![\"\"](\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/deloitte.png\")
<\/a>The estimated global volume of data is expected to grow 10x between 2016 and 2025 from 16 Zettabytes to 160 Zettabytes (1 Zettabye = 1 Trillion Gigabytes)[1]<\/a>. However, while data is forecasted to grow exponentially, the number of professionals capable of analyzing that data is growing linearly, at best. One of the many reasons Narrative Science was founded is to address this issue.<\/p>\n To tackle this problem, the team at Narrative Science is employing the use of natural language generation (NLG)<\/strong>, a software process that automatically transforms data into narratives written in natural language. Narrative Science uses NLG to improve organizational productivity by automating time-intensive data analysis and routine reporting activities, two well-known pain points in the technology and media industries. The company chose to focus on these applications due to its unique roots, as it was founded through a collaboration between two professors from the McCormick School of Engineering and students from the Medill School of Journalism, Media, and Integrated Marketing Communications at Northwestern University[2]<\/a>.<\/p>\n <\/p>\n The company\u2019s initial prototype, called StatsMonkey<\/em>, was made to automatically generate short news recaps of baseball games from relevant game data such as players, game score, and hitting performance[3]<\/a>. After seeing the tremendous potential for the technology, the company successfully commercialized its IP with the launch of its advanced NLG platform called Quill,<\/em> which analyzes structured data to automatically generates narratives written in human-like prose. The company\u2019s Quill platform, offered as a software-as-a-service (SaaS) product, is used by online media outlets and sports networks to vastly increase the efficiency of the wire reporting process, a traditionally time-intensive effort due to the large number of games and events these organization cover.<\/p>\n <\/p>\n How it Works<\/strong><\/p>\n Narrative Science focuses on the production of machine generated and automated content<\/strong>, a sub-sector within NLG. Companies in this sub-sector use machine learning and pattern recognition to scan large data sets, discover key insights, and automatically generate written narratives. At a technical level, Narrative Science\u2019s production engine works by amassing high-quality data, teaching algorithms to fit that data into some \u201cbroader understanding of the subject matter\u201d (such as the rules of a baseball game), and then using a team of \u201cmeta-writers\u201d (trained journalists) to turn that analysis into natural language using templates that vary in structure according to the subject at hand (such as sports or finance).[4]<\/a> Over time, the algorithms automatically learn to communicate data in the tone, style, and language of each client, as the platform is capable of understanding user intent and identifying what is most important to the target audience[5]<\/a>.<\/p>\n <\/p>\n <\/a><\/p>\n Product Expansion: Quill for the Enterprise<\/strong><\/p>\n After focusing initially on sports, Narrative Science saw an opportunity to further leverage the company\u2019s machine learning capabilities by adding additional features that allow it to deliver customized insights<\/strong> for all types of enterprises. In the short-term, the shift towards becoming an \u201cinsights\u201d company will allow Narrative Science to expand its footprint across the enterprise, creating value for both external stakeholders of an organization (such as a consumer who read the paper) as well as internal stakeholders (such as a CEO that reads an internal report). Instead of producing simple game recaps, helping organization realize true potential of their data should enable Narrative Science to differentiate itself in an increasingly crowded market.<\/p>\n <\/p>\n New Product Development: Dynamic Narratives<\/strong><\/p>\n Additionally, Narrative Science is also in the process of launching Dynamic Narratives<\/em>, a suite of natural language extensions that can be embedded business intelligence platforms to explain not readily obvious in charts, tables, or graphs. For this effort, the company was honored at the Chicago Innovation Awards <\/em>in 2017[6]<\/a>.<\/p>\n The numbers don\u2019t tell you anything. It\u2019s the understanding of those numbers and translating them into something that is readable that\u2019s a story that matters -Narrative Science CTO and Co-Founder Kristian Hammond. (Levy, 2018)<\/em><\/p>\n <\/p>\n Next Steps for Narrative Science<\/strong><\/p>\n One area I hope the company\u2019s management considers focusing on is in expanding local news coverage. Due to the immense pressures on the media industry and business model, an increasing number of small and independent news organizations have been forced to close or consolidate with larger firms in recent years. To its credit, the company is saying the right things, as management recently stated its hope to eventually be used to uncover the \u201csmall-scale\u201d stories that journalists overlook [7]<\/a> But these applications need to be more carefully considered going forward.<\/p>\n Open Questions Still to be Addressed <\/strong><\/p>\n Despite the company\u2019s claims, there is genuine fear in the media industry that Narrative Science, and startups like it, will eventually one day replace journalists altogether. Is this fear warranted? Will the computers at Narrative Science replace paid writers? Will there still be a need for reporters in 10 years?\u00a0 If so, what will their role be?<\/p>\n (791 Words) <\/p>\n <\/p>\n [1]<\/a> Aguilar, A. (2018). The data landscape: A report for Facebook<\/i>. [online] Deloitte UK. Available at: https:\/\/www2.deloitte.com\/uk\/en\/pages\/technology-media-and-telecommunications\/articles\/the-data-landscape.html [Accessed 14 Nov. 2018].<\/span><\/p>\n [2]<\/a> Adams, T. (2018). And the Pulitzer goes to\u2026 a computer<\/em>. [online] the Guardian. Available at: https:\/\/www.theguardian.com\/technology\/2015\/jun\/28\/computer-writing-journalism-artificial-intelligence [Accessed 14 Nov. 2018].<\/p>\n [3]<\/a> Narrativescience.com. (2018). About Us | Narrative Science. [online] Available at: https:\/\/narrativescience.com\/Resources\/About-Narrative-Science\/About-Us [Accessed 14 Nov. 2018].<\/p>\n [4]<\/a> \u00a0Levy, S. (2018). Can an Algorithm Write a Better News Story Than a Human Reporter?. [online] WIRED. Available at: https:\/\/www.wired.com\/2012\/04\/can-an-algorithm-write-a-better-news-story-than-a-human-reporter\/ [Accessed 13 Nov. 2018].<\/p>\n [5]<\/a> Hammond, J. (2018). Narratives Science Products- Quill. [online] Narrativescience.com. Available at: https:\/\/narrativescience.com\/Products\/Our-Products\/Quill [Accessed 13 Nov. 2018].<\/p>\n<\/a><\/a>
\n<\/strong><\/p>\n