A full warehouse is a buffer between production throughput efficiency and customer service, or is it an excuse and a costly monument to supply chain ineffectiveness?
I WALK supply chains everywhere I go thinking customer service. Why? Not because I’m bored, but because every product or service you and I experience involves a supply chain. And I notice when service is missing. The cacophony of radio and media which shouts, “Try our service, we’re the best” turns me off. Empty promises easily made by those who don’t deliver. But, many down the chain have to deliver – I know, I’ve been ‘delivery’ most of my life.
I love walking warehouses, and they’re always full. But, is it all the right stuff or is it hiding hopeless planning and constrained coordination? Should I be staggered at efficiencies of put away, picking, packing and shipping, or is this effort expended to get delivery efficiency from a logistics stage that shouldn’t be there? Is this DC crammed with intentional overstocks to hold future margins high and not cost ease service delivery to customers and the economy? My stance is that warehouses are often not required today. Many are swollen with dead stock like working capital cemeteries, leaving little money or space for stock that protects customer service.
How to avoid a warehouse: apply your APICS knowledge; make it second nature, not second-hand.
Think supply chain value, not profit centre
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Coordinate: Buying, manufacturing and order-filling to more exact customer demand.
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Location of stock: Retailers blend one-step and two-step delivery. Suppliers direct-deliver key value items (KVIs) to retail stores while slower movers go retailer, DC then to stores.
Optimise production and inventory schedules
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Demand forecast to ID exactly what your customers want and backtrack to what to produce, what to buy when and how much of each. The data is there, just use it.
Seek planning effectiveness before execution
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Filter out high level noise in manufacturing/ distribution plans before diving into detail. Focus on the products and the parameters that matter. It’s inventory management basics, which can be armed today with AI fueled by machine learning, getting dynamic accuracy into plans.
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Make to order. Use a project process to plan and control purchase/manufacture activities.
- Make to stock (batch/repetitive):
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Demand forecasting, short horizon collaborating between production and key customers to deliver what’s needed now, straight from the factory – no warehouse for waiting.
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Manufacturing operations, optimal sequencing reducing work-in-progress (WIP), Kaizen/Kanban for material movements.
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Postponement and appropriate order sizing, not the same always because it’s easier – unmanaged economic order quantity builds stock, not service.
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Source. Use inventory management/inventory optimisation dynamically, so finished goods stock mix is optimal for next day delivery. No or smaller warehouse.
Systems
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Enterprise resource planning (ERP) got better, smarter, faster. It holds your data, transforming it into customer value and cost efficiency. It’s your planning and execution engine.
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IT manages the ordinary, on schedule – feeding you exceptions; with AI/ML included, it even makes decisions.
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IT, properly applied, moves your business from reaction to prediction, from buffer stock to right stock, ready to go.
Relationship and knowledge
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Predict customer/supplier behaviour at product level – systems eliminate uncertainty, eliminating stock.
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Share plans up and down supply chains, synchronising supply/delivery to these. Deliver what’s needed, not what’s convenient.
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Seek order-taking innovations – multi-channel ordering (phone, system-to-system electronic data exchange, Internet portal, over the counter).
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Seek flexible delivery innovations – smaller trucks for fine distribution, cross dock large to small trucks, drop-off points for customer collection like offices or transport stations/stops, leverage Uber Eats or taxi seats.
Synchronise, put in the planning and collaboration effort. Unlearn the ‘SAA way’ bad habits like one truck/ route fits all. Use systems and knowledge, yours or artificial, to predict with accuracy. Well, it’s your job and if you don’t know it, get someone who does. And put out the lights when you close unnecessary warehouses.