Uwe Weiss is CEO of Blue Yonder, a leading provider of predictive analytics. He has more than 20 years of experience in the enterprise software sector and he is an expert in cloud computing and SaaS. Mr. Weiss was the co-founder and CEO of various successful start-ups and growth companies, most recently of Crossgate AG. In this guest post, Weiss discusses how smart services and automated decisions hold considerable potential for enterprises.
The digital economy increasingly is penetrating the “classic” industry sectors such as production, machine and equipment manufacturing. A prerequisite for this penetration is that production environments and objects be Internet-enabled, equipped with sensors and connected with one another in a network. In this way, machines and facilities provide information about their own condition and any work steps that are needed. Objects such as bottles in a bottling plant can also provide this information. According to Henning Kagermann, President of ACATECH (National Academy of Science and Engineering) and former CEO of SAP, this information represents “digital service building-blocks.”
Smart services increase margins in after-sales
What do these services look like and how enterprises benefit from them? Manufacturers of capital goods are increasingly discovering after-sales as an attractive and margin-rich business space. What was earlier a necessary part of common sales practice is today often its own profitable organizational unit — and the smarter it is, the more profitable. If machines, facilities, vehicles and other high-value consumption goods report their condition using sensors, then replacement part demand can be accurately and automatically forecast using predictive analytics. Enterprises avoid delivery bottlenecks in after-sales by means of accurate sales and demand planning, and at the same time reduce the storage capacities that have to be used. Predictive Analytics can automate mass decision-making. In materials planning, that has a big impact on revenue.
Additional smart services are used for machine control and machine monitoring. By continually analyzing machine data and facility data, performance problems and defective parts can be recognized early. Short-term and expensive use of service personnel and machine downtimes are avoided. Resource use can be anticipated and planned, with the right replacement parts being made available. That increases productivity and efficiency in enterprises.
Smart services: for industrial enterprises, there is no alternative
German industry, which leads the world, should know by now that there is a danger connected with this great possibility: the risk of missing the right moment to do something or the best opportunity. This is particularly true in competition with American companies and aggressive startups. “The relationship among original manufacturers, suppliers, and service providers will be redefined in the coming years,” says Henning Kagermann. Industrial enterprises that operate on the “business as usual” model could quickly become dependent on a new generation of digital service providers.
We are here to provide enterprises with innovative business models so that they can secure and expand their market share. But as software providers, we know that Predictive Analytics applications that can be implemented easily are only one side of the equation. The transition to a smart service world can only be successful if each individual enterprise and each individual employee buys into it. In the “Smart Service World” operating manual, it states: “Enterprises in future need to be ready to cooperate increasingly across industries and sectors and to decisively and intentionally expand and adapt their product- and services portfolio.” Experience from many projects in various industry sectors has taught us this: A change in consciousness, to thinking in terms of digital value-added interconnections pays off. Costs sink, sales increase, and business models fit for the future are created.
Blue Yonder, as a provider of forecast solutions, is showing how data science can be profitably used, every day. Blue Yonder, based in Karlsruhe, Germany, has a goal of democratizing big data. This means that business users at companies should be able to work with predictive analytics solutions using simple user interfaces.