Demand planners have to cope with multiple problems to get their job done. One is the Irritation of Intermittency. The “now you see it, now you don’t” character of intermittent demand, with its heavy mix of zero values, forces the use of advanced statistical methods, such as Smart Software’s patented Markov Bootstrap algorithm. But even within the dark realm of intermittent demand, there are degrees of difficulty: planners must further cope with the potentially costly Scourge of Skewness.

Skewness is a statistical term describing the degree to which a demand distribution is not symmetrical. The classic (and largely mythic) “bell-shaped” curve is symmetric, with equal chances of demand in any time period falling below or above the average. In contrast, a skewed distribution is lopsided, with most values falling either above or below the average. In most cases, demand data are positively skewed, with a long tail of values extending toward the higher end of the demand scale.

Bar graphs of two time series
Figure 1: Two intermittent demand series with different levels of skewness
Figure 1 shows two time series of 60 months of intermittent demand. Both are positively skewed, but the data in the bottom panel are more skewed. Both series have nearly the same average demand, but the one on top is a mix of 0’s, 1’s and 2’s, while the one on the bottom is a mix of 0’s, 1’s and 4’s.

What makes positive skewness a problem is that it reduces an item’s fill rate. Fill rate is an important inventory management performance metric. It measures the percentage of demand that is satisfied immediately from on-hand inventory. Any backorders or lost sales reduce the fill rate (besides squandering customer good will).

Fill rate is a companion to the other key performance metric: Service level. Service level measures the chance that an item will stock out during the replenishment lead time. Lead time is measured from the moment when inventory drops to or below an item’s reorder point, triggering a replenishment order, until the arrival of the replacement inventory.

Inventory management software, such as Smart Software’s SmartForecasts, can analyze demand patterns to calculate the reorder point required to achieve a specified service level target. To hit a 95% service level for the item in the top panel of Figure 1, assuming a lead time of 1 month, the required reorder point is 3; for the bottom item, the reorder point is 1. (The first reorder point is 3 to allow for the distinct possibility that future demand values will exceed the largest values, 2, observed so far. In fact, values as large as 8 are possible.) See Figure 2.

Histograms of two time series
Figure 2: Distributions of total demand during a replenishment lead time of 1 month
(Figure 2 plots the predicted distribution of demand over the lead time. The green bars represent the probability that any particular level of demand will materialize.)

Using the required reorder point of 3 units, the fill rate for the less skewed item is a healthy 93%. However, the fill rate for the more skewed item is a troubling 44%, even though this item too achieves a service level of 95%. This is the scourge of skewness.

The explanation for the difference in fill rates is the degree of skewness. The reorder point for the more skewed item is 1 unit. Having 1 unit on hand at the start of the lead time will be sufficient to handle 95% of the demands arriving during a 1 month lead time. However, the monthly demand could reach above 15 units, so when the more skewed unit stocks out, it will “stock out big time”, losing a much larger number of units.

Most demand planners would be proud to achieve a 95% service level and a 93% fill rate. Most would be troubled, and puzzled, by achieving the 95% service level but only a 44% fill rate. This partial failure would not be their fault: it can be traced directly to the nasty skewness in the distribution of monthly demand values.

There is no painless fix to this problem. The only way to boost the fill rate in this situation is to raise the service level target, which will in turn boost the reorder point, which finally will reduce both the frequency of stockouts and their size whenever they occur. In this example, raising the reorder point from 1 unit to 3 units will achieve a 99% service level and boost fill rate to a respectable, but not outstanding, 84%. This improvement would come at the cost of essentially tripling the dollars tied up in managing this more skewed item.

Thomas Willemain, PhD, co-founded Smart Software and currently serves as Senior Vice President for Research. Dr. Willemain also serves as Professor Emeritus of Industrial and Systems Engineering at Rensselear Polytechnic Institute and as a member of the research staff at the Center for Computing Sciences, Institute for Defense Analyses.

As we approach the midpoint in 2013, there is still a lot of economic uncertainty complicating your supply chain planning processes. Some look at this shaky economy and postpone needed investments that can position their organizations for a strong future.

However, this is not the time to retreat from your supply chain improvement initiatives. Rather, it’s a time to double-down on your efforts to prepare for the inevitable business opportunities that lie ahead.

