What an AI-Native General Ledger Means for FP&A: John Glasgow

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现在，让我们进入节目正题。

And now, onto the show.

来自Data Rails，这里是今天的FP&A。

From data rails, this is FP and A today.

欢迎收听今天的FP&A。

Welcome to FPNA today.

我是您的主持人格伦·霍珀。

I'm your host, Glenn Hopper.

今天的嘉宾是Campfire公司的首席执行官兼首席财务官约翰·格拉斯哥。Campfire是一款原生AI驱动的ERP系统，旨在帮助高增长企业更快完成结账、从会计数据中获得更深入的洞察，并在无需组建庞大财务团队的情况下实现规模化发展。

Today's guest is John Glasgow, CEO and CFO of Campfire, an AI native ERP built to help high growth companies close faster, get richer visibility from their accounting data, and scale without having to build an oversized finance team.

约翰是一位有FP&A和战略财务经验的从业者，曾任职于Adobe。

John's an operator who has spent time in FP and A and strategic finance, including at Adobe.

他还通过合作伙伴关系和产品工作，亲身体验了技术栈的另一面。

And he's also lived the other side of the stack through partnerships and product work.

在创立Campfire之前，他曾担任Invoice To Go的高管，并主导了该公司以6.25亿美元出售给Bill.com的交易。

Before founding Campfire, he was an executive at Invoice To Go and led its $625,000,000 sale to bill.com.

随后，他加入Bill.com，负责业务发展和合作伙伴关系。

Then he joined bill.com to lead business development and partnerships.

Campfire的诞生源于对传统ERP系统的亲身挫败感，以及财务团队为使报告可行而不得不付出的‘摘要税’。

Campfire came out of firsthand frustration with legacy ERPs and the summarization tax that finance schemes pay just to make reporting workable.

自推出以来，Campfire已加入Y Combinator，并筹集了超过一亿美元资金，旨在为AI时代重建总账系统。

Since launching, Campfire has gone through Y Combinator and raised over a $100,000,000 to rebuild the general ledger for the AI era.

在本集中，我们将深入探讨是什么促使约翰挑战总账系统，Campfire有何不同之处，以及这对希望获得更佳洞察力、却不愿把大量时间花在数据准备上的FP&A团队意味着什么。

In this episode, we'll dig into what pushed John to take on the GL, what Campfire is doing differently, and what it means for FP and A teams that want better insights without spending all their time prepping data.

约翰，欢迎来到FP&A今天。

John, welcome to FP and A today.

格伦，谢谢你的邀请。

Glenn, thanks for having me.

非常高兴能来到这里。

Really excited to be here.

我一直是这个节目的粉丝，很荣幸能作为嘉宾参加。

Definitely a fan of the show and excited to be a guest.

是的。

Yeah.

我也是。

Likewise.

我也很欣赏你，我知道我们之前在其他播客里也聊过。

And I'm similarly fan of yours, and I know we've talked on on other podcasts before.

很高兴能再次交谈，深入探讨一下。

So just happy to to be talking again and to really dive in.

我很喜欢你们在Campfire所做的工作，非常期待和你聊聊这个话题。

I love what you guys are are doing at Campfire, and I'm I'm really looking forward to talking about it.

谢谢。

Thank you.

谢谢。

Thank you.

是的。

Yeah.

我的意思是，这是一段有趣的旅程，我很高兴今天能分享更多。

I mean, it's it's been a fun journey, and I'm excited to share more today.

很好。

Great.

很好。

Great.

好的。

Alright.

那我们就开始吧。

Well, let's let's dig in then.

所以我们的观众会很喜欢这一点，你在成为创始人之前，曾多年从事财务规划与分析和战略财务工作。

So for our audience is gonna love this, that you spent years in FP and A and strategic finance before becoming a founder.

那么，带着这种视角，你在那段运营期间最具有塑造性的经历是什么？这些经历如何影响了你今天对财务系统的看法？

So with that lens, what were the most kind of, I I don't know, formative experiences during that operator period that kind of shaped how you think about finance systems today?

是的。

Yeah.

这是个很好的问题。

It's it's a great question.

有几个时刻特别让我印象深刻。

There's a few moments that that really stood out.

其中一个是在大规模的公开市场中的经历。

One was in the public markets at scale.

在Adobe，我负责战略财务，花了大量时间分析数据。

So at Adobe, I was in strategic finance and spent a lot of time analyzing data.

最终，我学到了几个关键的经验。

And ultimately, there was there was a couple key learnings.

其中一个经历是，作为财务团队，我们实际上在分析所有的历史数据和会计数据。

One was, as the finance team, we were actually analyzing all of the historical data, all of the accounting data.

而会计团队则负责准备这些数据。

And the accounting team was preparing the data.

我觉得，我们的会计团队本可以花更多时间来分析这些历史数据，或者说会计数据。

And I thought there was an opportunity for our accounting team to spend more time analyzing historical data or call it accounting data.

因此，我认为角色上存在一种自然的转变，而我们希望在Campfire中扮演一小部分角色，通过赋予会计团队超能力，让它们变得更加战略性。

And so I think there's, like, a natural shift in the role that, you know, we'd like to think we're playing a small part in at Campfire in allowing the accounting teams to be even more strategic by giving them superpowers.

另一个重要的经历发生在私有市场的Invoice To Go公司。

And I think the other big one was at Invoice To Go in the private markets.

我们是一家C轮融资的科技公司，主营发票软件。

We were a series c tech company, and we were an invoicing software.

在财务、企业并购和合作伙伴关系等领域，由于公司规模较小，我的职责非常广泛，我亲眼目睹了市场上缺乏优秀的软件。

And in finance, in corp dev, and partnerships, and just very broad role given our our size, for me, I saw firsthand that there was not great software.

当时市场上并没有适合中型企业的优秀ERP系统。

There was not great ERP for a mid sized company that existed in the market.

我们出去调研了一下，发现有一些大型的遗留系统供应商。

And we went out and looked, and there were some big kind of legacy incumbents.

但最终我们意识到，为什么没有一款现代化的ERP系统？作为客户和合作伙伴，我在这一领域花了整整十五年时间。

But ultimately saw, like, why is there not a modern ERP and spent a lot of time as a customer and as a partner in this category, fifteen years.

