Since my two previous posts were about Datenvergnügen and the Datechnibus, I have apparently declared October to be Neologism Month on the Data Roundtable. (Even though both Datenvergnügen and Datechnibus might be more portmanteau than neologism.)
This week’s new term is Data Psychedelicatessen.
First of all, psychedelicatessen is not my creation. That honor belongs to Stanisław Lem, who coined the term in his science fiction novel The Futurological Congress, which depicted an apocalyptic future where all knowledge is derived from hallucinogenic drugs rather than direct experience. In the novel, people would visit the local psychedelicatessen to acquire their hallucinogens of choice.
Just a few examples included genuflix, which induced moments of spiritual awakening, algebrine, which endowed users with an encyclopedic knowledge of mathematics, amnesol, which removed unwanted memories, and authentium, which created memories of things that never happened.
I am certain that most organizations would consider data-driven decision making to be better than hallucinogen-driven decision making.
Although I have no plans to write a business fiction novel depicting an apocalyptic future where all business intelligence is derived from hallucinogenic drugs rather than data analysis, in my mostly hallucinogen-free experience, organizations are data-driven in theory, but in practice, not so much.
Many organizations have a data warehouse. Some organizations also have a MDM hub. But I am convinced that every organization has a Data Psychedelicatessen, which business decision-makers visit in order to acquire their hallucinogens of choice whenever the data doesn’t support the decision that they want to make, or they need to justify the non-data-driven decision they have already made.
Just a few examples include gastroflux, which aids the digestion of “going with my gut” decisions, datamine, which convinces the user that the only reliable data is their own personally cultivated data, selectium, which renders invisible any data that doesn’t support the decision-maker’s preferences, and qualitol, which convinces the user that data quality doesn’t impact decision quality at all.
Data or Hallucinogens?
Is your organization using high quality data to guide its business decisions?
Or is your organization frequently visiting its Data Psychedelicatessen?
If it’s the latter, what are the hallucinogens of choice in your organization?