Webinar recap: Uses and best practices for end-customer demand

Date Posted: December 05, 2018

In October, Alloy was a featured guest on a webinar hosted by APICS Atlanta and Supply Chain Now Radio, “The Power of Connecting to End-Customer Demand.” Through the presentation and Q&A, we defined downstream demand, why it’s important and how brands can efficiently use this data to their advantage. You can find the full recording of the webinar here, but here’s a quick summary of the key points

Shipments, orders, point of sale, ecommerce, social sentiment, pre-orders
What is downstream demand?

There are many different “levels” of demand that you can consider, from wholesale orders to POS data to future predictors like preorders. We believe demand should be anchored by the end consumer. At a minimum, brands should analyze sell-out across in-store and online purchases. Resellers/retailers share this data directly and it can provide a wealth of insights for supply chain and sales teams.

An added nuance is ensuring your downstream demand data is unconstrained and granular, what we call true demand. Unconstrained demand paints a picture of how many products you’d sell if you never ran out-of-stock in store. Granularity refers to the specificity of the data that you receive, down to the individual SKU and store level. This granularity is key to understanding root causes of issues and how performance varies across products and geographies.

For example, if you only know you have an aggregate out-of-stock rate of 5%, that doesn’t give you a clear sense of the scope of the problem or very much information to help solve it. All of those out-of-stocks could be occurring in your highest-performing stores and seriously impacting your revenue! That’s why it’s key to drill down past the aggregates and averages and look at a more granular dataset. It is the only way to pinpoint the root cause, size the problem and address it.


Recovering lost sales from out-of-stocks is one key benefit of using true demand data. It also helps optimize inventory management and reduce costs, enabling companies to reduce safety stock while improving on shelf availability. Customer service KPIs, such as OTIF deliveries, perfect order performance and cycle times all improve thanks to a better understanding of how products are moving through customer locations. As a result, companies develop stronger, closer relationships with their customers and improve demand forecasting and planning.

These are just a few of the advantages of using downstream demand, but they give a good idea of how it can improve revenues and efficiency. So with all of these benefits, why don’t more organizations rely on downstream demand for their operations?


The reality is, there are real barriers to integrating downstream demand. Taking advantage of POS data requires a clear plan of action to overcome each one.

  • Access. The first obstacle many teams have to overcome is access—simply getting the data out of silos and ready for use
  • Analysis. The second challenge is the analysis itself. Granular data is voluminous, so successfully wrangling it to derive valuable insights can be more complex than a pre-written Excel formula.
  • Action. The last barrier brands must overcome is actioning, or aligning the team and processes to act on the data-driven insights while the opportunity still exists.
Best practices

From our experience working with manufacturers to overcome these challenges, we have identified some consistent best practices that enable companies to efficiently use demand data and realize benefits like the ones outlined above.

1. Automate data preparation. Many data scientists spend a large portion of their time on simple data cleaning tasks, instead of on extracting insights from the information. The more of this preparation you can automate, the more time your team will have to focus on higher-level objectives.

2. Make insights tailored and actionable. Different people within your company have different goals and metrics that they care about, so make sure each audience can get tailored reports and analysis that maximize the value they get out of them.

3. Move as close to continuous forecasting as possible. Narrowing the gap between changes in consumer demand and updates to your forecast can significantly improve forecast accuracy.

4. Make forecasts actionable. Along the lines of #2, show different team members the level of forecasting detail that applies to their needs. Some roles might be interested in forecast values for specific accounts, while others are much more interested in what factors are driving demand or the implications in terms of production needs.

5. Manage by exception: Implement a smart system that allows you to focus on the biggest opportunities first. Otherwise, it’s easy to become overwhelmed with the volume and granularity of insights.

Downstream demand is a powerful driver for sales and supply chain management, but can also be more complex data than you’re used to working with. With the insights and tips shared in this webinar, we hope you  feel empowered to begin working with true demand and reaping its benefits.

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