The New JDA Flowcasting Solution

Last Tuesday it was announced that the CEO of JDA had been replaced with an interim CEO. Perhaps because I tend to be product focused, I find the most significant recent announcement the news that JDA had productized a Flowcasting solution. Previously, RedPrairie, a firm acquired by JDA, had a joint partnership to provide consulting services in this area.

We’ve gone through several iterations of how to effectively balance supply and demand in the retail/consumer goods supply chain. Flowcasting is currently the most advanced form of the next wave forward – demand driven supply chain management.

Historically, a consumer goods firm did forecasting based upon historical shipments. Anyone with exposure to supply chain management knows this did not work well; there were significant bullwhip effects.

Various forms of retail/consumer goods forecast collaboration have emerged to help cure the disease. The most prominent was Collaborative Planning, Forecasting & Replenishment (CPFR). To oversimplify a bit, in this initiative, the retailers and manufacturers compared their own forecasts and worked to come up with a consensus forecast. These collaborative forecast initiatives had positive impacts on inventories and service levels. But store, shelf-level out-of-stocks (OOS), the most critical KPI in this supply chain, barely changed.

The next wave forward is demand driven supply chain management. In this wave, consumer goods firms leverage a variety of different types of downstream data, including POS data provided by the retailers, to power more efficient supply chains. Some suppliers are using the POS data to improve short term forecasting, particularly promotion forecasting, and to highlight places where there are breakdowns in getting promoted products onto the shelves. This can blow back and change the shipment plan between the manufacturers’ and retailers’ distribution centers (DCs). But I have not seen the impacts propagate further upstream than that.

The JDA Flowcasting solution changes this. It is an interconnected retail/CPG supply chain model that starts with the sell through forecast and propagates backwards. The model understands store and retail DC reordering policies, as well as CPG manufacturing and delivery lead times. This single model of the business across the entire supply chain is shared by retailers and manufacturers. Because this is a cloud-based solution, the only logical architecture for deep collaboration, it allows for an executable plan between the manufacturer and retailer who are working off of a common point of view of what’s being sold at the store.

This is a multi-enterprise planning solution. Stop and think about that! For years, leading critics of SCM technology have pointed out that manufacturers have had one set of tools that aimed to optimize their supply chain while downstream customers have used a different set of solutions to independently optimize their supply chain. Yet it has long been a central tenant of supply chain management that optimizing links in a supply chain was not the same as optimizing the end to end supply chain. Now there is a multi-enterprise planning solution built on a unitary model.

The JDA solution supports:

  • Scenario creation and comparison, particularly scenarios that support a proactive restructuring of the supply chain. For example, would the shelf level OOS numbers stay the same while the manufacturers supply chain costs dropped, if the retailer ordered by pallet layers rather than by cases?
  • Root cause analysis which identifies shelf level issues and assigns root-causes that can include poor perpetual inventory performance in the store, systemic over or under forecasting, and poor replenishment occurring anywhere in the joint supply chain.
  • Supply Chain Analytics that proactively mitigate future overstocks and out-of-stocks.

The JDA Flowcasting team briefed the ARC supply chain team and showed us some screen shots from their new solution. The analytics and root cause features are impressive. But the large numbers of new scenarios that can be run is what really grabbed me. I, for example, have never seen a supply chain solution that can show how changing dimensions of the shelf facings ripples back and impacts the manufacturing supply chain.

JDA’s poster child for this solution is Kraft. The JDA team shared some really good results that Kraft had achieved. But I prefer not to hear these kinds of things second hand.

Fortunately, at the recent JDA user conference, Aldo Sanerelli spoke. Aldo is the Director of Logistics and Distribution at Sigma Alimentos. Sigma Alimentos is a leading food company with a direct store deliveries business model. The company is headquartered in Mexico. They are still early in this process, but their goal is to have consumption forecasts drive time phased capacity planning across transportation, warehousing, and production. They have already seen improvements in days on hand inventory, fill rates, in-stock performance, and thus ultimately the sales they have achieved. According to Aldo, “this is not a supply chain solution, it is a business solution.”


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