We have a growing problem of bias in research. It often occurs when someone has a goal or objective in mind and then sets out to prove something is right. Their perspective is justification for an existing belief than actually asking an open question. At other times, the researcher leaves out pertinent information that would lead to a different conclusion. Bias skews the results and can lead to expensive consequences as decisions are derived from faulty findings.
Consider a scientist who wants to justify his decision for some personal or professional reason. Being involved in the conducting of a study on an existing decision may make the person prone to all types of bias because they have a personal stake in the results. Letting someone else do the research might be a more appropriate choice.
This is what I would call a bias by objective: The objectives of the research is not to answer an open question but to justify one's pre-existing beliefs.
There are also times when researchers leave out important information so they can skew the results. They may willing or unknowingly only look at certain data and ignore competing data. Sometimes this is not intentional because the person doesn't know what data is truly valid and what is not. Other times it is an intentional act of omission.
Bias by Omission: Not including competing information or pertinent data sets.
What is the cost of such bias?
That is hard to calculate. Sometimes that cost is very low and few people will see or use the research. It was used as an opportunity for the publisher to get something out there and the mistakes are minor while the entire research is beneficial. Other times, in the case of medical research and strategic research, the results can cost companies millions of dollars in poor decisions or in an attempt to replicate findings.