Paying Attention to the Right Signals – Part 1 of 3

In a world of accelerating change and disruption, customer behavior is fundamentally changing, and the new challenge is paying attention to the right signals to be able to predict where your customers are going even before they know themselves.

These changes manifest in two ways: on a macro scale, or long-wave signals, and as micro-behaviors, or short-wave signals. Anthropologist Grant McCracken once likened scanning cultural signals of change to “listening to shipping lanes on a short-wave radio” – there is no shortage of information in the 24/7 world of always-on news, but discerning what is an enduring signal versus noise can be difficult.

Making sense of signals of change helps get to the “why” behind the disruptive forces that surround us; a critical first step in being able to future-proof your business. In this three-part LinkedIn article series, I will delve into why you need to pay attention to both long- and short-wave signals, and how to ultimately synthesize this information.

Push, Pull, Predict -- Short-wave signals

Short-wave signals are rapid-fire changes that are all around us. As we lead our digitized lives, we leave behind a nearly constant data stream that data scientists collect and analyze. This data is harvested by companies to help them serve us better – who hasn’t appreciated a helpful add-on purchase suggestion or a new playlist created based on our past behaviors? Obviously, there is also a dark side to all of this data. With recent events, we realize the vast quantities of minute data that we are continuously providing to platform companies need some guidelines, boundaries, and regulation to ensure it isn't abused.

To better understand these short-wave signals, let’s look at how the business world has evolved. Over the last 100 years, we have moved from a world of “Push” to “Pull” to “Predict.”

·    The Era of Push. In the 20th century, companies worked at the scale of miles -- First miles (supply side) and last miles (demand side)... mass production to mass distribution to mass marketing. The data captured and managed was manually intensive, coarse-grained and was not personalized.

·    The Era of Pull – At the tail end of the 20th century, we started moving to the world of 'Pull' This was the era of 'big data'. Through internet and search, companies could understand what customers wanted through the 'database of intentions' -- it works at the scale of meters... understanding the context of the customer (who, what, where, how, etc.) through LoMoSo - Location, Mobile, and social data. The signals were captured digitally, were fine-grained and were highly personal. The “mass to mass to mass” world rapidly became a "micro to targeted to bespoke" world.

·     The Era of Predict – With the rise of platform business models, and digital technologies, machine learning, IOT, etc. companies have started being able to anticipate what people wanted before they even knew it themselves. Through digitizing the physical world, and having more understanding of customers, they have started competing at the scale of microns. Going further, companies are beginning to understand the neuroscience of our behaviors, paying attention to our unconscious motivations and drives. On the supply-side, companies are able to take advantage of a digitized physical world. With IOT, drones, and smart assets, we know as much about the physical world as we do about the digital world. Data science, machine learning, and cognitive (deep learning) all allow us to know what people are going to need/want before they even realize it themselves.

As more and more data and information become available and companies become increasingly adept at mining and interpreting shortwave signals the race quickens to be the fastest and the best. How “short” of a signal about your customer can you detect and how rapidly can you use it to improve their experience? Companies at the front of this race will be best equipped to win customers and survive in an increasingly competitive market.

About the author

Kes, executive director of research at KPMG's Innovation Labs, is a globally recognized thought leader at the intersection of human experience and technology. His career spans two decades through the worlds of technology, business, and innovation strategy. He is an award-winning innovator, whose research has been honored and cited by Gartner and Forrester. Recognized as a strategic leader, Kes has spearheaded digital transformation projects for some of the biggest names in government and the FORTUNE 50. Learn more about the KPMG Innovation Labs at https://www.kpmg.com/us/innovationlabs.