Rules and regulations on advice change almost daily due to new legislation and case law. So to ensure high-quality advice that serves the customer best and reduces the risk of ill compliance to a minimum, you need an advice framework that is both
- rigid in the sense that no advice can escape being submitted to it
- hyper-agile in the sense that it can be adjusted to new insights in the blink of an eye.
A framework such as this can be achieved in 4 steps.
Step 1: Develop a hyper-agile architecture
A hyper-agile advisory framework is a framework that can instantly change and have the organization act on that changed framework right away. This requires automation to support it. So the IT landscape has to be designed to support hyper-agility as well.
A hyper-agile architecture has
- API-based integration
- consolidated aggregated data
- low-code decoupled business rule management
Step 2: Create a cross-functional, collaborative team
Bring the knowledge of the business and the expertise in IT systems together. Make a cross-functional team, that in collaboration builds the advisory framework.
Using low-code business rule implementation allows the business to instantly reflect on what is being built.
Step 3: Make the feedback loop part of your operations
Hyper-agility means instantly reacting to what happens in the market. That is not the same as being able to act in panic mode. It is also naive to think you will get everything perfect in the first go.
An active feedback loop that is part of the standard operations creates ongoing improvement. The effect is
- higher quality of advice
- more pleasant work
- anticipating – and therefore being better prepared for – the change that is to come
Step 4: Make optimization part of your routine
Optimization of your digital systems goes beyond the question of which business rules to implement. It’s about ensuring your clients receive the right nudge at the right time. It’s about how clients experience their advice and their customer journey.
Optimization requires analysis of the behavioral data and creates
- a higher client response
- higher client satisfaction
- subsequently higher revenue