Transforming technology into a catalyst for innovation

The story of digital taking the centre stage couldn’t ring more true these days. Today’s world lives and breathes digital with customer expectations climbing ever higher in B2C, as well as B2B. Take personalisation, for example. 71% of modern-day consumers expect personalisation and 76% gets frustrated when they don’t get it. It only makes the need for innovation greater. This is just one example of how customer desires are paramount these days.

Once upon a time, businesses would put their trust in major technology suites, handing them all the tech they could ever need. These foundations are effective but rigid.

Today, these large-scale monolith suites are joined by an entirely different approach: composable thinking. Although there are plenty of organisations out there with the needs and wants matching the monolith solution, composable is making a name for itself.

Composable tears down the traditional barriers of the traditional tech suite. It allows you to change and adjust systems on the go and create what is a truly custom composable set-up. It’s a modular way of thinking with change becoming part of your everyday digital operations. 

Unlike a suite approach, where a single vendor supplies all the software components you need, composable architectures focus on composing small, loosely coupled components and using existing best-of-breed technology that can be integrated to form innovative solutions and work together to supply the optimal customer experience across different channels.

Composable relieves tech teams in unprecedented ways, bringing discoverability, adaptability, autonomy, and – finally – flexibility.

Manual upgrades can break just about any tech team’s day. On average IT teams spend 40% of their time delivering upgrades to the front-office. That’s why Cloud and Cloud Native are no longer emerging trends, but realities here to stay.

Cloud computing provides users with a flexible, scalable, and cost-effective way to access and utilise computing resources on-demand. Cloud-native refers to the design and architecture of applications that are optimised for deployment and operation in a cloud computing environment. 

The Cloud and cloud-native development allow for experimentation by way of microservices, containerization, continuous delivery and DevOps – with higher deployment frequency, lower maintenance costs and scalability.

No UX journey should be forced to begin from scratch – thanks to modern design systems and component libraries providing us with battle tested UX for new ideas to reuse.

A design system is a collection of guidelines, principles, and tools that ensure consistency and coherence across an entire product or service. Like components, visual styles, and patterns. It’s what makes something stand out digitally and as one-of-a-kind. 

A component library is a collection of pre-designed, reusable UI components that can be easily assembled to create user interfaces. These components are designed to be modular, so they can be mixed and matched to create custom interfaces that meet the needs of specific applications.

There’s a very real chance you’ve noticed the term data mesh popping up all around you lately. Little surprise in that, really. After all, in recent years organisations have been told that a single database - one where all data gets stored together - is what we all should strive for. In practice, we often see that this centralised approach creates an excess of data flows.

Data mesh is a decentralised approach to data architecture where small, independent teams are responsible for specific domains or data sets. This promotes data autonomy, enables teams to move faster, and breaks down silos to improve collaboration and insights.

In short: you don’t just throw all the data into one barrel but make connections between the different teams for the benefit of coexistence. With data mesh you let the data flow from one team to another. As a result, data & intelligence, which was previously exclusively an IT matter, is a responsibility and resource that’s shared across the business.

Just like Google moving towards a cookieless reality, data mesh involves a cultural shift in the way that companies think about their data. Instead of data acting as a by-product of a process, it becomes the product, where data producers act as data product owners.

Security management is so much more than another reason for delays in security testing. In the past, it only made all too much sense to make room for security somewhere near the end of the software development lifecycle. If it’s so important - why wait until the end?

Smart security management means doing it more often and placing it all over this process, relying on the ​​Secure Software Development Lifecycle (SSDLC) - for example. 

0. (Pre)Sales: Security Risk Classification / Acquiring Maintenance

1. Governance: Roles & responsibilities / Strategy & KPI's / Policy and Compliance / Project Access

2. Training: Secure Development

3. Requirements: Security Requirements / Quality Gates / Security & Privacy Risk Assessment

4. Design: Use of appropriate & supported technology / Security View / Threat modeling / User interface design

5. Implementation: Proactive Controls / Protection of Source Code / Encryption/ Peer code reviews / Dependency tracking / Static application security testing (SAST) / Web application firewall / Environment & Test data

6. Verification: Penetration test / Dynamic application security testing (DAST) / Thread model attack surface review

7. Release: SDLC Compliance Review / Transfer to Run team

8. Operations: Incident Response / Monitoring & Alerting / Logging / Environment Management / Security Updates & EOL / Defect Management

Let’s consider security an enabler, integrated in every stage of the lifecycle.