10 Principles of Real-Time Decisioning

Here are 10 principles which help shape today’s world of real-time decisioning:
1.    Decisions, not data, create value
 
It’s the action taken from a decision that creates or protects value. Having real-time data, analytical tooling, and advanced technologies doesn’t enable meaningful, tangible value if you are unable to get a handle on the decisions that need to be made.
 
2.    Organisations needs to respond to the world as it is
 
The datasphere can be an overwhelming place. In an event-driven age where every sensor update, ATM interaction, swipe, tweet, and click bombards applications with a continuous stream of data, organisational responsiveness is the new advantage. 
 
Thriving in this event-driven age comes down to an organisation’s ability to predict and detect events as they happen, with organisations deploying contextual, real-time data and historical insight to spot where events are happening and ‘decision windows’ opening.
 
3.    Not all decisions are real-time
 
Organisations need to make multiple kinds of decisions – from the ad hoc strategic discussions around boardroom tables to the millions of continuous and automated sub-second event-driven decisions that underpin 24/7 operations. Between these two extremes are broader decision types, with different characteristics and ways to leverage data and analytics. 
 
Whilst boundaries between decision types are not always clear, the time constraints usually are. Not all decisions require a real-time response. Understanding the decision time constraints – specifically the frequency of the decision and the decision window – determines if there’s a business need for real-time decisioning.
 
4.    ‘Right-time’ analytics drives real time decisioning
 
While a decision may need to be real-time, it doesn’t necessarily mean the analytics, data and tooling driving that decision always needs to be. Often, when people are talking about needing real-time analytics, they are actually referring to the ability to predict, detect or respond to real-world events and take action in a time appropriate manner1.
 
To capture the value of data, organisations need to marry the speed of analytics and the data available to the available time of the decision window. This means that understanding the decision at hand and the acceptable latency is key to determining the ‘right-time’ analytics for your real-time decisioning.
 
5.    Decision-delay, value-decay: the last responsible moment
 
The lean software development principle “decide as late as possible” has a mixed reputation due to its justification for all sorts of whacky decision making. However, in real-time decisioning, the concept of the last responsible moment is an impactful lens to explore the trade-off between speed, accuracy and value optimisation.
 
Understanding a decision’s ‘last responsible moment’ requires an organisation to consider the decision from a ‘decision-delay, value-decay’ perspective to evaluate the opportunity cost of delaying a decision whilst seeking more information, or making a decision prematurely without complete information.
 
6.    Humans versus the machine: the balancing act of real-time decisioning
 
Automating decisions is similar to automating any other business process – you codify a set of rules that link data with decision choices, and a continuous feedback loop provides a self-learning, self-correcting system.
 
Of course, not all real-time decisions can be automated, and there will always be exceptions and higher-order, judgment-based decisions that require human intervention. Nevertheless, automated decision making fuelled by data instead of human expertise is the fashionable solution, but real-time decisioning is about the sweet point between the two.