The Tea Bag Test: Does Your Digital Investment Actually Infuse?
I've borrowed a metaphor from Maud Bailly (EcCom Member @ Accor) that cuts through the noise: digital as a tea bag.
The bag alone is worthless. What matters is the infusion—the water quality, temperature, vessel, steeping time, and final taste.
Applied to business, this forces a simple question: Are your digital investments actually steeping into the value stream, or are they trapped in project silos that impress more than they transform?
From a customer or employee perspective, digital is never the goal. What counts is a seamless journey, fast decisions, clear information, and access to the right service at the right moment.
That’s where Lean thinking provides the robust framework to see this reality clearly.
From Projects to Value Streams: Where Lean Meets Digital
Lean management gives us three essential lenses:
Waste that consumes resources without creating value
Value streams that connect all steps end-to-end
Measures that let us steer from facts, not perceptions
At the executive level, this serves two objectives:
Concentrate digital efforts where they genuinely shift economic trajectory
Structure a system that learns fast and improves decisions over time
Think of Lean as the method to ensure proper infusion. Without it, you’re just adding hot water to a sealed bag.
The Gemba reality check: Go see how work actually happens. Name the specific waste:
Multiple data re-entries
Wait times between approvals
Incomplete files bouncing backward
Features developed but rarely used
Constant context-switching for teams
These aren’t technical details. They translate directly into immobilized time, additional risk, and missed opportunities. They consume innovation capacity as much as operational performance.
Making this waste explicit—say, via an A3 synthesis—lets you connect irritants directly to revenue, risk, or margin issues. You’re no longer talking about comfort. You’re talking about performance.
Structuring the Cup: Digital Value Streams & Innovation Capacity
Before touching org charts or technology, look at the cup: the end-to-end value stream.
A Value Stream Mapping exercise on a priority flow reveals:
Total cycle time for a customer request
Mandatory checkpoints and associated queues
Zones where digital genuinely accelerates
Zones where it mostly adds complexity
This view is critical for innovation. It lets you ask:
Which customer segment or journey would a breakthrough actually transform?
Where would radical simplification unlock new services?
Which partners should we integrate to create a differentiated offering?
A well-designed cup isn’t just a clean process. It’s a framework that makes new value propositions, collaborations, and business models possible.
Organizing the Tea Bag: Product Teams, Lean, and AI in the Flow
Once you’ve observed the water and clarified the cup, you can examine the bag: how you organize teams to steep it all together.
I see this bag as an intentional blend:
Product teams aligned to specific value stream flows, bringing together product, tech, design, data, and business expertise
Lean culture that questions waste, stops what doesn’t deliver value, and stabilizes what works
Technical platforms that reduce friction for innovation (shared tooling, integrated security, accessible data)
AI capability designed into journeys from the start, not bolted on afterward
AI, used seriously, enables you to:
Filter and route demand, avoiding low-impact work launches
Automate complete cognitive tasks while keeping humans in command
Strengthen analysis and decision support with traceable outputs
Make organizational knowledge accessible in natural language to teams who need it
At this stage, innovation is no longer just digitizing what exists. You genuinely give yourself the ability to rethink pieces of the value stream where economic and customer impact justifies it.
Setting the Temperature: Cadence, Trade-offs, and Visual Management
Even with a good cup and bag, poor temperature yields disappointing results. In transformation, the equivalent is cadence, trade-offs, and piloting visibility.
Three levers I’ve seen work particularly well:
1. Clear cadence for product teams
Short, readable cycles where you regularly ship visible improvements, examine what’s actually used, what’s broken, what deserves to be stopped.
2. Structured trade-offs by value stream
Portfolio management that starts from key value streams and real capacity, rather than demand accumulation. This requires accepting explicit trade-offs and making them visible.
3. Visual management with immediately actionable indicators
Simple dashboards—physical or digital—grouping a few metrics chosen with business partners:
Real journey time on a flow
Perceived effort by users
Volume processed daily or weekly
Number of incidents and mean time to resolution
For AI: result quality and human corrections
The key question: If I see this metric move, do I know what decision to make? If not, it’s not a good steering indicator.
Strong visual management lets leadership, business teams, and digital squads synchronize without reporting overhead—and make adjustment decisions earlier.
Measuring to Learn: Innovation as Discipline
Innovation isn’t a constant geyser of ideas. It’s a discipline: start from a well-posed problem, formulate a hypothesis, test at small scale, measure, decide.
In this Lean logic, three measurement families are essential:
Customer-side performance: Real journey time, perceived effort, completion rate
Usage and value: Active adoption, retention, impact on a concrete business metric (e.g., volume processed, risk avoided, average basket)
Learning: Time between an idea and a robust lesson, ability to industrialize what works and decommission what doesn’t deliver
For AI, add specific indicators: result quality, share of responses corrected by humans, potential drift from expectations, compliance with ethical and regulatory frameworks.
The goal isn’t to pile up metrics. It’s to install a shared foundation that lets all levels talk about the same reality. That foundation enables continuous innovation because it gives you permission to stop, redirect, or reinforce.
Practices That Actually Make the Difference
Rather than prescribe actions, I’ll share what I’ve seen work in organizations where digital and AI genuinely changed things—without posturing or excess hype:
Start with one identifiable value stream
Choose a clear journey or segment with strong business stakes. Look at it together through Lean principles: Gemba, waste, simple synthesis. This creates common language between leadership, business, and digital teams.
Give an explicit mandate to a dedicated product team
On that flow, build a cross-functional product team with clear scope, a few readable indicators, shared visual management, and permission to experiment within guardrails. The dynamic difference is often striking.
Introduce AI where it helps you learn faster
For example, on demand qualification, decision support, or knowledge access. Set up security, privacy, quality guardrails and explicit criteria for continue-or-stop decisions upfront. AI becomes a learning accelerator, not a gadget.
These practices are simple in appearance, but they change the conversation. You’re no longer talking about “doing digital” or “launching an AI use case.” You’re talking about transforming a value stream, with an economic compass and tangible proof.