Skip to main content

Building capabilities that deliver: Start with the experience you already have

By

 When we started developing our cloud capability, one of the first things I wanted to understand was what experience we already had.

People across different locations had worked on cloud projects, solved difficult problems and learned things that could help other teams. Finding this information took effort. It was spread across teams, locations and systems. Each group collected information for its own needs. Sales needed customer references. Delivery teams knew the technical details. Regional leaders looked at people and availability. Communities followed skills and certifications.

Everyone had part of the picture. We needed to bring these parts together in one place.One of our working tools was an inventory connecting projects, technologies, locations and the people involved. The important part was agreeing what information we needed and how others would use it.

A technology name alone tells you very little. I wanted to know what the team had delivered, the constraints they had faced and who could explain the decisions. This gave us a better starting point when discussing a new opportunity. We needed a way to connect a challenge to a person, knowing to who to go when there are questions. It also helped us decide where to invest.

For example, experience needed by one team might already exist in another region. Connecting the teams could be the first step. In another area, several projects might depend on the same person. There, developing more people would become a priority.

These situations require different decisions. Before asking for a training budget, recruiting or building an accelerator, I want to understand the gap we are trying to close.

Keeping the information useful is another challenge. Someone needs to own it. Teams need to understand why contributing matters. Project descriptions need updating, and the people listed may have moved to other roles.

This becomes especially important when we use the information in a customer conversation. We need confidence that the experience is relevant and that the people behind it can still support us.

I see this visibility as a practical foundation for growing a capability. It helps us draw on our experience and make better decisions about what to build next.

Comments

Post a Comment

Popular posts from this blog

How to audit an Azure Cosmos DB

By
In this post, we will talk about how we can audit an Azure Cosmos DB database. Before jumping into the problem let us define the business requirement: As an Administrator I want to be able to audit all changes that were done to specific collection inside my Azure Cosmos DB. The requirement is simple, but can be a little tricky to implement fully. First of all when you are using Azure Cosmos DB or any other storage solution there are 99% odds that you’ll have more than one system that writes data to it. This means that you have or not have control on the systems that are doing any create/update/delete operations. Solution 1: Diagnostic Logs Cosmos DB allows us activate diagnostics logs and stream the output a storage account for achieving to other systems like Event Hub or Log Analytics. This would allow us to have information related to who, when, what, response code and how the access operation to our Cosmos DB was done. Beside this there is a field that specifies what was th...
Post a Comment
Read more

Why Database Modernization Matters for AI

By
  When companies transition to the cloud, they typically begin with applications and virtual machines, which is often the easier part of the process. The actual complexity arises later when databases are moved. To save time and effort, cloud adoption is more of a cloud migration in an IaaS manner, fulfilling current, but not future needs. Even organisations that are already in the cloud find that their databases, although “migrated,” are not genuinely modernised. This disparity becomes particularly evident when they begin to explore AI technologies. Understanding Modernisation Beyond Migration Database modernisation is distinct from merely relocating an outdated database to Azure. It's about making your data layer ready for future needs, like automation, real-time analytics, and AI capabilities. AI needs high throughput, which can be achieved using native DB cloud capabilities. When your database runs in a traditional setup (even hosted in the cloud), in that case, you will enc...
Post a Comment
Read more

Azure Well-Architected AI workload Assessment

By
  AI is everywhere, part of the IT solutions we build and run today. Having an AI service, a good model, and data is not enough. As for cloud, the real difference is how we build, manage and run the whole solution. Microsoft created the Azure Well-Architected Framework for AI Workloads exactly for this reason — to help teams design AI systems that are reliable, secure, and cost-efficient. The assessment has six main categories that we cover in the next section. Based on the results, we can gain a good understanding of the current AI workload estate and a list of actions to improve how you run and manage your AI workloads . Designing the AI Application The first step in building your AI application is to consider how you will structure it. Using containers for tasks like data processing or model inference helps maintain consistency across the system. This approach makes it easier to update, move, and manage different components. When you have multiple steps in your workflow, such as...
Post a Comment
Read more