March 12, 2025 • 6 mins
Is it better to work with a single ISV for all your Business Central needs, or should you mix and match apps from multiple vendors? In this episode, Ryan and Emma explore the pros and cons of ISV consolidation, breaking down key factors like interoperability, support, and scalability. Learn how businesses can avoid ISV sprawl, streamline operations, and ensure seamless integration. But is putting all your eggs in one software basket the right move? Tune in for an in-depth discussion on making the best choice for your Business Central setup.
Website: https://dmsiworks.com
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(05:20):
Welcome to Inside Insight, your quick hit
(54:36):
of tips, tools and trends for
(01:36:51):
manufacturing, distribution and dynamics.
(02:05:00):
365 Business Central brought to you by
(02:54:17):
0Insight Works.
Emma (03:05:20):
Welcome to the deep dive. You know, if
(03:49:07):
you're involved in running a business that
(04:27:26):
handles, say, physical inventory.
Ryan (04:52:00):
Or manufacturing complex logistics,
(05:24:22):
anything like that.
Emma (05:48:40):
Exactly. And you use modern software like
(06:31:36):
Business Central, you are probably kind of
(07:14:33):
completely overwhelmed by the noise around
(07:51:21):
AI.
Ryan (08:00:10):
Absolutely. Everyone is promising a
(08:32:23):
revolution.
Emma (08:40:10):
Right. But what we need, what you need are
(09:33:33):
specific, practical, measurable gains,
(09:57:17):
things that actually make a difference in
(10:38:48):
your day to day. So our mission today is
(11:32:12):
to cut right through that hype. We're
(12:13:43):
going to look at precisely how AI agents
(13:01:11):
are changing the, well, the fundamental
(13:36:46):
math of efficiency for ISVs, the
(14:12:22):
independent software vendors.
Ryan (14:30:10):
Yeah. And we're pulling these insights
(15:04:07):
directly from an expert analysis. It was
(15:43:44):
shared by Mark Hamblin of Insight Works.
(16:17:41):
This was during the 2025 Biz Apps Partner
(17:02:57):
Executive Summit, specifically in the ISV
(17:36:55):
Partner Breakout session. So this isn't,
(18:10:52):
you know, theoretical marketing stuff.
Emma (18:39:10):
Right. This is a technical blueprint.
Ryan (19:04:30):
Exactly. For how these specialized
(19:35:30):
logistics applications are fundamentally
(20:00:18):
changing.
Emma (20:10:30):
And that context is so crucial. I think
(21:03:21):
we're focusing on how AI is transforming
(21:49:35):
the core job of the isv, which is, you
(22:49:03):
know, making life dramatically easier for
(23:28:41):
the users, the people who deal with
(24:14:56):
complex physical products in that messy
(24:54:34):
0Emma: real world logistics environment.
Ryan (25:26:20):
Precisely. And the goal itself hasn't
(26:01:23):
changed. ISVs have always wanted to
(26:36:27):
maximize user output. Of course, what has
(27:17:22):
fundamentally changed, and this is really
(27:52:26):
the key takeaway here, is the execution.
(28:33:20):
We finally have the tools to deliver on
(29:20:06):
these, I mean, decades old aspirations.
Emma (29:56:30):
Okay, let's unpack that history, because I
(30:32:01):
think it makes the current shift even more
(31:12:37):
profound. For decades, the priority for
(31:43:04):
every software vendor was just this
(32:13:31):
relentless pursuit of efficiency.
Ryan (32:33:50):
Right. How do you make the user faster at
(33:13:37):
checking things in, moving things out or
(33:44:34):
fulfilling an order?
Emma (34:00:29):
And that focus, that historical focus, was
(34:35:44):
really distilled into a concept that Mark
(35:11:00):
Hamblin introduced years ago.
Ryan (35:32:30):
Yeah, he called it more value per click.
Emma (36:07:10):
More value per click. It's such a
(36:37:06):
powerful, simple metric, isn't it?
Ryan (36:58:30):
It is.
Emma (37:07:10):
It just immediately frames that
(37:32:02):
traditional goal. And back then it meant,
(38:06:50):
you know, know reducing the number of user
(38:46:38):
interactions to get something done.
Ryan (39:14:10):
If receiving a shipment took 10 steps
(39:44:02):
before, the goal was to find a way to make
(40:26:42):
it five clicks.
Emma (40:39:30):
And that was a huge undertaking.
Ryan (41:04:10):
Oh, massive. Think about the complexity
(41:44:56):
involved in shaving off just one click in
(42:39:19):
a mission critical workflow. Yeah, I mean,
(43:26:54):
that required huge database optimization,
(44:00:53):
restructuring UI layouts, maybe combining
(44:34:52):
several screens into One developers would
(45:15:39):
spend months trying to squeeze out these
(46:03:14):
marginal gains.
