Essentials for Data Strategy
The first step in delivering transformational change through data is by creating a strategy. Having these essentials in your data strategy is vital in order to see your intended results.
Key Takeaways
Data strategy is about a framework that allows you to generate business value through the application of data and analytics.
Data strategy isn't just about data.
You might think of things like data management, data governance, and moving data around, which are really important components. But actually, a data strategy is about a framework that allows you to generate business value through the application of data and analytics across an organization. Here we discuss the foundational building blocks of a solid data strategy:
Vision and Value
The vision and value of the data strategy is all about aligning your data initiatives and programs and work and efforts around a business outcome that aligns itself to the business strategy.
People and Skills
Regardless of the size of your organization, there are a set of capabilities that are needed in order to technically sort the data. And from a business perspective, get the most value out of it, and ensure that you drive business change.
Responsibility of Data
You need to think about who is going to take ultimate responsibility for the data strategy within your organization, lots of people are opting for a chief data officer in this space. And that chief data officer needs to put a team made up of business engagement, solution delivery, and governance to ensure that you can maximize those opportunities that you want to go after.
Organization of the People who are Responsible for the Data
How you organize those people and skills in the right way that will maximize those opportunities that you're trying to go after. And this is about:
Do you put those people centrally in one team?
Do you distribute those people across your organization?
Do you have some sort of hybrid where you have central capabilities and best practices, but local subject matter expertise.
Operation Model
In managing data, you also need to think about the operating model. And this is how you will work. This is the methodologies that you will use. This is the thinking that needs to go into how you will operate in order to be agile, responsive, proactive, and iterative and innovative with your data efforts.
Governance over the Data
Data governance is all about how do you drive trust in the data in the numbers in the insight in the output the algorithms give, so that people believe in what they're looking at and believe what they're seeing.
Technology and Architecture
Technology is about choosing the right tools and architecture is about designing how you knit those tools together. The architecture that you put in the applications that you build in those technologies, we need to think about how you get data into your organization, we need to think about how you manage and govern and look after that data, we need to think about how you visualize and get insight from that data. We need to think about how you build models, algorithms, machine learning engines that deliver real high value outputs for you. You need to think about how do we provision and push that data potentially to other systems to other companies, to other parts of the business so that they can receive that data and do something with it in their own right.
Roadmap
The roadmap is about laying out a plan for all the other pillars that we've talked about in a time horizon so that we have a framework that we can manage, facilitate and communicate how we're going to make all of this business change. This in its own right becomes a really fundamental tool to help explain to the organization and help you judge yourself and test yourself and score yourself about how you're performing in terms of implementing and executing your data strategy.
Having these elements incorporated into your data strategy provides you with a framework that helps you articulate how you'll deliver business value through the application of data and analytics.