Recommendations
The weekly queue, minus the dashboard archaeology.
Coodra is built around ranked actions, not endless chart hunting.
Recommendation types
Reorder recommendationsWhat to buy next using movement, lead time, safety stock, and margin context.Stock-risk decisionsProducts likely to stock out, sit too long, or quietly waste shelf space.Margin leaksProducts where cost, discounts, price, or mix make the numbers wobble.Catalog qualityMissing fields, noisy records, and data gaps before they poison the queue.
What affects ranking
Factor
Meaning
Urgency
How quickly the decision may become expensive or disruptive.
Confidence
How much relevant data supports the recommendation.
Impact
Whether the action likely matters enough to bother a busy operator.
Review history
Whether similar items were approved, skipped, corrected, or investigated before.
What a person can do
A recommendation should end with a human choice: approve, skip, adjust, investigate, or mark the data as incomplete. Those outcomes matter because the next queue should learn from the work, not reset itself every week like nothing happened.