u/FirmMail7716

Former procurement person here (NCR, 5 years). Left the industry, but I'm thinking about building tools to solve real procurement problems.

Instead of guessing what hurts, I wanted to ask people actually in the trenches:

What part of your vendor selection process is the most painful/time-consuming?

• Searching for vendors and vetting them?
• Collecting and analyzing RFQ responses?
• Comparing proposals side-by-side?
• Negotiating contracts?
• Onboarding once you've selected someone?
• Something else?

Be honest—what would genuinely save you time if it was automated?

Former procurement person here (NCR, 5 years). Left the industry, but I'm thinking about building tools to solve real procurement problems.

Instead of guessing what hurts, I wanted to ask people actually in the trenches:

What part of your vendor selection process is the most painful/time-consuming?

• Searching for vendors and vetting them?
• Collecting and analyzing RFQ responses?
• Comparing proposals side-by-side?
• Negotiating contracts?
• Onboarding once you've selected someone?
• Something else?

Be honest—what would genuinely save you time if it was automated?

So I've been seeing a lot of articles about companies and startups struggling with AI. People saying AI is replacing jobs, companies aren't getting profit from it, you know?

But here's what I think: Companies are using all these AI tools, right? But there's no proper guidance on how to use them. That's the real problem. There are so many tools out there now, but people still don't know how to use them properly and efficiently.

What's really happening is that people are investing time in learning. And yeah, it takes time. Even though all these tools are available, people are still learning how to leverage them in the best way.

What I call "The Implementation Valley" — that's where we are right now. That gap between having the tools and actually knowing how to use them efficiently. People need to invest more time learning.

I understand why existing companies are worried. If something already makes you profit, why switch? Why spend time learning something new? It's a risk.

But I think once everything settles—once people really figure out how to use these tools efficiently—that's when the real profit will come. That's when the real use of AI will actually take place.

So right now, people just need to invest more time in learning these tools. That's it. Learn them now, get efficient with them now, and then you'll see the real benefits later.

That's just my perspective, you know?

Linkedin - https://www.linkedin.com/in/mugesh-mdeveloper
Github - https://github.com/Mugeshgithub?tab=repositories

Former procurement person here (NCR, 5 years). Left the industry, but I'm thinking about building tools to solve real procurement problems.

Instead of guessing what hurts, I wanted to ask people actually in the trenches:

What part of your vendor selection process is the most painful/time-consuming?

• Searching for vendors and vetting them?
• Collecting and analyzing RFQ responses?
• Comparing proposals side-by-side?
• Negotiating contracts?
• Onboarding once you've selected someone?
• Something else?

Be honest—what would genuinely save you time if it was automated?

Former procurement person here (NCR, 5 years). Left the industry, but I'm thinking about building tools to solve real procurement problems.

Instead of guessing what hurts, I wanted to ask people actually in the trenches:

What part of your vendor selection process is the most painful/time-consuming?

• Searching for vendors and vetting them?
• Collecting and analyzing RFQ responses?
• Comparing proposals side-by-side?
• Negotiating contracts?
• Onboarding once you've selected someone?
• Something else?

Be honest—what would genuinely save you time if it was automated?

Dear UFO Enthusiastic,

Not a UFO blog. A full data science pipeline. 

Key findings from the NUFORC database (1941-2014):

- 61% of sightings happen between 8pm–2am, consistent across all 74 years

- The 2012 UFO spike is largely a smartphone artifact. Once bias-corrected, the trend becomes much flatter

- Washington State surpasses California in sightings per capita after population normalization

- 77 reports describe silent flight combined with instant acceleration simultaneously

- Triangle-shaped object reports have nearly tripled since the 1980s

Built with Next.js and a Python NLP pipeline. Every statistic is computed from real public data — nothing fabricated. Full methodology included.

Live Link in first comment- Kindly check it out and provide your feedbacks ( Open source)