Manhattan adds AI explainability to ActivePlanning

Manhattan Associates has introduced Sightline within its ActivePlanning software, a feature designed to show the reasoning behind AI-driven supply chain planning decisions.

Built into ActivePlanning, Sightline explains forecasts, recommendations and inventory decisions in plain business language. It can trace the factors behind outcomes from a single order line to a wider network view.

The addition addresses a longstanding problem in supply chain planning: users often have to leave core systems and examine spreadsheets or separate reporting tools to understand why a forecast changed or why a replenishment recommendation was made. Manhattan says the new tool keeps that analysis inside the application and delivers answers in seconds rather than after hours of manual work.

According to the company, the feature provides visibility into forecast inputs, safety stock decisions, vendor minimums, lead times, promotional effects, fulfilment shifts and network movements. That allows planners to review the logic behind projected orders, inventory positions and forecast changes without relying on outside tools such as Microsoft Excel or third-party business intelligence software.

Planner visibility

The launch reflects wider demand for clearer explanations of AI outputs in business software. In supply chain systems, AI is increasingly used to adjust forecasts, guide replenishment and influence allocation decisions, but users often struggle to see exactly what drove a recommendation.

Manhattan is positioning Sightline as a way to address that trust gap. By surfacing the rationale behind model outputs within the planning workflow, it aims to make AI-led recommendations easier for planners to test and act on.

The system also adds configurable views designed to match how planning teams organise their work. These views can be arranged by role, promotion, activity or a combination of those categories, and span forecasts, projected orders and planned inventory levels.

A new workspace for planners supports those views and is intended to reduce time spent answering routine questions about why a number changed or why a recommendation was generated.

AI explainability

The move comes as software suppliers face growing pressure from customers to provide more transparency around AI-based decisions. Explainability has become a central issue in sectors where planners and operators need to justify decisions internally and respond quickly when outputs appear unusual.

In supply chain planning, that challenge is especially acute because a forecast or order recommendation can be affected by many variables at once, including historic demand, supplier constraints, promotions and changes in fulfilment patterns. Tools that offer visibility into those drivers may help companies shorten investigation times and reduce dependence on analysts with specialist technical skills.

Brian Kinsella, Senior Vice President and Chief Product Officer at Manhattan, outlined the company's view of the launch.

"At Manhattan, we are committed to continuous innovation and simplification, which helps our customers work smarter and move faster," said Brian Kinsella, Senior Vice President and Chief Product Officer at Manhattan. "With Sightline, we're giving planning teams a powerful new way to understand the drivers behind every outcome, accelerate decision-making and drive higher productivity across the supply chain."

While Manhattan described the tool as a new step for planning software, the practical effect will depend on how customers use it in day-to-day workflows. For planning teams, the immediate appeal is likely to be the ability to investigate exceptions and changes without switching between multiple systems.

That may be especially relevant for organisations managing large product ranges or broad distribution networks, where a small change in a forecast can have knock-on effects across orders, stock levels and fulfilment plans. Bringing the explanation for those changes into the same interface as the planning decision could change how quickly teams respond.

The launch also shows how software providers are adapting AI features for business users who are not data scientists. Rather than asking planners to interpret technical model outputs, vendors are increasingly presenting AI reasoning in operational and commercial terms that align with everyday planning work.

For Manhattan, the addition strengthens ActivePlanning by tying AI outputs more closely to user oversight. Sightline is designed to embed explainability directly in the planning system so users can investigate outcomes where decisions are made.