Making Good: the frontline was never the weak link

Making Good, part 1 of 4

Every brand makes its promise in a boardroom. It gets kept somewhere else: at the front desk at 6am, on the store floor during the Saturday rush, on the line when a machine throws an alarm, in the lab when a batch record needs a second signature.

That distance is what this series is about. We call it Making Good, and the name carries two meanings on purpose. The enterprise makes good on what it promised. The person on shift gets what they need to make good in the moment of work, which is the harder half and the one this alliance is built for.

This week RedeApp and Capgemini announced an alliance built around that distance. I'm using these four posts to lay out the argument underneath it, with the sources showing.

Why was the frontline the last place to get tools?

Because for thirty years the budget math said so. Connecting a frontline worker cost real money, and a connected worker was worth only a little more than an unconnected one. The line item lost, year after year.

The result is easy to measure. Roughly 80% of the global workforce, about 2.7 billion people, works without a desk (Emergence Capital; McKinsey; BCG). By industry estimates those workers have received about 1% of enterprise software spend (Emergence Capital; Gartner), and only 23% say they have the technology they need to be productive (Deloitte).

That left the frontline as the least equipped part of the business, and the part carrying the brand.

What changed?

The value side of the equation. When an agent can answer the policy question and route the call-off to the right manager, a connected worker is worth far more than a reachable one. I call this the frontline value inversion, and part four of this series puts numbers on it.

Most enterprise AI hasn't noticed yet. MIT's Project NANDA reported in 2025 that 95% of enterprise generative AI pilots showed no measurable P&L return. The method is contested, so treat it as directional. My read of the failures is simpler than the number: the agent didn't know the organization, or the people it was built for never opened it.

Why RedeApp and Capgemini together?

Because each of us covers half of the problem. Capgemini runs AI as an enterprise program and knows how to move a large organization. RedeApp is the frontline system of record inside that program, and Shelbe, our AI, answers from the organization's own documents, shows its source and stays inside each person's permissions.

It also comes with usage. Across RedeApp networks, 44% of monthly users come back every day, against a 13% industry average (RedeApp network telemetry, 2026). An agent nobody opens delivers nothing.

Neither company could do this alone. That is the design.

Where does the alliance start?

Life Sciences | Hospitality | Retail | Intelligent Industry

Each one runs on frontline execution. In each, a missed message turns into overtime or a compliance problem before the shift ends, and each can measure what a better-connected shift is worth.

What's in the rest of the series?

Next Wednesday I'll take the two questions I've heard most since the announcement: how this differs from Copilot, and why the HR platform's messaging isn't enough. After that comes what your counsel will ask before any of it goes live, and then the math.

The full announcement is on the RedeApp and Capgemini alliance page. If you run a frontline workforce, bring me one decision your organization made this week. I'll show you how far it actually traveled.