May 30, 2017 | Pia Opulencia
Why Your Business Intelligence Needs Artificial Intelligence
The promise of big data and its insights is very real, yet the adoption of BI platforms has run into some barriers. TDWI states that at organizations where 50% of employees have access to business intelligence tools, only 20% of that group actually use them. Why is this? One challenge is the systems aren’t always user-friendly. Another is that data interpretation skills aren’t commonplace among users.
As Narrative Science’s co-founder and CEO Stuart Frankel wrote in a recent issue of Harvard Business Review: “All of this suggests that trying to force people to become data literate is an uphill battle.”
So how has the market addressed these BI challenges?
Stuart shares, “Many attempts at solving the data literacy challenge have been explored; ranging from staffing consultancies as data advisors, to rolling out IT systems to support ad-hoc query, analysis, and reporting, to self-service business intelligence and visualization software to meet the dynamic reporting needs of business users.”
These tools historically have been geared towards data-savvy folks within the IT organization and have developed capabilities targeted at their particular skill sets. The shift towards self-service BI and visualization tools for everyday business users has raised the bar in terms of ease of use. But such tools can create as many problems as they solve, according to some critics:
Put a collection of data and visualizations in front of 10 users and they will each draw their own meaning from it. This is what makes self-service BI powerful but also dangerous. This happens for many reasons--self-serving bias, lack of analytical skills, lack of understanding of basic statistics, etc. If a picture is worth a thousand words, then it is probably worth a thousand interpretations too. Any information presented visually is always open to interpretation. Give users the ability to choose which pictures they look at and they will tell the story they like best.
Does that sound like a good solution to the business intelligence data literacy challenge? No, it doesn’t.
Intelligent narratives – a new way to do BI
Self-service BI tools fall short in meeting the needs of business users because they lack an accompanying narrative to help users truly understand the data they are consuming. In the last year, there has been a rise of narrative integrations for BI platforms as enabled by Advanced Natural Language Generation (Advanced NLG). Advanced NLG is a form of artificial intelligence that transforms typical data output into everyday language. Using Advanced NLG to automate routine data analysis and communication tasks can greatly increase workplace productivity and allow employees to focus on more high-value activities.
With Quill, businesses can work with existing IT and BI functions to better communicate insights from data, reducing overall time for data-driven decision making. Quill can augment existing analytic practices by providing a means for business users to quickly understand and act on their data via Intelligent Narratives. As BI pioneer Tom Davenport explains:
Stories have always been effective tools to transmit human experience; those that involve data and analysis are just relatively recent versions of them. Narrative is the way we simplify and make sense of a complex world. It supplies context, insight, interpretation—all the things that make data meaningful and analytics more relevant and interesting.
Intelligent Narratives From Narrative Science
If you find this vision of better BI enabled by Intelligent Narratives intriguing, we encourage you to learn more about them. Start empowering your BI and your employees with AI today.