因此，我积累了很多关键经验，这些经验塑造了我作为创始人的经历。

And so just a a lot of key learnings that kinda shaped my experience as a founder.

你可能会认为，要解决总账问题，应该先走注册会计师审计这条路。

You know, you would think to tackle the GL that you would come up through the sort of the CPA audit path and all that.

但你其实是特许金融分析师。

And you're you're a CFA.

对吧？

Right?

我在你的领英资料上看到过这个信息吗？

Did I see that on your on your LinkedIn?

是的，我确实是。

I am.

是的

Yeah.

十多年前了。

Over ten years ago.

但没错，2014年我获得了CFA资格。

But, yeah, 2014 got the CFA designation.

是的

Yeah.

而且，在我职业生涯早期，当我还是一名有志于成为CFO的人时，当时有很大压力，认为没有CPA就永远当不了CFO。

And that's, I guess, early in my career before, you know, as I was an aspiring CFO, there was that big pressure that, well, you you could never do the CFO role without a CPA.

我认为这个角色已经发生了很大变化。

And I think the the role has changed a lot.

当然，会计部分非常重要，这一点你可能比我更清楚，因为你一直在搭建总账。

And, obviously, all the accounting part is very important as you realize probably way better than I do building out the the ledger.

你看待总账的方式更像一个下游数据使用者，而不是典型的CPA或只是关注会计端的记账和录入工作。

You looked at the ledger differently more as like a downstream customer of the data that comes from it than the typical CPA or, you know, just going through the the accounting side, what's being booked and entered and all that.

你认为这种财务视角，是否让你对总账的看法与那些拥有传统会计背景的人有所不同？

Do you think that that finance lens made you think of the ledger differently maybe than someone with that sort of traditional accounting background would?

我的意思是，你能想象一个会计师发现了Campfire吗？

I I mean, look, I could an accountant found Campfire?

是的。

Like, yes.

但我必须说，对我影响深远的一件事是Invoice To Go的收购。

I but I I I will say, one thing that was formative for me was the Invoice To Go acquisition.

所以我们最终在没有投行参与的情况下完成了收购。

So we end up being acquired with with with no banker through the sale.

这笔交易的双方都没有投行介入。

There was no banker actually on either side of the transaction.

因此，我深度参与了整理核心会计数据，比如各部门的供应商支出。

And so I got really involved in pulling together just kinda core accounting data, vendor spend by department.

甚至由于我们的ERP系统设置，合并全球子公司的报表实际上都非常手动。

Or just even consolidated global reporting across subsidiaries was actually quite manual given our ERP setup.

于是，出现了一种新的视角，让人不禁问：为什么一切都这么手动？

And so there was like this new perspective coming in as like, why is everything so manual?

为什么一切都这么混乱？

Why is everything so broken?

问题不在团队，而在于软件。

And it wasn't the team, it was the software.

团队已经尽其所能地用各种临时办法来修补了。

The team was doing everything they could to to band aid together.

很多简单的集成功能都缺失了，他们说：嘿，这个集成就是不行，或者全球合并功能根本没法正常工作。

There was just a lot of missing, like, simple integrations, and they're like, hey, the integration just, you know, doesn't work right, or the global consolidation just doesn't work right.

因此，在深入梳理这个过程时，因为我们收到了500项尽职调查请求，而我正是负责主导这次出售的人。

And so there the more I unpacked through that because we had 500 diligence requests, and I was the one leading the sale.

所以我最终必须完成所有这些要求。

And so ultimately, I had to deliver them all.

于是我卷起袖子，深度参与，整理所有数据，并把它们交付给收购方。

And so I end up really rolling up my sleeves, getting super involved in pulling together all of the data and getting it out the door to the acquirer.

于是我就把2021年大部分时间都花在了核心会计流程上，深入理解会计工作是如何运作的，这让我真正意识到：我们需要重新思考整个软件层，为这些团队提供优秀的软件，让他们能专注于自己最擅长的事情。

And that just call it the the the 2021, spend so much time on core accounting workflows and understanding, like, how core accounting works that it really led me to say, like, we need to rethink the entire software layer, get these teams some great software, and allow them to do what they do best.

天啊。

God.

这真的很有趣，因为我以前从未这样想过。

That's really interesting because I hadn't really thought about that before in that way.

在我担任CFO之前，我像我说的那样，是从财务规划与分析（FP&A）这条路径成长起来的，那时我才真正开始学习会计。

So I, before I was a CFO, I came up, like I said, through the the FP and A side and I really started learning about accounting.

我在电信行业工作，每年都会经历几次并购。

I was in telecom and we went through a couple of mergers and acquisitions every year.

老实说，我认为正是在那里，我第一次了解了会计以及我们从会计部门获取的数据类型，意识到那不过是试算平衡表，还要从所有这些数据中提取一切。

And honestly, I think that's where I got my first understanding of accounting and the type of data that we were getting from accounting and just realizing, you know, it's trial balance and trying to pull everything out of all that and everything.

那时候我其实并不知道——这已经是很多年前的事了，我们根本没有现在的技术。

I didn't really you know, this was a million years ago too, so we didn't really have the technology.

那时候，你知道的，数据室真的是实体房间，你要亲自去那里翻阅资料。

It was kinda you know, this is back when data rooms were actually a physical room and you were going through that.

所以并购看起来确实是让那些没有会计背景的人深入整个尽职调查过程的好方式，因为你必须真正理解调整后的EBITDA以及尽职调查期间所做的一切。

So but that is M and A seems like a good way to really for people who didn't come up through that accounting background to really be able to dive in that whole due diligence process when you've really gotta understand, you know, you're getting to adjusted EBITDA and everything you do during the the due diligence period.

这真的非常有趣。

So that's that's super interesting.

既然你提到了InvoiceToGo，你之前在那里，并经历了bill.com的收购。

And since you mentioned Invoice To Go, you were there, went through the bill.com acquisition.

所以我们之前聊天时提到过，你从账目的双方都经历过。

And so you we were talking before the show, you mentioned kind of being from that on both sides of the of the ledger.

那么，从这段经历中你学到了什么，直接促使你决定去解决最终的那个问题？

So what did you learn out of that that directly influenced the ultimate problem that you decided to try to solve?

