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Business analytics has become the highest ranked technology innovation, according to our benchmark research on business technology innovation, but a lack of trained resources and inefficient technology have hampered the best of organizations when they attempt to roll out analytics. Our benchmark research on business analytics in 2012 found that the majority of analysts in organizations spend more of their time on data-related activities than on analytic tasks, and our 2013 research on business technology innovation finds little improvement. At the same time, organizations are dissatisfied with trying to gain insight from dashboards of charts; see “The Pathetic State of Dashboards”. The worst thing wrong with business analytics today is that we are not able to read them quickly to determine what is relevant and what insights might demand action.

A company called Narrative Science aims to change that with new technology that can analyze data to create human-readable narratives in text form. Just like reading the cover page of the Wall Street Journal with text and a supporting chart, Narrative Science has developed the software to create these narratives from the data. The platform, called Quill, provides consistent form and depth in the text that is originated from the data and analytics that could be sourced from reports, spreadsheets, data files or databases. Using an expert systems approach, Narrative Science identifies data and facts, determines and prioritizes relevant elements and places them in a text structure. This approach changes the paradigm in how analytics are consumed by business management and managers.

I recently visited the company’s Chicago headquarters to get some perspective on the origins and advancements of its technology. I found a team very focused on how to use data and analytic processing techniques to present the right depth of information – that which can be read easily yet offer meaningful insights. Operating beyond the traditional business intelligence software market and approaching the needs of people from what they should be able to read has provided Narrative Science a fresh approach to what they offer in Quill.

I put Narrative Science’s technology to the test by providing the company some data from our latest benchmark research on technology innovation to see how it would work against a semistructured set of data and analytics. It created an intelligent narrative on a specific question that let me read and understand what was in the research. I included this episode in my keynote presentation at our recent Business Technology Innovation Summit to indicate how technology is advancing business analytics in ways beyond just the power of big data or the depth of analytic processing. This example is just one of hundreds of scenarios that Narrative Science could address with their software.

Narrative Science’s largest business challenge is prioritizing where to focus its efforts. It has a large market opportunity, and the company needs to grow its foundation of business processes to support a range of customers. It will likely require further capitalization for expansion, since the technology can be used in so many areas of focus. From an analytic process perspective, intelligent discovery using data to determine correlation and causation is no easy feat, let alone determining how to create the proper form of text output that can be read in a logical narrative and paragraph form. Narrative Science will need to provide the right level of controls with Quill to ensure that the software can handle large numbers of users and large volumes of data while generating meaningful documents that can created, distributed and read. Technically the product is easy to use but ensuring that it can make easily accessible the information from an on-demand or delivery perspective is critical for its future. Business professionals should also be able to train it on templates that describe the data and utilize cloud computing to handle the processing needed and make the results available on smartphones and tablets.

Despite these challenges which can be overcome, the company seems poised for growth. Customers can use its technology to make their workforce smarter at using analytics and data. Ventana Research was so impressed with Quill that we awarded Narrative Science our 2012 Technology Innovation Award for Business Analytics. The technology addresses the usability challenge in business analytics, which our research found to be the highest in importance for organizations selecting analytics technology. Of course the technology does presume that people must be able to read, but that should be an easier skill to find than the ability to eyeball pie charts and bar charts to tease out any issues in the visualizations, or trying to find the facts that matter the most.

It is not often that we see significant advancements in technology for business, but with Quill, Narrative Science has the potential to change the way organizations use and consume business analytics as information. It also could make sense of big data by bringing to the surface useful information. I look forward to seeing how Narrative Science makes Quill more easily available to digest the many existing data streams in organizations and transition today’s fixation with charts and dashboards to a narrative of insights.


Mark Smith

CEO & Chief Research Officer

Over the last several months, my colleague VP and Research Director Tony Cosentino and I have been assessing vendors and products in the business intelligence market as part of our upcoming Value Index. Tony recently wrote about the swirling world of business analytics, covering many of the dynamics of this industry. He and I have been reviewing the breadth and depth of over 15 of these vendors using our Value Index methodology, which examines the products closely in terms of usability, adaptability, reliability, capability and manageability. As we have gone through this analysis, we see the dashboard as the most common tool for displaying business intelligence. The early forms of dashboards appeared in the 1980s, but in my honest evaluation, today’s dashboards have not gotten much more intelligent in all those years. The graphics have gotten better, and we can interact with charts in what is commonly called visual discovery so you can drill into and page through data to change its presentation. So some progress has been made, but the basic presentation of a number of charts on the screen has not improved significantly and worse yet neither has the usefulness of the charts. Let’s face it: It’s a big mistake to place several bar and pie charts on a screen side by side and assume that business viewers will know what they mean and what is important in them. We cannot assume that individuals in an audience have the ability to interpret charts and draw the right conclusions from them; just being pretty or interactive will not communicate the desired message.

