OPTIMIZING YOUR DISTRIBUTION CENTER TO BOOST REVENUE
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rowing pains are as natural a part of business as they are life. But what happens when a core aspect of keeping the business healthy and operational is not keeping up with growth and stands in the way of future success? Companies that are facing strong growth often find themselves stretching distribution centers beyond capacity. That threatens fulfillment obligations, which can stop growth dead in its tracks. Nobody wants to sit opposite a CFO and proclaim that a new, expensive distribution center is needed. Although that is sometimes the wisest decision, often existing space and processes can be optimized to boost the efficiency of existing resources. Doing so, however, is a project worth doing right since failure comes with such a high cost. PHASE 1: DATA IS THE SECRET SAUCE DC optimization begins with a 12-16 week long planning/concept design phase where possible scenarios are developed. It is key to understanding what problems need to be solved and how solutions will be measured. That is done through key
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year and peak season: this includes order numbers, shipment ID numbers, order dates, ship dates, customer numbers, carrier code and service level Forecast demand details: Include details for each SKU and projected SKU over a five-year period Order details: order and line numbers, units of measure, quantity ordered and shipped Location in warehouse: internal location identifier zone aisle, bay, level and position, quantities and type of storage location Inbound receipt details: purchase order and item numbers, number of items ordered, quantity received, and receipt dates Customer data: customer number identifier, name, type, billing and shipping address
By Kirk Waldrop performance indicators (KPIs), which will be used to benchmark progress. Ideal KPIs for most DCs include: estimated productivity by functional area storage space requirements facility and equipment capacities estimated labor costs Once KPIs have been agreed upon, operational data must be analyzed to determine optimal product flow. Processes and functional area data that should be studied include receiving, put-away, reserve storage, replenishment, picking, and value-added services. At the same time, the impact of considerations like the use of third-party logistics (3PL) providers, facilities consolidation, transition planning and compliance programs, and the full network should be analyzed. That’s a pretty big order, and it comes down to collecting accurate operational data in several areas. Item information for each SKU handled: this includes item numbers, descriptions, grouping information, special handling requirements, dimensions and weight per unit, case, and pallet Order history information for the past
JANUARY-FEBRUARY 2016 | www.PARCELindustry.com
Accuracy in data collection is key as any error can easily throw off distribution capacity requirements over both short and long terms. Determining optimal equipment and space requirements for each area of a facility also depends on accurate data. The best approach is to analyze each functional area independently and outline up to four handling approaches per location in terms of design, cost and efficiency; then, rank each alternative according to how it satisfies the established KPIs. Finally, look at the big picture and understand the sum of all the parts to find the best solution. PHASE 2: GETTING GRANULAR WITH THE DETAILS Called the detailed design phase, the second stage of DC optimization involves refining the top three conceptual layouts with future growth projections in mind. Doing so requires taking a detailed look at what the future is likely to bring. Consider things like: Potential acquisitions that may affect growth and handling capabilities New product introductions or ecommerce offerings that will alter fulfillment requirements Additional business or operational changes that might impact the design concept that is ultimately decided on The goal of the detailed design phase is to provide clear insights into the feasibility and actual cost of a selected concept.