是的。

Yeah.

我的意思是，InvoiceToGo当时有数十万客户，遍布全球超过150个国家，他们都在使用我们的开票服务。

I mean, Invoice To Go, we had hundreds of thousands of customers in literally every country, over a 150 countries using us for invoicing.

因此，我们与他们的ERP系统相连，并最终被一家应付账款公司收购。

And so we were connected to their ERP, and we sold to an accounts payable company.

所以我当时在现金流入这一端，后来又转到了现金流出这一端。

So I was on, like, the cash in side and then went to the cash out side.

因此，从ERP的一端出发，通过被bill.com收购转到另一端，我接触了各种ERP系统，也花了一些时间在合作伙伴领域。

And so being on one side of the ERP and moving to the other via the acquisition to bill.com, operated with the ERPs, and spent some time in the partnership world as well.

所以作为客户，正如我之前提到的，但同时作为合作伙伴，我发现我作为客户感受到的挫败感，其实也以同样方式在合作伙伴层面大规模地存在。

So as a customer, as I acknowledged there, but then also as a partner, saw that the the frustration that I felt as a customer was actually being felt at scale via the partner hat that I wore.

这成了一个持续的主题：天啊，所有的ERP系统都过时了，而我们的工作方式却已经不同了。

And it was like this kind of constant theme of like, gosh, all the ERPs are outdated, and how we work is differently.

感觉像我这样的人，根本没参与过我所使用软件的开发，这种普遍的挫败感无处不在。

And it feels like someone like me, you know, wasn't involved in building the software that I used, and there was just this general level of frustration.

我看到这种问题如此普遍。

And I just saw it so widespread.

在收购合并后，我们拥有了合计50万客户，这些企业遍布全球，都在说：我们需要一个更好的ERP系统。

We had combined 500,000 customers in the post acquisition world, and these are businesses all over the world saying like, hey, we need a better ERP.

因此，我认为这给了我一个非常直观的视角，让我意识到我亲身经历的这种痛苦，其实广泛存在于整个行业。

And so I think as being a call it a first just like a a great visible perspective into this, like, pain that I felt that I could like, hey, it's actually widespread.

于是我有了这个想法，也许有点疯狂，但我可以进去做点什么来改变现状。

And I got this idea, and maybe it's a little crazy, that I could go in there and do something about it.

这对我来说太不可思议了，因为多年来，有那么多人有着完全相同的挫败感。

That's so wild to me because so I mean, for years, so many people had that exact same frustration.

但你竟然决定投身于此，我很好奇，是否有一个特定的时刻，让你从‘这真让人沮丧’转变成‘好吧’？

But to go and and make the decision that you did to go, you know, go in on this, I'm wondering, was there, like, a specific moment when you went from, yeah.

总账必须彻底抛弃，从零重建。

This is frustrating to, okay.

我就是那个能搞定这件事的人。

The general ledger needs to be thrown out, rebuilt from scratch.

有没有那么一个瞬间？是逐渐形成的，还是像大马士革之路那样的顿悟时刻，让你突然有了这种领悟？

I'm the man to do this.

是的。

Was there something was it a a gradual, or was it more of that, like, Road to Damascus moment where you just had this epiphany around it?

是的。

Yeah.

确实有一个关键时刻。

There was definitely a moment.

我们的客户包括许多ERP系统的最大合作伙伴。

I mean, we were the largest partner for for many of the ERPs.

我花了很多时间与所有知名企业的高管层打交道。

And I spent a lot of time at the executive level with with all of the household names.

我记得其中一位高管，一位拥有C级头衔的人，专程飞过来，与我一对一见面。

And I remember one of them, an executive, someone with a c level title, and I won't name any names, flew out, and one on one met with us, met with me, one on one.

他告诉我：我们就是ERP系统，每个客户都会先把你踢走，也不会踢走我们。

And told me like, we are the ERP, and literally every customer will rip you out before they rip us out.

所以，要与我们合作、拥有共同客户，就得付这笔费用。

And so here's the tax to do business with us, to have a joint customer.

这就是他们的条件：如果你不支付这笔突然出现的天价账单，我们就直接终止你的共同客户体验。

And as this is the offer, and we're just shutting off the joint customer experience if you don't pay this obscene bill that came out of nowhere.

那笔金额高得惊人。

And it was it was a shockingly large number.

我认为，这一点，以及所有其他合作伙伴，都纷纷找到我，说：你能帮帮我们吗？

I think this, and all literally all the other partners were coming to me in the ecosystem and saying like, can you help us?

我们都收到了同样金额巨大的账单。

We're all being sent the same kind of large bill.

让我感到震惊的是，现有的ERP公司如此短视，他们竟然如此自信，认为从合作伙伴和客户的角度来看，根本没人有别的去处。

And I think it was shocking to me that the existing ERPs were so shortsighted in how they thought, that actually, they they felt so confident enough that literally nobody had anywhere else to go from a partner and from a customer perspective.

他们说，作为客户，切换成本太高，无法离开我们；而在我们所处的行业和规模范围内，市场上根本不存在其他选择——他们就是这么运作的。

They're saying like switching costs are too high to leave us as a customer, and there's literally no other options in the market for, you know, the vertical that we're in, and the size that we're in, and that's literally how they were operating.

有一天晚上，我坐在晚餐时，心想，这个市场简直太糟糕了。

And so I was sitting down one night at dinner, and I was like, this market is just so broken.

我气得不行，正是在那一刻，我决定要亲自做点什么来改变它。

And I was literally so upset that that was literally the moment that I decided I was gonna personally do something about it.

我很喜欢这一点。

I love that.

而且，你知道，我与各种ERP都有合作。

And I, you know, I work with ERPs across the board.

我不想对任何一方妄加评判，但如果你看看市面上那些大型ERP系统，它们几十年来看起来都一模一样。

I don't wanna cast aspersions one way or another, but if you look at the big ERP systems that out there that are out there, they look the same for decades.

只是被推着去创新。

And it was just pushed to innovate.

没有竞争对手，因为他们知道，虽然不完全是垄断，但他们的市场份额确实非常稳固。

No competitors because they knew they had the I mean, it's not not exactly monopoly power, but they were in a strong, you know, whatever percent of market share or whatever.

