Analytics Democratization: Start with a Maturity Roadmap

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Click to learn more about author Rishi Diwan.

Nestled between multi-experience AR/VR and human augmentation on Gartner’s top 10 strategic technology trends for 2020, data democratization isn’t the topic your kids will be asking about when you pick them up from school – but it may be the most undervalued. 


Learn new analytics and machine learning skills and strategies you can put into immediate use at your organization.

Data democratization is a fancy term for the most common question a company faces: Who gets access to data, and what can they do with it? 

Accessibility and speed – no matter a user’s location or expertise – are critical for ambitious organizations, but today’s knowledge workers need access to analytic insights, not just data. Therefore, I prefer the term “analytics democratization.”

As the pandemic has sent millions of workers into home offices, our reliance on a centralized IT function is changing too. Analytics democratization enables members of your team to find and analyze data to make impactful, data-driven decisions – without expert assistance. 

OK, So You’ve Got the Data – Now What?  

If data is accessible to an average user – not just your data scientists – that’s fine and good. It’s what they can do with the data that makes data democratization both interesting and powerful. 

Wherever your organization lands on the spectrum of democratization, some level of culture shift is usually required for the change to be meaningful. Is data stored in silos created by internal dynamics? How is external data used (or not) to give a complete picture of the analytics problem or business problem you’re trying to solve? With data, you don’t know what you don’t know – or, you often don’t know how data can help you – until you get access to it. 

But providing access is step 1. What happens next is where things get interesting, but the potential pitfalls get realer too. If you’re going to spend the capital to make culture changes about who gets access to data and when, it’s good to have a strategy to make sure the juice is worth the squeeze. Here are some best practices: 

1. Write up your analytics maturity roadmap. Begin with an overall look at your Data Strategy – how does analytics help you run your business now, and how will analytics help you adapt and innovate as you move up in analytics maturity?

2. Develop an employee education process. Data Strategy will look different to different teams, depending on skill level and function. Your employees will need to expand their thinking on what’s possible in a given role, how they can contribute to the success of the company using data, even without a Data Science or analytics background – and you’ll want a formal way to support your team’s Data Literacy. You may even set up a Data Center of Excellence or Data Academy like Airbnb, who developed an in-house Data University and curriculum for its employees. 

3. Prioritize infrastructure changes, if necessary. Check your roadmap. Will moving to a new infrastructure help you on the journey? Think about simplicity of management and cost but also timelines to support the needs of the business. 

4. Leverage machine learning and AI. When Data Science remains a science experiment, the return on investment remains unrealized. Find ways to bring model-driven insights to the core of your business, and deploy models closer to the data. 

5. Keep going. Remember that the process of democratizing analytics is never complete. Celebrate wins as you go. 

Infrastructure Challenges Are Real 

Based on research my organization conducted last year, senior business decision-makers initially demonstrated confidence in being able to democratize analytics. Digging deeper, we found that nearly half (46%) believed that analytics democratization wasn’t possible for them. Four out of five respondents reported IT infrastructure challenges, performance limitations, and infrastructure constraints. To open up access to data and analytics, businesses need to determine if employees are able to actually work with the data at their disposal. Good questions to ask are: 

  • Is there sufficient Data Literacy within our business?
  • Can my colleagues get the insights they need from the data at hand?
  • Does our organization need to increase analytics democratization even further?

Data and Analytics Transparency with an Abundance Mindset    

Your company’s strategy, infrastructure, and employee Data Literacy will always be unique, but the need for data democratization is unavoidable now for the world’s most ambitious organizations. 

Shifting from a restriction to an abundance mindset may be the most consequential thing you can do for your teams and business.  

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