June 1st, 2005

It is estimated that the retail industry spends about $20 billion a year on software. However, some industry observers assert that only the biggest retailers are actually budgeting for better software to help them manage inventory and demand.

The small- to mid-sized sector of the retail industry shares the same pain points as their larger competitors: poor availability of stock or simply too much stock. In the past, only the enterprise sector could afford technology to optimize business processes and realign supply chains to meet the ever-changing and fluctuating consumer demand, but now the mainstream can, too, using the latest demand management technology that is now leveling the playing field.

Having the wrong amount of stock is a universal problem for all retailers. But optimizing business processes; deploying demand management technology; managing the sheer complexity of operations through automation; and responding dynamically to changing consumer demands are not as daunting or impossible as they used to be.

Demand management or demand planning tools improve demand forecasting capabilities and help retailers analyze supply-side and safety stocking issues. The complexity is tempered by striking the right balance of products and locations, and knowing where the stock levels should be in order to meet the demand. The old adage of the right stock at the right place still rings true!

There are various factors in determining what drives stock levels. Out-of-stocks, over-stocks on slow moving items, safety stock and operating costs all drive a retailer's performance levels, including profitability and efficiency.

If a retailer doesn't have the stock on hand for regular and promotional items, for example, chances are customers will flock to competitors, and the retailer's store revenue will erode. Another issue is overstock on slow movers and safety stock. While customers may not notice, retailers certainly recognize the strain of tied up working capital, which impacts margins and profits.

Not only that, retailers face higher operating costs as a result of grappling with larger numbers of SKUs. Sorting large numbers of SKUs also creates errors, and manual processes add labor costs.

These, in turn, sow lack of confidence among consumers in the retailer. In a 2004 study conducted by the Food Marketing Institute, researchers examined the causes and consumer responses to out-of-stock situations:

--- Buy Item at Another Store: 31 percent
--- Substituted Different Brand: 26 percent
--- Substituted Same Brand: 19 percent
--- Delayed Purchase: 15 percent
--- Did not purchase: 9 percent

The study also highlighted the root causes of regular out-of-stock situations:

--- Store forecasting (ineffective algorithms): 33 percent
--- Store stocking (inadequate/incorrect shelf space: 22 percent
--- Store ordering (inappropriate replenishment intervals): 18 percent
--- Management errors (inaccurate/obsolete product information): 13 percent
--- Warehousing (poor ordering policies, data accuracy): 11 percent
--- Manufacturer availability (packaging/raw materials, capacity issues): 3 percent

With demand management forecasting and replenishment solutions today, mainstream retailers have been able to improve in-store service levels to more than 90 percent without having to stack items to the rooftops of their organizations. Moreover, retailers can process millions of SKUs in a matter of hours by completely automating their forecast-to-replenishment process.

How does a retailer enable the right process? In its 2005 trends, AMR Research recommended that the retail industry invest in processes.

"The ability to leverage demand data thoroughly is now high priority for retailers to inject insight for all aspects of customer demand into every retail process flow, to achieve tighter execution, more accurate forecasting, and a reduction in out-of-stocks, resulting in potential 10 percent sales and five percent margin growth."

That's where demand planning comes in. Demand planning can reforecast, reanalyze and recalculate safety stock on a daily basis, setting dynamic minimum and maximum levels, and then make recommendations on the appropriate replenishment equation, which can be fed back into the system for execution.

The results are staggering and include improved out-of-stock positions, reduced inventory investments, and administrative savings through reducing the number of people who have to be shuffling papers, freeing up time to focus on planning and performance management.

In one stark example, before implementing a forecast-to-replenishment solution, a mid-sized retail discount chain's order suggestions were produced using its own legacy system. Orders were created overnight for review and for process by the retailer's personnel the next day.

With a diverse range of products, the retail replenishment executive commented that there was an estimated 40 percent intervention rate, demand was erratic, and the system wasn't recommending suitably accurate orders. By continuously intervening manually, the level of stock turn was continuously too low.

However, through a demand management solution, the discounter was able to combine historic and current policy, and price and promotion information to automate the functions of forecasting, inventory optimization and replenishment. This resulted in order intervention only two percent to five percent of the time. The net result was an inventory accuracy rate of between 90 and 95 percent, translating into enormous efficiency savings!

Mainstream retailers now have the same demand management tools at their disposal as their larger competitors, and they should be making the most of this new opportunity in the marketplace.

Source: Line 56