HOW TO EFFECTIVELY MANAGE DEMAND WITH DEMAND SENSING AND SHAPING USING POINT OF SALES DATA

Predicting what and when the consumer will buy has never been an easy process for manufacturers or retailers. Burdened by the daunting task of precisely matching supply with demand, manufacturers are constantly improving processes to achieve the highest forecast accuracy to ensure when the consumer walks into the store, the product they are looking for is on the shelf. During times of economic uncertainty, the need for more accurate forecasting becomes increasingly critical as companies work to trim costs in the supply chain to ensure stability and profitable growth-without sacrificing customer service.

With this in mind, manufacturers are actively looking for the best methods to gain visibility or "sense" consumer demand. These efforts have included programs such as Vendor Managed Inventory (VMI), Efficient Consumer Response (ECR), and Collaborative Planning, Forecasting and Replenishment (CPFR). But each of these initiatives has challenges and does not necessarily capture true consumer demand. With VMI and ECR, inventory policy management drives the replenishment process instead of consumer demand. With CPFR the driver is demand planning. CPFR is focused on a broader buyer-seller relationship, which gives the manufacturer greater visibility of demand along with more time to respond to specific changes including planned promotions or special events.

With demand planning as the key driver in the CPFR process, the challenge is deciding which demand signals will drive the collaboration process. Many companies prefer to leverage multiple demand signals (order history, shipments, Point of Sales (POS), new product plans, promotions, syndicated data, etc.) to calculate their forecasts.

Even though CPFR programs have been successful in getting consumer-centric supply chains on the same page, some initiatives have not achieved the mass adoption anticipated for several reasons. Most of the companies still relying on product-centric supply chains-in which manufacturers push their goods out into retail and wholesale channels-can no longer afford to build inventory and wait for customers to buy. They need to get as close to consumer demand as possible. Leveraging POS data is an excellent way.

The growing use of POS data helps manufacturers take a giant step in using consumer driven demand. Over the past several years, the availability and accuracy of POS has increased dramatically. POS data is often viewed to give a truer picture of consumer demand because it is unencumbered by elements such as batch sizing, shipping quantities, and lead times. It can provide an early indicator of what's selling and what's not-critical information for new product introductions (NPIs) or short shelf-life products. This gives manufacturers the lead time necessary to make adjustments in their manufacturing and distribution plans, ensuring they are appropriately positioned to meet changing demand patterns.

The adoption and availability of technology that captures and analyzes POS data has led to its increasing integration into the demand management process. Manufacturers that have successfully incorporated POS data into the demand management process are experiencing increased forecast accuracy, improved NPIs, lower out-of-stocks, and decreased total costs. According to AMR Research, "Reducing out-of-stocks can contribute as much as 4% to the bottom line."

For example, when a consumer goes into a mass merchant retailer and buys a popular mascara, the product is scanned at checkout, creating POS data. The mascara manufacturer receives a demand signal that indicates the specific product has been purchased at a specific store at a specific date and time. They gain visibility and start refining their replenishment plans within hours. This granularity gives a very clear picture. Relying on traditional forecasting techniques would base the plan on order or shipping information. The forecaster would assume that because 10 cartons of mascara were shipped from the distribution center in September, market demand equals 10 cartons. Better visibility requires leveraging POS data to refine the demand plan and truly understand timephased replenishment needs.

BENEFITS AND CHALLENGES OF POS DATA

The benefits of leveraging POS data as a primary or secondary demand signal are significant. It improves accuracy because scanning is far more precise than keying in numbers from a pricing label. It gives a quick, near real-time look at the products moving through a specific retail channel. Additionally, POS data provides a granular SKU/store-level insight along with aggregate information to better manage inventory, trigger replenishment, and analyze sales patterns including the success of promotion plans.

There are also challenges that come with POS-based demand signals. First, syndicated data available from IRI, Nielsen and others, the primary source for corporate marketing analysis because of its broad sample, is available only at the category level. Furthermore, syndicated data does not include POS data of major retailers like Wal-Mart and thus may not cover global markets. The format in which data is available also creates problems because there is no single standard format, including EDI (Electronic Data Interchange), calendars, and selling horizons on the data from major retail chains. Also, since POS data is available in huge volume, it can be challenging to manage in a timely fashion. However, over the past five years or so, POS data accuracy has improved significantly as a result of technology upgrades and consistent cashier training. Additionally, retailers and manufacturers have a better understanding of the rich data and timely insight that can be harvested through POS .

Manufacturers must be driven by the demand of consumers and thus utilize POS data to more accurately predict, sense, plan, and respond to real-time demand signals across a global network of suppliers, retailers, and consumers. When executed effectively, a supply chain driven by consumer demand will positively impact profitability, inventory investments, customer satisfaction, and asset utilization. In The Handbook for Becoming Demand-Driven, AMR Research published a compelling assessment of the benefits of a consumerdriven demand business model, which found that the most advanced demand sensing companies have achieved a distinct competitive advantage across the business including 15% less inventory, 17% higher perfect order performance, and 35% shorter cash-to-cash cycle time.

