In most large enterprises, advanced analytics is no longer a novelty. In these organizations, large investments have often been made in data infrastructure, data science teams, and machine learning capabilities. Despite these investments, however, most analytics programs remain highly fragmented, tactical, and disconnected from the broader business mission. They lack a North Star; a unifying strategic focus that ties all analytical efforts together towards an end goal.

A few of the organizations at the forefront of AI development and deployment have started to address this challenge by adopting a unifying analytical objective. Through the concept of Next Best Action (NBA), they establish a central North Star that brings focus and cohesion to their various analytical efforts.

“Next Best Action is not just another analytics project – it’s the North Star that turns fragmented insights into coordinated decisions, aligning every model and analytical endeavor toward integrated, purposeful, and outcome-optimizing action.”
-Matthew McKee, VentureArmor AI Founder

The Case for a Unifying Analytics Focus

If we think about enterprise analytics as an optimization problem supporting an organization’s overall mission – and I believe we should – then the absence of a clear objective function often leads to wasted and fragmented effort. In any optimization setup, four elements are crucial:

A Clear Goal: What is the business ultimately trying to achieve? Maximize Customer Lifetime Value, Sales, Profitability, Loyalty, or another enterprise objective?
Decision Variables: What levers does the business control that can influence outcomes? (e.g., Product selection, Pricing, Placement, Promotion).
Constraints: What limitations must be respected? Budgetary limits, Discount Ceilings, Cost Structures, Execution Capacity Constraints, Inventory Levels, Regulatory Compliance Rules, and more must be considered.
Business Operating Model and Dynamics: What is the larger framework linking internal processes? For example, the relationship between Price Changes and Sales Volume (captured through Price Elasticity Modeling), or between Marketing Spend and Acquisition Rates.

The analytical optimization problem to solve in this context involves determining how to best accomplish an organization’s goals, using the optimal configuration of decision variables, within the confines of operational constraints, while exploring the possible paths forward in the context of a massively multi-dimensional mathematical representation of a business’ operating model.

Again, without a clear definition of these elements, advanced analytics devolves into disconnected projects: a churn model here, a sales forecast there, a customer segmentation exercise in another department; each valuable individually, but collectively directionless. Next Best Action offers a way to frame and link all of these analytics efforts cohesively.

What is Next Best Action?

At its core, Next Best Action is about deciding on the optimal move for a customer (or prospect, or internal stakeholder) at any given point in time, within any given channel, based on a customer’s context, preferences, and predicted future behavior. It is a customer-centric, dynamic, and model based decision optimization framework for an enterprise rather than an individual campaign-driven or channel-driven point analysis.

Next Best Action (NBA) answers the question, “Given everything we know, what should we do next to best serve this person and achieve our business objectives?“

In this sense, NBA transforms often fragmented and disjointed enterprise analytical efforts from a series of passive individual “tree-focused” exercises into a cohesive enterprise bottom-line objective optimization engine; encompassing a view of the entire “forest” of opportunity and operational complexity within a business.

When implemented properly, NBA both integrates and accelerates optimal decision making across all of these considerations, enabling optimized decision making within a continuous decisioning system.

Enterprise Analytics as an Optimization Problem

To optimally operate effectively under this framework, enterprises often must develop robust models for:

Customer Segmentation : Understanding who customers are and how they behave differently.
Attrition and Retention Modeling: Predicting customer churn and crafting strategies to prevent it.
Risk Modeling: Ensuring that actions comply with risk appetites and regulatory frameworks.
Demand Elasticity Models: Understanding how changes to decision variables impact outcomes.
Cross-sell / Upsell Models: Identifying where growth opportunities lie within the existing customer base.
Resource Optimization Models: Making sure capacity constraints are respected (e.g., service centers, logistics).

Each of these analytical efforts feeds into a larger NBA ecosystem, providing inputs or constraints. Importantly, none of these models is an end in itself. While they are each uniquely valuable, their value is amplified when they are combined to inform better next best actions. The combined whole of these models is far greater than the sum of their individual parts.

How Does Generative AI fit into this picture?

Generative AI has captured the spotlight, dominating headlines and reaching the very top of Gartner’s 2023 Hype Cycle Curve for Artificial Intelligence, at the “peak of inflated expectations”. While the excitement is undeniable, so too is the transformative potential, especially in unlocking value from unstructured data sources like text, images, and video.

However, amid the enthusiasm, discipline remains critical. In the context of a Next Best Action driven analytics strategy, Generative AI should not be pursued for its novelty alone. Ideally, every GenAI initiative should have a clear and mathematically definable connection to NBA, and it should be obvious how it will help an organization achieve its NBA-related objectives.

Before development begins, we advocate for a simple but rigorous standard: Can the outputs of the GenAI application be directly tied to improving the enterprise’s ability to make more informed, faster, or more effective decisions? If not, it risks becoming another siloed innovation; impressive in isolation, but disconnected from holistic enterprise value delivery.

Unfortunately, examples of misalignment are already widespread. Consider the explosion of website-embedded GenAI based customer chatbots. While vendors offering these chatbots often claim they generically “improve the customer experience”, or “save money on engagement costs”, many of these tools fail to deliver measurable improvements in either decision-making or business outcomes. In many cases, these chatbots can actually derail otherwise optimizable Next Best Action related offer/engagement presentment opportunities, and ultimately deliver negative incremental value when compared to other engagement options.

In short: Generative AI can be a powerful engine within a Next Best Action framework, but often only when tightly aligned to the mission of purposeful and holistic goal-driven decision optimization within an organization.

Practical Considerations

Of course, moving to an NBA-centered analytics strategy is not simply a technical exercise. It often demands:

Organizational Alignment: Business units, marketing, customer service, and analytics must collaborate around shared goals.
Real-time (or Near Real-time) Data and Decisioning: NBA frameworks often require updating recommendations dynamically as new information arrives.
Governance Structures: Clear rules must exist to arbitrate between competing actions (e.g., should we prioritize loyalty incentives over upsell offers?).
Measurement and Learning: Every action should feed back into the system to refine future decisions.

NBA is therefore not just a technical framework; it is an operating philosophy.

Conclusion

Enterprise advanced analytics endeavors should not exist in fragments. It should not be a collection of isolated models and projects with no common thread. Analytics should be thought of, and built, as an integrated optimization system, with clear goals, controllable variables, and well-defined constraints.

Next Best Action provides the North Star needed to unify these efforts.
By anchoring all analytical developments to a decisioning framework focused on “what should we do next for this customer,” enterprises can ensure that every model, every dataset, and every algorithm has a meaningful role to play.

“The future of enterprise analytics is not more dashboards or stand-alone models. The future is more intelligent and coordinated action, and Next Best Action is the best way to get there”
-Matthew McKee, VentureArmor AI Founder

About VentureArmor

At VentureArmor, we specialize in helping businesses unlock the power of AI and Next Best Action (NBA) to drive operational excellence and customer satisfaction. Our expertise in AI analytics, pricing, and data-driven solutions enables us to deliver tailored solutions that meet the unique needs of our clients. Contact us to learn more about how we can help your organization achieve its goals through the strategic application of AI. VentureArmor: Delivering ROI with AI.