Every organisation, no matter the size or industry, must have a data strategy in place. Here we discuss how to create an effective enterprise data strategy.
If a business is going to be run in a smart way, it must be guided by strategy and data. Whether your organisation is Google-sized or family-run, all companies in all industries must therefore develop a data strategy to be successful. It’s one thing to know you need one, and it’s another to understand what should be considered and included in an effective data strategy. Instead of leaving this important task to chance, read on to learn the essential elements of an effective enterprise data strategy.
Why Every Company Should Have a Data Strategy
It’s simple. Data has become the fuel of the 4th Industrial Revolution. In order to get the most out of data, you must have a data strategy. In the scramble to keep up with others, many companies make the mistake of hoarding data and investing in data analytics and data storage technologies that ultimately aren’t right for their business. This often costly mistake can be avoided by spending the effort to create a data strategy. A data strategy helps you understand and clarify how the data will be used in practice and chart a course for how you will use data to achieve your company’s goals.
The amount of data continues to grow, and as it multiplies, it becomes more complex to manage and extract insights. While it might have been possible in the past to get by without a data strategy, the increasing strategic importance and the explosive growth in the volumes of data today make that no longer a reality. To have efficient and effective data management, a data strategy must be put in place.
Start with Use Cases
Data can be an incredibly valuable business asset, but only if you have a plan to access the data that can help you achieve your company goals. There are millions of ways data can support business, but if what you’re collecting isn’t aligned with helping achieve your goals, it’s as beneficial as if you weren’t using data at all. To avoid this misstep and unlock the value of data, it is vital to first figure out the most important use cases for your organisation.
This focus on your organisation’s uses cases will help you develop a good data strategy that helps you achieve your business objectives. I recommend developing three to five key data use cases. You can use this handy Data Use Case Template to build out data use cases with the detail you need for a thorough data strategy.
It’s no surprise that the first step in the Data Use Case Template is to “Link to a Strategic Goal.” A well-designed data strategy must start with your business strategy and the key things you wish to achieve as a business. When I work with companies on their data strategy I challenge them to evaluate potential data use cases through five different lenses, and in the following order:
- Improve evidence-based decision-making
- Understand your customers and markets
- Offer smarter products and services to your customers
- Improve internal processes
- Add additional revenue by monetising data
After you complete the template for each Data Use Case, which helps you prioritise your data projects, you’re now ready to transition to the Data Strategy Template.
I encourage organisations to define the top three data priorities for the year, but I also find it valuable to identify one or two “quick-win” data uses. These quick successes will help demonstrate the value of data to your organisation.
The Data Strategy Template pulls together all the elements you need to consider for an effective data strategy, and that might also be cross-cutting issues among your data use cases. These include:
Data requirements: Identify what data you need and how you will source it. Does it include structured and unstructured data? Is it diverse enough?
Data governance: It’s important to consider the current state of data quality, security, access, ownership, ethics and privacy within your organisation.
Technology: In this area, consider the four layers of data (collecting, storing, processing/analysing and communicating insights from the data) to be sure that you have the infrastructure in place to support the data you need.
Skills and capacity: Most organisations are still trying to close data knowledge and skills gaps. This is where you identify training needs and possibilities to outsource data collection or partner with a data provider if appropriate.
Implementation/change management: Are there any challenges that might hinder your data strategy, such as leadership buy-in for data-based decision-making?
In order to make the most of the strategic asset of data in your organisation, you must have a data strategy. To learn more about making a robust data strategy, please check out my book, Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things, in which I outline the process that has helped thousands of companies and government organisations around the world develop their own data strategy.