BECOMING MORE DEMAND-DRIVEN

So how do manufacturers become demand-driven? You must first realize that technology alone will not transition you from a product-centric to a consumercentric manufacturer. It requires a combination of people, process, and technology. With a common focus on the consumer, you can begin breaking down internal corporate barriers between departments. This will ensure the commitments you make to retail customers will be delivered by your entire organization. Don't let organizational silos limit your success.

Realizing, that manufacturers struggled to respond to sudden spikes in demand or unexpected surges in inventory, profitable growth continues to be an elusive goal. In fact, the majority of manufacturers are driven by forecasts modeled on historical shipments or orders to retailers rather than on sales to end consumers. This traditional approach is geared to keeping production plants efficient but often leads manufacturers to "stuff" their channels with costly excess inventory.

With shorter product life cycles, increasing customer expectations, and needing to support a portfolio of NPIs, supply chain leaders must supplement the traditional demand planning process with POS demand signals. With more timely access to POS data, manufacturers can sense changes to demand more quickly. Figure 1 shows the researchfirm, Aberdeen Group, finds that 50% of companies report that it takes more than one month to sense changes in demand, which is unacceptable in today's marketplace.

Aberdeen recommends that companies with any of the following attributes should focus on establishing more rapid demand sensing and response capabilities:

* Maintain safety stock levels to account for poor short-term forecast accuracy.

* Have short-to-medium lead times for products (one to six weeks).

* Use promotion-intensive marketing strategies that require strong SKU-level forecast accuracy.

* Fail to have the right SKU mix on retail shelves, creating measurable losses in sales and gross margins.

* A desire to improve customer-service levels, as well as to have smoother upstream manufacturing processes.

Supply chain technology has evolved quickly over the past decade, often outpacing capabilities that manufacturers have been willing or able to implement. The current dynamic market may be the catalyst needed to give a consumer-driven business strategy a top priority. Even with the increase in the use and availability of POS data for demand sensing, it is just one component of a comprehensive demand management process that also includes demand planning, demand shaping, and demand collaboration to profitably and efficiently match supply with demand. (Demand sensing means sensing a change in the demand pattern using downstream data such as POS and Radio Frequency Identification-RFID; demand shaping, on the other hand, means to shape the demand using marketing, price, promotion, trade and sales incentives.) Together, these techniques establish a process for predicting, dynamically sensing, shaping, and reshaping demand to move your business from reacting to demand, to anticipating demand, to driving demand across strategic, operational, and tactical planning horizons.

KEYS TO A ROBUST DEMAND MANAGEMENT

Although the concepts of demand planning, demand sensing, demand shaping, and demand collaboration seem simple, their implementation requires a holistic approach to demand management. With a consumer-driven demand business strategy, forecasting increases in importance as it evolves into a robust demand managementprocessthatbecomes the foundation for upstream supply chain activities. To gain valuable insight into your business, consider the following changes in demand management.

* Plan for Key Customers and Channels: It is critical to model and forecast your top customers and/ or channels to better understand key drivers, specific demand patterns, and customer service requirements. Although readily available in leading demand planning solutions, only a minority of manufacturers leverage customer-level and/or channel-level forecasting for their most important customer ship-to locations.

* Leverage Downstream Data: Complement traditional forecasting processes with downstream data including syndicated data, POS, and, in some cases, RFID. These more timely indicators coming from consumer demand will increase supply chain responsiveness to current market activity.

* Flexible Planning Periods: If appropriate for your business, the availability of POS data can help your team move from a monthly to a weekly forecasting process. At a minimum, it will allow you to fine-tune and synchronize replenishment activities. Most businesses need a comprehensive demand plan that supports strategic, operational, and tactical planning horizons for a variety of roles in the business. An accurate long-term forecast is critical to aligning production capacity and sourcing resources.

If adopted as a key demand signal in the demand planning process, POS data gives manufacturers a strong competitive advantage. Particularly in the CPG industry, POS data can significantly decrease shelf level out-of-stock rates and increase demand forecast accuracy. More and more manufacturers have turned to demand planning solutions to increase visibility and capture and use POS data to create the demand forecast.

FUTURE OF POS DATA

In today's economy, the demanddriven supply chain is a powerful weapon for businesses of all sizes. With dynamic market swings, volatile fuel prices, less predictable consumers, and intense global competition, corporate profit margins are experiencing a convergence of pressures. While researchers have talked about the importance of using POS data in the demand management process for almost a decade, the adoption rate by manufacturers was initially slow. Today, many fastmoving consumer goods manufacturers are increasing forecast accuracy by leveraging POS data in addition to data from orders and shipments. The insight that a planner gains by having access into multiple demand signals has been proven to advance the accuracy of the overall forecasting process and ensure improved customer service.

Consumers are fickle and predicting what they will purchase is never an exact science, but the technology to aid in this process has reached a level where it is possible to establish a clear and timely prediction. The volatility of the economy is always at the forefront of a manufacturer's strategic direction. As a result, finding a better way to manage demand becomes more critical to building profitable growth. As the accessibility and reliability of POS improves as well as the adoption of demand planning systems to leverage the data, more and more manufacturers will benefit from the POS demand signal to reduce inventory, improve customer service, and boost profitability.

Source :Karin Bursa