The challenge is not a lack of data. It’s the gap between having data and using it consistently when orders are created.
When assortment and quantity decisions vary by rep, customer, or visit, the impact is immediate: missed sales, lower order values, sub-optimal portfolio decisions, stockouts/overstocks, and inconsistent execution across territories.
Most organizations already have ERP, POS, forecasting, inventory, and promotional systems in place. But insights are often fragmented, delayed, or difficult to apply at the outlet level. As a result, reps are left to rely on habit or personal judgment instead of clear, data-backed guidance
This playbook explains how Suggested Order helps close that gap.
Rather than replacing existing systems, it acts as a decisioning layer on top of them, turning enterprise data into clear, outlet-level ordering guidance inside the workflows sales reps already use.
The result is simple but powerful: better orders, faster visits, and stronger execution at scale.
You'll see how Suggested Order helps teams:
Grow the basket with better assortment decisions.
Protect availability with more accurate quantities.
Win back selling time with draft orders and standardized workflows.
When applied consistently, these improvements can drive tangible results, including:
Up to 25% improvement in assortment quantity.
Up to 20% reduction in under-selling.
5x faster order preparation.
Just as importantly, Suggested Order is designed to scale. The playbook shows how to start with a focused 90-day pilot, measure business outcomes (not tool usage), build early adoption, and then scale what works across teams and markets.
The takeaway is simple: stronger execution doesn’t require more tools. It requires better decisions, embedded into every visit.
Download the playbook to see how data-backed ordering becomes practical, repeatable, and scalable.