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Preparing for Uncertainty with Cost-Cutting Analytics in Consumer Products

Certain global and national signals have led financial planners, corporations, and consumers all to wonder if we’re headed toward a recession (or semi-recession, according to some). Recessionary periods have historically hit hard on wholesale and retail sales, as well as investment, unemployment levels, access to affordable healthcare, and income. While there is much debate and little clarity over upcoming economic growth, an inverted yield curve and increasing global conflicts of trade and politics are reasonable signals to prepare for uncertain times ahead.

Preparation for consumer products companies could include things like cutting costs in areas such as travel or restructuring accounts payable processes, but enabling more strategic cost-cutting analytics will generate more sustainable returns than other quick fixes. Below, I’ve outlined some leading use cases for cost-cutting analytics that consumer products leaders are using to establish cost savings now and return dividends in the future to stabilize and protect margins across manufacturing and supply chain.

Predictive Maintenance: In a straightforward example of machine learning in action, predictive maintenance uses data from sensors on factory equipment to predict when a part needs to be replaced to avoid down time or downstream effects of faulty equipment. Industry leaders are seeing success with this application and taking it further by creating a digital twin of their factories (and supply chains), using internet of things (IoT) data from sensors to gain real-time visibility to all products moving through their factories. Unilever is investing to expand their virtual versions to roughly 300 global plants in 2020.

Optimize Production: Identifying and monitoring waste throughout your production line is the first step in reducing it. All manufacturing results in some by product but building visualization to monitor inputs and outputs at all stages of production can help identify when waste becomes excessive due to a breakdown in equipment or processing. Additionally, exploratory analytics of production processes can identify opportunities for cutting costs. For example, at a tobacco manufacturer, we found an opportunity to manipulate machine speeds to maximize production throughput while minimizing quality rejects, rather than running at maximum speed, which was resulting in excess rejected product.

Inventory Optimization: Costs can run high for storing and moving inventory, and it can be complex to manage the full network of inventory across manufacturing and distribution centers, especially with escalating customer expectations for availability and free shipping and returns for online purchases. Building strong forecasting for demand and understanding drivers of demand, including external data sources like weather and localized holidays can generate more accurate and granular safety stock levels to reduce costs of both overstocking and out of stocks.

Network and Logistics Optimization: In a complex supply chain network, there are many opportunities to reduce costs through analytics. Route optimization in real-time can alert logistics providers to changes in route that will expedite shipping or lead to better collaboration on a return route. Forecasting external delays can avoid timely and costly interruptions and using IoT sensors for predictive fleet maintenance can prevent delays or costly repairs due to equipment failure. Proctor & Gamble is investing in a control tower supply chain analytics platform for full visibility to goods movement in their network, anticipating a 2-5% margin improvement and 5-10% improvement in asset utilization and reduction in the movement of empty trucks.

These are just a few example use cases demonstrating the power of analytics to drive long-term, sustainable returns and ensure protection against external economic or geopolitical forces. Our management consulting group recently analyzed over 350 publicly traded organization’s performance during the last recession. In this analysis, 5 themes emerged across the organizations who maintained performance through financial instability: invest for the future, drive new behaviors through KPIs, operate with agility, simplify the strategy, and recommit to a shared purpose. Are you having conversations about cost-cutting analytics now to solidify your company’s position in our near-term economic climate?

Coauthor and contributions by Eric Gardner

Tags: Advanced Analytics, Analytics, Data & Analytics, Data Analytics & Insights, Managed Analytics