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Drive More Innovation Using Data-Driven Business Architecture

Data is an essential component guiding how businesses make important decisions. There are so many different sources of data feeding into and out of a business mean we need to govern data in a way yields the most benefit. Using a data-driven business architecture, you can design your business and teams around your data in a way that allows you to capitalize on it.

What is data-driven business architecture? Also known as data-driven design, data-driven business architecture is the harnessing of all business data in a way that it is sourced, processed, managed and controlled, and ultimately used effectively. It is all about the management of the flow of data through the business.

With the rate at which technology and user needs are advancing, data-driven business architecture has become extremely complex in a short space of time. So how do you ensure that your data architecture can be used to drive business innovation?

1. Treat Your Data Architecture As Ever-Changing and Evolving

Your data is constantly changing and moving, as is the world around us. Creating a design that is too fixed or structured could prevent future options that are required to meet emerging business needs. Your data architecture should be designed for change so that it can evolve with your business and revenue models. Implement a fluid system that allows for trial and error and apply the mindset of constantly learning about your data, the data sources, and the best practices for your data.

2. Democratize access to data across the organisation

Enabling your employees and shareholders to have access to relevant data at the right times is an essential step towards innovation.

Since your data is constantly moving, all relevant team members need real-time access where possible. This allows businesses to scale all tools and processes at a rapid rate, while enabling collaboration between data teams on the best practices for your data-driven business architecture. Proper architecture will incorporate all teams and their ideas on how to get the best outcomes from your data to achieve business goals and discover future strategies.

3. Fine-tune Your Data Capture Techniques

Data quality can be impacted by poor data capture methods, which reduces the value of the data. Data quality issues miss possible business opportunities and waste precious time of staff. Fine-tune the ways data is captured, and what standards are applied to it, in order to ensure that it a reliable resource that critical business decisions can be based on. By understanding the uses of the data, you can define exactly how it should be captured and what data quality is necessary. You can also then determine how the data needs to be accessed, who needs it and what it is used for.

At Robinson Ryan, we know that proper data promotes the best business practices. Data underpins the wisdom behind everything a business does, and it needs to be accessible by the right people. Find out more about our consultancy services that support, protect, and enhance your data. 

If you are interested in expanding your knowledge on data management, check out our range of courses here.

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Tim Goswell Practice lead

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