The importance of understanding your peak demand

To be ready for peak periods, it's important to define service achievement targets. It's just as important to set targets for demand.

Understand Your Peak Demand

Setting targets for demand is important because retailers need to measure their web site’s capacity, based on this target. Set the demand target too high and you will spend too much on capacity. Set the targets too low and you run the risk of insufficient capacity and, as a result, poor customer experience when the web site experiences overload.

The first step is to quantify the demand your web site is likely to experience over its peak trading period.

The flow chart below outlines our process for doing this, using the example of an online retailer:

 In an ideal world, the business would have accurate forecasts of demand for the forthcoming peak period. However, in our experience this is often not the case. Often, demand forecasts are aspirational or poorly defined.

We help our clients forecast demand using a number of techniques, including:

• Time series decomposition
• Regression analysis
• Arrival rate distribution analysis
• Bursty demand analysis

We’ve observed substantial growth in mobile and mobile application demand in recent years. The forecast should be broken down by channel, because each could generate different technical demand:

Once the forecast business demand has been established, this must be translated into a technical demand forecast. Our methodology for delivering this includes the following techniques:

• Systems analysis
• User behaviour modelling

If you are forecasting for an e-commerce site, it is important to consider demand from ‘scrapers’. Many online stores have their inventory and prices ‘scraped’ by automated robots operated by rival companies or resellers. In our experience this demand can be substantial.

Remember any forecast will be wrong – it’s just a question of how wrong! Once the peak period has passed, calculate your forecast error.

Here is an example:

If you are within 10%, pat yourselves on the back. If you are not, as in the example above, then it's an opportunity to learn why and update your forecasting method for greater accuracy in the future. 

Summary

Demand planning is a fundamental step in preventing your web site from crashing. Unless you can predict demand with a reasonable level of accuracy then how can you plan to prevent a crash?