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Is your Enterprise Architecture data dormant or dominant?

We are all doing it, or at leat attempting to... Collecting and using vast amounts of information to support decision-making, improve processes, and drive innovation.

Customer data is analysed and pulled apart in an infinite number of ways to give a competitive advantage. However with Enterprise Architecture (EA) data, it is often going underutilised, relegated to dusty repositories or simply overlooked due to not being understood. This is despite EA data being the key to knowing how organisations tick, allowing identification of inefficiencies, anticipating risks, and uncovering opportunities for optimisation and innovation.

Too many organiasations fail to realise the full potential of their architecture data due to various reasons, including but not limited to:

  • Not knowing where it is: The thinking of “we don’t have the data” or “we don’t know where our data is” is almost universal for organisations commencing their EA journey. I promise you though it is there but scattered in multiple locations and it’s just a case of consolidating them.

  • Having it but knowing it is stale (or worse, just plain wrong): Many old school EA practices have diagrams stuck in Visio, PowerPoint or on Excel spreadsheets that have been gathering dust and not updated for years. Even if they are on an proper “EA tool”, these can be simply diagrams based on that data, and just as dusty.

  • Not getting it: The visualisations of the EA data just look too complicated to get any value out of it to. Why can’t the reports and data be simply represented for everyone to understand?

  • Having impenetrable organisational silos: Organisational departments are too blinkered and focussed on their own areas. To deliver real value an EA function needs to be across all of these and not constrained by department prejudices.

  • Low value perception: A common line of thinking is organisations need to have a perfect EA model before value can be realised. If you try to boil the ocean from the start then this perception will occur, and so this totally outdated notion needs to be turned on its head.

  • Ivory towering: Having EAs sit in an “ivory tower” hoarding their data and only opening up snippets of it when asked will destroy any value quicker than all of the other items combined.


data analysis

How to untap the potential of Enterprise Architecture data

1) Sponsorship

First and foremost, there needs to be a directive from the top. There’s no point putting in place actions and activities when half the organisation isn’t coming along for the ride. Without executive support and it being part of the overall organisational strategy, achieving real value from EA data is doomed right from the start.

2) Business Acceptance

A progressive EA function encourages “collaboration and alignment” among every organisational department providing transparency, communication and knowledge sharing. This means simply implementing an EA tool won’t work. It can really change how teams work and come up with new ideas so requires a proper change management process to ensure business acceptance is there from the start. See another blog of mine on Changes to technology are not about the technology for more details on this.

3) Implement a proper fit for purpose EA tool

Move beyond static diagrams and documents by adopting dynamic modelling and visualisation techniques that utilise a centralised data repository and allow stakeholders to explore architecture data interactively. These tools can also introduce operational activities like interactive dashboards, data maintenance automation, workflows, heat maps and dependency graphs can provide insights and trends in real-time.

4) Treat the implementation as a journey

As mentioned earlier, trying to boil the ocean from the start will mean any value will not be realised for a long time. Enthusiasm and interest will wane, and the rollout will fail. Switch this around by approaching the implementation loads to target specific business problems that give immediate value and ROI, using this to define the scope of your work. Then move to the next one, then the next…

5) Let EAs focus on value driven activities, not data management

The world is getting more and more complex and the amount of data EA insights are drawn from is forever growing and changing. Having EAs spend their valuable time on data maintenance tasks takes away from them providing activities where they truly create value. The trick is to make everyone be responsible for their data in the repository. Yes, it sounds scary but there are lots of techniques that can be implemented to really streamline and simplify this activity. See another predictive blog of mine on What is the future of Enterprise Architecture for more details on this.

So how does Ardoq fit into all this?

I recently did an independent global review of “EA Tools” and from my analysis, Ardoq came out on top as being my selected tool of choice for achieving all of this. Ardoq really impressed me with its new way of thinking. They are changing how we see things and making enterprise architecture more valuable and accessible outside of just the EAs. They're bringing all organisational stakeholders together, even those who aren't tech-savvy, to get the most of EA data.

Reach out to me directly for an obligation free discussion if you would like to find out how I can assist you improve the way you can utilise your Enterprise Architecture data.

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