我的意思是，当时市场上几乎没有其他选择，除非你记得，在这波新ERP出现之前，大家都一直在谈论ERP的拆分，因为当时已经出现了很多不同的SaaS产品，人们觉得我们可以自己拼凑一套系统。

I mean, it was there just weren't a lot of options out there unless people were I remember for a while before this this wave where new ERPs were coming, everybody was talking about unbundling ERP because there were all these different SaaS products out there and people were like, well, we can basically put together our own.

当然，这样做带来了所有数据孤岛的问题，很难让这些系统彼此互通和数据流转。

Of course, that had all the data problems of having siloed data and being able to get them all to talk to each other and and pass through to each other.

但也许我本该先说这一点，我知道我们之前已经简单介绍了背景，显然Campfire就是一个ERP系统。

But and I guess, maybe I should have led with this, but and I I know we gave a little background and clearly, Campfire is an ERP.

但对于那些不太了解Campfire的听众，你能为我们介绍一下Campfire是什么，你们具体想取代财务体系中的哪些部分，而不是——比如说——

But for our listeners who haven't followed Campfire closely, could you walk us through what Campfire is and what part of the finance stack that you're explicitly trying to replace versus I don't know.

另一方面，你们又想与哪些系统进行集成吗？

Maybe there's some that you're trying to integrate with on the other hand.

这是个很好的问题，格伦。

It it's a great question, Glenn.

随着产品的发展，答案也在变化。

And the answer is changing as the product evolves.

这就是Campfire。

Here's what Campfire is.

我们是一款为现代中型和大型会计与财务团队打造的原生AI ERP系统。

We are an AI native ERP for modern, like, mid market and enterprise accounting and finance teams.

我真心想赋予他们超能力，这些是我当初担任这个角色时所缺乏的，无论是董事会报告、月度结账，还是我提到的并购工作。

And I really wanna give them superpowers, the superpowers that I didn't have when I was in the role, whether it was board reporting, whether it was just closing the month, or whether it was m and a that I described.

赋予他们自动化所有交易性会计和核心报告的能力，从而让他们专注于战略工作。

Giving them superpowers to automate all of the transactional accounting, the core reporting, and allow them to do strategic work.

专注于我过去没能花足够时间去做的战略工作。

Focus on strategic work that I was not able to spend as much time on as I wanted to.

这自然意味着我们能帮助他们更快地完成月度结账。

And this just inherently means like, we allow them to close the month faster.

我们还能帮助他们组建更精简的团队。

And we allow them to run a maybe a leaner team.

我知道很多人工智能领域的人士目前并没有增加编制，但他们的公司正在增长。

I know a lot of folks in the AI world are not getting a lot of headcount, but they're the company is growing.

我们帮助他们更快地完成结账和向董事会或其他利益相关者提交报告。

And we allow them to to deliver on kind of speed to close and speed to report to the the board or whatever their stakeholders are.

一些增长最快的人工智能公司，比如 Replit、Decacon 和 Posthoc，都是我们的客户，我们非常高兴能帮助他们实现规模化发展。

And some of the fastest growing AI companies like Replit and Decacon and Posthoc are customers of ours, and we're thrilled to to allow them to scale.

但我们也有医疗健康公司、航空航天公司，以及专业服务公司。

But we also have healthcare companies, we've got aerospace companies, we've got a professional services companies.

使用 Campfire 的客户群体非常广泛。

There's a broad array that are on Campfire.

感谢你的播客软件。

Shout out to your podcast software.

Zencaster 也是我们的客户。

Zencaster is a is a customer of ours as well.

这太棒了。

That's great.

而且我知道，我在人工智能和金融领域经常演讲，每个人都在为人工智能会抢走我的工作而陷入存在主义危机。

And I, you know, I I do a lot of speaking around AI and finance, and everybody's kind of having this existential crisis around AI is gonna take my job.

我觉得你刚才所经历和描述的那些，我不确定。

And I think what what you went went through and described there I I don't know.

我的意思是，显然，如果我们达到通用人工智能，那就会有完全不同的考量层次。

I mean, obviously, we reach AGI, you know, there's a whole whole different level of of considerations.

但你刚才谈到的，正是我一直在阐述的观点，我经常引用一句话。

But what you talked through there is is the same argument that I make of and there's a quote that I always use.

这是克利福德·斯托在八十年代，或者说是八十年代末说的，我想是这样。

It's Clifford Stow said this in in the eighties, think is or late eighties, I think.

是的。

Yeah.

我觉得这始于RPA，或者我们所经历的任何形式的自动化。

And I think of this as it started with, you know, RPA or whatever kind of automation that we've moved up.

但克利福德·斯托尔的原话是：数据不等于信息。

But it is the quote from Clifford Stoll is, data is not information.

信息不等于知识。

Information is not knowledge.

知识不等于智慧。

Knowledge is not wisdom.

智慧不等于理解。

And wisdom is not understanding.

我认为，如果你反过来想，就会形成一个金字塔结构：最基本的自动化只是把数据转化为仪表盘，将原始数据变成某种信息。

And I think if you flip that over, you kinda have this pyramid of where, you know, basic automation of just taking the data and turning it into a dashboard that turns that raw data into something's information.

现在我们正沿着这个层级向上推进，AI 能够完成的事情，已经超越了三十年前 ERP 系统刚诞生时的能力，也超越了它们后来迁移到云端时的功能。

And then we're kinda moving up that chain now where AI can start doing some more things than what ERPs could do thirty years ago when they were first built and then moved in into the cloud.

我认为 Campfire 正在做的事情——也许你可以帮我再稍微梳理得更清晰一点。

I think that what Campfire is doing is and and and maybe you can help refine this a little bit more.

但正如你所说，我看到的是，团队可以更小，而人类所贡献的价值却高得多，不再是像以前那样在不同系统间来回转手数据，或者只是加快对账速度、处理那些每天重复的例行任务，而是从无意识的机械劳动转向更有意识的深度工作。

But what I see, you know, like you said, you can have smaller teams, but the value that the humans are bringing is much higher than swivel chairing data from one system to another or the you know, if it if it speeds up reconciliations or sort of the repeatable tasks that we do every day going from kind of that mindless level work to more mindful work.

