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From data science to citizen data scientist (and what it means for all of SaaS)

data
(Image credit: Shutterstock / carlos castilla)

Love it or you hate it, data is here to stay. 

If it scares you, you can try to ignore it. If it comforts you, you probably want to crunch it. But the fact remains: these days, every single one of our actions generates data. Think about any day in your life, and you’ll have created data. Using your GPS to drive to work; your mobile phone to pay for groceries at the supermarket at lunchtime; your Google searches throughout the day when you’re taking a short break. Every single person is generating mind-boggling volumes of data every single day, just by going about their usual routines.

The good news is that, even if it scares you, there is a lot of valuable information hiding in that data which ultimately helps to make our lives easier. 

Whether it’s finding the fastest route to work, keeping an eye on our finances, or having a more intuitive search engine to rely on at work. While at one point this data was the preserve of the IT team - BI specialists, data scientists and other qualified data experts - now it’s for all of us. You no longer need a PhD in data sciences, or 15 years experience in technology to understand a dataset. All you need is access to a BI dashboard and a passion for learning, and away you go. 

These days, anyone can be a citizen data scientist. 

What exactly is a citizen data scientist? 

‘Citizen data scientist’ was a term first introduced by Gartner. 

They define it as: “a person who creates or generates models that use advanced diagnostic analytics or predictive and prescriptive capabilities, but whose primary job function is outside the field of statistics or analytics.” 

In other words, these are non-technical employees who use data science tools to solve business problems. They have a strong business background, and are able to combine that expertise with user-friendly technologies to make sense of their data and make smarter business decisions. 

These citizen data scientists don’t have to sit in IT, and are spread right across an organization; from sales and marketing through to customer services or human resources. 

Critically, their business experience and awareness of its priorities enables them to integrate data science outputs into business processes. And it doesn’t end there, because the ability to turn data into insights isn’t only of value in a business context; savvy individual data consumers are starting to rely on data to make better decisions in their private lives too.

What are these insights that can help us make better decisions?

The main reason is to become smarter. Data helps us decide what the best possible course of action might be, and makes our lives easier. More data-driven than finger in the air. 

In a business context this might be for the purposes of e-commerce, where vendors can use consumer behavior to decide how to structure a website to improve sales; or in logistics where historical travel data can help to plan the fastest possible routes for deliveries. In a consumer context, this might be someone wanting to keep track of their personal finances or save money more effectively using an app that keeps a record of spending patterns. It can even go as far as optimizing your car usage so that it creates less CO2. 

In every scenario, by giving consumers the ability to analyze their own data, in the moment, they can make better, more data-driven choices.

You decide what to do with the data 

There are lots of reasons why data consumers would want to take over the steering wheel for their data and become a citizen data scientist. 

Firstly, it has become almost impossible not to use data in our daily professional lives. Most businesses today measure performance through KPIs and more and more business decisions are made based on what this data tells them. They rely heavily on their data to take the next step, so if you’re not engaging with the data yourself, you might be a few steps behind. 

Secondly, there simply aren’t enough data scientists to keep up with the demand for insights. And with the ever-growing volume of data, a data scientist’s time is now being spent on more complex, analytical tasks like data modelling, preparation, AI and ML algorithms, which leaves less time for day-to-day business analysis. 

And thirdly (perhaps most importantly), the technology is now available to not just put them in control, but also enrich data by putting it into an important functional context. 

Technology has paved the way for a mass democratization of data science, with drag and drop tools making it easier than ever to slice and dice business data and remove complexity. And because business users have the subject matter expertise for their particular function, this means they can start to understand and put the data into a context that was previously not possible with dedicated data scientists.

So why is this important for SaaS product owners in a business context? 

Simply put, because technology that allows business users to become citizen data scientists means that they can make relevant, data-driven decisions without requiring technical expertise. From the perspective of an employee, this is a revolutionary approach which will see SaaS companies/products driving positive change in the organizations of their end users. Equipping users with the tools they need to analyze their own data will: 

  • Alleviate work from data experts so that they can focus on core analytics 
  • Foster a culture of data best practice across an organization with businesspeople encouraged to use technology for decision-making.
  • Position the SaaS product as innovative, supportive and built to create actionable insights for better decisions. 

Ultimately, no business user should be limited to a single data snapshot created by a data scientist with less business context. They need to explore and create their own views on the data, based on the expertise and context they bring to the table. As a result, the rise of the citizen data scientist and analytics-enabled SaaS platforms are likely to go hand in hand. 

Karel Callens, CEO & Co-Founder, Cumul.io

Karel Callens

Karel Callens is the CEO and Founder of Cumul.io.