Remote work was forced on many employers last year by the COVID-19 pandemic, leading to a simple, mid-pandemic consensus that “remote work is here to stay.” But as the crisis fades, organizations will get to choose where employees do their work — now with a new set of tools, expectations, and experiences.
As Marc Andreessen said recently, we are undergoing "a permanent civilizational shift” where we can divorce "physical location from economic opportunity.” He’s probably right in the long term, but we still have many questions to answer before that utopian dream is realized.
Data-driven personalization is the practice of delivering relevant content to your customers based on the information you've gathered about them. Before data and personalization, brands had to generate demand for their products or make assumptions about their audiences using generalized data. But thanks to the internet and mobile devices, it's possible to communicate with heightened awareness about your market.
A data-driven approach enables you to collect data and use that data for a better customer experience throughout the entire customer life cycle. More importantly, it allows you to communicate the right message at the right time, based on where the customer is in that cycle, increasing engagement and conversion rates.
But the secret to making this personalization work is trust, which is earned through responsibly managing your customers' data. You have to strike the right balance between data and personalization, and your customers' privacy.
Here's exactly how to do that.
Five minutes before dinner (Amira made home made mushroom pasta; I made bread), we realized that we were out of butter.
Without even hesitating, she grabbed a bottle of whipping cream from the back of the fridge and poured it into a jar. She then tossed in a kefir grain which she always cultivates and keeps in the fridge, closed the lid and handed me the jar. "Please shake this until it's butter," she requested. So I did.
Once the buttermilk fully separated from the butter, we removed the grain, poured the buttermilk into a jar and put the button in ice water. Amira squeezed out the last bits of buttermilk, and there it was: delicious butter!
Like Captain Kirk confronted with the Kobayashi Maru, she hacked the cream instead of accepting defeat.
Amira just doesn't believe in the no-butter scenario.
It's widely understood that 5G is set to transform business. But you can't talk about the coming 5G transformation without talking about 5G and big data. And you can't talk about 5G and big data without talking about artificial intelligence (AI) and multi-access edge computing (MEC). There's a ton of change coming. But don't be overwhelmed. Be prepared.
To oversimplify, 5G is needed to distribute AI to the edge and to devices. And AI is needed to bring intelligence to complex 5G networks. Widely distributed AI, edge computing and 5G all should drive very fast, very low-latency interactions throughout an organization.
Here's why the future of business IT depends on the symbiotic relationship between 5G, Big Data, AI and multi-access computing.
We're staying for a month in a town in Provence called l'Isle Sur La Sorgue, which means "The Island on the Sorgue." The Sorgue river starts as a natural spring coming out of the ground. At some point, the river splits in two, then re-joins later down the river. The land between the split is this amazingly charming town, an "Island" on the Sorgue river. Over the centuries, local residents have built canals throughout the town to support various industries, and so there's water everywhere (it's basically the opposite of California).