|Photo by: Marisa Alia-Novobilski via Wright-Patterson Air Force Base|
It's difficult to be an expert, says John Weathington, writing for the Tech Republic, as he says, "You do not have direct responsibility or control over the outcome; as such, adoption of your advice is largely dependent on how well you can convince the benefactors of your wisdom to follow your recommendations."
He adds that that to be able to exert more influence in the organization, one has to bolster their data science capability.
Experts can influence others to take their advice but when the receiver has some knowledge of the subject area, there can be a contest of opinions so that the expert has to have some other base wherein to sway the argument in their favor. In such situations, informational power and data science are handy.
The expert who knows the data information has the power base that's difficult to obtain. And with credible data plus knowledge and wisdom, he can sway arguments.
But it is important for the expert to build a relationship with the data science team and not bring his own data science capabilities that are self-contained and self-supporting This will not be good since data science is a complex matter that needs a solid background in several disciplines It will most likely be distraction trying to develop knowledge in a completely different area and trying to focus on your own subject matter.
Partnering with the organization's data scientists is the right alternative in order to collectively thread company data into information, knowledge, and wisdom, expanding the experts base of knowledge.
It is also advised that being competitive and confrontational is not advisable because it defeats the purpose since the goal is not to prove you're right but rather for them to adopt your advice. It will not be good to show others that they were wrong and you're right but the objective is to show other information that they're not aware of.
Using data science will help the expert influence an organization as great ideas are nothing unless adopted so having a good relationship with the data scientists will be the first step one has to make as an expert.