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The global coronavirus pandemic put a giant exclamation point on the uncertainty that retailers, distributors, and manufacturers have always had to contend with. Tremendous effort is now being directed toward forecasting, supply planning, and ensuring that purchase orders are correctly placed and that product reaches its destination in the right mix and quantities. Yet regardless of how good companies get at planning, “stuff happens,” and they need to be able to rapidly adjust to evolving situations on the ground.
Agile demand-supply alignment can be defined as the ability to realign supply and demand, during execution, in the face of demand volatility and supply disruptions. The sooner that deviations from plan are known, the wider the range of options available to deal with emerging issues. The greater the delay in addressing undersupply, the greater the impact on the cost and feasibility of solutions, as well as on customer satisfaction. Though less time-critical, oversupply situations have carrying costs and can lead to profit erosion due to markdowns or liquidation.
Supply-chain planning cycles are growing steadily shorter, from monthly to weekly to daily, ultimately evolving into an incremental, continuous planning model. The planning process is now embedded within execution processes.
Ideally, supply disruptions and demand-volatility issues are predicted well before they happen, rather than being detected after they happen. Visibility into a supplier’s production status is particularly poor in many supply chains. The OEM, brand owner, or retailer often isn’t aware of delays in the supplier’s acquiring raw materials or hitting production milestones, until it fails to book a container by the required date. Cultivating a trusted supplier relationship, whereby bad news gets delivered early, is key. Supplier portals let suppliers update order status throughout the production cycle, but they still require training and constant reinforcement of the importance of timely, honest updates.
For many companies, accurately detecting deviations from a forecast early can be devilishly hard. When the inventory mix at a store or distribution center is wrong, shoppers don’t find the size, color, and style they want, and that sale is often lost. Manufacturers that sell through retailers face the further challenge of lack of direct visibility into end-customer consumption. Modern demand-sensing software, drawing on the right data, can create a more accurate picture of near-term demand.
When disruptions and deviations occur, information is needed to assess the impact, understand alternative resolutions, and make decisions. Solutions that automate the gathering of that widely dispersed information provide an up-to-date understanding of the current situation.
An intelligent organization prioritizes the most consequential disruptions, in order to properly apply its resources and identify the root causes of persistent multiple delays. They can consider multiple options for solving the problem through cross-functional, inter-enterprise collaboration. And they can compare various solutions, with an eye toward their impact on sales, profit, customer satisfaction and other key metrics.
Providers of advanced control towers and autonomous supply-chain platforms are developing algorithms to prioritize issues and pull together the needed data to compare outcomes side by side. They are investing heavily in artificial intelligence and machine learning, which can observe actions taken under various circumstances, analyze the outcomes, and build models to recommend situation-specific actions in the future.
Outlook
Each business pursues a variety of initiatives to improve demand-supply alignment agility. Functional managers will typically focus on their own areas of control. Senior executives with cross-functional influence should seek to implement more holistic approaches. Agility in aligning supply and demand will serve an organization well, in normal times as well as during those of major disruptions.
Bill McBeath is Chief Research Officer with ChainLink Research.
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