In Plato’s Meno, Socrates asks a deceptively simple question:
How can you search for something when you don’t know what it is?
This is Meno’s Paradox – and it turns up in modern business transformation more often than leaders realise. Organisations set out to achieve something new – a better customer experience, a more efficient process, a more data-driven culture but quickly discover they don’t have a clear picture of what “better” really means in practice. This is especially true of AI led transformation and change. They can’t define the destination in detail until they’ve already started the journey.
When transformation is approached solely with rigid blueprints and fixed requirements, the result is predictable: slow starts, misaligned priorities, and solutions optimised for yesterday’s challenges and opportunities.
All retail banks are under intense pressure to transform how they engage customers through marketing, sales and service interactions to improve exchange of value. Driven by:
- Shifting customer expectations for seamless, personalised experiences
- Competition from fintechs and big tech platforms
- Regulatory demands for transparency and compliance-by-design
- The need for increased operational efficiency to drive cost: income ratio improvement
The goal seems straightforward: create consistent, intelligent engagement across channels, products, and moments. But here’s the problem at the outset, most banks don’t know:
- Which journeys matter most for customer loyalty or revenue
- Which data and models predict the best engagement outcomes
- How to harness the power of advanced analytics and AI at scale
- Where the true operational friction points lie
This is Meno’s Paradox in action: banks can’t design the ideal engagement model without answers to those questions, but they can’t get the answers without starting to build.
Pega’s CDH platform promises end-to-end orchestration of customer engagement, spanning:
- Engagement – Unified journey management across digital, branch, and assisted channels
- Personalisation – Real-time tailoring of offers, messages, and experiences
- Decisioning – AI-powered next-best-action to balance customer needs and business goals
- Transformation – Agile delivery with low-code tools, AI enabled processing, hyper-personalised content, and embedded compliance
However, these capabilities magnify the paradox. Pega is a powerful, flexible platform, but without a clear, evolving understanding of what “great engagement” means for this bank, it risks being implemented as a static system, missing its adaptive potential.
There are some excellent examples of leading banks in the UK, Australia and the USA treating strategy and delivery as one continuous, exploratory process. In the context of high-performance customer engagement, they use Pega not just to execute, but to discover.
Principle 1: Journey-Led Exploration
- Start with targeted pilot journeys (e.g., onboarding, dispute resolution) that deliver value quickly and surface deeper insights.
Principle 2: Hypothesis-Driven Design
- Frame engagement models as testable experiments: If we do X, customers will Y.
- Test, measure, and refine inside Pega’s decisioning engine.
Principle 3: Co-Creation and Integration Across Functions
- Bring together frontline, compliance, analytics, and digital product perspectives to shape what “next best” means.
Banks applying this approach achieve:
- Weeks, not months, to first measurable engagement gains
- AI models that learn faster from real-world data
- Relevant and meaningful service interactions
- Increased cross-sell and retention through more relevant marketing and sales interactions
- AI enabled automation where it delivers the greatest impact
AI’s Role in Resolving the Paradox
Pega’s AI capabilities speed up discovery by surfacing hidden patterns and opportunities. But human teams remain essential to interpret signals, set priorities, and ensure compliance. The winning formula is AI for pattern recognition + people for strategic sense-making.
Three Key Takeaways for Banking Leaders
1. Treat delivery as discovery
- Your first deployments in Pega should be designed to learn, not just to launch. Use them to uncover the real drivers of customer satisfaction, value growth and retention, and operational efficiency.
2. Build adaptability into the strategy
- Avoid locking into rigid multi-year plans. Aim instead for carefully designed transition states letting AI insights, operational feedback, and evolving compliance requirements continuously reshape your engagement model.
3. Make “next best” a shared definition
- Cross-functional collaboration – from marketing and service, products, channels, and journey management to data, content and compliance – ensures Pega’s decisioning aligns both with customer needs and business priorities.
A Final Word
Meno’s Paradox reminds us: transformation begins not with perfect answers, but with better questions. In 2025, the banks that will succeed with their investment in enterprise customer engagement will use Pega, or other similar platforms, as both execution engine and strategic pathfinder, navigating toward more human, responsive, and data-rich engagement, even when the full road ahead isn’t yet visible.
Get in touch today to learn more.
