An optimized supply chain delivers $
Written by Bobby Miller and Pat Smith
Leading consumer goods companies are adopting a breakthrough methodology, Predictive Replenishment, which generates value by integrating strategic, tactical and operational processes. This supply chain planning approach encompasses three functional areas:
- Strategic: Supply Chain Network Design that continuously adapts and links products flows to downstream processes
- Tactical: Demand Sensing and Inventory Optimization that predicts customer requirements based on market-driven demand signals and POS data
- Operational: Order Fulfillment and Transportation Planning that can create perfect orders and shipments
Each of these functions contributes to overall supply chain planning and optimization. However, they are often disparate, with little to no visibility from one function to another. Leading consumer goods companies are boosting business performance by linking these individual, functional silos into a single cohesive methodology. By doing this, they are maximizing supply chain processes and uniquely positioning their business to manage and improve “total cost to serve.” This optimization is called Predictive Replenishment.
Creating Opportunity from the Top Supply Chain Obstacles
A 2012 analyst firm survey of supply chain executives indicates the discontinuity within the optimization and planning processes. It also highlights the opportunity to link these processes to achieve and sustain a new level of supply chain and business value creation. What do companies say is their top obstacle to achieving their supply chain goals? According to the survey, the top four obstacles are:
1. Forecast accuracy and demand variability – It’s not just about trying to get the best possible forecast, but to simultaneously characterize the variability at the item/location level of detail. Forecast will never be perfect, so how we understand variability becomes key to driving an inventory policy that will deliver service goals.
2. Inability to coordinate and synchronize end-to-end Supply Chain processes – Too many conflicting KPIs. For example, manufacturing is incentivized to maximize assets (long runs and few changeovers), but logistics and distribution are focused on inventory turns/reduction and optimizing transportation cost. Finding equilibrium – to work towards the right trade-off to accelerate business performance – is doable if everyone is focused on the same metrics of service, inventory and profitability.
3. Lack of visibility across the supply chain – The biggest opportunity with the fastest return is the propagation of the demand signal with the understanding of the variability properties to improve the signal given to both manufacturing and transportation processes. Ideally, work with the lowest level of demand granularity to build your foundation (daily ship-to or POS).
4. Supply Chain Network complexity – You either have too much push in your distribution networks (you push manufacturing lots out to the network without a detailed understanding of how to split that lot so inventory is at the right place in the network to deliver service) or too many tiers where double handling and freight cost hinder gross margin and inventory turns. By leveraging network design along with a bottom-up statistical forecasting approach, you can improve your supply chain visibility and reduce network complexity.
An optimized supply chain delivers $ (source: ORTEC)
Predictive Replenishment is about integrating and synchronizing the strategic, tactical and operational functions to accomplish four goals:
1. Foster Collaborative Decision Making: The decision making process is often done in silos within an organization. However, making decisions that are collaborative across functions creates a bidirectional flow of information. This creates more controllable business outcomes.
2. Create an “Outside-In” Approach: Moving from a mindset of “what are we going to make today” to “what are we going to sell today” is often called an “Outside-In” approach to demand management. It takes advantage of demand streams, such as order lines, store-level POS data, or customer warehouse data to provide visibility into future demand.
3. Reduce Latency in the Planning Process: Reducing the amount of planning time and increasing the frequency of high quality decision-making helps improve customer satisfaction, asset utilization, profitability and cost (i.e., transportation, inventory and trade promotion).
4. Smooth the Transition from Strategic to Operational Planning: Synchronizing upstream and downstream functions (technologies and processes) allows planning and execution to converge. As noted earlier, providing an integrated demand signal and propagating it across the value chain gives visibility to logistics, manufacturing and the customer-facing team to deliver the best service at the most effective cost structure, while accounting for known constraints of lead-time and capacity (both manufacturing and transportation). Taking a more proactive vs. reactive approach to planning removes time delays and demand signal discontinuity for each stakeholder in the organization.
Companies can achieve the following sustainable business benefits by accomplishing these four goals are:
- 30%+ improvement in forecast accuracy
- 20%+ efficiency with inventory investment
- 5-10% transportation spend savings
- 1% + increase in revenue
- 1% point in margin growth
Reaping the benefits of Predictive Replenishment.
The following chart summarizes how Predictive Replenishment helps organizations achieve business goals.
Take a crawl, walk, run approach to starting the Predictive Replenishment journey. This not only builds capabilities (both technical and business process), but creates sustainable momentum for accelerating business performance. Consider the following to start your journey:
Crawl: Understand and leverage your data. Leverage demand signals that you have access to today in your ERP, but perhaps don’t utilize to improve your forecast. Look for a solution to augment your current forecasting that can do a detailed bottom-up approach to understand variability and how to improve the disaggregation of your forecasting process. Consider how demand sensing technology can help identify and improve the signal vs. noise ratio to enhance short-term forecast accuracy.
Walk: Multi-echelon inventory optimization (MEIO) is an opportunity that can deliver great benefits when paired with an improved forecasting and demand sensing process. The goal of MEIO is to deliver service levels against the business objective (typically least cost of inventory). Within 6 to 12 months, companies can demonstrate benefits in both service and inventory by leveraging technology and business process that allows the coupling of the crawl and walk phases.
Run: Bring supply chain design and flow path optimization into the tactical decision making process. This is about taking the macro picture (e.g. cost-to-serve) and translating that into tactical. When leveraged with MEIO, flow path optimization and operational planning will deliver margin maximization and enhanced service level performance. If there is a lack in skill set or technology, outsource it. Costs are reasonable and the insights gained by working with the right vendor and consulting experts will pay for itself many times over.
This article was originally published in Logistics Viewpoints
Written by Bobby Miller and Pat Smith. Pat Smith is the managing director of ToolsGroup North America. Mr. Smith brings more than twenty years of sales and management experience including four at ToolsGroup. Previously he held senior roles at companies ranging from Consumer Packaged Goods leaders such as Pillsbury PLC (acquired by General Mills) to software companies such as Optiant (acquired by Logility), Park City Group and Marketron. Mr. Smith holds a BS in Business Management from Providence College.