Sense Making
Experience Management by Sense Making
Q: What’s the business value of a data analytics solution that fosters better sense making through Experience Management?
A: Whatever it’s worth to your company to know what’s going on – so you can figure out what’s best to do.
In data analytics, “sense making” is the process of understanding the connections within your data’s Experience about people, places, things and events – either to anticipate what will happen next, or to understand the cause-and-effect of prior outcomes. As such, it usually involves having a human “in the loop” to conduct a process of investigation and discovery within large data sets.
Saffron Natural Intelligence Platform
Continuous Sense Making is a central feature within the Saffron Natural Intelligence Platform, and when applied via SaffronAnalyst it enables more sophisticated, timely and accurate decision making in support of critical and often revenue-impacting business issues.
Let’s say your company serves the capital markets, and you want to know everything you can about the current activities of risk-averse investors who conduct online stock transactions. Or maybe you work in a law office and are trying to identify cases that all have similar characteristics to the one you’re currently working on. These are just a few instances where a business might benefit from powerful data analytics for Sense Making. In some military cases, the issues are truly life or death.
How it Works
Within Saffron, associative memories retain everything about a person, place, thing or event, within both space and time. Saffron also remembers their connections with other people, places, things, and events within space and time. Additionally the system stores the frequency of these occurrences, while also providing a semantic and statistical framework for analysis.
Sense Making is supported by Saffron’s Connections, Networks and Analogies REST APIs, and our end-user application interface – SaffronAnalyst – is an illustrative gateway that makes Sense Making simple and easy.
For a simple implementation of Sense Making, visit www.tweetdive.com.
Industry Use Case
National Security
Overview
While applicable in virtually any business environment, Sense Making is well known for its value in military Intelligence analysis. Saffron has first-hand experience applying this dimension of our robust data analytics solution to the problem of IED (Improvised Explosive Device) defeat in Iraq.
Sense Making Objective
Draw on Experience to save lives by finding enemy insurgents and stopping random bombings before they occur.
Customer Situation
The U.S. Army and its coalition partner war-fighters in Iraq needed the ability to decide and act at the tactical level to eliminate, capture or exploit insurgent targets directly or indirectly involved in IED activity. To be effective, this targeting had to be done prior to actual IED attacks (and at the time of our forces’ choosing) in order to prevent loss of life for both civilians and war-fighters.
Saffron Technology played a lead role on the team formed to enable and enhance the analytic workflow of war-fighting intelligence analysts. SaffronAnalyst was developed by Saffron to provide an analyst user interface consistent with the workflow and thought processes of an actual Intelligence analyst. Although the system was already capable of identifying associations and their frequencies between basic entities like people, places and things –– Saffron was asked to provide this analysis within the existing analyst workflow by integrating Saffron’s Sense Making capabilities with other third- party tools to provide an end-to-end analytic workbench.
The Customer-Saffron Solution
We worked closely with military Intelligence analysts, and Saffron’s engineers were trained in all the current methods of analysis used by the customer. The customer’s existing processes involved manually extracting entities and building a co-occurrence matrix. Saffron identified immediate opportunities where the Saffron Natural Intelligence Platform could improve the “time and speed to results” over their current manual process.
Saffron engineers observed Intelligence analysts in action and spent time on-site witnessing their analytical process in real time, against real targets. This made it easier to identify where SaffronAnalyst should integrate into the analysts’ workflow, so as to enhance –– but not disrupt –- current procedures.
The solution called for adding new features and capabilities to Saffron’s existing product to incorporate the desired components of the current manual process. At the same time, the customer created new approaches to parsing unstructured data. To ensure a streamlined and accelerated data-analysis process for the customer’s smaller operational units, Saffron and the customer teamed with a third-party ETL (data Extract, Transform and Load ) vendor.
Results
Integration of the two products was developed, tested and implemented in under four weeks. Intelligence analysts reduced the time for creating their Critical Entity Link Charts by 80% in the final benchmark test. And Saffron further enhanced its Sense Making tool.
Technical Approach
Many organizations face a similar challenge of quickly analyzing large volumes of intelligence data with a small team of people. Saffron Natural Intelligence Platform’s Sense Making capabilities make it ideal for helping organizations and their workgroups analyze large volumes of such data in a short amount of time.
Instead of two-dimensional models and manually designed tables, Saffron uses dynamic, multi-dimensional memories to quickly identify connections and their frequencies of occurrence within massively dense and “noisy” data sets.
In this particular case, Saffron was integrated with entity extraction tools including SRI, Inc.’s NetOwl and Basis Technology, Inc.’s Rosette, and ingested varied unstructured data sources into SaffronMemory Base. Saffron’s analytic results were then integrated with i2, Inc.’s Analyst Notebook to provide complete transportability of the Connections, Analogies and other supporting evidence from Saffron directly to the Intelligence analyst’s desktops. In addition, new visualization capabilities for SaffronAnalyst were added, including new link analysis capabilities, entity management, export to ESRI’s ArcGIS product, analyst interest collaboration, and more. Throughout, Saffron’s Connections, Analogies and Network Reasoning Methods were used in this Sense Making implementation.
The value emerges in the extraordinary speed and accuracy with which the Saffron Natural Intelligence Platform returned its data analysis, giving Intelligence analysts enough confidence to act, and enough time to save lives.
Conclusion
Experience Management by Sense Making is Saffron’s proven, sophisticated method of fast, comprehensive and pertinent data analysis.
To learn more about how SaffronAnalyst can improve your organization’s strengths in Sense Making data analysis, contact us. To see how Saffron’s capabilities for connecting and analyzing data can make sense out of simple yet disparate data sets, visit our public demonstration application built over Twitter, at www.tweetdive.com.
Download a PDF of Sense Making Use Case – Download