如果你使用 Campfire，你是否看到自己能花更多时间做真正创造价值的工作？我的意思不是说移动数据没有价值，但如果能自动化它，就像在制造业中引入机器人一样。

Do you see that come out of if you have Campfire, that you're able to spend more time doing that real value add work at the I mean, I'm not saying there's not value in moving data, but if we could automate it, it's like adding robots and manufacturing.

对吧？

Right?

是的。

Yeah.

AI 非常强大。

AI is is very powerful.

我认为我们都认同，我们并不清楚最终状态会是什么样子。

I think we're all aligned that, like, we don't know what the end state looks like.

它确实非常强大。

It is very powerful.

昨天，有人发给我一个上世纪五十年代的广告，说推出了一款新型会计打字机。

Yesterday, someone sent me an ad from, like, the nineteen fifties, and a new accounting typewriter had come out.

它真的能自动化很多总账任务。

And it was literally like automate a lot of the general ledger tasks.

它就像是加快了结账速度。

It was like speed up the close.

它就像是更快地对账发票。

It was like reconcile like invoices faster.

这实际上和我们在Campfire正在做的很多工作是一样的。

It was literally a lot of the same things that we're working on at Campfire.

显然，随着会计打字机的出现和演进，以及Excel的推出，会计岗位也发生了变化。

And obviously, the accounting role shifted as the accounting typewriter came out and evolved, and then Excel came out.

你可以由此看到会计整个演变过程。

And, you know, there you can talk to the whole evolution of accounting.

我们现在正处在会计的又一次变革中。

We're in another evolution of accounting.

我认为上一次大的变革是从本地部署到云端。

I think the last big one was on prem to cloud.

对吧？

Right?

我认为，由于数据的敏感性，财务工作负载是最后迁移到云端的之一，但它们现在已经进入云端了。

I think, like, financial workloads were some of the last ones to go into the cloud given the sensitivity of the data, but they have made it into the cloud.

许多从传统环境转向Campfire的人，仍然是从本地部署环境迁移到Campfire的。

Many folks from migrating to Campfire are still coming from an on prem environment to Campfire.

他们本质上跳过了一代被称为云1.0的会计软件，直接进入了AI原生软件的时代。

They're essentially skipping a generation of accounting software called Cloud one point o, you know, where the AI native software era.

所以我想说，我的建议是持续进化。

And so I would say, like, my advice is continue evolving.

持续重塑自己。

Continue reinventing yourself.

我的意思是，现在每个人都在谈论这样一句话：你不会被AI取代。

I mean, everyone's talking about this one adage right now of like, you you will not be replaced by AI.

你会被懂得如何使用AI的人取代。

You'll replaced by someone that knows how to use AI.

这话可能确实有些道理。

You know, there's probably some some truth to that.

但我的建议是，即使你还没准备好使用AI会计软件，也要持续学习。

But my advice is just continue learning even if you're, like, not ready for AI accounting software.

想想看，有哪些任务你可以用AI来自动化，哪怕只是用Chatty Bitty、Anthropic，或者某种AI工具。

Think about, like, what are some tasks you can automate to AI even if it's just in chatty bitty, or it's in Anthropic, or some some flavor of AI.

但要开始把它引入你的工作流程中。

But start to introduce it into your workflows.

就从这里开始。

Start there.

想想看，我们如何把交易性任务从依赖人转向依赖软件。

Think about, like, how do we go to software as opposed to people for transactional tasks.

如果是那种临时性的任务，比如我过去做过很多从零到一的财务模型，也做过很多一次性董事会的预测分析，比如‘如果我们做X会怎样？’

If it's something that's more ad hoc, like I've, you know, done a lot of zero to one financial models in my day, a lot of one off kind of board swags for, hey, what if we did x?

当然，这些永远都会用Excel来做。

Like, of course, that'll always be in Excel.

手动工作永远都会有需求。

There will always be need for manual work.

但如果是一些重复性任务，就在下一次结账之间的空档，看看能否将其自动化。

But if it's some repetitive task, take the time in between the next close, and look at if we can automate it.

无论是用AI还是其他方式。

Whether it's AI or otherwise.

先开始自动化吧。

Just start to automate it.

如果无法用基于规则的方法实现，那就转向AI。

And if you can't do it with rule based, then then go to AI.

我们已经看到，有人用AI在Campfire中编写应计项目。

And we've seen it, a, people are writing accruals with AI in Campfire.

有人在做波动分析。

People are doing their flux analysis.

有人在做重分类。

People are doing reclasses.

我们正在为他们处理大量交易编码工作，远超简单规则系统的能力范围。

We're doing a lot of the transaction coding for them way beyond what a simple rule based system can do.

这股力量非常强大，能帮助你将角色演变为我之前提到的那种形态。

There's a lot of power, and it can help you evolve the role into what I mentioned earlier.

我们的使命是给财务和会计团队赋予超能力，这实际上是在赋予你超能力，而不是取代你。

Our mission statement to give a superpowers to finance and accounting teams is really giving you the superpower, not replacing you.

你说话的时候，我想象有人从本地部署的会计系统转向最先进的AI驱动总账系统。

It's funny as as you were talking, picturing someone going from an on prem accounting system to the state of the art AI powered general ledger.

我想象着，财务和会计人员天生就倾向于规避风险。

I'm picturing this, like, finance and accounting people, we're we're risk averse by nature.

你不会希望财务领导层的人成为赌徒之类的。

You don't want anyone in finance leadership to be a riverboat gambler or whatever.

但我想象的是，那个多年来极度抗拒变革、可能有点固执的CFO，最终从本地部署系统转向Campfire，然后对其他管理层说：看吧，我早就告诉过你们，十五年前根本不需要花一年半时间实施ERP系统。

But I'm I'm picturing, like, the the super resistant to change for years, maybe curmudgeonly CFO that finally goes from on prem to Campfire and and telling the rest of the management team, see, I told you, we didn't need to spend a year and a half implementing an ERP fifteen years ago.

我们现在正迈向最前沿的技术，这将带来怎样的转变啊？我是说，很难想象从旧有的本地部署会计系统转向像Campfire这样的系统，会引发多大的变革。

We're now going to the state of the art, and that's gonna be I mean, I I can't imagine what level of shift that becomes to go from sort of limitations of an older on prem accounting system to something like Campfire.

