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As consumer goods (CG) companies move to a Demand Driven Supply Network, an essential element to the transformation is a better understanding of consumer demand through rigorous analysis of point-of-sale data. This month, CGT sat down with Karen Laucka, Director of Industry Marketing, Consumer Goods & Retail, for i2. Karen draws upon her experiences in the industry, including her role as Demand Manager at The Gillette Company, to discuss how leading-edge companies are changing their processes and reaping benefits through better use of point-of-sales (POS) Data.
With supply chains being driven by consumer demand, what steps should CG companies take to improve product availability on the retail shelf? We've seen the best results when both inventory and demand management best practices are implemented in conjunction with one another. These are the best practices that differentiate top performers from the rest:
The utilization of ABC segmentation to drive inventory strategy. CG companies need to have different supply chain strategies and posture for different kinds of "segments" based on consumption pattern, criticality, velocity and other attributes.
A focus on understanding consumer buying behavior by monitoring POS and constant visibility of inventory in the pipeline. Companies can turn visibility into action by having a process that interprets this buying and feeds it back into their inventory strategy to align inventory position with market expectations.
The use of postponement strategies when designing the supply network. Companies should use segmentation as well as multi-echelon inventory optimization to design deployment strategies to position inventories and trigger replenishments from various points in the supply chain.
Optimizing inventory levels to account for risk. Best practices include the use of stochastic multi-echelon inventory planning tools to optimize inventory policies to account for supply and demand risk.
Closed-loop, continuous learning. This involves the practice of understanding the drivers of variability and monitoring the demand and inventory plans against the latest actuals so that plans and supply network strategies can be revised accordingly.
How can manufacturers better use POS data to achieve this goal?
CG manufacturers can utilize POS data as the data feed for the development of their demand forecasts. The use of POS data can result in a more accurate demand forecast since it is based on true consumer demand rather than the manufacturers order and shipment. POS data also provides the ability to analyze and forecast at the level where the demand (and corresponding variability) occur at the store/SKU level. At a minimum, POS should be monitored for unplanned demand spikes and trend changes.
However, for effective use of POS in the manufacturer's supply chain planning, a link between POS and the planning variables must be established. Our recommendation is to begin using POS data in pockets to validate the new process and algorithms and minimize risk of disruptions to the supply chain. POS data should be monitored in real time and made visible throughout the supply chain so that demand, supply, inventory and replenishment plans can be dynamically aligned with the latest consumer demand.
POS can be leveraged to better understand consumer buying behavior. When advanced analytics (such as clustering and pattern recognition) are applied to POS data, organizations can develop optimal inventory segmentation strategies, plan targeted promotions, identify and retain their most profitable customers, and develop more effective new product launches.
How are leading CG companies managing disparate and unclean data?
The implementation of a centralized "demand signal" data warehouse and the use of data cleansing and analytics services can help an organization eliminate these challenges. With this approach, disparate data sources can be consolidated and the data can then be cleaned, mapped to manufacturer planning views and analyzed to provide meaningful data points for each type of user that receives that data. Also, the use of data and workflow management tools can automate the scheduling of an increasing number of data loads (as POS data availability becomes more frequent) and alert users when this data is available for analysis and planning. Many of the major software solution providers are now providing data warehouses that are specifically designed to act as a "demand signal" data warehouse as well as the cleansing and analytics services.
how can CG companies help retail partners incorporate real-time POS data for more frequent replenishment cycles?
To support these frequent replenishment cycles, CG companies must optimize the design of the supply network through segmented inventory strategies and the proper use of postponement strategies to develop a pull-based supply network designed considering true consumer demand (POS data).
For example, high volume or strategic SKUs that the retailer never wants to be out of stock require frequent replenishment and should be positioned as close as possible to the retail store and leverage transportation strategies such as direct store delivery. Real-time POS data should be used to provide visibility to the latest consumer demand and buying patterns to trigger appropriate revisions to inventory policies, replenishment plans and orders as well as allocation strategies. These revisions should be shared with the retailer in real time so that the retailer is informed and, if required, allows them to make changes to the plan.
How will RFID, and subsequent data that comes along with it, benefit firms?
RFID data will improve the replenishment process by increasing the quality of forecasted replenishment orders, improving inventory allocation strategies and identifying impending out-of-stock situations at the store.
Using the information that RFID tags will provide, manufacturers will have visibility into how many cases of product were shipped from a distribution center and which cases were put on the shelf at the store. If this information is combined with POS, the manufacturer will have an idea of how much inventory is in store, how much is on the shelf and how long it is expected to last. This information can then be used to adjust forecasted replenishment orders or expedite the shipping of an existing order to quickly avoid out-of-stocks.
Which industry segments are best utilizing POS data to become more demand driven?
Due to market conditions that are characterized by frequent new product launches, customer-specific packaging and promotions, and extremely fast-moving launch cycles, media and entertainment has been one of the first industries to utilize POS data both extensively and successfully in its demand and replenishment processes.
One of i2's leading customers in this industry is using POS data to plan total release quantities, determine initial store allocation quantities, inventory requirements and promotions with a high degree of accuracy despite the highly variable and accelerated demand that surrounds each new release. To support the large number of customer specific packaging requirements they have used postponement strategies that allow them to delay adding customized materials until they have better visibility of demand. They have combined this approach with a responsive replenishment process that uses real-time monitoring of POS and direct store delivery that enables them to change replenishment plans based on the latest demand signal. RFID technology that facilitates tagging cases for a specific store shelf has allowed leading media companies to take this consumer-focused approach to the next level with vendor-managed inventory (VMI) programs for key retailers that plan and replenish at the shelf level for each store. This approach offers a lot of promise in that it will prevent out of stocks where it is most important -- at the retail shelf where the consumer goes to select the product.