Author: Paul
(3 min reading)

Data driven vertical architectures

Microservices and microfrontends developed by autonomous product teams have become the golden child for corporate digitization strategists. In the last decades, players like Netflix, Amazon, Spotify, Google and Co. inspired a new way of thinking towards software architectures that are more flexible and value centered than traditional monolithic systems.

As every major shift of paradigm poses new challenges to the adopters, this also holds true for the identification and the management of digital products in, so called, vertical architectures. Among many others, the following challenges stick out:

  • Product development teams must have reached a certain level of agile maturity and corresponding technical skills in order to prevail in this new dynamic environment.
  • The management must continuously provide a clear answer to the question of why, when and how the isolated product teams add value to the overall process landscape of the organization.
  • Meaningful software products exist in the context of requirements that steadily make well-defined aspects of the business either more effective (e.g. gain additional revenue through better UX), efficient (e.g. save manual effort through automation) or both. While those software products are in productive operations, they generate quantitative and qualitative data (logs, tracking events, Net Promoter Score, etc.). As each and every product in a vertical architecture is part of the overall value chain, its business evolution can be observed by a Key Performance Indicator (KPI) based on that data.

Take e-commerce as an example:

  • Finding relevant search results,
  • receiving attractive product recommendations,
  • mitigating fraudulent order attempts,
  • constantly improving a seamless multi-device / omni-channel interaction flow in the customer journey.
  • And several more ...

Those are all examples of persistent goals mapping to isolated, best-in-class solutions in the value chain that all prove to be meaningful through their individual KPIs. To stay competitive and evolve the overall architecture, meaningful process steps and their corresponding KPIs must be precise and persistently transparent.

At, we strongly believe in meaningful software products that prove to be valuable for users, stakeholders and the business. We successfully supported businesses around Europe in the following areas:

  • Methodologies, workshops and market benchmarks to identify meaningful products and features.
  • Hypothesis and insight generation (Data Science and UX research).
  • Product development (management / Advisory and engineering) in microservice architectures (vertical).


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