是的。

So yeah.

不过，闲话少说，我想说的是。

Anyway, but apropos of nothing, I guess.

但当你解释这一切的时候，我脑海里浮现的就是这个画面。

But that was the picture as you were as you were explaining all that that went through my head.

对于Campfire的价值主张，特别是当我们面向FP&A听众时，那些整天做差异分析、预测和超越传统总账系统收支概念的利益相关者沟通的人，你觉得它的价值在哪里？

The the value proposition for Campfire, thinking about specifically talking to our FP and A listeners, you know, people who live in variance analysis and forecasting and stakeholder storytelling beyond just the the debits and credits that we think of with a typical general ledger system.

Campfire能为FP&A团队提供什么样的价值主张？

What is what is that value prop for the FP and A team that Campfire offers?

是的。

Yeah.

作为一名前FP&A和战略财务人员，你要真正思考一下，你其实是众多数据使用者中的一个。

I mean, as a former kind of FP and A strategic finance person, think, really think about, like, you are one of the many data customers of the data.

我认为，能为你提供高质量、详尽且标注清晰的数据，这才是理想的状态。

And so I think, like, getting you great, high quality, detailed data that's very well labeled, to me, is is the dream.

而在传统的ERP系统中，许多系统都无法处理大量数据和复杂的维度，但Campfire的核心能力恰恰在于它能处理极其庞大的数据量。

And so in a legacy ERP, so many of them can't handle large amounts of volume and complex dimensionality that Campfire at its core can handle incredible, incredible volume.

我们从未见过任何人，即使有五千万行的总账数据——这已经是惊人的数量了——你还能给我们提供如此详尽的信息。

We've never seen anybody, even with, you know, fifty hundred million rows of of ledger data, which is an insane amount, that you can bring us any amount of detail.

因此，人们转向使用Campfire后，就不再将数据汇总到总账中了。

So folks move to Campfire, and they stop summarizing data into the general ledger.

他们以更细粒度的数据直接导入会计软件。

They bring it in at a granular level into the accounting software.

抱歉。

Excuse me.

我们可以在子账簿层面做到非常详细，同时仍能汇总到总账。

We can be very detailed at the sub ledger level, and we can still summarize onto the general ledger.

但最终，你所有的数据集都会保留在ERP系统中。

But ultimately, you're gonna have the dataset in the ERP.

从审计的角度来看，审计人员非常喜欢这一点，因为他们无需再离开ERP系统去追溯其他地方的数据。

And this is like from an audit perspective, you know, auditors love it that they don't need to go trace everything outside of the ERP.

至于你提到的FP&A团队，无论是预测、按部门划分的供应商支出，还是按业务单元的其他数据维度，甚至是产品级别的贡献毛利，各种自定义维度都可以实现。

FP and A teams, to your question, like, whether it's a forecast, whether it's, you know, vendor spend by department with another cut of data, like, by business unit, all sorts of custom dimensions, like product level contribution margin.

我们的许多AI客户非常关注毛利和贡献毛利，如果你不够谨慎，这些指标可能在一个月内就出现剧烈变化，因为AI计算和令牌成本可能非常高，我们可以为客户层面、产品层面、贡献毛利层面提供极其细致的分析，并且能以更实时的方式获取这些数据。

Many of our AI customers are incredibly focused on, call it, gross margin contribution margin, and it can quickly, within a month, turn on you if you're not super careful because AI compute and token cost can be so high that we can bring in incredible granular detail for customer level, product level, contribution, gross margin level analysis, and and we can get it in a more real time view.

这就像是重新思考了FP&A的角色，以Adobe为例，我们花了数周时间对每个产品的LTV与CAC进行分析，最终几乎关停了一条产品线。

And so just like this rethinks the FP and A role that one example is at Adobe, we spent weeks and weeks doing an LTV to CAC analysis by product, and ultimately, like, essentially shut down a a product line.

那是一条较小的产品线，但我们还是关停了它，并将其并入另一条产品线。

It was a small one, but we, like, shut it down and we fold into another one.

但我们每18个月才做一次这样的分析，因为过程实在太耗时。

But we only did the exercise every 18 months because it took so long.

这主要是因为我们把所需数据的大量信息汇总到了系统记录源——我们的ERP系统中。

And it was largely because we were summarizing a lot of the the data we needed into the into the the system of record, our ERP.

所以，如果我们能获取到更细致的原始数据，是否就能加快工作的准备速度？

And so it's like, if we can get the granular detail, then can we, like, speed up the prep of the work?

那样的话，我们就能建立更紧密的反馈循环。

Then we have a much tighter feedback loop.

从而真正释放决策潜力，让团队能够基于数据采取行动。

Then we can actually unlock a lot of the decision making and allow folks to go act on the data.

因此，这一直是我在Campfire工作中最喜爱的部分之一——财务和会计团队会来找我。

And so that's been one of my favorite parts at Campfire is finance and accounting teams come to me.

有人刚刚告诉我，一个客户去董事会展示了他们自从使用Campfire后对营运资本的重新思考。

Someone just shared with me that a customer they went to the board and showed how they rethought working capital now that they're on Campfire.

首先，因为他们有时间了，因为现在他们的结账速度大大加快了。

A, because they had time, because they've they closed so much faster now.

他们重新设计了整个开票流程。

They've rethought the entire invoicing process.

其次，他们利用Campfire自动化了大量任务，因此能够以一种完全不同的方式去跟进客户账单，这最终演变成了一项重大的战略举措，并在董事会中进行了汇报。

But also, b, they used Campfire to automate a lot of the tasks, and so they're able to actually, like, go out to customers and, like, actually chase invoices in a complete different way, that it turned into this large strategic initiative that they brought to the board and talked about.

而这正是让我感到兴奋的地方。

And and and that's what gets me excited.

我认为，我们需要深入分析你提到的这些数据。

I think it's important that we double click on the data that you're talking about here.

因为当你谈到这些时，我在想Stripe的数据与总账中的数据之间的区别。

Because as you were talking about it, I'm thinking of Stripe data, for example, versus what's in the general ledger.

所以，也许我们先来看看你提到的摘要问题。

So maybe first, let's look at the summarization problem you talked about.

