There are Little Myths and Big Myths.
Little Myths are untrue, but they only keep us from doing something that might otherwise be valuable. For example, until the 19th Century people thought tomatoes were poisonous because they are related to deadly nightshade. But the only bad thing this little myth caused was less-delicious salads and pizza.
A Big Myth, on the other hand, causes us to do something destructive.
One of the more morbid Big Myths was blood-letting: removing blood from sick patients to heal them. Of course removing blood actually made them weaker and less able to resist disease. Witch burning in 17th century Salem also fits this terrible “Big Myth” category.
Sadly, finding meaning when you have a great deal of information suffers from a Big Myth. The fact is every enterprise of significant size has data spread across multiple locations. Every single one. Many people believe—and some very smart people will tell you—the only way to extract meaning when you have data spread across locations is to bring all that data together into one place. This is called ”data consolidation.”
Data consolidation may sound easy, but actually moving and gathering information from many locations into a single building, a single data center, is wildly expensive, incredibly time-consuming, and surprisingly risky. It is risky because many of these projects get started and end up failing after wasting years and enormous amounts of money.
I’d like to tell you a true story: John, that’s not his real name—but he told me the story himself—is the CIO at a major healthcare system. He told me he had been in the job for three years and his predecessor, the previous CIO, lost his job because the employees of the company needed to find a way to do analysis using all their information and the previous CIO did not know how. Employees knew they wanted their analysis to build on all the information they owned—across hospital systems, clinics, specialists, etc.—and they were told they needed to consolidate that information into one location to let people do that analysis. But they had no idea how to start and neither did the old CIO.
So they fired the old CIO and hired my new friend, John, specifically to consolidate all the data from all the data centers.
Because he came in behind a significant failure, John was able to ask for and receive a large budget, and he had the full backing of management and employees, and he had a plan on how to get the job done.
At this point I was pretty excited. John had been on the job for three years with a primary focus goal of consolidating all of their national data. So I ask the obvious question: “How’s it going?”
“Oh,” he said quietly, “we haven’t consolidated anything yet.”
He had spent plenty of money…and at this point, years were passing quickly, but they had not actually made any progress. Three years later.
To be fair, the need to consolidate your information to analyze it is only a “big myth” if doing it destroys value, right? That is, consolidation is only destructive if there is a path to the same goal which is quicker, less expensive, and less risky.
And that’s the point. There is.
Chiliad allows any authorized person to find and analyze any information—in any format, any volume, and any location—as if it were all consolidated in one place. That multi-year, multi-million dollar, risky process…is no longer needed.
To be sure, there are still some uses of data for which consolidation still makes sense. But do you have to consolidate just to find meaning, relationships, and themes to make better decisions?
No. That would be a Big Myth.