Data, Business, End Game

Let’s take a risk with this guest post! I’d like to pose a somewhat philosophical question with this first guest post: what do you think is the end game for the Business of Data?

We’ve long seen a clear trend in automating the growing or manufacturing of physical goods, from cabbages to cell phones. Automation reduces the costs of producing these goods. It also often standardizes and improves their quality or performance. One of the principal ways it achieves these ends is by removing human labor, cost and variability from the process. In Western economies, jobs have moved from agriculture to manufacturing and on to services. So far, this process has resulted in higher living standards, as more people can afford more goods.

The Business of Data is also being substantially automated. This process started slowly four decades ago. Secretarial and basic accounting work has been largely replaced by office automation. Operational applications and self-service websites have sped up sales and eased payment. As data and text analytics improves, services jobs are displaced. Software has replaced journalists in basic sports and financial reporting. Accounting and tax filing software does better, faster and cheaper than junior accountants. Financial analysts could be replaced if companies like Kensho achieve their aims. By early 2013, IBM Watson had already proven 40% more capable in lung cancer diagnosis than human doctors; today it’s doing R&D in cancer orders of magnitude faster than human researchers.

Combine data analytics and automation, and the changes become more spectacular. Imagine Uber using Google’s driverless cars. Automated drones making Amazon’s deliveries. Fully robotic surgeons. According to Oxford academics, Frey and Osborne in the 2013 paper, “The Future of Employment”, computerization could eliminate nearly half of today’s jobs within 10 to 20 years. They did not assume Kurzweil’s famous Singularity.

So, what is the end game in the Business of Data and Automation? Western business is based mostly on competition by driving down the cost of production. Labor has long been a major component of this cost. The same labor, of course, provides the means of consumption. A tipping point comes when enough labor cost is eliminated that consumption becomes unaffordable for a significant percentage of the population. In the past, this tipping point was avoided because new jobs replaced those eliminated. The problem I see today is that there are no new categories of human labor in significant quantities that cannot be performed better or more cheaply through analytics and automation.

This is a serious philosophical question with very real, practical implications. Focusing solely on the Business of Data in its current form misses the bigger picture of the Business of Business. We need to fundamentally redefine our concept of and reason for doing business. Is the purpose of a business really to make profits for the few? Or is it a social enterprise to enable and support cooperation and collaboration between the many, allowing the balanced exchange of goods, value and skills?

I offer you this for your consideration as we ponder how truly prosperous the rest of 2015 might yet become.

Founder of the data warehousing industry and among the foremost authorities worldwide on business intelligence (BI) and beyond. He is a widely respected consultant, lecturer and author of “Data Warehouse–from Architecture to Implementation”, and numerous White Papers. His new book “Business unIntelligence–Insight and Innovation Beyond Analytics and Big Data” is published in October 2013 by Technics Publications.

 

 

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