ProHance

What if your overtime data has been wrong this whole time?

Not because of bad intent. But because no single system could see the full picture.

A leading U.S. insurance company found this out the hard way. It was costing them $100,000 a year.
Their teams logged OT manually. Managers approved hours they could not verify. Payroll was slow, inconsistent, and impossible to audit cleanly.

They had Rippling for biometric punch-ins. But time tracking alone could not tell them whether those hours were actually productive.

ProHance integrated with Rippling, Outlook, and Power BI to close that gap. It auto-synced punch and productivity data, eliminated manual calculations, and gave real-time visibility into every hour worked.

After 12 months:
$100,000 saved in OT costs.
100% transparency in overtime tracking.
A fully compliant, auditable process.
A significant drop in payroll processing time.

If your HR or Ops team is still running overtime on spreadsheets, the cost is higher than you think.

Book a demo: https://www.prohance.ai/book-a-demo-linkedin.php

Your CX data is telling a story. But is your team reading it fast enough?

Every operation has a signal trending in the wrong direction. Most leaders miss it. Not because it isn't there, but because it's buried.

If the orange bar caught your eye, your team caught it too. They just had no way to act on it.

ProHance surfaces these signals in real time, across every channel and every shift. So your leaders stop guessing and start moving.

Your vendor reports look clean. But are they telling the truth?

Most enterprise leaders trust the timesheets. The relationship feels healthy. Governance looks solid on paper.

Until the numbers stop making sense.

Here's what happened at a Fortune 50 logistics company:

Utilisation reports showed full capacity. Headcount kept growing. Yet costs were climbing and deliveries were slipping.

ProHance PEM was deployed across 400 vendor resources. The data 30 days later was hard to ignore:

- Average productive work: just 4.5 hours/day
- 40% of capacity sitting idle, billed at full rate
- $6.3 million in outsourcing spend with zero verified effort

The vendor was not the problem. The governance model was.

If you're managing large vendor teams or GCC operations, this is worth a conversation.

Book a demo and see what your vendor data is really telling you: https://www.prohance.ai/book-a-demo-linkedin.php

🔍 Here's what Goldman Sachs just confirmed:

AI isn't delivering a broad productivity revolution. Yet.

But in two specific, well scoped use cases, the median productivity gain is 30%.

That's not incremental. That's transformational. When the scope is clear.

So why isn't it translating economy wide?

Because most organisations are deploying AI without:

📌 Baseline visibility into how work currently happens
📌 A framework to measure before vs after
📌 Clarity on which workflows benefit most

The companies seeing 30% gains aren't just "using AI."
They know where to point it.

Meanwhile, companies actively discussing AI have reduced job openings by 12%. Not because AI replaced people, but because it exposed hidden capacity.

💡 The implication for CXOs:
AI doesn't automatically equal productivity.
Visibility does.

💬 Is your organisation measuring AI's impact on productivity, or just tracking adoption?

👉 Want to see how visibility drives real AI productivity? Talk to us: https://www.prohance.ai/book-a-demo-linkedin.php