This article was originally published in Wired magazine, you can read it here

Agility is key in an unpredictable world. Our networks, of people and data, can unlock this agility, enabling us to form novel connections, discover new opportunities, spot patterns and build teams to deliver against opportunities. They offer option value, delivering benefits that will be described as serendipitous or lucky after the event.

I was recently reminded of this latent value when IDEO ran a make-a-thon in which we brought together a diverse group of designers, developers and entrepreneurs to solve a series of challenges for social good. We tapped into our networks to convene the group to create working examples of products and services. The results, all prototyped by the end of the weekend, included a proximity-sensing bike light that frowns when cars get too close, and apps for Amnesty International to help those in danger of unlawful detention. Had we not had these eclectic networks to tap in to, we would never have managed to assemble the group, and therefore the solutions, so rapidly.

Just because we don’t all value our networks explicitly doesn’t mean they’re not valuable. TED, Wired and other conference organisers increasingly recognise that forming connections is a significant part of the value they offer, charging attendees even when the talks themselves are often released for free. With this in mind it’s amazing that employers rarely look into the depth and diversity of a candidate’s networks before making a hiring decision. We should all place an emphasis on cultivating our networks. We’ll be increasingly surprised at the value that emerges.

In addition to the value in human networks, there is often latent value in networks of different data sets. For example, by combining seemingly unrelated data, Walmart discovered that Pop-Tarts sales in the US rocket when there’s a hurricane warning, a finding that now helps them to stock smartly.

As individuals, we can unlock personal learnings by combining disparate, seemingly unconnected data in our daily lives. For example, 30 years ago Seth Roberts decided to reinvent himself. He was overweight, with insomnia and acne. Yet he has managed to change his life over the last three decades through continuous personal experimentation.

Through repeated trial and error, and by looking at all sorts of apparently unrelated data, he found that his mood improved by watching an hour or more of TV each morning, specifically life-size talking heads — yet if he watched such shows at night, there was no improvement. He looked to the Stone Age for an explanation and concluded that early humans had lots of face-to-face contact every morning but little after dark, a pattern that Roberts’s TV viewing now mimicked. He would never have had this hunch prior to its emerging from the data.

Roberts’s decades-long process of gathering eclectic data and then looking for correlations was a highly labour-intensive process — and, of course, totally unrealistic for most people and businesses. Yet it’s becoming simpler to collect data, with products such as pedometers and apps on our smartphones.

It isn’t just the costs associated with generating and capturing data that are approaching zero. The costs of processing it are also dropping. This enables us to apply computing power to tasks that we would never have been able to justify previously. For example, Wolfram Alpha Pro will mine multiple data sets for correlations even when undirected, so we no longer need to have a clear hypothesis to test — instead we can simply wait for learnings to emerge. Let’s begin gathering data even if we’re unsure why, trusting that the value will reveal itself in the future.

Metcalfe’s law states that the value of a telecommunications network is proportional to the square of the number of connected users of the system. I believe that this applies to our human and data connections too. So start making connections to create your own human and data networks and always err on the side of openness to enable the serendipitous to emerge. You’ll be making your own luck.