Suggested Order: How Field Reps Propose the Right Quantities

In short: A suggested order is a ready-made list of products and quantities that appears on the rep's screen during a customer visit, calculated from the customer's order rhythm, shelf stock, warehouse availability and case pack size. A good suggested order does not decide for the rep; it puts forgotten items and an estimated quantity on the table, and the rep agrees the final order with the customer.

A rep visits dozens of outlets a day. With hundreds of products per store, answering "what did they buy last time, and what is left on the shelf?" from memory is hard. The result is familiar: a steady seller is left off the order, another product is over-ordered, and the next visit turns into a talk about returns or empty shelf space.

What is a suggested order?

A suggested order is a calculation that estimates how much a specific customer needs until the next delivery and shows it as the starting value on the rep's order screen. The suggestion is a starting point, not an obligation: the rep can raise or lower the quantity or remove the line.

A suggested order differs from a simple repeat order. "Copy the last order" ignores what is left on the customer's shelf and seasonal change. A suggestion looks at consumption speed and current stock together.

Which data is a suggested order calculated from?

Order rhythm

How often and how much a customer buys of a product is the basis of the suggestion. Looking at the average of the last few orders rather than a single one reduces the effect of one-off large orders.

Stock on the customer's shelf

If the rep checks the shelf and back room and enters the remaining quantity, the suggestion gets much closer to reality. Where shelf audits already happen, this count can be part of the merchandising tracking flow.

Warehouse availability

If a suggested product is out of stock in the warehouse, the line should reach the rep with a warning; otherwise the customer is promised something that cannot be delivered. We explain how live stock reaches the field in stock visibility in field sales.

Promotions, seasons and case packs

Active promotions and seasonal items can push the suggestion up, and if the sales unit is a case, the quantity should be rounded to whole cases. We cover the pricing side in promotion and discount management.

A simple calculation logic

You can start well without a complex forecasting model. The logic: find the customer's daily consumption, multiply it by the number of days until the next delivery, add a small safety margin, subtract the stock on the shelf and round the result to whole cases.

Example: If a store buys about 10 cases of a product every two weeks, it uses roughly 0.7 cases a day. With the next delivery in 14 days, the need is about 10 cases; if 3 cases are left on the shelf and 1 case is added as a safety margin, the suggestion is 8 cases. These numbers only illustrate the calculation; tune them with your own customer data.

When should a rep change the suggestion?

The suggestion looks at the past; the rep sees today. The customer may have taken on a competing product, the shop may be about to close for renovation, or a local event is coming up. In these cases the quantity should change, but the reason should be logged with a short code (competitor, promotion, closure, shelf space).

Over time, reason codes improve the suggestion itself. If reps keep lowering it for the same customer, either consumption is calculated wrongly or something has structurally changed at that customer. You can only tell the difference if the reasons are recorded.

Common mistakes

Presenting the suggestion as a mandatory quantity: Reps and customers stop trusting the screen; the suggestion must be an editable starting value.

Ignoring shelf stock: A suggestion based only on past orders pushes extra product onto customers whose shelves are still full.

Not checking warehouse stock: Suggesting items the warehouse does not have means short deliveries and lost trust.

Showing new customers an empty screen: For customers without history, the typical basket of similar customers in the same segment can serve as the starting suggestion.

Inflating suggestions under target pressure: Revenue rises in the short term, and the next visit brings returns and discount requests.

Roll out suggested orders step by step

1. Narrow the product scope

Start with regular, fast-moving products; for slow movers and new items, use promotion or introduction lists instead of suggestions.

2. Define the delivery rhythm

The suggestion depends on the time until the next delivery. If visit and delivery frequencies are not defined for your customers, settle that first.

3. Add a shelf count to the visit

Keep the counting step short: a single number for products that have a suggestion is enough.

4. Monitor changes

Review monthly how often and why suggestions are changed. The goal is a balance where reps mostly accept the suggestion with small corrections. Reading suggestions together with sales quota progress also clarifies the rep's priorities during the day.

Suggested orders with S-Leader

In the S-Leader field sales app, customer history, stock and orders live in one mobile flow, which makes it easier to connect suggestion logic to the rep's order screen. New customers have no history yet, so the account must be set up correctly first; see our article on new customer setup. At ÇAP Teknoloji we design your suggested-order rules with S-Leader to fit your product range and delivery rhythm. Contact us for a demo.