Inventory Optimization: A Natural Fit

Inventory Optimization: A Natural Fit

A new inventory management system nurses Nature’s Best’s fulfillment operations back to health.

Brea, Calif.-based Nature’s Best, the largest privately owned wholesaler/distributor of health and natural food products in the natural products industry, built a successful business around keeping customers healthy. But an outdated inventory and purchasing system threatened the company’s own well-being.

In January 2011, the company—which provides certified organic, natural, and specialty products to retail stores throughout the south, central, and western United States, Alaska, Hawaii, and Asia—decided to provide procurement staff with automated support.

“We depended on our category and purchasing experts to buy successfully, and that inherently put us at great risk,” recalls Russell Parker, senior vice president of marketing, brand management, and inbound logistics at Nature’s Best.

The company’s buyers had 10 to 20 years of experience in the natural products industry, knew the company’s product categories, and had an instinctual and seasonal knowledge of the inventory. Operating under the yoke of an outdated legacy system, however, became problematic.

The existing procurement system didn’t allow Nature’s Best to move forward in a number of areas. It couldn’t add staff, respond to turnover, or handle additional distribution centers. At the time, Nature’s Best was handling a whopping 25,000 stockkeeping units (SKUs) from more than 1,600 vendors.

“We realized we needed leading edge software, and so we began a review process that led us to Inventory Optimization,” says Parker.

The software suite from Atlanta-based supply chain solutions provider Manhattan Associates is designed to handle complex retail, wholesale, and multi-channel inventory management challenges, such as balancing capital investment constraints or objectives and service-level goals over a large assortment of SKUs, while taking into account demand and supply volatility.

Inventory Optimization enables Nature’s Best to set channel-specific service levels so that Web, call center, and store orders can each be filled from the source, and at specific times,” says Rodney R. Daugherty, senior director, product strategy, Manhattan Associates.

By implementing the Inventory Optimization software, Nature’s Best was able to add a second distribution center without hiring additional buyers. “We doubled the workload, but didn’t need to add staff because of the software’s ability to design and set in advance all key procurement parameters,” says Parker. “We took all the manual functions our buyers performed, and leveraged the software to make decisions and calculations for them.”

A good example of this process is a grocery store aisle stocked with two seasonal favorites: eggnog and lemonade.

While customers may seem maddeningly fickle, some of their buying patterns are highly predictable. As Thanksgiving approaches, shoppers preparing for the long holiday season expect to see their local grocer’s dairy case fully stocked with eggnog. Six months later, when the temperature rises, shoppers return to the cooler looking for lemonade—but only through the hot summer months.

Both eggnog and lemonade are perishable items and present a challenge for the wholesale distributor: maintaining proper inventories to maximize profitability.

“We’ll get orders for two or three cases of eggnog in the first two weeks of November,” says Parker. “That number will escalate to six cases, then to 40 cases, then to 80 to 200 cases. That’s a significant ramp up for any kind of product.”

Demand for eggnog stays strong until Christmas Eve, then it wanes. By Jan. 2, demand plummets, and retailers don’t want to tie up valuable shelf space. Even though Nature’s Best’s buyers were very good at knowing what inventory they needed to make available during specific weeks, and when demand would cease, the “human factor” could sometimes result in less-than-accurate inventory.

“Our buyers used to make these decisions by the seat of their pants,” says Parker. “But on Dec. 23, when they’re still selling 80 cases, but they’ve only got 40 cases on hand, their inclination is to buy 40 more cases because they know customers will yell if they’re out of stock. As buyers, they have an inclination to not let go.”

From an inventory perspective, buying the 40 cases is a fatal flaw. More often than not, the anticipated demand never materializes, and weeks later the unsold inventory goes out of code. Historically, because most of the eggnog was bought for a negotiated discount that was passed on to the customer, Nature’s Best’s gross margin eroded significantly.

“The 40 cases they threw out completely wiped out the gross margin dollars they made on the previous 400 cases,” says Parker. “So they did all that for nothing, except making a few straggling customers happy.”

Forecasting Demand

That was then. Now, on Nov. 1, Inventory Optimization recognizes it is eggnog season, so it delivers a forecast. The system determines the pricing, the minimums, and whether or not there’s a deal involved in the purchase, then recommends an order of 20 cases.

