A demand planning application should generate value that goes beyond statistical forecasts. Sometimes this is easier said than done since it requires thoughtful system configuration and shared data insights.
With the IPO of cloud-based data warehousing company Snowflake, the value proposition of demand planning software has changed. In R, Google OR-Tools, or even Excel, it’s no longer difficult to generate a statistical forecast. However, creating an accurate forecast that incorporates relevant business inputs remains a challenge for many companies.
The real value of demand planning tools
Demand planning tools aren’t just for producing statistical forecasts. They’re also excellent tools for creating value-added workflows and rule sets. Workflows allow you to manage your forecasts using an exception-based approach, enabling you to focus on the areas that have the most significance based on automatically-generated metrics (e.g., percent error). You can create workflows and rule sets for new products, supersessions, or any other scenario that can be built into a monthly demand management cadence.
In addition to generating forecasts, demand planning tools such as those built by Vanguard, Logility, or Blue Yonder also allow for:
- Adjustments and overrides: Use historical data to sharpen and add insight to your business forecasts.
- Documentation: Set forecast checkpoints and track approvals by time, user, and reason, which aids in your compliance with the Sarbanes-Oxley Act (SOX).
- Dynamic forecast adjustment: Automatically apply a single adjustment across all linked forecasts.
- Forecast aggregation: View your forecast at a higher level in the hierarchy and make adjustments, which, in turn, apply to other items in the hierarchy.
Does your demand planning tool play well with others?
With today’s need for quick and easy access to advanced analytics, having the capability to export data to a cloud-based data warehouse such as Snowflake becomes even more important. With a data lake, Power BI or Tableau can become a one-stop business intelligence tool – a BI application that can pull in supply chain data plus information from other relevant sources such as SAP ERP or Salesforce. This makes it possible for your organization to work from the same data set regardless of the BI tool in use and promotes an agreement on, and the accomplishment of, a unified set of business objectives.
From a demand planning software standpoint, this means that your goal should be generating best-in-class forecasts and workflows, leaving analytics to the BI application. Your analytics can then provide insight into market intelligence from various sources and give context to cross-functional business needs. This approach enables an environment that facilitates the creation of a cross-functional consensus forecast.
Machine learning-enabled forecasting and planning platforms are the ideal tools to comprehensively manage your business. By configuring these systems to fit your supply chain’s needs, you can build an accurate demand picture and, as a result, create confidence in the output and secure management buy-in. As the new year approaches, don’t be left out in the cold with a poorly-configured suite of applications that doesn’t match your overriding business needs.
The right combination of tools and shared data assets makes for well-formed decisions. Reach out to us to see how Chainalytics can help you maximize the value of your supply chain planning systems. Our combination of top supply chain talent, proven methodologies, and exclusive market intelligence consistently puts our clients ahead of the curve.
Isaiah Liao is a manager in Chainalytics’ Integrated Demand & Supply Planning consulting practice. He leads implementations of supply chain software to improve business planning processes and managing supply chains at strategic and operational levels. Additionally, he is a deep technologist working with vendors to ensure product capabilities and roadmaps meet customers’ needs.
