Digital innovation across every node of the supply chain is occurring – and fast. Smart factories, smart warehouses and smart transportation are becoming a reality as manufacturers invest in technologies such as artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), robotics and more. Within manufacturing, we’re seeing machines, systems and devices become more connected and intelligent, driving significant changes in how companies sense and respond to market signals.
In our role as partners helping manufacturers on their digital journeys, we continue to see key trends emerge universally. First, our customers aspire to be a “connected enterprise,” where real-time demand signals from their retailers, ecommerce consumers and channel partners are continually evaluated and responded to with real-time responses from their warehouses, transportation fleets and factories. Additionally, our customers are beginning to learn from this gold mine of real-time data to automate business decisions, reducing errors and increasing productivity across a broad range of operations from ordering, expediting, pricing and others. Hence, supply chain digitalization is effectively occurring at the intersection of real-time visibility and intelligent automation, and it is becoming an important differentiator for manufacturers.
There are many factors – such as a company’s business model, industry, competitive framework, etc. – that companies should consider when evaluating which digital technologies will drive the most value within their organizations. Respondents of JDA’s Intelligent Manufacturing survey report that while plans for deploying digitalization technology vary, it’s clear that digitalization plays a part of most companies’ current or future supply chain strategies. One key element of advancing supply chain digitalization is cloud technology. In fact, 47 percent of respondents indicate that cloud-based applications are part of their current supply chain strategies, and 31 percent report that cloud-based applications will be part of their strategies in the next 2-3 years. Additionally, 42 percent say Software as a Service (SaaS) is part of their current supply chain strategies, and 33 percent indicate that it will be part of their supply chain strategies in the next 2-3 years.
Of the survey respondents who are working toward operating a fully integrated digital supply chain within the next 2-3 years (labeled here as “aspirational manufacturers”), 65 percent are on-track, reporting that supply chain digitalization is a major priority for their organization in 2018. Aspirational manufacturers reported a current investment in digital strategies and solutions, with 59 percent reporting investments in cloud-based applications and 58 percent citing investments in SaaS.
Harnessing the power of cloud to support cutting-edge innovation
As manufacturers migrate their supply chains to the intersection of real-time networks and intelligent automation, they are faced with several key technology choices. The key characteristic of a real-time network is the ability to consume digital signals continuously from every node of the supply chain. This requires harnessing the latest IoT capabilities to understand the latest location of inventory, including last-mile visibility for inventory in motion such as on truckloads, as well as last-inch visibility for inventory at rest in warehouses, stores or factories. Additional information streaming in – such as temperature, humidity, noise – further helps inform the supply chain about not just the presence of inventory but also its quality. Continuously learning from this data and making intelligent choices requires manufacturers to develop and deploy specialized algorithms and innovation with unprecedented speed.
Cloud technology is becoming a necessity for companies that want a faster path to cutting-edge innovation. To take advantage of AI- and ML-driven cognitive solutions, companies need extensible cloud capacity that can be increased or decreased based on the processing power needed to compute massive petabytes of big data. There is no longer a need for companies to invest in infrastructure to support peak capacity year-round, which is why AI and ML applications are naturally more inclined toward a SaaS or cloud deployment.
It is no surprise that over the past several years, the industry has shifted toward cloud-based and SaaS applications. There is certainly an economical advantage to this approach, as it provides a lower total cost of ownership compared to on-premise deployments. Other factors like compliance requirements for new data governance laws and the need for increased security are also accelerating the adoption of cloud and SaaS technology.
At JDA, we’ve partnered with Microsoft to build our cognitive, SaaS solutions on the market-leading Microsoft Azure platform. One of the many reasons JDA selected Microsoft Azure as its cloud partner is because of its comprehensive range of cloud services. Microsoft Azure’s scalability, extensibility, security protocols and widespread coverage in terms of data centers and regions is unmatched in the industry.
The combined power of Microsoft Azure’s cloud services, our cognitive SaaS solutions and Luminate platform, and our partnership with MuleSoft to increase connectivity is moving us toward our vision of the Autonomous Supply Chain™. This game-changing approach enables a real-time network of systems, cognitive algorithms and data sets that can be continuously updated with data from partners, IoT sensors and big-data providers of weather, loyalty information, news, events and more – further fueling manufacturers’ digital supply chain transformations.