A googol is a 1 followed by 100 zeros. There are bigger numbers, and words for those bigger numbers, but a googol is as large a number as I am likely to need. In fact, the number of objects in the universe apparently does not even amount to one googol, as Neil deGrasse Tyson pointed out in his book A Brief Welcome to the Universe.
According to Tyson, large numbers like a googol “don’t count things, [but] instead count the ways things can happen.”
When Larry Page and Sergei Brin adapted the word googol to be the name for their internet search engine, they did so for the very reason that Tyson suggested. Page and Brin knew that Google’s success would not depend on large numbers per se, but on the properties, behaviors, and effects of large numbers.
Page and Brin based their company on the concept of a virtuous cycle of data. At the time, that meant that the more web pages that Google could index, the more useful the search engine would be, and the more useful the search engine was, the more web pages it would index. Over time, for Google and other tech giants, more data—as well as more sophisticated analytics--has led to the design of better products and services; better products and services have brought more users; more users have brought more data; and more data has led to even better products and services. And the cycle seems to have no end.
For Google, the virtuous cycle has driven the launch, continuous innovation, and escalating monetization of wildly successful products like Google Adwords, Gmail, and Google Maps. Along with tech giants like Amazon, Apple, and Microsoft, Google transformed the concept of the virtuous cycle of data into the defining macroeconomic platform of the modern age.
For companies able to make the most of this cycle, the results have been more revenue, more new-product opportunities, faster innovation, greater efficiency, lower unit costs, and market valuations in the trillions of dollars.
Equally significant, the multiplier effect of this cycle has created a gulf between companies that have accumulated and use these mind-blowing amounts of data and, well, everyone else.
No contemporary company, for-profit or not-for-profit, can function independent of the macroeconomic platform created by this virtual cycle. That most definitely includes healthcare provider organizations.
On the clinical side, we are seeing major breakthroughs in the use of big data and machine learning algorithms to improve the accuracy of diagnosis and the targeting of treatment, particularly in cancer care. However, this research is highly complex, requires huge pools of data, is expensive to conduct, and has proven difficult to translate from the laboratory to the clinic. As a result, participation is very difficult for any but the largest companies, many of which are for-profit life sciences companies.
On the operational side, we are seeing the rise of companies that, through outsourcing arrangements, are gathering huge amounts of data to improve the performance of administrative functions like revenue cycle, medical records, and procurement management. We are seeing similar arrangements in emergency medicine, radiology, and other clinical services.
Further, we are seeing Amazon use its wealth of consumer information and its innovations in customer engagement to escalate its movement into healthcare. Last month, Amazon announced it was expanding its virtual care service into all 50 states, with plans to provide in-person care in 20 major cities starting this summer.
The modern economic platform is based on a virtuous cycle with data and scale at its core. This is the bedrock cycle of the new economic platform; it is the playbook big tech companies use to achieve their dominant competitive position. It is a platform very different from any that traditional healthcare providers have had to function on in the past. But it has become healthcare’s macroeconomic platform the same as it is for every other industry vertical.
The challenge now is for healthcare provider organizations to leverage the virtuous cycle consistent with the size and complexity of the organization, and to participate in the macroeconomy at the highest possible level.
