Tag: Decision Making Beyond

18
Apr

Innovation Methods Mapping Preview

Two + years in the making, Humantific, in concert with OPEN Innovation Consortium is sharing the preview version of the new book:

Innovation Methods Mapping / DeMystifying 80 Years of Innovation Process Design.

If you would like to send us a comment, or be placed on the pre-order list for the print version of the book please feel free to leave a comment below and or email: methodsmapping (at) openinnovationconsortium (dot) org

OVERVIEW
This workbook presents a new kind of methods analysis framework applied to 50 innovation process models spanning a period of 80+ years. Embedded in the framework is a new form of innovation process literacy, designed to enhance understanding of historical and current process models, as well as inform future process design.

PROJECT PURPOSE
This study has been created and shared for educational purposes.

This book is designed to fill what the consortium perceives to be a void in the field of innovation process knowledge.

As an OPEN Innovation Consortium initiative, the goal of this book project is to help move the art, science and design of innovation process modeling forward into the 21st century.

ABOUT OPEN INNOVATION CONSORTIUM
See Open Innovation Consortium in the Initiatives section of this Humantific website.

To receive information on other Humantific projects, events and initiatives feel free to subscribe to Humantific Quarterly.

09
Dec

Consider TIME / Big Data For WHEN?

In this new series, Humantific SenseMaker Insights, we will be sharing a few tips based on our 15+ years of work and experience in the realm of helping organizational leaders make sense of complex fuzzy situations. Sometimes mountains of data exists in those often pressing situations, while in others, little or no data exists–but regardless there is need to drive forward.

Today, in the avalanche of Big Data crashing on all of our shores and in the marketplace push to consider data a “new natural resource”, a now abundant shapeable material, do you ever get the feeling that something important in that messaging is not being acknowledged, explained, or talked about?

In the competitive (some might say over-hyped) marketplace, what we often see missing in Big Data conversations is the simple acknowledgement that data sets are particularly useful in the construction of certain types, not all types of pictures. Apart from the many technology-related advances, certain basic data-related principles still apply–at least until humans figure out how to work around or change the underlying physics of the universe..:-)

Recently a Humantific Visual Analytics Team undertook an analysis of 200 years of data visualizations with the goal of better understanding what kinds of pictures have been made, historically, using various forms of data. Some readers might be surprised by the findings.

Acknowledging that not all data visualization is being used in the context of organizational or societal innovation it is this particular realm that we remain focused on and interested in. The interconnections between information and innovation acceleration have been at the center of Humantific’s work for more than fifteen years. While swimming in the data tsunami lets not forget a few innovation fundamentals.

In all of our visual sensemaking work we are building-block agnostic. We are not tied to only being able to make pictures based on data-sets alone. Others might be. At Humantific data is just one material used in the construction of informing pictures.

Among our first questions in any visual sensemaking engagement is this one introducing the consideration of time: WHEN is the picture that you seek to create? Asking WHEN inevitably informs the equation of what it is that will likely be needed to construct your picture. Data might or might not be the right “material”. To consider such a question, we, at Humantific, use a simple SenseWHEN viewing lens that contains these three parts: Yesterday, Today and Tomorrow.

We recognize that the creation of Yesterday (Past), Today (Present) and Tomorrow (Future) pictures require quite different considerations and building materials. We have known for some time that data analytics and data visualizations are great for constructing pictures of Yesterday and Today. Tomorrow pictures are often inspired and/or informed by data, but no data exists for the not-yet-arrived future, regardless if that future is next year, next week, or ten minutes from now.

While we certainly acknowledge all the promising innovations underway in the realm of data-based predictive analytics, it remains true that today, in one way or another, pictures of Tomorrow have to be created from a “magic” mix of facts, presumptions, visions, projections, and ideas. In addition, many leaders are certainly well aware that in the context of organizational change and societal change (wicked problems), pictures of Tomorrow (solutions) most often have to be constructed in a manner that is conducive to buy-in by multiple constituents, ie: cocreation.

At Humantific we do a lot of futuring work with organizations and, so, are often called upon to help design and construct interfaces, tools, and experiences to help humans cocreate pictures of Today-Tomorrow as well as the subsequent bridge-building. Organizational leaders often call upon our team to lead the multi-stakeholder cocreation of the bridges of change between the Today and Tomorrow pictures. How are we going to get to that future? Often it’s going to take considerable work and change, including behaviors. We will talk more about this and share additional insights in this direction in future posts.

To undertake the sample view across a 200+ year period of data visualizations, the Humantific Visual Analytics Team utilized 5 well known books, including William Playfair’s 1786 AtlasGraphic Methods for Presenting Facts (1917), Graphic Presentation (1939), Visual Complexity Mapping Patterns of Information (2011), and Information Graphics (2012). Inside the 5 volumes we viewed nearly 1000 visualizations.

Looking across that two century time span, what we found was that 98% of the data visualizations were pictures of Yesterday or Today. Out of the 989 diagrams created over a two century period only 2% were attempts at pictures of Tomorrow.

In terms of proportional orientation, the earliest book from 1786 was not significantly different from the latest Information Graphics compendium for 2012. In Playfair’s 1786 book, 100% of the visualizations were comprised of Yesterday and Today pictures. In the new book Information Graphics, published in 2012, 95% of the visualizations were comprised of Yesterday and Today pictures. That is not much of a change across two centuries!

While embracing the many opportunities that Big Data represents, we have found in our own experience that organizational and societal changemaking tends to be more complex than data crunching, data visualization and data based projections. While all of those activities can certainly be informative we recognize that there is a lot more to changemaking and futuremaking then understanding pictures.

We share these kinds of perspectives with the organizational leaders working with Humantific, as they are tasked with figuring out how best to envision futures and then drive change in organizations and societies.

The Big Truth about Big Data is that it is unlikely that “data visualization” alone will get you to the future that you have in mind for your organization or your society. It can help you get there. It can help you better understand Yesterday and Today, which often informs Tomorrow–but let’s be real and acknowledge that more and different kinds of work are also going to be needed along the way. Humantific is already working on the other side of this realization. The “Beyond Big Data Visualization Era” is not only already here, it has been here for some time…:-)

Inspired by Humantific:

“The Other Visualization.”

Related here on this Humantific site:

Making Sense of the Early SenseMakers

Lost Stories Information Design History

Before, During and After Isotype

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