我本人也经历过这种情况，但我很想知道从你的角度看，这种痛点在实际的财务规划与分析工作中是如何体现的，以及当你获得更丰富的交易级细节后，会发生哪些变化。

And I've I've lived this experience, but I'd I'd love to hear from your side where you see that pain show up in in the real FP and A work, and and what changes when you get more that that richer transaction level detail.

是的。

Yeah.

有两个非常具体的领域。

Two two very specific areas.

一是财务规划与分析团队正试图更多地使用人工智能。

One is FP and A teams are trying to use AI more.

一个简单的例子：很多人会将预付费用汇总后录入他们的ERP系统，或者像你提到的，将收入数据汇总后录入ERP。如果你在这样一个汇总了收入数据的ERP系统上直接叠加人工智能，那么你几乎得不到任何有价值的洞察。

One simple example, so many folks are summarizing, like, their prepaids into their ERP, or to your point, the revenue data into the ERP, that if you slap AI on top of an ERP with summarized revenue data, then you're essentially gonna get no insights that are of any value.

但对于Stripe来说，即使你每月有1000万笔Stripe交易，我们也能将每一笔Stripe交易以记录级的粒度导入我们的收入辅助账簿，然后再在上面叠加人工智能。

So worry but for Stripe, even if you have 10,000,000 monthly Stripe transactions, we're able to pull in every single Stripe transaction at a record level into our revenue sub ledger, and then you put AI on top of that.

这种细节层次极其丰富。

That is incredibly rich detail.

因此，无论是手动操作还是使用AI分析数据，FP&A团队面对的都可能是100行或1000万行的汇总记录。

And so FP and A teams, whether they're manually doing it, or whether they're using AI to analyze the data, call it a summarized entry of a 100 rows, or 10,000,000 rows.

我们都知道，拥有这种丰富数据具有巨大的价值，因为这样就能完整保留各个维度：业务单元、客户、产品、地域等。

We all know that, like, there's this incredible value in having that rich because then you can the dimensionality is all in place, business unit, customer, product level, geo.

你可以实现从月度到每日，甚至每小时的实时可见性。

You have, like, through the month, daily, even hourly visibility.

你甚至可以观察整个月份内的季节性变化。

You can look at seasonality through a month.

你还可以在月度内及时调整，因为数据会按照小时等频率持续流入。

You can even course correct through a month because data is kinda piping in, you know, whatever cadence hourly.

仅凭收入子账簿的数据，你就能够做很多事情。

There's just a lot that you can do with just the revenue sub ledger data alone.

是的。

Yeah.

而这正是我想谈到的持续结账和实时可见性，因为多年来，你们这些软件公司一直在谈论持续结账，大家都在努力向这个方向迈进。

And that's I wanna get to that sort of continuous close, that real time visibility, because that's, you know, your software companies out there for years have been talking about continuous close, and everybody trying to move to that.

真正实现这一点的人数非常少。

The number of people who've actually gotten to it is very low.

但即使没有完整的结账流程，正如你所说，在月中深入分析这些数据，能够实时做出修正，也是非常重要的。

But even without the full close, like you said, drilling into that level of data during the month, pretty significant when you can make real time corrections.

但你也提到了最丰富的数据集。

But you also talked about the richest possible dataset.

我在想，这涉及到维度、标签、收入相关数据，以及客户和产品属性。

And I'm thinking about that in terms of dimensions, tags, revenue artifacts, and customer and product attributes.

在实际操作中，对你来说，‘丰富’意味着什么？

In practical terms, what does rich mean to you?

我想知道，你们所采用的方法，为什么传统的ERP系统没有做到这一点？

And I guess the approach you've been able to take, why have the legacy ERPs not done that?

为什么历史上实现这一点一直这么困难？

Why has it historically been so hard to do that?

是的。

Yeah.

而且，你可以说，好吧，我可以去其他系统里获取数据。

And look, you can say, like, well, I can go into some other system and grab data.

但如果你想计算贡献毛利、业务单元，你就需要从ERP系统中获取成本端的所有数据。

But then if you wanna do contribution margin, you wanna do business unit, you need everything from the ERP, from the cost side to do it.

传统的ERP系统，其大部分代码都是在九十年代编写的。

The legacy ERPs, fundamentally, most of the code was written in the nineties.

所以我认为，仅仅因为我们年轻了大约二十五年，在数据架构上就拥有根本性的优势。

And so I think just being, call it twenty five years younger, there's just a fundamental advantage that we had from a data architecture.

作为这些系统的前客户，我知道它们哪里出了问题。

And for me, as a former customer of the systems, I knew what was just broken with them.

其中一个问题是可扩展性、维度数量，以及作为最终用户配置它的便捷性。

And one of them was scalability, and and dimensionality, and the ease of configuring it as an end user.

因此，我们将这些特性融入核心，仅仅因为更年轻、诞生于AI时代，并且构建在云基础设施能够以九十年代无法实现的方式扩展的环境中，我们就拥有巨大优势。

And so, like, putting those into the core, we just have a big advantage of just being younger and built in the AI era and built in an era where cloud infrastructure scales in in ways that it that it did not when, you know, architecture was architectural decisions were made in the nineties versus now.

是的。

Yeah.

还有，我记得我当时是下游用户，所以根本不知道我们到底有什么功能。

And the other like, I remember and again, I was downstream of it, so I don't know what capabilities we even had.

但当我还在电信行业时，上世纪九十年代末到二十一世纪初，我们拿到的数据类型，我现在都记不清了。

But my first when I was in telecom, late nineties, early two thousands, the type of data that we got I I don't even remember.

我只是个客户，那时候我还没接触过ERP和会计系统。

I just and again, I was a customer, and this is before I got into ERPs and accounting systems.

我只是在等财务部门的报表，但那时候我根本没听说过标签和维度这些概念。

I was just waiting on the reports from from accounting, but I don't remember tags and dimensionality back then.

我不记得在我的职业生涯中，这些功能是什么时候出现的，但我们现在讨论的，是完全不同的新层次——AI驱动的自动打标，这太重要了，它几乎能从第一笔交易开始就自动工作，而不需要之前那些复杂的规则。

I don't remember at what point in in my career those were were added, but we're at a whole new level with what we talked about before the show, where you have AI enabled auto tagging, which is so significant that can work basically from that first transaction without all the elaborate rules that you'd have to have around it.

