Layers of Effect

Before we start forecasting, let’s reframe the way we look at the products and experiences we either make or use. If you were to ask any layperson in the street, “What is Twitter?”, they would probably give you an answer along these lines:

• “It’s a site where I can connect with my friends and family!”

• “I use Twitter to follow up on what famous people are up to.”

• “It’s where I go for dank memes.”

Great. But Twitter is so much more than a generic social media platform. And it’s got some pretty complex effects. The following graphic shows the breakdown of products into three sections: primary, secondary, and tertiary.

Primary

These are the effects that you think of first when you think of a product or experience. Primary effects are pitched as the heart of a product. They are always intended and known. For example, Yelp’s primary effects is that it is a platform for people to review and learn about establishments. Primary effects may evolve over the course of time, but they typically do not change too drastically, especially if they have already set off and made an impression on the market. These effects are confined in the innermost, opaque box to highlight that they are known and intentional.

Secondary

These are the effects that might not pop up immediately as the defining characteristic of a product, but are still just as relevant to the company’s shareholders. For Twitter, while its primary effect might be serving as a social media platform, a secondary effect would be how it acts as an ad revenue generator. Again, similar to primary effects, these are not set in stone and can evolve over time. These effects confined in the outermost, opaque, coral box to highlight that they are also known and intentional.

Tertiary

These are the effects that are either unintended or unforeseen. These can be good or bad; in any case, tertiary effects are always surprises that start cropping up after users have had their hands on the product. For example, a tertiary effect of Facebook would be the role it played in perpetuating the spread of fake news due to its algorithm. A tertiary effect of Twitter is the massive trolling and cyberbullying (as well as the ensuing emotional trauma) that happens on its platform. In the above graphic, the tertiary circle is feathered out, representing the fact that there can be an unlimited amount of tertiary effects. They aren’t quite the same as edge cases, although there is some overlap; tertiary effects are not always the result of extreme parameters.

Those with the privilege of creating products have the responsibility of defining ethical primary and secondary effects, as well as forecasting tertiary effects to ensure that they pose no significant harm.

Now that we’ve established how to reframe products and experiences, we can start forecasting. The forecasting part is the most complex, which is why I’ve developed a toolkit for designers to begin to wrap their minds around it.

You’re probably scratching your head wondering, how on earth do you forecast tertiary effects? How are mere mortals supposed to predict consequences and reactions that haven’t happened yet? Forecasting all the “unintended” ways users might interact with a product is tricky. But it’s not impossible. In fact, it might be more familiar than you think.

The skills involved in forecasting should not be new to anyone. If you’ve ever found yourself binge-watching a television series in one weekend, only to find out that the next season was a year away from being released (*cough* GoT *cough*), you’ve probably encountered the natural instinct to try and predict what would occur. People forecast other people all the time. Also consider this: when forecasting for tertiary effects, quantity matters more than quality. It’s not about being 100% accurate. The important part is being creative and imagining as many tertiary effects as you can, so you can hone in the harmful ones and prevent them from happening.