Economic recovery is a time of sales opportunities. You want to make sure that you’re prepared to take advantage of them. Good demand and inventory planning can help.With the right software and planning processes, you can achieve a sound statistical basis for decision-making going forward while making informed adjustments as circumstances dictate. You can improve your ability to read demand signals, spot trends, model future events, and bring your inventory into balance with demand.

Here are six areas of demand and inventory planning where changes you make now can lead to big payoffs when new opportunities arise:

1. Optimize your inventories

When the customer calls, you want to be able to ship. At the same time, you want to control your costs. The surest way to meet that goal is to find the inventory “sweet spot.” That’s where you have the minimum amount of inventory required to satisfy product demand over a specified lead time and at a desired service level.

The ability to accurately set safety stock and inventory levels can set you apart from the competition, and make a difference in your bottom line. However, getting to that point requires a shift in your planning focus from just forecasting future demand to optimizing stocking levels to fill future orders.

If you’d like to know more about achieving the “sweet spot,” you can find a good article published in APICS Magazine here.

2. Implement intermittent demand forecasting solutions

Companies in the service parts, auto aftermarket, and capital goods industries commonly experience intermittent, “slow moving” demand for a large percentage of their inventory items. Accurately forecasting demand and estimating safety stock levels for these types of items is probably the toughest challenge demand planners face. If you can accurately forecast your intermittently demanded parts and products, and have the correct amount of inventory and safety stock on the shelf, you’ve got most of the competition beat!

The reason for this is that items that have intermittent demand do not have normal demand patterns or distributions, making them difficult to forecast using traditional forecasting methods (see the diagram below).

Bar chart illustrating intermittent demand

So, if you have an accurate means of forecasting intermittent demand and estimating safety stock requirements, you’ll be ahead of your competitors that don’t.

If you’d like to know more about forecasting and planning items with intermittent demand, you can find an informative white paper here.

3. Improve lead times

The economic downturn has forced companies to rethink their sourcing strategies because of uncertain demand back home, long lead times to obtain their goods, rising labor costs abroad, and increasing transportation costs. Shortening replenishment lead times can reduce the time required to get the products you need and helps make your supply chain more efficient. It also makes it easier to react to changes in demand when recovery comes.

4. Prioritize service levels

Prioritizing service levels for your products can help insure that the items important to your sales are given the attention they need. For items that are highly demanded, consider setting service levels higher than for those with less demand. Also try doing a revenue-based ABC analysis of your company’s stock-keeping units (SKUs) and set service levels accordingly in your software planning solution.

For example, you might set the service levels for your “bread and butter” items at 95-99% or higher, while setting service levels much lower (at 70-80% or even less) for other items. In this way, you may find that you need much less stock for some of your SKUs and more stock for others to effectively achieve your overall service level goals.

5. Use more recent demand history in creating your forecasts

Because the economy has been changing so fast, it may be time to shorten the demand history used in generating your forecasts so more emphasis is placed on recent trends and demand patterns—reflecting the “new normal”—rather than those contained in outdated history from 3 or 4 years ago. This, of course, should be done in consultation with your management team and preferably as part of an organized S&OP process that thoroughly evaluates both the risks and benefits of adopting this strategy.

6. Invest in technologies and resources that help you capitalize on opportunities

Investing in the right tools and processes increases your competitive advantage. If you aren’t doing so already, here are some valuable things to consider:

• Start an S&OP process, or fine tune your current process, to include key stakeholders in the supply chain and also ensure that demand forecasting and inventory planning provide key inputs in that planning process.

• If your forecasting software is not good at picking up trends, or cannot handle the portion of your inventory with intermittent demand, find software that’s up to the task.

• Find software that will take your forecast results and generate accurate inventory stocking levels to satisfy demand for your products, components or raw materials over specified lead times and at service levels you desire.

• Look for software solutions that are scalable, yet have a relatively low total cost of ownership, fast payback and high ROI.

• Finally, don’t scrimp on training; get all the training and consulting you need to get the “biggest bang” from your software investments.

Do you have anything to add? What are you doing to prepare for the economic recovery? Please leave a comment.

Charles Smart is the founding President of Smart Software. He currently serves as Vice Chairman, on Smart Software’s Board of Directors, as a company spokesman and in development of strategic business relationships. Prior to founding Smart Software, he was a management consultant at the Stanford Research Institute (SRI International) and Policy Analysis, Inc., and served as a Lieutenant in the U.S. Navy.