Traditionally, people--especially economists--thought that human behaviour was dictated by outcomes. That is, we seek to maximize our outcomes, like getting a large profit. Consequently, most of the incentives and disincentives in business are outcome-centred like bonuses or suspensions. Working to maximize outcomes is called distributive justice.
In the mid-seventies, the social scientists John W. Thibaut and Laurens Walker combined their research on psychology of justice and the study of process to look into what makes people trust a legal system enough to follow the laws voluntarily. They discovered that people care as much about the fairness of the process as the outcome the process generates. Simply put, people want to be treated like people and not numbers.
FairProcess, or procedural justice, universally requires adherance to three principles:
By no means does fair process imply consensus. In fact, people are more than happy to let someone make the final decision provided they understand why that decision was made and that it was the best decision for the best reasons. And of course if you try to ForceConsensus?, you will experience many failure modes, especially the ConflictParadox where we get buried staring at the trees instead of seeing the forest.
Because fair process builds trust and commitment, people will go above and beyond the call of duty, volunteering where before they would have to be coerced. Moreover, it is clearly optimal to use both mind and body instead of just body. This builds on the Group Dynamics theory of Kurt Lewin (1947), which states that people learn and adopt new imposed behavioural methods faster if they have a chance to influence the methods' introduction and application through consultation (Coch and French Jr., 1948).
On the other hand, once fair process has been violated, the victims often demand far more compensation than what they've been slighted. They tend towards retributive justice, trying to punish those that have harmed them and ensure it never happens again. The resulting red tape could cripple the organization.
FairProcess is a humanistic management style which goes far past Wiki:FredrickWinslowTaylor's ScientificTheoryOfManagement?. It is essential in all organizations, businesses or OnlineCommunity, to break past the power imbalance.
Source: Kim, W. C., and Mauborgne, R. (1997). Fair process: Managing in the knowledge economy. Harvard Business Review, July-August, 65-75.
Coch, L., and French Jr., J. R. P. (1948) Overcoming resistance to change. Human Relations, 1, 512-533.
Lewin, K. (1947) Forces behind food habits and methods of change. Bulletin of the National Research Council, 108, 35-65.
Summary by SunirShah.
FairProcess is one of the fundamentals of this site, so it appears in many places. Click on the title of this page to see the backlinks. Alternatively, some important related pages are OpenProcess, and the more practical, OnlineDiary.
After quite a bit of reading, I think one should be aware that many "academic" authors (especially economists and philosophers) use common words (like "fair") with a specific technical meaning. When this is done openly (as apparently done above), it can provoke interesting conversation. When the technical use is hidden or obscured, it can lead to many pointless arguments over peripheral disagreements (while ignoring more important conflicts).
Personally, after studying philosophy for a few years (including a couple years as a philosophy major in college), I decided that "Philosophy is the politics of pure ideas" (optional quotes around "pure"). At its best and worst, formal philosophy is largely a system of convincing people to adopt certain ideas, as politics convinces others to adopt certain actions.
In the case above, it seems that they have added "engagement" as a part of "Fair Process". It's an interesting idea, and I would certainly agree that engagment tends to lead toward more "fairness". I don't believe engagement is necessary for people to agree on the fairness of a process, however. Explanation is in a sense part of engagement, but I think it is also useful for "classic" meanings of fairness. (One could consider explanation to be one's engagement in the clarity of a decision.) Clarity (possibly "transparency"?) is probably the most convincing part of the argument--it is critical that people believe that they are judged by relevant, rational, and clear decisions.
An interesting idea--thanks for the summary. --CliffordAdams
Ironically, one of the most "fair" ways to treat people is to treat them only by the numbers. Consider two employees (Dave and Frank) competing for a bonus. Both have generally equal records, but Dave created 50% more profit for the company last year. Fairness "by the numbers" would indicate that Dave should get the award, even if Frank is a more popular/funny/interesting person, and/or Dave belongs to an ethnic/religious/racial minority. (This assumes company level profit is somehow a metric of individual performance and contribution. Maybe Dave would go insane under the performance pressure if he didn't have a clown like Frank to laugh with; systems need many types to function, engagement validates this reality by encompassing the individual details and human process.)
One interesting related idea was in an article about possible risks in "neural net"-based programs for evaluating loan requests. The goal is to feed the program the information about the applicants, and train the program to make low/medium/high-risk kind of decisions similar to an experienced loan-processing manager. Some people are concerned that such a neural net may learn to mimic human discrimination (called "redlining" in the loan industry). See  for the article, and  for several replies.
Apparently a similar case occurred around 1987 in a similar system used to screen applicants to a medical school. When they studied the program, they found that it attached some weight to the applicant's name. Apparently, the program detected a correlation between names of ethnic minorities and the results typically given by a human decision-maker. In some cases, simply changing the name of an applicant could change the results. See  for the story (near the end).
fair adj: [only relevant items listed]
Synonyms: fair, just, equitable, impartial, unprejudiced, unbiased, objective, dispassionate. These adjectives mean free from favoritism, self-interest, or bias in judgment.
This research is based on Tom Tyler, NYU social psychologist (aka Fair Process effect).