Runes AI Platform / Commercial Excellence

Commercial Excellence

The trends that move margin surfaced at the granularity where they are still actionable, ranked by value at stake, with the driver identified and an action attached.

What the application does

Early detection of trends buried in aggregate reporting

End-market softening, price erosion in specific segments, input cost movements, freight and surcharge creep, and mix deterioration surfaced at the granularity where they are still actionable, rather than three months later in the consolidated number.

The issues actually moving margin, with the action attached

Ranked by value at stake, each with the driver identified, the rationale visible and a specific action. A business unit leader does not have to work through dashboards and then call three people to find out what happened.

Gap to target, decomposed

The shortfall against plan broken into the drivers creating it, so the conversation starts from what to do rather than what happened.

Detailed margin and pricing analysis on demand

Pocket margin by customer and SKU after freight, terms, service cost and rebates. Price dispersion across comparable accounts, with increase candidates sized by elasticity and churn risk.

Raw material pass-through and action tracking

Input cost movements traced to the affected finished goods and customers with the recovery amount quantified, and every agreed action carried forward with an owner and a value until it lands in the P&L.

Signs you need this

You missed the quarter, and the explanation arrived ten days later in pieces from three functions whose numbers did not agree. Reconciling them took another week.

Unfavourable mix is the usual explanation for a margin decline, without naming which customers, which products or which end markets produced it.

You learned about an end-market slowdown from a customer or a competitor’s earnings call before seeing it in your own order book.

The monthly review pack runs sixty slides, the discussion rarely gets past slide twelve, and the detailed question the CEO asks becomes a two-week analysis request.

Actions are captured in minutes and circulated after the review, but by the next cycle there is a new fire to fight and last month’s actions are an appendix.

Raw material prices are up and it is not clear which product lines and customers are affected, or by how much.

What is AI about this

Every combination, every refresh.

Continuous scanning

Every combination, not a sample

A mid-size manufacturer has hundreds of customers across dozens of products and end markets, which is more combinations than any analyst reviews in a cycle. The system examines all of them every time the data refreshes, so a deterioration in one segment is flagged in week two rather than in a quarterly deep dive nobody had time to run.

Generative AI

A finding turned into a decision

Each issue arrives with the driver, the value at stake, the reasoning and a specific recommended action, with every figure traceable to source.

Knowledge graph

Context that makes the recommendation survivable

Contract clauses, most-favoured-nation provisions, competitive situations recorded in CRM notes and negotiation history are read and structured, so the system does not recommend a price increase on an account where a contract or a competitive position rules it out.

Agents

Monitoring between reviews, and remembering

Agents watch the portfolio between cycles. When a recommendation is dismissed, the stated reason is captured so the same item does not resurface unchanged next month.

See it on your own portfolio.

A thirty-minute discovery call, including a demo of the application and what it would take to run it on your business.

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