How Do You Prioritize Data Projects?
11 December 2021
Every business could come up with hundreds (or thousands) of potential data projects. How do you prioritize? Follow this step-by-step process, complete with fill-in-the-blank templates, to choose data projects that will provide the most value for your company.
All companies – no matter what size – in all industries must have a data strategy in place to be successful.
Data has become one of the most valuable and important business assets for companies. Businesses need to figure out a strategic approach to identifying what data they need and how to use that data to drive business performance.
But what’s the best way to prioritize data projects, when you have hundreds, if not thousands, of potential use cases?
Don’t leave this important task to chance. In this article, I’ll walk you through the process I use to help large and small businesses prioritize projects and create an effective enterprise data strategy.
Brainstorming Strategic Data Use Cases
There are endless opportunities for using data in your organization. So the key is to ask yourself, "What do we actually want to achieve as a business? What are some of our key challenges and objectives?"
When I work with organizations, I usually look at four different lenses when we’re trying to come up with a list of possible use cases. You can use data to:
- Help you better understand your customers. Who are your users? What are they saying, thinking, and buying? What are the biggest market trends?
- Offer smarter products and services to your customers, and add value by providing more customized experiences. I've written other articles on my site and created videos on my YouTube channel that illustrate how companies use data to develop smarter products, from companies like Google to Amazon and others.
- Improve internal processes. How can you streamline your operations, run your business better, do better marketing, or optimize your manufacturing processes?
- Monetize. Could you sell or rent your data? For example, Mastercard is taking data about the buying habits of their users, and packaging up that information to sell it to other companies.
Flesh Out the Details of Your Use Cases
For each data project you’ve brainstormed, you want to add a bit more detail. I’ve created this Data Use Case Template to help you fill in answers to the questions below.
- Identify your strategic goals. What is the business challenge your company wants to address?
- Find a way to measure it. How can you identify some measures of success? If I use data to help me with a particular business challenge, how can I measure if it's boosting performance and helping the company be more successful?
- Assign an owner to your use case. Who will your data customers be? Is this something that the marketing team is using, or the operations team, or someone else in your organization? This will help you identify the type of data you actually need.
- Figure out the source of the data. Where will the data come from, and are there any data governance implications (for example, legal requirements like GDPR) that you need to watch out for?
- Understand how you will turn the data into insights. What analytics approaches will the company use? This will help you identify implementation challenges and identify skills that you might need to develop within your team.
Again, can you use this template to fill out this information for each of your key use cases, and then you will have the starting point for your data strategy.
After you’ve defined your case studies, identify the most strategic ones for your company. This Data Strategy Template will help you cement your data priorities, as well as identify cross-cutting issues, themes, requirements and goals.
The key is not getting lost in the weeds or feeling overwhelmed by your options. Start with your existing business strategy, and your biggest challenges and opportunities. Then explore how data could help solve those.
To start with, choose 1 to 5 use cases, depending on how big and ambitious you want to make your data strategy. These will be the most strategic long-term use cases.
Then I also recommend defining 1 to 3 “quick wins” that you can accomplish fast and demonstrate value right away. This will help you get buy-in from people because they can see results from your data strategy right away.
With the help of this article and the templates I’ve linked to above, you should be well on your way to establishing a solid data strategy and implementing it to develop real value in your company.
For more on this topic check out my book ‘Data Strategy: How To Profit From A World Of Big Data, Analytics And Artificial Intelligence.
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