From Big Data to small data, the digital world measures and values every interaction. Digital technology enables every touch point, click, conversation, picture, and byte of digital exhaust to be used to improve decision-making. In fact, data provides the foundation for success in a real-time digital business. This is why organizations must carefully design a data strategy as the first step in digital transformation.
To get started, successful organizations map out a data-to-decisions framework (see Figure 1). This framework uses all types of upstream and downstream data (for example, structured, unstructured, big, small, and contextual) to align with business processes, creating information flows. From order to cash, procure to pay, campaign to lead, hire to retire, and incident to resolution, context is applied to information flows.
In the next step, algorithms apply context attributes such as role, relationship, weather, product, geo-spatial location, time, sentiment, and even intent to the information flows. The bigger the data set, the more opportunities for algorithms to find patterns of insight. The goals are to ask questions of the data and expose patterns of insight, using performance, deduction, inference, and prediction.
Traditionally, most systems stop after discovering insight. In a digital business, though, insight powers the ability to guide decision-making. By using the ability to take actions based on data, organizations can consider how to identify the next best actions, make recommendations, suggest risk mitigation, and even suggest that no actions be taken. By designing a data-to-decisions framework, organizations gain the ability to build a digital business and enable real-time business.
Once a data-to-decisions foundation is established, organizations can think about how they can apply the framework to augment decision-making. Successful leaders start by putting together a list of questions they seek answers for. They prioritize that list and then begin addressing these questions within the data-to-decisions framework. The secret to success is not what answers can be provided, but what questions should be asked. Successful organizations learn how to ask questions that have never been asked before, sometimes by employing techniques such as design thinking.
Figure 1: Use the data-to-decisions framework to drive real-time business
With mastery of data to decisions, organizations eventually will move from real-time to right-time models. Real-time immediately provides data to decisions as requested, resulting in a data deluge. Unfortunately, real time on its own may not be fast enough. Organizations may need to anticipate when data should be delivered. Why? Real time describes the speed at which the transformation from data to decisions must occur. Right time is about the precision that relevant, contextual information can provide once cognitive capabilities are applied to the data-to-decisions framework. In other words, right-time systems ensure organizations see what they need to see before they even know they need it.
So where do you begin?
1. Start by identifying the questions your organization seeks to answer.
2. Ask what traits make up the most valuable products, employees, customers, and suppliers. These traits drive the questions around what context matters.
3. Determine the information flows and business processes that drive context.
4. Understand the people and devices touched to provide the next level of journey mapping.
5. Apply the data sources and channels of data to recommendation engines and decision frameworks.
After taking these 5 steps, you can then start creating big data business models powered by insight. Digital technologies, data, and algorithms should all be aggressively used to create business models that take advantage of insights. Visibility, relevance, and immediacy will come from these insights-based business models. The goals are to simplify the complexity of decision making and enable real-time digital business.