 The lack of adoption of business intelligence that includes dashboards is notorious in this industry, and so are the billions of dollars that companies have spent on BI products in the last decade. It is not helpful to make a big statement that the technology has failed; we should look for reasons that have held it back. Here we might start by questioning whether the tools present the right information in a useful form for business people or if organizations have properly configured what tools they have purchased. If the goal is to inform them through dashboards, then maybe we need to make it explicit what the dashboard or collection of charts actually mean. Typically, this means describing in words the issues or priorities that need to be examined further. A little discipline in populating the dashboard could help, such as presenting only the charts that clearly point out issues that need attention and determining which ones to use by applying analytics. If we ask why Microsoft PowerPoint is so popular as a business intelligence tool, we probably would find that the answer is the descriptive text boxes that accompany charts, providing summary sentences or emphasizing specific bullets in a list on the slide. While many people do not like the static nature of Microsoft Excel based charts in presentations or PDF versions of them, they do through human intervention with annotation and commentary provide better explanation of the charts than dashboards are doing today. If we expect our organizations to move beyond personal productivity tools and work in a collaborative enterprise environment with dashboards, we better understand how business intelligence should adapt to the way people work and operate not the other way around. In this case it may not be true that, as the old saying goes, one picture is worth a thousand words but a hundred or so hundred words explaining the relevance of the chart could really help.

Many technology vendors believe they need to provide better context in their dashboards, so they try to align the charts to the geographic area of focus, or to the product line of responsibility or to management key performance indicators to make them more usable. Providing better role-based dashboards that are generated based on the individual’s level of responsibility and the business context is a good first step, though most business intelligence vendors do not provide this level of support. But just presenting charts tuned to the context of the individual’s role that may or may not require action is not enough. We need to prioritize the information and make it like the news, with headlines and stories that people can read to determine if they need to make decisions or take action. Whether you are reading the physical or the digital version of The Wall Street Journal or USA Today, newspapers have survived over the centuries as the main source of what humans read in formats they can comprehend. When is the last time you saw a dashboard that communicated the story of its charts and explained the analytics? Well, once upon a time analytics and logic were applied to generate stories, in the early 1990s in a product called IRI CoverStory. Then it was classified as an expert system that programmatically would create English sentences based on the interpretation of the analytics in a memo that the system created. I would even be happy if we had titles and sub-titles to the charts that were dynamically created and represented something to guide an individual to what the purpose of the chart is to represent. Many of the current business intelligence technologies do not even allow for a free form text box that can be placed besides a chart which is really sad as this is one of the most basic methods used in business today. It would be great if dashboards could make these steps forward and make it easier to understand what is presented, but 20 years later, they have not.

 Another thing dashboards need to do is help individuals take action based on the information they receive. My colleague Robert Kugel has written about action-oriented information technology frameworks and how they can help increase the productivity and effectiveness of our workers. To date, most developments of the notion of an action-enabled dashboard have focused on data discovery and supporting root-cause analysis; that can’t match the familiar people type actions that happen in our organization – collaboration through dialogue to address issues and opportunities.

 Some of my industry colleagues have written books on dashboards to capitalize on the hype surrounding the topic. It’s about time for a set of books about the death of the dashboard or moving beyond dashboards; the current designs are not advancing the ability to take appropriate action on the information presented or provide the right level of guidance using analytics. We are entering the next wave of discussion on visual discovery, but so far much of this focus is just about using visualization on greater volumes and velocity of data, not making it more useful for the general population of business users. If we want to learn from the disappointing decades of business intelligence deployments, then we should find out what our business users really need to take action and make decisions on the information; delivering prettier charts won’t help. Until then, we are just perpetuating the past, and we know it has not had the best track record in advancing usefulness and adoption of business intelligence and dashboards.

I will follow up on this rant of the state of dashboards by writing about the lack of improvement in the types of metrics and indicators as they relate to overall business analytics, which are another source of the problems that underlie our current methods of delivering and providing access to analytics through business intelligence. We all can do a much better job in meeting the needs of business and truly advancing the usefulness of technology that still holds promise for significantly impacting organizations’ effectiveness.


Mark Smith

CEO & Chief Research Officer

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