Despite the focus on innovation, true ground breaking innovations are rare. With Supplier InfoNet, SAP seems poised to shake supply chain management to its foundation. I recently had the opportunity to see a demo of Supplier InfoNet and speak to Vineet Seth, Vice President Product Management & Marketing at Global Business Incubator in Palo Alto, California.
In 2008 SAP set up a new organization to better capitalize on new market opportunities and decisively respond to competitive threats by incubating new initiatives. The primary goal of the organization is to identify and accelerate the commercialization of material business opportunities adjacent to SAP's core business. According to Vineet Seth, they are not only engaged in research, but also in developing disruptive innovations. One of the products that this has yielded is SAP Supplier Infonet, a SaaS solution aimed at controlling the risks in the supply chain by monitoring supplier performance from different angles.
The product is based on aggregating supplier performance data from different sources. The main source of information is from customers’ ERP systems regardless of whether the system is SAP or another provider. These customers agree to deliver supplier performance data (e.g. on time deliver, defective parts per million, average lead time, etc.) from their system to Supplier InfoNet. In return for the data, all customers have access to an anonymous version of the collected data. It wouldn’t be an exaggeration to call this type of gathering and sharing of data revolutionary, but there is more to it. The system also utilizes information from other sources such as 3rd party content providers, news sites, blogs etc. These data sources are screened by SAP, using advanced software, to determine relevancy, normalize and consolidate it and to offer it subsequently to their customers. This leads to a value proposition consisting of three elements.
First, the system provides a dashboard enabling the user to check how a supplier performs against relevant KPI’s and how that relates to the performance of that same supplier for other customers in the network. Second, the system can deliver qualified predictions about developments to be expected based on the trends in KPI scores and external data sources. An example of such a prediction could be that there is a 75% chance that the delivery time of a supplier will advance from 21 to 45 days in the next three months. The predictions are stated with grounds, for instance the closure of a production facility, a sharp spike in the demand for raw materials or any other reason. Thirdly the solution allows customers to look deeper into the supply chain. A customer is not only able to follow his own suppliers, but also his suppliers’ suppliers and even further down the chain (multi-tier).
View sub-tier suppliers for potential alerts/risks
A demo provided by Mr. Vineet Seth clarifies the options that the new product provides. Similar to social networking sites like Twitter and LinkedIn, a user can pick suppliers it wishes to follow. They can follow not only their own suppliers, but also the suppliers of their suppliers. The logic behind this is comparable with that of LinkedIn. It is possible to see in a network diagram that a supplier is linked to other suppliers, even though the names of these suppliers are not visible. To see them, the users must ask for permission from their own supplier (tier 1). This tier 1 supplier can then decide which supplier he wants to make visible to his customer. Subsequently the user can configure which KPI’s are relevant and the thresholds that determine when an alert should be triggered if deviations occur. One user might want to follow the delivery time very precisely and expects an alert when the delivery time has been exceeded a couple of hours while another only wishes to receive such an alert after exceeding the confirmed date by a day. By defining multiple thresholds different alerts (green, yellow, red) can be issued, depending on the gravity of the deviation.
Along with KPI alerts the system can also provide news alerts based on the unstructured news sources. A supplier might be involved in a law suit driven by a payment backlog, or can have a production facility shut down caused by a natural disaster, etc. These alerts will also be categorized red, yellow or green depending on the seriousness of the situation.
The dashboard offers the user opportunities to drill down into underlying information and analyze the causes and consequences more precisely. The performance of a supplier can be compared with the performance of that supplier at other customers. If this unveils significant deviations then this might be a reason to have a good chat with that supplier. A user can analyze the trend of a KPI and display the potential impact of that trend on spend and revenue.
Supplier InfoNet uses sophisticated machine learning techniques to predict performance
It is clear that SAP’s product goes beyond any other solution in this area so far. Supply chain managers seem to have gotten a tool that takes controlling supply chain risks to a new level. But how does this work in practice? Mr. Vineet Seth explains that this product requires a market by market approach. It is clear that the added value of the solution increases exponentially when multiple parties within a given industry sector are using it. SAP started with a pilot, in the U.S.A, aimed at the sectors Aerospace & Defense and Discrete manufacturing. The concept is especially valuable for parties in industrial manufacturing. Other sectors that they intend to serve are Automotive, High Tech, Oil & Gas and Telecom.
The power of this model is in the network. The growth curve of added value can be compared with that of social networks. The more parties participating, the more complete the picture gets and the more interesting the solution becomes. This means that there is a tipping-point per market. Currently the concept of a social business network seems to be being met with enthusiasm. No doubt it will inspire SAP to find other areas to apply this concept, both within supply chain management and other functional domains.