Technology Has a Weekend Problem
Blog: The Tibco Blog
It was obvious during the recent election…there were far fewer meaningful stories on the weekends. That’s not in itself too surprising, but it is equally obvious if you order from Amazon after 5pm on Friday as I did recently: Nothing really moves until Monday. Sure, you get a notification on Friday that your item shipped, but it hasn’t moved an inch. How can this be? What about always-on customer service? What about the rise of the customer and the need to meet customer expectations?
We constantly hear about the world changing rapidly through technology, but in the end, it has a weekend problem.
The people problem
Technology’s weekend problem may seem small, but it’s part of a bigger problem that shows up all across the business spectrum. Regardless of how smart we make our machines, they rely on some very, very ancient technology: humans. The human systems we’ve built aren’t ready to disappear simply because we move data more quickly. Even more, just because we can learn things through powerful reporting and analytics doesn’t mean we can eliminate the human element. So much has been made of technology that we sometimes fail to consider that there’s a massive human element in all of this. With so much talk about robotics and the dangers of artificial intelligence, we lose sight of the fact that all of our technology has this weekend problem. And that’s OK.
While this won’t get my package to me sooner, organizations need humans to work alongside the technology that’s changing everything. It has to be a complementary relationship. At TIBCO, we call that augmenting intelligence and it is the middle road between the hype of AI and skepticism that technology won’t really change everything. Computers can spot patterns and help create business models (algorithms), but that’s not where the story ends. Mark Palmer said it best:
…as your business inevitably becomes more algorithmic, you’re faced with the next problem: Many algorithms, once discovered, have a remarkably short shelf-life. Algorithmic excellence in analytics requires more than just great math; you must also become as agile at killing off weak or vanquished algorithms as a NASCAR pit crew changing worn tires—you need to be replacing them with promising new ones. And you need to do it continuously, quickly, mercilessly and with abandon. In the digital business era, it’s the survival of the fittest algorithms.
This Darwinian approach, at the street level, means that humans have to be very good at evolving their business model, their algorithms, alongside technology. Workers aren’t the weekend problem, they’re the ones needing to use their intuition and experience to move things forward more rapidly (and safely) than non-human systems would allow.