Emma (46:26:30):
So an incredible amount of manual effort
(46:59:10):
to save a user a little bit of manual
(47:41:10):
effort.
Ryan (47:45:50):
Exactly. But here's the crucial context.
(48:20:09):
When that idea was first introduced, it
(49:00:12):
was largely aspirational, right? The
(49:28:48):
technology just wasn't there yet. To
(50:03:08):
automate the most complex parts of the
(50:43:10):
workflow, the user had to be the one to
(51:34:40):
initiate those steps.
Emma (51:51:50):
But that barrier is gone now. And this
(52:39:28):
brings us right to the core of this
(53:27:07):
technical shift and why this old
(54:02:51):
aspiration is suddenly. Well, it's
(54:32:38):
completely attainable, Right?
Ryan (54:51:50):
We're transitioning from that aspiration
(55:26:09):
to the current reality. AI and agents.
(56:14:12):
These are the tools that finally turn more
(57:09:07):
0Ryan: value per click into an expected standard.
Emma (57:57:10):
And here's where the mechanism of the
(58:30:57):
shift becomes so powerful. We aren't
(58:59:55):
talking about AI as just a supporting
(59:33:43):
tool, like helping you write an email or
(60:12:20):
something.
Ryan (60:19:50):
No.
Emma (60:26:30):
According to the source material, AI is
(61:14:38):
now an engine for efficiency. It's
(61:55:54):
fundamentally integrated into the
(62:23:24):
application itself.
Ryan (62:38:30):
And this is the key technical insight we
(63:25:16):
need to focus on, especially for you in
(64:12:02):
the logistics space. Historically, the
(64:41:16):
user initiated almost everything based.
Emma (65:10:30):
On what they saw on the screen.
Ryan (65:34:30):
Exactly. Now, agents can respond
(66:08:50):
dynamically to external events, and this
(66:50:02):
is critical. Trigger automated processes
(67:24:22):
entirely on their own.
Emma (67:55:50):
That idea of responding to an external
(68:28:54):
event, that changes the entire dynamic.
(68:57:15):
What kind of external events are we
(69:30:19):
talking about here?
Ryan (69:44:30):
Well, we're talking about real time data
(70:22:32):
from the outside world that doesn't depend
(71:00:35):
on a user hitting refresh. Think about
(71:38:37):
integrating webhooks from shipping
(72:00:21):
carriers. An external event could be the
(72:38:24):
carrier's API pinging your system with an
(73:16:27):
updated eta, or a confirmation that a load
(73:59:55):
just left the depot.
Emma (74:24:20):
So the agent sees that status change
(74:57:18):
before the user even opens the order
(75:30:17):
screen.
Ryan (75:35:00):
Absolutely. Or in a warehouse, an external
(76:19:39):
event might be a sensor reading, a
(77:04:19):
temperature probe spiking, a door
(77:36:13):
unlocking, a weight sensor tripping. When
(78:14:30):
an item is placed on a loading dock, the
(79:11:55):
agent observes the physical world,
(79:43:49):
recognizes that trigger, and then
(80:15:43):
autonomously performs the necessary
(80:41:14):
software response.
Emma (80:58:00):
Which means the user is suddenly relieved
(81:35:36):
of one of the biggest burdens of business
(82:18:34):
software. They are no longer required to
(82:56:10):
babysit every single transaction. The
(83:23:01):
software is starting to think ahead for
(84:00:37):
them.
Ryan (84:08:40):
That's it. If we connect this to the
(84:54:41):
bigger picture, it means the system
(85:29:12):
handles all those routine actions in the
(86:09:28):
background. Confirming a delivery
(86:32:29):
notification, generating a goods.
Emma (86:55:30):
Received note, all the little repetitive
(87:25:47):
steps.
Ryan (87:30:50):
The system just manages those, reducing
(88:09:36):
the need for that constant manual
(88:48:22):
interaction.
Emma (88:57:30):
But wait, this sounds amazing, but where
(89:36:58):
does the margin for error creep In, I
(90:22:04):
mean, if you're relying on the system to
(91:07:10):
confirm a receipt automatically, doesn't
(91:35:22):
that demand almost perfect pristine data
(92:09:11):
quality?
Ryan (92:17:30):
That's a critical question. And yes,
(92:52:51):
achieving this no click efficiency
(93:22:19):
absolutely requires extremely high data
(93:51:47):
quality. Okay, but that's the beauty of
(94:33:02):
the agent structure. The system is
(95:08:23):
designed to handle the say 80 or 90% of
(96:01:25):
transactions that are routine. And the
(96:36:47):
exceptions, it's the 10%, the exceptions
(97:12:08):
that it flags for human intervention.
