In this post, Part 1 of this series, we explore the essentials of deploying a live supply chain. In Part 2 we’ll look at why data scientists will be increasingly key to supply chain success.
Supply chain management is both science and art, and the supply chain operations of leading retailers, consumer products companies, and other manufacturers have been honed to the highest degree.
Unfortunately, the highest degree is no longer sufficient. That’s because established processes are labor-intensive, prone to error, and too slow in providing relevant information to the systems and people who need it. Meanwhile, market dynamics – your customers, your competitors, and the business conditions that affect you – take place in real time.
The solution is to replace your established but now inadequate operations with a live supply chain.
Running on real-time data
A live supply chain runs on real-time data, or at least “right-time” data. It connects employees, partners, customers, assets, and devices. It lets you make predictions and take actions at the speed of the marketplace.
Until very recently, we didn’t have the tools to make this possible. So we made sales forecasts based on sales history – which someone once said is like driving a car forward while looking in the rearview mirror.
But today we do have the tools, and that’s changing the competitive landscape. That is to say, your competitors are actively moving toward live supply chains. And that means you have to respond. Because your competitors aren’t just becoming more efficient. They’re actually reimagining your industry – like when Uber leveraged real-time data to upend ride services.
That real-time data, and where it comes from, will vary depending on your sector. It might come from commerce networks. It might come from social media. It might come from IoT sensors. It will cover everything from how your suppliers are sourcing raw materials at one end of your supply chain to how your products are being used by customers at the other.
The quantity of data is potentially enormous. Just think of the sensors on the average delivery vehicle. You can measure tire pressure and engine performance to predict when maintenance is needed. You can monitor driver behavior to make sure delivery is safe. You can track GPS coordinates to ensure delivery is on time. You can sense the temperature of the storage unit to make sure goods remain saleable. You can track the products themselves to be sure they haven’t been tampered with.
Changing business, changing business models
All this data needs to be fed into your business systems to drive design, planning, logistics, and other operational processes in sync with changing conditions. Some of that data is structured, but much of it is unstructured. It also comes in a vast array of types; that delivery truck probably has more than 100 sensors generating data in nearly as many formats. So you need a real-time system in which you can harmonize and analyze that data.
What does that entail? You have to store it at the lowest level of granularity. You need to parse it so that you’re managing only the data you need while ignoring the data you don’t need. And you must summarize the results at the right level for each job function or stakeholder. Without investing in sophisticated systems and advanced analytics to turn data into actionable information, your supply chain won’t come close to being live.
But the payoffs of that investment include better customer insights, more accurate supply visibility, improved demand forecasts, and real-time decisions that can lead to improved profitability.
They can also lead to competitive advantage through new business models. The example we often cite at SAP is our customer Kaeser Compressor, which transformed itself from a maker of industrial air compressors into a provider of compressed air. In the past, Kaeser sold air compressors that customers had to maintain themselves. Today, the company sells compressed air produced by air compressors that Kaeser maintains for them. Customers get the compressed air they need without the hassle of managing the equipment, while Kaeser achieves higher profit margins.
But Kaeser never could have achieved that transformation without real-time data. For its new business model to be profitable, Kaeser has to ensure that its air compressors operate with the highest uptime possible. That requires smart sensors that provide real-time visibility into operating conditions to allow for preventive maintenance.
In the same way, your supply chain need to capture, analyze, and act on real-timed data. It’s what will make your supply chain live. And what will help your new business models come to life.
Learn more about how running a live supply chain can help you thrive today and innovate for tomorrow at SAP.com.
This story originally appeared on EBN.