所以我特别关注AI驱动的自动打标功能，就像你说的，它能从第一笔交易就开始运作，而无需设置这么多复杂的规则。

So I'm I'm particularly interested in AI enabled auto tagging that can work, as you said, from that first transaction without having to put in all these elaborate rules.

这会如何改变维度的经济性呢？

How does that change, I don't know, the economics of dimensionality?

那么审核和审批流程会变成什么样，才能让财务团队确信，无论是人工还是AI打的标签，信息都是准确无误的？

What does the review and approval workflow look like so that finance teams can stay confident that whether it was tagged by a human or the AI that that the information is tagged correctly?

这是个很好的问题。

That's a great question.

很多人问我，什么是原生AI的ERP系统？

So many people ask me, like, what does it even mean to be an AI native ERP?

我们是唯一拥有自己基础模型的ERP系统。

And we are the only ERP with our own foundational model.

因此，我们经历了非常痛苦的过程，构建了自己的前沿模型。

And so we've gone through this very painful exercise of building out our own frontier model.

这意味着我们能够在非常安全的环境中，利用现代新一代AI技术，让每个客户都拥有一个针对其自身数据微调的专属模型。

And what that means is we're able to, in a very secure environment, harness modern kind of next gen gen AI, and allow each customer to have their own model running that's fine tuned for their own data.

我们能够实现许多人都认为过去不可能做到的事情——比如，进行全方位的维度标签工作实在太耗时，或者我们的团队没有时间去管理这些复杂的标签。

And we're able to take what many would say was, like, previously not possible, which is, like, it was too much work to do all of the dimensional tagging, or our team doesn't have time to manage the nth.

当我提到维度时，可能指的是客户层面的毛利率。

And when I say dimension, it could be, like, customer level gross margin.

对吧？

Right?

你们在标记计算资源吗？

Are you tagging, like, you know, compute?

你们甚至会在客户层面、区域层面，或者任何粒度级别上做标记吗？

Are you tagging even the team at a customer level or region level or really any level of granularity?

它可能只是部门级别的运营支出。

It could just be department level OpEx.

因此，通过自动化更多的成本归因，你们可以为ERP的数据客户提供更精准的分析。

And and so, like, allowing you to automate more of the attribution of cost allows you to have, again, for the data customers of the ERP.

所以这实际上意味着，规则固然不错，但每个人最终都会拥有数百条规则，然后变得非常繁琐且难以管理。

And so what it really means is, like, rules are great, but everybody ends up with hundreds of rules, and then it becomes very unwieldy and hard to manage.

然后你们还得不断添加新规则，每次有组织调整时，都得重新调整所有规则。

And then you're always adding more, and every time there's this apartment change, you gotta redo all the ruling.

这样一来，就变得不可持续了。

And so that becomes untenable.

它在总账科目方面很有用，但对于人们所需的长尾维度来说就不够用了。

It's great for, like, chart of account, but for the long tail of dimensionality that folks need.

我们发现很多工作都是在电子表格中完成的，里面充斥着VLOOKUP、求和以及各种复杂的操作。

We're seeing a lot of it was just being done in spreadsheets, and there's v lookups and summits and all sorts of gymnastics going on.

所以问题是，我们如何将那些非常干净的数据集卸载下来——好处是，会计人员非常擅长对数据进行标记。

And so it's like, how do we offload what is very clean dataset, which is the good thing is accountants are very good at tagging data.

我们拥有非常干净的数据，而生成式人工智能在干净数据上表现得尤为出色。

We've got very clean data, and Gen AI thrives with clean data.

因此，我们的基础模型在自动化大量标记工作方面表现得极为出色。

And so our foundational models are doing an incredibly good job at automating a lot of the tagging.

当然，如果准确率不是100%，系统会将结果发送给你审核，你也可以自定义自动化的程度。

And, of course, it sends to you for review if it's not a 100%, and you can customize how automated it is.

而且我们现在已经有上市公司在使用，所以我们已经做了大量工作来支持AI环境下的SOX合规。

And we're in a we have public companies today, so we've done a lot of work to support kind of socks in a AI world.

但我要说的是，这赋予了会计团队超能力，让他们能够以极高的准确率标记更多数据，从而为数据使用者提供更全面的数据可视性。

But I'll I'll say, it has allowed the accounting team to, again, give them the superpowers by tagging more data with a, you know, high degree of accuracy to provide more data visibility for the data customers.

这些数据使用者可能是销售、市场、董事会，任何利益相关方，包括财务规划与分析团队。

And that could be sales, marketing, the board, really any stakeholder, including FP and A.

这对我来说非常有趣，我相信这其中有很多是独家秘方和专有信息，也是Campfire出色的原因之一。

This is super interesting to me, and I'm sure there's so much in this that is secret sauce and proprietary information and part of what makes Campfire great.

但我必须更深入地了解一下，你们自己训练了模型。

But I have to dig into this a little bit bit more that you guys trained your own own model.

因为我觉得，目前前沿模型中包含的都是通用信息，它们已经非常强大，而且有大量开源和开放权重模型可供使用，人们甚至可以自行运行这些模型。

Because I think with all the the generalist info that's in the frontier models right now, and they're so good, and there's so many open source and open weight models out there and and models that people can run.

对于大多数事情来说，拥有这些世界上最聪明的通用型大语言模型已经足够了。

And for most things, having, you know, these LLMs that are the world's smartest generalist are sufficient.

但显然，当你拥有超出RAG系统、自定义GPT或其他方案之外的专有信息时，就能针对你的具体目标实现高度精准的定制。

But, obviously, when you have that proprietary information beyond what you would put in a rag system or a custom GPT or whatever, you can get hyper specific on what you're trying to do.

我不会深入探讨你们模型中那些风格或所谓的秘密部分，但我一直在思考，我不知道。

And I'm not gonna get into all the, you know, style, you know, the the the sort of the secret parts of your model, but I think about and I don't know.

也许它已经被成功地应用了。

Maybe it is being used to great success.

我只是不清楚，因为这是专有的，仅限于他们内部使用。

I just haven't it's proprietary and within their organization.