Further, it has calculated the shelf life, so those 20 cases it initially buys will not go out of code before customers start to purchase during November.

Moreover, because of previous years’ histories, the system sees the huge demand spikes in November, and five to seven days later, it indicates that Nature’s Best should place an order for 100 cases.

“No buyer in their right mind would order 100 cases; but with Inventory Optimization, the data and the sales forecast set you free,” notes Parker. “It’s just as important to make the sale in the beginning as it is to cease the order at the end. On Dec. 23, the system looks forward, sees sales historically dropped down to two cases, and no longer recommends an order.

“The impulse to continue buying is set aside, and margins are maintained,” he adds.

Key Factors

From Nature’s Best’s perspective, Inventory Optimization offers three key advantages: Customer focus combined with financial responsibility, automated decision making, and demand-driven execution.

“One of the program’s key parameters is a desired service level,” explains Parker. So, for instance, if Nature’s Best wants a 97-percent in-stock position, the software calculates what is needed for that level or better. It then asks if it is a financially sound decision to achieve this stock level requirement.

In that way, the software ensures that it doesn’t buy beyond a set shelf life, goods are sourced in the most efficient way, and opportunity buys are maximized. It also allows labor and warehouse costs to be factored in.

“For example, the system compares the costs associated with ordering a pallet of juice once a day versus once a week,” says Parker. The software calculates and recommends optimum frequency. It also accounts for the needs of sales and financial functions.

For inbound logistics, Inventory Optimization maximizes efficient truckload shipping in competitive lanes.

Automated decision-making is also important. In the past, deciding to buy just one SKU took a buyer anywhere from two to seven minutes. Today, Inventory Optimization makes multiple rote buying decisions in a few seconds.

“This intensely algorithmic system thinks like the buyers have for several decades, but does it in one-sixteenth of a second,” says Parker. That frees buyers and category managers to focus their time on managing vendor relationships and developing new product offerings.

“The software does all the heavy lifting,” continues Parker. “It does the thinking. It does the analysis. It updates itself. It reviews and discards outlying data. It makes recommendations—and recommends changes—for everything from forecasts to order frequency.”

Improving demand forecast accuracy was also an essential requirement for Nature’s Best. By more accurately estimating the quantity of a product that consumers will purchase, Nature’s Best replaced educated guesses with quantitative methods. For instance, it started using historical sales data to make better decisions and assess future capacity requirements. The Manhattan Associates system is demand-driven; it is designed to execute based on how products really sell, which includes factors such as seasonality, promotions, and special deals.

“Nature’s Best required the ability to balance the cost of carrying inventory against the cost of acquiring inventory,” says Manhattan’s Daugherty. Many buyers order on a fixed schedule, simply because that is the way they’ve done it for years. This habit can lead to unforeseen imbalances.

Instead, an Inventory Optimization feature called Order Frequency Simulation balances the cost of carrying inventory versus the cost of acquiring inventory. This feature finds the most profitable days of supply for a given vendor line (a supplier and the group of products bought from that supplier) on which Nature’s Best should always order to maintain desired service levels and just enough inventory.

“Every time an order is placed, Inventory Optimization records and retains the reason that suggested order quantity was purchased: x amount covers safety stock based on demand and lead-time deviation; x amount covers lead time; and x amount covers the order cycle and days of supply,” says Daugherty.

Garbage In, Garbage Out

A crucial factor in maintaining accuracy is maintenance. The system makes weekly recommendations to buyers to ensure the integrity of data being used.

“It’s the oldest story in the software business: garbage in, garbage out,” says Parker. “So the focus of the buyers’ time is spent on maintenance: ensuring that how we adjust is based on course corrections the system recommends. This procedure guarantees high-level decision-making.”

The entire implementation cycle took fewer than 90 days. Return-on-investment of the software purchase occurred within a few weeks of system start-up. In the month after implementation, Nature’s Best reduced its out-of-stock conditions by 23 percent over the prior year. The second distribution center was added within six months of the software system going live, without the need to hire more personnel. The company’s top-line sales were increased through better seasonal forecast accuracy.

“The success of the software was demonstrated through receiving consistency, better fleet utilization, more consistent onboarding patterns with vendors, and better in-stock positions due to not over- or under-reacting to spikes in demand,” says Parker.

Today, the inventory management software continues to deliver a bumper crop of benefits to Nature’s Best.

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