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At eleven forty at night, a restaurant sends a voice note:

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two cases of cooking oil,

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five kilos of chicken, and "the usual" sauces.

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Tomorrow morning,

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someone has to work out what "the usual" means.

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Here's how AI can turn a distributor around, step by step.

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Picture a food supplies distributor.

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Thirty staff, a few hundred restaurant and café customers.

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Orders arrive every way imaginable: chat messages,

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voice notes, photos of handwritten lists, phone calls.

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Every one gets retyped by hand.

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Late-night orders get missed.

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Wrong items go out.

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The phone rings all morning with "where's my delivery?".

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Payments come in late.

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And the order desk is under constant pressure.

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It starts by sitting with the order desk:

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counting how orders arrive,

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how long each one takes to key in,

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and how many need correcting later.

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Then the awkward cases: "the usual",

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an item that's out of stock,

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an urgent same-day delivery,

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a new customer with no account,

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an account over its credit limit.

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Each step gets sorted: automate it,

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let AI do it with a person checking, or keep it human.

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Then the AI learns what an experienced order clerk knows:

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every product and pack size,

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each customer's usual order and delivery days,

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which items can be swapped when stock runs out,

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the cut-off times, the credit terms.

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Now "the usual" actually means something.

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Here's the heart of it.

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Whether an order comes as a message,

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a voice note in Malay,

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English or Mandarin, or a photo of a handwritten list,

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the AI turns it into a draft order: products matched,

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quantities checked, "the usual" filled in from history.

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And here's the expert part: it shows how sure it is.

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Anything it isn't sure about goes to a person to check.

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Then the order goes straight into

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the distributor's existing system,

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and the customer gets a confirmation.

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Calls get answered too, at any hour.

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"Do you have stock?"

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"Can I add one more case?"

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"What time is my delivery?"

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The AI answers from live stock and delivery information.

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Price disputes and account questions go to a person.

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Most "where's my delivery?"

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calls disappear when customers simply know.

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So each customer gets a message

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when their delivery is on the way,

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with an arrival window.

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Drivers capture proof of delivery.

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If an item was short, it's flagged straight away,

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not discovered weeks later in a dispute.

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Invoices are built from what was actually delivered,

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so they're right the first time.

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Customers get a friendly reminder before a payment is due,

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by message and email.

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And if an account goes over its limit,

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a person reviews it before the next order.

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No harsh automation, just no more forgotten invoices.

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Then the relationship.

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The system notices patterns,

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so a customer who orders oil every

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Monday gets a timely nudge: "the usual?".

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Customers who've opted in hear about

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new products that suit their kitchen.

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And new restaurants find the distributor too,

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through an online catalogue,

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a proper business profile,

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and ads aimed at new restaurants

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opening in its delivery areas.

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And the team?

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Order clerks stop retyping and start

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handling the exceptions and the relationships.

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Sales reps visit customers instead of chasing orders.

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The warehouse gets clean pick lists earlier.

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When the pressure comes off, good people stay.

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One delivery route goes first.

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Everything is measured and

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adjusted before the rest follow.

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So here's the end of the turnaround.

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Orders in within minutes, in any form.

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Every order captured, even at midnight.

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Fewer mistakes.

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Customers who know where their delivery is.

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Faster payments.

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And a team that wants to stay.

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That's what AI can do for a distributor.

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It doesn't replace the people who know your customers.

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It takes away the retyping and the chasing,

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so they can look after them.

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If you're wondering what this

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could look like in your business,

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I'm always happy to talk it through on LinkedIn.