Emma (97:47:30):
Okay, so let's focus on the outcome of
(98:21:08):
that. The no click workflow.
Ryan (98:42:10):
This is where we see that aspiration of 178 99:29:50,000 --> 100:11:32,500 Ryan
Welcome to Inside Insight, your quick hit
(54:36):
of tips, tools and trends for
(01:36:51):
manufacturing, distribution and dynamics.
(02:05:00):
365 Business Central brought to you by
(02:54:17):
0Insight Works.
Emma (03:05:20):
Welcome to the deep dive. You know, if
(03:49:07):
you're involved in running a business that
(04:27:26):
handles, say, physical inventory.
Ryan (04:52:00):
Or manufacturing complex logistics,
(05:24:22):
anything like that.
Emma (05:48:40):
Exactly. And you use modern software like
(06:31:36):
Business Central, you are probably kind of
(07:14:33):
completely overwhelmed by the noise around
(07:51:21):
AI.
Ryan (08:00:10):
Absolutely. Everyone is promising a
(08:32:23):
revolution.
Emma (08:40:10):
Right. But what we need, what you need are
(09:33:33):
specific, practical, measurable gains,
(09:57:17):
things that actually make a difference in
(10:38:48):
your day to day. So our mission today is
(11:32:12):
to cut right through that hype. We're
(12:13:43):
going to look at precisely how AI agents
(13:01:11):
are changing the, well, the fundamental
(13:36:46):
math of efficiency for ISVs, the
(14:12:22):
independent software vendors.
Ryan (14:30:10):
Yeah. And we're pulling these insights
(15:04:07):
directly from an expert analysis. It was
(15:43:44):
shared by Mark Hamblin of Insight Works.
(16:17:41):
This was during the 2025 Biz Apps Partner
(17:02:57):
Executive Summit, specifically in the ISV
(17:36:55):
Partner Breakout session. So this isn't,
(18:10:52):
you know, theoretical marketing stuff.
Emma (18:39:10):
Right. This is a technical blueprint.
Ryan (19:04:30):
Exactly. For how these specialized
(19:35:30):
logistics applications are fundamentally
(20:00:18):
changing.
Emma (20:10:30):
And that context is so crucial. I think
(21:03:21):
we're focusing on how AI is transforming
(21:49:35):
the core job of the isv, which is, you
(22:49:03):
know, making life dramatically easier for
(23:28:41):
the users, the people who deal with
(24:14:56):
complex physical products in that messy
(24:54:34):
0Emma: real world logistics environment.
Ryan (25:26:20):
Precisely. And the goal itself hasn't
(26:01:23):
changed. ISVs have always wanted to
(26:36:27):
maximize user output. Of course, what has
(27:17:22):
fundamentally changed, and this is really
(27:52:26):
the key takeaway here, is the execution.
(28:33:20):
We finally have the tools to deliver on
(29:20:06):
these, I mean, decades old aspirations.
Emma (29:56:30):
Okay, let's unpack that history, because I
(30:32:01):
think it makes the current shift even more
(31:12:37):
profound. For decades, the priority for
(31:43:04):
every software vendor was just this
(32:13:31):
relentless pursuit of efficiency.
Ryan (32:33:50):
Right. How do you make the user faster at
(33:13:37):
checking things in, moving things out or
(33:44:34):
fulfilling an order?
Emma (34:00:29):
And that focus, that historical focus, was
(34:35:44):
really distilled into a concept that Mark
(35:11:00):
Hamblin introduced years ago.
Ryan (35:32:30):
Yeah, he called it more value per click.
Emma (36:07:10):
More value per click. It's such a
(36:37:06):
powerful, simple metric, isn't it?
Ryan (36:58:30):
It is.
Emma (37:07:10):
It just immediately frames that
(37:32:02):
traditional goal. And back then it meant,
(38:06:50):
you know, know reducing the number of user
(38:46:38):
interactions to get something done.
Ryan (39:14:10):
If receiving a shipment took 10 steps
(39:44:02):
before, the goal was to find a way to make
(40:26:42):
it five clicks.
Emma (40:39:30):
And that was a huge undertaking.
Ryan (41:04:10):
Oh, massive. Think about the complexity
(41:44:56):
involved in shaving off just one click in
(42:39:19):
a mission critical workflow. Yeah, I mean,
(43:26:54):
that required huge database optimization,
(44:00:53):
restructuring UI layouts, maybe combining
(44:34:52):
several screens into One developers would
(45:15:39):
spend months trying to squeeze out these
(46:03:14):
marginal gains.
Emma (46:26:30):
So an incredible amount of manual effort
(46:59:10):
to save a user a little bit of manual
(47:41:10):
effort.
Ryan (47:45:50):
Exactly. But here's the crucial context.
