,
18:53
Speaker 3: because I'm able to react faster, and able to be
18:57
Speaker 3: more flexible, and able to be more agile. So I
19:01
Speaker 3: actually get really frustrated when I hear people talking about
19:04
Speaker 3: planning and we talk demand, demand, demand, and we don't
19:08
Speaker 3: talk about supply and supply variability and how we reduce
19:12
Speaker 3: supply variability. I mean, is that just me? Is that
19:16
Speaker 3: just my pet?
19:17
Speaker 1: It's not, at least from my perspective. I think for
19:21
Speaker 1: a while now the pendulum has swung towards over investment
19:24
Speaker 1: in prediction at the expense of preparation. And I use
19:29
Speaker 1: that term a little bit generically, but it could be
19:31
Speaker 1: preparation on the supply side in terms of safety, stock
19:35
Speaker 1: inventories and things like that, nature lead times that you recommend. Yeah,
19:39
Speaker 1: so I think we've headed a lot towards prediction. I
19:42
Speaker 1: think a lot of that is again triggered by vendors
19:45
Speaker 1: in the marketplace bringing machine learning.
19:47
Speaker 2: And AI and new tools. So again the bright shiny
19:50
Speaker 2: object syndrome.
19:51
Speaker 1: Everybody chases that for a little bit, but there's only
19:54
Speaker 1: so many dollars to go around, so it's at the
19:56
Speaker 1: expense of something else, And sometimes it's at the expense
19:58
Speaker 1: of critical thinking.
19:59
Speaker 2: Right.
20:00
Speaker 1: You might not even need better or new tooling to
20:03
Speaker 1: do your supply planning better. You might just need to
20:05
Speaker 1: revisit those planning parameters. But yeah, I think it's a
20:10
Speaker 1: balancing act between prediction and preparation.
20:13
Speaker 2: And yeah, you have.
20:14
Speaker 1: Some industries like spare parts that it doesn't matter how
20:17
Speaker 1: well you're forecasting is not going to solve the problem here, right,
20:21
Speaker 1: It's got to be on the supply side.
20:23
Speaker 2: Yeah.
20:23
Speaker 3: I mean, my key takeaway I think for folks would be,
20:27
Speaker 3: you know, start with what is the problem that you're
20:29
Speaker 3: trying to solve? What are you trying to have better service?
20:32
Speaker 3: Are you trying to reduce cost? Are you trying to
20:35
Speaker 3: bring you know, more more items to market quicker? Like
20:40
Speaker 3: whatever the problem or problems are, I think you have
20:43
Speaker 3: to start there, and then you have to figure out, well,
20:46
Speaker 3: what is what are the decisions that I need to
20:48
Speaker 3: make in order to enable that? And what is the data?
20:51
Speaker 3: Like it's like peeling back the onion, right, like starting
20:54
Speaker 3: with the customer kind of working your way back and
20:57
Speaker 3: where do I not have alignment? Where? Where does data
21:02
Speaker 3: not reflect reality? I think that that's where people really
21:06
Speaker 3: need to start. They don't need to start with, oh,
21:08
Speaker 3: I'm going to go out and buy a new tool,
21:10
Speaker 3: or oh I'm going to go out and buy this
21:12
Speaker 3: fancy you know, you know Agentic, you know, Bolton or whatever.
21:18
Speaker 3: Because look, and I love technology. I'm an early adopter.
21:21
Speaker 3: You know. We've talked about like I live in the
21:24
Speaker 3: Midwest in a not very big city, and I have
21:27
Speaker 3: an ev right, Like, I can prove that I'm not
21:29
Speaker 3: opposed to technology, but I think that we're fundamentally not
21:34
Speaker 3: looking at the problem appropriately.
21:36
Speaker 1: Yeah, data is at the foundation there, so you can
21:38
Speaker 1: layer on all the technology that you want on top
21:41
Speaker 1: of that. But in pardon my French, but if your
21:43
Speaker 1: data is crap. It's not gonna it's not going to
21:45
Speaker 1: drive the right planning decisions. So yeah, it's it's it's
21:49
Speaker 1: at the foundation of everything and it has to be
21:52
Speaker 1: correct otherwise you've got to crack in that foundation.
21:55
Speaker 3: That's something unique that sol Venture has really come to
21:57
Speaker 3: market with, right, like this concept of data health and
22:01
Speaker 3: data performance and how does that work.
