Building a value based Corporate Culture, Big Data: Ethical and Regulatory Framework
BUILDING A VALUE BASED CORPORATE CULTURE
A values-based culture holds that an organizations’ values are what support its’ vision, shape its’ culture, and reflect what is important to the organization. In essence, they are the organization’s identity – the core principles and beliefs.
Remember back in 90’s when the new catch word was “team” and “teamwork”. More recently “employee engagement” has also taken hold. The problem is that simply using a new theory without a full understanding of it is like putting a new mission statement on the wall every few years. In this sense, you can’t say your going to implement a Values- Based Culture without understanding that there is more to it than putting some values on the wall and expecting people to live them.
This same article by the Economist went on to say there is still a big difference between actual values implementation and theory. In a study conducted by the Boston Research Group…
“Only 3% fell into the category of “self-governance”, in which everyone is guided by a set of core principles and values that inspire everyone to align around a company’s mission”
This does not surprise us at all. In her book Built On Values, Ann Rhoades provides a comprehensive blueprint for creating a Values-Based Culture. Her process reveals that company leaders must lead by example and are the ones most responsible for driving the values. One of the key success factors is living the values. You cannot expect your employees to live a value that clearly is not held by leaders and management.
There are many components to a values-based approach to management. Some of the most important are.
- Make sure values are defined in ways that are simple and understandable by everyone in the organization.
- Understand the link between stated values and what that means in terms of employee behaviors.
- You must hire, reward, recognize, and even fire people based upon stated values.
- You must maintain the simple discipline needed to keep your culture from falling into old habits.
ETHICAL AND REGULATORY FRAMEWORK FOR BIG DATA RESEARCH
Vast quantities of data about individuals are increasingly being created by services such as mobile apps and online social networks and through methods such as DNA sequencing. These data are quite rich, containing a large number of fine-grained data points related to human biology, characteristics, behaviors, and relationships over time. They hold tremendous potential for scientific inquiry, as they can enable researchers to explore research questions at an unprecedented level of detail. In addition, the costs of obtaining, storing, and analyzing these types of data are quite low, and falling, relative to the costs of conducting traditional research studies. For these reasons, large-scale data are leading growth in fields such as computational social science and biomedical big data research. As just one example, public health researchers are supplementing traditional methods of disease outbreak detection with streams of data from social networks, chat rooms, and web search queries. Interest in big data for research is expected to continue to rise as the number of large-scale data sources rises and the capabilities for big data analysis advance. We argue, however, that the current research framework is ill-suited to the oversight of large-scale data research.
In response, this Essay outlines elements of a new ethical framework for big data research. It argues that oversight should aim to provide universal coverage of human subjects research, regardless of funding source, across all stages of the information lifecycle. New definitions and standards should be developed based on a modern understanding of privacy science and the expectations of research subjects. In addition, researchers and review boards should be encouraged to incorporate systematic risk-benefit assessments and new procedural and technological solutions from the wide range of interventions that are available. Finally, oversight mechanisms and the safeguards implemented should be tailored to the intended uses, benefits, threats, harms, and vulnerabilities associated with a specific research activity.