(48:20:09):
When that idea was first introduced, it
(49:00:12):
was largely aspirational, right? The
(49:28:48):
technology just wasn't there yet. To
(50:03:08):
automate the most complex parts of the
(50:43:10):
workflow, the user had to be the one to
(51:34:40):
initiate those steps.
Emma (51:51:50):
But that barrier is gone now. And this
(52:39:28):
brings us right to the core of this
(53:27:07):
technical shift and why this old
(54:02:51):
aspiration is suddenly. Well, it's
(54:32:38):
completely attainable, Right?
Ryan (54:51:50):
We're transitioning from that aspiration
(55:26:09):
to the current reality. AI and agents.
(56:14:12):
These are the tools that finally turn more
(57:09:07):
0Ryan: value per click into an expected standard.
Emma (57:57:10):
And here's where the mechanism of the
(58:30:57):
shift becomes so powerful. We aren't
(58:59:55):
talking about AI as just a supporting
(59:33:43):
tool, like helping you write an email or
(60:12:20):
something.
Ryan (60:19:50):
No.
Emma (60:26:30):
According to the source material, AI is
(61:14:38):
now an engine for efficiency. It's
(61:55:54):
fundamentally integrated into the
(62:23:24):
application itself.
Ryan (62:38:30):
And this is the key technical insight we
(63:25:16):
need to focus on, especially for you in
(64:12:02):
the logistics space. Historically, the
(64:41:16):
user initiated almost everything based.
Emma (65:10:30):
On what they saw on the screen.
Ryan (65:34:30):
Exactly. Now, agents can respond
(66:08:50):
dynamically to external events, and this
(66:50:02):
is critical. Trigger automated processes
(67:24:22):
entirely on their own.
Emma (67:55:50):
That idea of responding to an external
(68:28:54):
event, that changes the entire dynamic.
(68:57:15):
What kind of external events are we
(69:30:19):
talking about here?
Ryan (69:44:30):
Well, we're talking about real time data
(70:22:32):
from the outside world that doesn't depend
(71:00:35):
on a user hitting refresh. Think about
(71:38:37):
integrating webhooks from shipping
(72:00:21):
carriers. An external event could be the
(72:38:24):
carrier's API pinging your system with an
(73:16:27):
updated eta, or a confirmation that a load
(73:59:55):
just left the depot.
Emma (74:24:20):
So the agent sees that status change
(74:57:18):
before the user even opens the order
(75:30:17):
screen.
Ryan (75:35:00):
Absolutely. Or in a warehouse, an external
(76:19:39):
event might be a sensor reading, a
(77:04:19):
temperature probe spiking, a door
(77:36:13):
unlocking, a weight sensor tripping. When
(78:14:30):
an item is placed on a loading dock, the
(79:11:55):
agent observes the physical world,
(79:43:49):
recognizes that trigger, and then
(80:15:43):
autonomously performs the necessary
(80:41:14):
software response.
Emma (80:58:00):
Which means the user is suddenly relieved
(81:35:36):
of one of the biggest burdens of business
(82:18:34):
software. They are no longer required to
(82:56:10):
babysit every single transaction. The
(83:23:01):
software is starting to think ahead for
(84:00:37):
them.
Ryan (84:08:40):
That's it. If we connect this to the
(84:54:41):
bigger picture, it means the system
(85:29:12):
handles all those routine actions in the
(86:09:28):
background. Confirming a delivery
(86:32:29):
notification, generating a goods.
Emma (86:55:30):
Received note, all the little repetitive
(87:25:47):
steps.
Ryan (87:30:50):
The system just manages those, reducing
(88:09:36):
the need for that constant manual
(88:48:22):
interaction.
Emma (88:57:30):
But wait, this sounds amazing, but where
(89:36:58):
does the margin for error creep In, I
(90:22:04):
mean, if you're relying on the system to
(91:07:10):
confirm a receipt automatically, doesn't
(91:35:22):
that demand almost perfect pristine data
(92:09:11):
quality?
Ryan (92:17:30):
That's a critical question. And yes,
(92:52:51):
achieving this no click efficiency
(93:22:19):
absolutely requires extremely high data
(93:51:47):
quality. Okay, but that's the beauty of
(94:33:02):
the agent structure. The system is
(95:08:23):
designed to handle the say 80 or 90% of
(96:01:25):
transactions that are routine. And the
(96:36:47):
exceptions, it's the 10%, the exceptions
(97:12:08):
that it flags for human intervention.
Emma (97:47:30):
Okay, so let's focus on the outcome of
(98:21:08):
that. The no click workflow.
Ryan (98:42:10):
This is where we see that aspiration of 178 99:29:50,000 --> 100:11:32,500 Ryan
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