22:04
Speaker 1: So it's always interesting. You know, you have a boutique
22:07
Speaker 1: consultancy and they start to do APS implementations and one
22:11
Speaker 1: of the first things that you realize repeatedly is that
22:13
Speaker 1: data is always going to be an issue. This isn't
22:15
Speaker 1: going to surprise anybody. So then over time you start
22:18
Speaker 1: to develop your own internal processes and templates for harmonizing data.
22:24
Speaker 1: And after seeing so many use cases across multiple APS implementations,
22:30
Speaker 1: multiple ERP systems, multiple industries, you're able to begin to
22:35
Speaker 1: templatize the process. And then you templatize it to the
22:38
Speaker 1: extent that you can productize it and have an off
22:41
Speaker 1: the shelf piece of software that helps accelerate time to value.
22:45
Speaker 1: And so that's what Solventure has done. We have a
22:49
Speaker 1: suite that's Solventure perform as multiple modules. One of them
22:54
Speaker 1: is data orchestration, and as you suggest, another one is
22:57
Speaker 1: data quality. So once we have all of your data
23:00
Speaker 1: in a data hub, we can put a layer of
23:03
Speaker 1: intelligence on top of that, which is data quality, and
23:06
Speaker 1: start to detect all sorts of referential integrity errors, values
23:11
Speaker 1: that don't make any sense, and apply all sorts of
23:14
Speaker 1: business rules that we can then bring up to the
23:16
Speaker 1: user before it actually enters the aps and causes problem.
23:20
Speaker 2: So we use this during.
23:23
Speaker 1: The project phase, but also post project as well. It
23:26
Speaker 1: has alert so that users can continue to see the
23:28
Speaker 1: health of their master and transactional data and correct issues
23:32
Speaker 1: in real time before they become a problem.
23:34
Speaker 3: In full transparency to the audience. This is what interested
23:39
Speaker 3: me so much about Solventure. When I came into the
23:41
Speaker 3: Meebok organization is as somebody that had led multiple planning
23:47
Speaker 3: implementations and planning transformations. We were always starting with the data,
23:52
Speaker 3: but then over time the data would be awful again,
23:56
Speaker 3: and it was like, how do I maintain the integrity
24:01
Speaker 3: of the data. And then beyond that, as I'm getting
24:05
Speaker 3: new tools, or maybe I'm doing murders and acquisitions and
24:08
Speaker 3: I'm bringing you new pieces into my business. It just
24:11
Speaker 3: felt like I was starting from scratch every time, trying
24:15
Speaker 3: to integrate data and make sure data was good. And
24:18
Speaker 3: that's really what this solution kind of helps to solve.
24:23
Speaker 1: Correct there's truth in data, right, And so I just
24:26
Speaker 1: mentioned during the project, implementation and post project, but I'll
24:29
Speaker 1: actually back it up and say pre project, a lot
24:32
Speaker 1: of customers, our prospects are nervous about doing an APS
24:37
Speaker 1: implementation or upgrade because they really don't have a bearing
24:41
Speaker 1: on the health of their data. They know that it
24:42
Speaker 1: can be a complete show stopper and they don't want
24:45
Speaker 1: to start the train rolling if they know they're going
24:47
Speaker 1: to have to stop it. So the same technology that
24:49
Speaker 1: we use during the project, we can bring in ahead
24:53
Speaker 1: of the project and do a feasibility assessment, a data
24:56
Speaker 1: scan and understand how complete is your data set that
24:59
Speaker 1: you need for APS and where are the gaps and
25:03
Speaker 1: we can help you prioritize those gaps so that you
25:05
Speaker 1: can hit the ground running when you are ready to
25:07
Speaker 1: start the project.
25:09
Speaker 3: Yeah, it's really I mean, like for me, it's really exciting.
25:12
Speaker 3: I love this concept of a canonical data model or
25:15
Speaker 3: a unified data model. And then really moving from if
25:21
Speaker 3: I'm lucky, once a quarter of people are looking at
25:24
Speaker 3: data to this really being more real time and serving
25:28
Speaker 3: up ay planner. Look at this, you know this is
25:32
Speaker 3: not planning appropriately because the data is wrong. I just
25:36
Speaker 3: think that that is so exciting.
25:37
Speaker 1: The reason we're able to do a canonical data model
25:39
Speaker 1: is because again at the top of the show, we
25:41
Speaker 1: talked about how probably eighty percent of APS systems are common, right,
25:46
Speaker 1: so they're all going to require lead times, they're all
25:49
Speaker 1: going to require quantities, et cetera, et cetera, right, that
25:53
Speaker 1: the model is not that different from vendor to vendor.
