Jian Huang is the Chief Executive Officer at Survature providing the vision for reinventing the way the world experiences surveys. He is a professor of computer science at the University of Tennessee (UT) researching data analysis, visualization, and human-computer interaction. His research has received funding from the National Science Foundation, the US Department of Energy, the US Department of Interior, Intel, NASA, and UT-Battelle. Jian received his PhD from the Ohio State University.

Recent Posts

When did ‘innovation' become a 4-letter word?

December 1, 2016 by Dr. Jian Huang

Hard to believe the holiday season is already upon us. Time once again to race towards a strong Q4 finish and prepare for a new year.

Here at Survature we run this race but are also uniquely positioned to watch others do the same. As a founder of a software startup, part of my job (and joy) entails talking to users and helping them to envision and manage their feedback data cycle. Through that process, many users have become friends of ours. A recent conversation really resonated with me. The reason—my friend leads innovation efforts at a multi-billion dollar company, his work makes a big impact on their global business, he is respected throughout the company, just architected a $100M partnership through a business model innovation, yet he feels “innovation” has become a bad word.

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Paralysis by Analysis is Killing Strategic Initiative

November 16, 2016 by Dr. Jian Huang

Strategy is a big word. Every decision maker faces the task of developing and deploying strategic initiatives many times throughout the year. Whether it is the C-suite, VPs with profit and loss responsibilities, directors in charge of initiatives, and managers leading front-line operations, everyone is looking for better information that will help drive strategic decisions.

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Building a strong data analytics pipeline. What should you outsource?

October 18, 2016 by Dr. Jian Huang

Much of the modern economy runs on fuel. Much of the future economy will run on data. In this analogy, data is the oil and analytics is the gasoline. Given this data economy, how do you build a strong data analytics pipeline of your own? Should you build your own refinery or should you buy gasoline direct? Simply put, does it make sense to outsource or not?

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3 Ways Data Analytics Delivers Business Value

October 4, 2016 by Dr. Jian Huang

During the recent StartUp Week, there were many events taking place nationwide. Data analytics was a popular topic across the board. At one of these events I spoke on a data analytics panel attended by aspiring entrepreneurs (who are pursuing ideas related to data analytics), practitioners, software developers, users, and bosses (who are paying for data analytics), a multitude of “what-if” questions flew in the air. It was an exciting event for all.

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"Hatless-Hackers" are driving organizational change in surprising ways

September 13, 2016 by Dr. Jian Huang

Knowledge workers from C-suites to entry-levels alike are adopting new web services to make previously difficult tasks easier to manage. However, these new solutions can result in headaches for IT departments, because many 3rd party software platforms exist in the “cloud”, which is open to business and compliance concerns due to privacy and security issues.

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3 things that feedback analytics must learn from business intelligence

August 10, 2016 by Dr. Jian Huang

Businesses of all shapes and sizes are increasing their use of data to reveal insights and drive decisions. No matter the source of the data—IoT sensors, predictive computer models, electronic transactions, human feedback, or other; there is a rapidly expanding need for a faster, more extensive, and more thorough view of what is happening, the causes, what to do about it and why.

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Forget about the ban on P value. There is a bigger issue.

July 1, 2016 by Dr. Jian Huang

In early 2015, the journal editors of Basic and Applied Social Psychology announced they would no longer publish papers that contain p-values. Nature published an article to further discuss the controversy revolving around p-value. It doesn’t matter which side you are on, it is obvious that we are all obsessed with p-values, because they have served as a rule of thumb for flagging noteworthy findings across the sciences. As the recent controversy shows, p-values are open to exploitation, which is sometimes known as “P hacking”.

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Do you know which business decisions to take action on first? An Action Priorities Grid can tell you.

May 23, 2016 by Dr. Jian Huang

When developing new strategic initiatives and guiding strategy deployment, decisions makers need a targeted and specific grasp of their customer and employee priorities. Advancements in online feedback collection and data analysis are yielding more and more sophisticated methods for gathering insights that lead to making more informed and better decisions. The Action Priorities Grid (APG) is one of the latest methods for doing just that.

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Are you capturing enough client-centric data to inform your workplace design projects?

March 9, 2016 by Dr. Jian Huang

More than ever before, architecture and design firms are hungry for client-centric data to gain a better understanding about a client’s needs and priorities. Firms that have a competitive edge are those that can demonstrate the capacity to better collect, decipher and validate a client’s complex project requirements.

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Did you know that NOT getting a response to a survey question can be a good thing?

February 10, 2016 by Dr. Jian Huang

One issue we see authors wrestle with when drafting an online survey is whether or not they should require participants to answer certain questions. The compulsion to force a response from someone is understandable. After all, the point of the survey is to collect as much information as possible and there are always certain questions in a survey that are more important to the survey author.

Where things get problematic is when a respondent comes across a question that doesn’t particularly apply to them or they simply don’t have a strong opinion. The survey should allow participants to skip these questions or provide a response that reflects their indifference. When a survey writer neglects to include these options and forces a respondent to answer it often leads to a couple of disastrous results.

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