Webinar Recap: Uses and Best Practices for End-Customer Demand

In October, Alloy was the featured guest on a webinar hosted by APICS Atlanta and Supply Chain Now Radio, “The Power of Connecting to End-Customer Demand.” We were honored to have the opportunity to speak and share some of our learnings with the APICS community!

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. Here’s a summary of the key points, and you can listen to the full recording of the webinar on demand.

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 and brands should be analyzing, at a minimum, sell-out across in-store and online purchases. This data is shared directly by resellers/retailers and 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 much 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, so you can identify root causes and address them when it makes sense.

Benefits

Recovering lost sales from out-of-stocks is one key benefit of using true demand data. It also helps with overall inventory management and cost reduction, enabling companies to reduce safety stock levels while improving on-shelf availability and ensuring products are in the right place, the first time. Customer service KPIs, such as on-time and in-full 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 increase the efficiency of their forecasting and planning processes.

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?

Challenges

The reality is that there are real barriers to adopting this type of data, although each can be overcome with the right plan of action.

  • 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 data, so being able to successfully wrangle information and derive valuable insight is more complex than a plug-and-play 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 companies of all sizes to overcome these challenges, we have come across some consistent best practices that enable both supply chain and sales teams to efficiently use and benefit from demand data.

  1. Automate data preparation: Many analysts and data scientists spend a large portion of their time on simple data cleaning and harmonization 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. Tailor insights by audience: Different people within your company have different goals and metrics that they care about, so make sure performance reports and analysis are aligned to each user’s function and level. No canned reports!
  3. Move as close to continuous forecasting as possible: Narrowing the gap between changes in consumer demand and updates to your forecast is one of the most beneficial things you can do to improve accuracy.
  4. Make forecasts actionable. Along the lines of #2, different team members use forecast outputs differently. Some roles are interested in forecast values for specific accounts, while others are much more interested in the overall implications for production. Share the right level of detail for each person to do their job.
  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 can be a powerful driver for improving performance, but can also be more complex data than many companies are used to working with. With the insights and tips provided in this webinar, you should feel empowered to begin working with true demand and reaping the corresponding benefits.