Reducing Uncertainty to Improve Customer Decisions

Consistently making better, faster decisions leads to better and more competitive business outcomes. Better customer experiences, retention, customer satisfaction and lifetime share-of-wallet are the goals.

Unfortunately, this can be a case of easier said than done. Improving decision-making requires certainty, and that takes effort, innovation and investment in people, processes and technology.

It is important to start with people – who can provide the domain expertise necessary to ensure wise, experienced decisions? Next, processes – how are all interrelated activities managed at every stage, such as originations, onboardings, fraud and risk assessment, approval/declines and next best action? Finally, technology – how does it power decision-making speed, accuracy and analytical insights to remove uncertainty?

At the recent FICO World conference, my keynote presentation discussed removing uncertainty from three perspectives: data management & force multiplication, analytics & personalized predictions, and information orchestration.

Data Management & Force Multiplication – Moving a heavy object is far easier when using a long lever. In fact, the longer the lever, the easier it is to move a previously immovable object. Similarly, the greater volume of data and insights applied to decision-making – lengthening the digital lever – the easier it is to make good decisions. Increasing leverage by adding AI, analytics, simulation and optimization fortifies decision-making still further. Customer insights, for example, enable you to create compelling user experiences and maintain a personalized, actionable strategy for every consumer, driving scale and efficiency across an organization.

Analytics & Personalized Predictions – Customer behavior can seem stubbornly unpredictable. Despite the best analyses, anticipating a customer’s future needs and actions remains an inexact science. In most cases, organizations possess the information they need to make optimal decisions, but the pieces are scattered about, like an unassembled puzzle. Once assembled, analytics give companies a much better way to understand and predict customer behavior. By continually applying AI, ML, analytics, simulation and optimization to a constantly improving collection of data, you can make hyper-accurate predictions about future customer needs more accurately than simple customer categorization. This enables richer personalization and increases customer satisfaction, retention and lifetime share-of-wallet.

Information Orchestration – As the number of customer interactions and touchpoints increase across a company, so does the amount of data, decision assets and stakeholder interaction and dependencies. It becomes increasingly difficult to orchestrate the interrelationships of data across applications as they impact one another in real time. People and circumstances are constantly in motion and changing. Orchestration can overcome uncertainty by providing change management control, traceability, verification/validation, auditability, automated checkpoints and other essential business capabilities. This helps you verify the accuracy and timeliness of information upon which they are basing strategic decisions.

Maximizing the value of data

To achieve business goals, companies should have a comprehensive information architecture and good functionality for orchestrating decisions. I have worked with many companies at varying stages of their transformations and have seen that the key to success is to dramatically maximize the value of data while improving the effectiveness, accuracy, consistency and certainty of decisions.

Data modelling, governance and integrity are the blueprint for structuring and organizing data. They promote decision certainty by increasing accuracy, efficiency and usability while providing patterns, trends and relationships from which analytic models can learn.

Because data quality is essential for optimal decisions, it’s important to understand its complexity and interconnectedness, while ensuring it is governed and tagged correctly. This improves your ability to derive insights and reduce uncertainty while minimizing legal and compliance issues.

Companies around the world are finding that by working backward from the decisions that need to be made, charting the information needed to make them and leveraging AI and analytics in their decision strategies, they can manage uncertainty with greater success.