Show HN: I've been building an ERP for manufacturing for the last 3 years

Feel free, my email is my HN username at gmail. As I mentioned in a sibling comment, I'm not in tech anymore (except for fun) but I'm happy to provide any insights or advice to any questions you may have. I last worked with ERP systems about 10 years ago, but the thing about these systems is that they don't really change, so hopefully my knowledge is still helpful!

As a quick summary, this is mostly all ETL (Extract, Transform, Load). Learn the lowest practical level language you can for each system so you can extract / query exactly the data you need (in SAP it's mostly SQL but there are a bunch of proprietary "languages" and extensions that can help. In MS it's mostly SQL, in Infor it's worth learning some RPG /CL, but only enough to get the data you need). Learn the notification paradigms each system offers (this can be as simple as scheduling jobs, it can be file-system watchers, it can be RPC based, etc. etc. Each system is different, but you need to know when to do stuff with the data. Both on change from external influences, and on completion of whatever job you ran). Thirdly, utilise a modern language for the "Transform" and "Load" phases of the job. I used to use everything from C, C#, Perl, Python, etc. These languages are much easier and much more powerful than something like RPG or pure SQL for a non-maestro. There are people who use complex stored procedures for everything, and that's cool, but it's also a steeper barrier of entry than using a modern, "batteries-included" language.

The reason I initially taught myself Go (13 years ago now) was due to the incredibly powerful and simple data manipulation packages built into it's standard library. It's a damn good language for doing high speed, low latency transformation of lots of data, while being simple and easy to code and deploy. Having said this, the afore-mentioned C, C#, Perl and Python were all working fine before I switched to Go! Use what you know, and what's available in the sytem you're working on.

If you have any questions feel free to send me an email.

Hey guys, Jeremy from UMH (www.umh.app) here. We are OSS as well and focus on data infrastructure for manufacturing. Let me write you guys via Discord to get in contact

I built a chat interface in 2017 (this was with chatscript dialog trees with hole-filling and semantic search) that was ostensibly to prevent our data scientists from redundant work, ie, before they spent all day writing a SQL script, describe the job of the script and see if one already exists. The chatbot would then ask for the parameters required for a script, run the job, and then present a CSV of the returned data.

As we collected user feedback and refined the UX, we got closer and closer to an option tree that could be better represented by a drop down menu. It was kind of depressing, but I learned that the actual job of that R & D wasn't to come up with a superintelligent chatbot that replaced data scientists, it was to come up with the infrastructure that would allow data scientists to put their python scripts in a common repository to allow re-use without re-installing locally and screwing around with pyenvs.

Anyway, I'm also traumatized by my involvement with a YC startup that actually had a very good (if ENRONish) product around peer to peer energy futures trading that completely fell apart when investors demanded they make it "AI"

the product was commercial analytics for healthcare sales teams. We worked with our customers (medical device & biotech commercial teams) to define granular patient cohorts (patients with a specific disease and specific pattern of treatment) and then analyzed provider (doctor / facility) interactions with those patients.

One onboarding problem was always - here's what I know about the doctors / facilities I care about, help me understand what I don't know. Well, what they knew was usually in a CRM, with very poor hygiene, or some ERP - dat assembled by hundreds of sales and ops people over years, sometimes decades. So generally the first step for us was to do an MDM exercise to join their data to ours.

This had a huge pay-off for both parties. For us we were able to make our product much more useful to them. For them, they now had a map of their territory they could use across multiple business units, multiple therapeutic areas (these usually operate independently and sometimes sell to the same buyers!)

I'm seeing the same opportunity/challenge in my new company, but this time focusing on the supply chain of these companies.

There are a lot of sensible comments on this thread but seems not a very strong consensus. I can see why! ERP is an extremely complicated space...

There was a thread a while ago about ERPs on a post about future start up ideas....i'll copy what I wrote there which you may find interesting...you may find that whole thread interesting:

'Ah ok. I'm an interested in this as a topic and would like to take a stab at this as I think it's an almost impossible project. I would like to caveat any opinion first by saying these: I have a great deal of experience customizing and creating little bits of bespoke functionality for various ERP systems (SAP obviously but also some of the smaller ones aimed at niche markets eg construction). I also have similar experience with similarly complicated and sprawling PLM systems. I've spent basically my entire software career around ERP and PLM systems and systems that break out pieces of ERP functionality and try to often do it elsewhere (usually badly), and then usually have to somehow bring everything back into an ERP system anyway, either manually or with at least some level of (but rarely complete) automation. I am a CS graduate from a 'famous' UK university (UCL). I'm also a qualified CAD engineer, project manager within agile (DSDM agile etc)...ITIL qualified etc. i.e I've spent a lot of time across these kinds of many tentacled systems that really do reach across the entirety of any large business. I've worked with these systems from FTSE 50 businesses to small 50 person manufacturing startups.

I've also been involved in the migration between PLM systems (horrible from a data perspective - all those CAD files etc) and also ERP systems (horrible but largely just the mapping between two different Entity Relationship Diagrams almost incomprehensible to any living human in terms of complexity).

It would be an incredibly ambitious undertaking to compete with one of the major players in either of these spaces. It is not something you could really even do at the scale of a start-up the likes of which YC and the media understand as 'start-up'. You would need so many not just 'early stage' founders with wildly different skillsets, you would need effectively an entire large manufacturing business, from end to end, in terms of personnel because your 'domain expert' essentially includes 'every business function you can imagine'. That's before you could even begin to think about software. It's a fascinating idea but think about it - procurement/purchasing, warehousing and logistics, engineering and design, sales and marketing, finance (very important here), HR, operations, R&D, Q&A...and these are just the ones I can think of that I have come across in my dealings with these systems. They really do touch every department.

The length of time to market would also be such that this kind of project would not really be appropriate to describe as a 'start up'. You'd essentially be creating a 'Unicorn Killer' and that unicorn killer would need insane resources to even have a chance at market success. The number and requirement for specialist migration tools into your new system from existing clients would be a 'massive' undertaking also.

It's such a bold idea but I think to describe an undertaking of that size 'start-up' would be to completely stretch the meaning of the term 'start-up' so far beyond its usage that the term would lose all meaning.'

Here is the original thread:

'https://news.ycombinator.com/item?id=39371805'

Good luck! I can't imagine trying this kind of project as a small team. You are very brave!