People Science: The Science Foundation

Article 2 of a series of 6

The foundation of science is the scientific method. The scientific method is a body of techniques for acquiring new knowledge and/or correcting and integrating previous knowledge. It is defined “a method of procedure that has characterized natural science since the 17th century, consisting in systematic observation, measurement, and experiment, and the formulation, testing, and modification of hypotheses.” The scientific method is considered a continuous and ongoing process of building and refining knowledge through hypothesis testing.

There is a base of knowledge and theories for people scientists to build and refine through hypothesis testing. This knowledge includes general knowledge from scientific research and theory as well as specific knowledge unique to your organization and your people.

To understand how to test hypotheses in people science its helpful to review the various ways hypotheses are tested in both natural and social sciences. In natural sciences, hypothesis testing is primarily done through either laboratory or field experiments. The type of experiment used is determined by the field of study and feasibility. The experiment design then determines the validity and complexity of statistical analysis. In practice, the more factors that can be controlled in an experiment the less complex the statistical analysis becomes. In social sciences, hypothesis testing is less likely to be performed in true experiments, instead using a combination or quasi-experiments, observational studies, and complex statistics.

Controlled Experiments

These experiments are conducted in a highly-controlled environment, limiting the impact of other factors, and isolating the impact of the factor or variable being tested. These types of controlled experiments are routinely used in medical research or drug trials.  By using highly controlled environments and random assignment, and repeating experiments several times, the possible impact of cofounding factors is minimized, enabling the experimenter to isolate the cause-and-effect that is being tested.

Field experiments

Field experiments are like controlled experiments except the experiment takes place outside of a highly controlled artificial laboratory setting. These experiments are often used in social science or economics to test the impact of different types of interventions. There are many use cases in People Science for field experiments as a means of testing the impact of interventions designed to improve development, performance, or retention. However, usage will require random assignment of employees which is not always feasible.

Quasi-experiments

If random assignment of subjects is not possible an experiment is considered a quasi-experiment. Quasi-experiments can take place in labs, but often occur in natural settings. People scientists can leverage quasi-experiments as long as it is possible for some employees to receive an intervention and for some to serve as the control group.

Experiment vs. Observational study

An observational study is used when it is not feasible to fit a system into a lab setting, completely control confounding factors, or apply random assignment. Observational studies often involve factors that are difficult to quantify or control and without randomization can led to a host of statistical and analytical issues. Observation studies are used extensively in the social sciences and will be one of the primary tools for people scientists as well.

Observation and experiments for People Science

Scientists use the scientific method to expand human knowledge. They apply experiments to a small and controlled sample of the population with the intent of extending conclusions to the rest of the relevant population. Scientists are rarely able to measure or analyse the entire population they are studying. The field of people science is distinctly different from other science fields in this context. People scientists are not trying to expand knowledge applicable to all of humanity or a very large population. The people scientist’s world of analysis is constrained to the microcosm of the people relevant to their organization. People science benefits immensely from population constraint for in people science, the sample and the population can be the same size, so greatly simplifying statistical analysis.

People science, like all other sciences, is routed in foundational scientific principles. As an emerging interdisciplinary field combining data science with relevant fields of the social sciences, people science pulls insights from data and knowledge from relevant research theories.  However, unlike other sciences, the people scientist is not seeking a level of irrefutably certainty in analysis. The business world changes rapidly and often speed of insights is as important. The time required to run a well-defined experiment could make the results obsolete in a rapidly changing company. The people scientist must be able to balance robust and valid science with investment and time available, which will define the People Science return on investment (or analysis?).

See also Article 1 – From Data Science to People Science

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