Companies Must Compete on Decision Velocity

GUESS WHAT is often credited for Alexander the Great’s success on the battlefield.

Speed of decision making, or decision velocity.

Most of his opponents had bureaucratic decision architectures, where minor decisions would travel up multiple levels of command before traveling back down to be executed. With Alexander the Great’s decentralized command structure enabled by trust, his troops beat their enemies by simply out-decisioning them.

Time is a friend to those who can make faster, more accurate decisions. Any organization that can make decisions twice as fast as (or 100 times faster than) its competitors will decimate them. Whereas the human brain might take minutes to decide, and it can takes hours for a decision to work through an internal organizational structure, machines and artificial intelligence engines can make decisions in milliseconds.

Whoever masters these automated decisions at high velocity will have an exponential advantage over those who don’t.

Speed has always been a critical success factor in winning wars on the battlefield and for competing to deliver mass personalization at scale and new customer experiences. You need to move troops faster, reach targets more quickly, and strike with speed and precision. However, what is often not talked about is how the speed with which decisions are made plays a role in claiming victory. In Alexander the Great’s day, circa 330 BC, having comparatively minor decisions travel up multiple levels of command meant it could take days to make a decision on the battlefield. Such a centralized control and detailed micro-management approach was no match for Alexander’s nimble teams.

The speed of decision making plays a similar role in the age of digital giants.

Modern CX strategies require organizations to compete on decision velocity. First you have to amass a huge number of users and collect rich first-party data and insights about their interactions—what I call data supremacy. Then you must train AI to recognize patterns in that data and automate decisions, processes, and tasks based on those patterns. The higher the number of users, the higher the number of interactions, the greater the amount of data, and the higher the quality of insights from which AI can learn all translate to a higher level of automation in an organization’s decision making. And the more an organization’s decision making is automated, the greater the chances it’ll rule its market.

Finally, this data must be paired with what we call a data-driven digital network (DDDN), which is the 100-year platform that builds a business graph – the brains behind future decisions and the heart of an autonomous enterprise. This requires analytics, automation, and AI to come together.

CX STRATEGIES START WITH QUALITY DATA—LOTS OF IT

Data is the foundation and the first priority for every DDDN’s growth and development. You must find and harvest all relevant sources of data and control, if not own, the upstream raw data sources. On the downstream side, you must control access to how the data is shared, monetized, and used. This means identifying where the biggest pools of quality data reside and understanding how data is consumed inside the organization.

However, the battle for data is often misunderstood. Many think data supremacy is only about accumulating the greatest troves of data. But having the most data does not necessarily mean you win. This is a battle for the most insight from well-curated, highly contextual data. Quality trumps quantity. The real goal is to understand the relationships among data. You want to learn how the data interacts with each other and what patterns arise from these interactions. This is the future of customer experience as we move from data to decisions and journeys to moments that matter. 

R “Ray” Wang is the author of the new book Everybody Wants to Rule the World: Surviving and Thriving in a World of Digital Giants (HarperCollins Leadership) and founder of Constellation Research.

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