25:56
Speaker 1: And then also we've now worked with enough ERP systems
26:00
Speaker 1: they were able to develop adapters from those respective EER
26:03
Speaker 1: systems to our canonical data model and then back out
26:06
Speaker 1: to whatever APS system you've chosen as well as.
26:10
Speaker 3: Opposed to an implementation where people are building point to
26:14
Speaker 3: point connections.
26:16
Speaker 1: Yeah, we've probably bypassed this whole ad hoc and customization
26:21
Speaker 1: thing and moved to a pre built solution again under
26:24
Speaker 1: the premise that we can help accelerate your time to value.
26:27
Speaker 3: I love it. I love it, Like I said, for me,
26:29
Speaker 3: super exciting. I love that we have formalized a collaboration
26:36
Speaker 3: and that you know solve Venture and Meebocker are really
26:40
Speaker 3: I think both invested to help our customers and help
26:45
Speaker 3: the market really understand that there's a better way. And look,
26:50
Speaker 3: by the way, I don't know that you and I
26:51
Speaker 3: are that novel. Like I've been listening to my two
26:54
Speaker 3: thought leaders, like Lauris Cissiri, like brand, They've been talking
26:58
Speaker 3: about this, but it feels like now the market is
27:03
Speaker 3: more receptive, then maybe they understand more than maybe where
27:08
Speaker 3: we were five years ago.
27:10
Speaker 1: Yeah, I think there takes a lot of beating on
27:12
Speaker 1: the drums to make to make people pay attention. But yeah,
27:16
Speaker 1: thanks to people like Bram and Laurisasari that people are
27:19
Speaker 1: starting to listen. But again, these things take a long
27:22
Speaker 1: time to change.
27:23
Speaker 3: Yeah, Okay, so this has been wonderful, but unfortunately we
27:28
Speaker 3: are kind of at the time. But I'm gonna I'm
27:31
Speaker 3: gonna bet there there are people out there that are like, oh, Dan,
27:34
Speaker 3: I really want to talk to you and pick your brain.
27:36
Speaker 3: So what is the best way for them to do that?
27:39
Speaker 2: Yeah?
27:40
Speaker 1: Absolutely, I'm I'm a fiend on LinkedIn, so so find
27:44
Speaker 1: me on LinkedIn, happy to connect, happy to talk to
27:47
Speaker 1: all of you.
27:48
Speaker 3: Yeah, I'm similar. LinkedIn is probably the best way to
27:52
Speaker 3: get a hold of me. Be patient. It Like I
27:56
Speaker 3: travel to a ton of conferences and I'll get like
27:58
Speaker 3: a big slug of LinkedIn messages. If I haven't responded,
28:03
Speaker 3: feel free to ping me again. Squeaky Wheel gets the
28:06
Speaker 3: grease to some extent. But you can also find me
28:11
Speaker 3: upcoming at the Gartner Supply Chain Symposium in Orlando. I
28:15
Speaker 3: will also be at Koopa Inspire in Vegas and at
28:19
Speaker 3: Home Delivery World in Nashville because I'm I love to
28:23
Speaker 3: be on the road, and you're everywhere I know well,
28:27
Speaker 3: you know, like I and my kids early, So that's it.
28:30
Speaker 2: Do you avoid the paparazzi?
28:32
Speaker 3: Ah, I wish I had paparazzi. I would love that,
28:36
Speaker 3: you know. I feel like that'd be a good thing
28:38
Speaker 3: for me. So before we wrap up, I want to
28:40
Speaker 3: thank our program sponsor and my employer, Meeboch. Meebok is
28:45
Speaker 3: a global supply chain consulting and engineering firm focused on
28:49
Speaker 3: helping organizations improve service, optimize working capital, and drive measurable
28:55
Speaker 3: performance across the end. In supply chain, we cover everything
28:59
Speaker 3: from strategy and planning to just general transformation through execution.
29:06
Speaker 3: In manufacturing, warehouse and distribution, and we work with clients
29:11
Speaker 3: to really turn these supply chain decisions into real business outcomes.
29:16
Speaker 3: So I appreciate everyone joining us, and I look forward
29:20
Speaker 3: to seeing you next time on Speaking of supply Chain.
29:28
Speaker 4: You've been listening to Speaking of Supply Chain a meboch podcast.
29:32
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29:37
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29:38
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29:40
Speaker 4: chain information.
29:42
Speaker 2: Thanks for listening. Until next time,