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7 Elements of Human Centric IT [Infographic]

7 Elements of  Human Centric IT [Infographic] | Distance Ed Archive | Scoop.it

"Government IT leaders and knowledge workers are faced with the task to make smarter decisions at faster speeds and with fewer resources. As the government IT landscape continues to change, agencies must focus on human-centric IT solutions to improve their business functions. This means crafting IT systems that connect people to process to transform service delivery.

GovLoop has partnered with Pegasystems to develop the infographic below. The infographic, Defining Human-Centric IT,  will walk you through this new model of governance and highlight the benefits of a human-centric design. This is the way forward for government and is rapidly changing the role of the public sector employee and leading to improved services for citizens." from source: http://www.govloop.com

#agile #innovation #change-management #information-technology #IT #ITC #communications #collaboration #mobile #tablets #progress #ROI #adoption #Transformers #Traditionalists #Transformation #Not-invented-here


ghbrett's insight:

This page points to a somewhat interactive infographic about 7  elements of human centric information technologies. While the target here is government, it is a model that can apply to any enterprise whether corporate or academic. The Traditionalists are those who do business as usual. Or else they are too busy being either time or financially constrained to try anything out of the track (rut) already planned. Whereas the Transformers are calculated risk takers who focus on the needs of their members/clients/audience. They adapt to and adopt new policies as well as new technologies. These changes will lead to further changes as they evaluate and move forward with their successes.

What I like about this infographic is that it presents a parallel viewpoint of the processes each culture uses for comparison. For example stage one: Traditionalist - "The Current Model leads to loss, error, and duplication; while the Transformer's tip 1 is to Think Big, Start Small. And so one.

Again consider this chart as a metaphor or model for your agency or enterprise. In some cases it is signing to the choir of transformers, on the other hand it may provide the Transformer guidance in approaching a Traditionalist Management process.

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NOT-HG-13-003: Request for Information (RFI): Training Needs in Response to Big Data to Knowledge (BD2K) Initiative

"The National Institutes of Health is launching Big Data to Knowledge (BD2K), an initiative to address how best to manage and utilize the large amounts of biomedical data that new technologies can generate (http://www.nih.gov/news/health/dec2012/od-07.htm).

 

... The era of ‘Big Data’ has arrived for biomedical research, bringing with it immense challenges as well as spectacular opportunities. In this context, ‘Big Data’ is meant to reflect the challenges facing biomedical researchers of all stripes in accessing, organizing, analyzing, and integrating datasets that are increasingly larger, more complex, and more numerous. These data are also of diverse types that must be integrated, including imaging, phenotypic, molecular, exposure, health, and many other types of biomedical, behavioral and clinical data. While used here for convenience, the phrase ‘Big Data’ is intended to be shorthand for the reality that biomedical research has become a data-intensive enterprise.

 

Advances in biomedical sciences using Big Data will require more scientists with appropriate expertise and skills, some of whom will be critical members of interdisciplinary teams. NIH is interested in increasing funding for long- and short-term training at all professional levels, in areas essential for accessing, organizing, analyzing, and integrating biomedical Big Data (e.g., computational biology, biostatistics, bioinformatics, the quantitative sciences, and related areas)." - from source: http://grants.nih.gov

ghbrett's insight:

Big Data, data mining, and the aggregation of data from varied resources are becoming more important to the research community. This initiative of NIH should provide findings and information that can transfer and be applied to other communities and agencies.

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