Transform the supply chain with unified data management

Were you unable to attend Transform 2022? Check out all the summits in our on-demand library now! Look here.

Many organizations lack the technology and architecture required to automate decision making and create intelligent responses across the supply chain, as demonstrated by the supply chain disruptions of recent years. However, these critical breakdowns can no longer be blamed solely on the COVID-19 pandemic. Rather, they can be blamed for companies’ slow adoption of automated supply chain decisions, which has resulted in inventory backlogs, price increases, shortages and more. Further contributing to the backlog is still single sourcing to one region instead of utilizing distributed regional capacities. These factors have added to the complexity of the systems and the disadvantages of lack of automation and the pandemic brought these existing critical breakdowns into stark relief.

This brings us to today and how this inability to effectively manage data streams is proving devastating to many companies. In a Gartner study of more than 400 organizations, 84% of supply chain managers reported that they could better serve their customers with data-driven insights. Just as many respondents said they needed more accurate data to be able to predict future conditions and make better decisions.

The challenge here is that companies manage their supply chains with a variety of disparate and disconnected tools and data sets. Instead of residing in a centralized location, critical information can be spread across the supply chain, held in functional silos and tied to individual technology solutions and operations teams, limiting transparency and optimization.

Ultimately, this affects the overall results of digitizing the supply chain. Human analysts, as well as advanced technology engines, may have difficulty accessing data that is relevant, current, and reliable. Data can be segregated across functions, resulting in a lack of end-to-end transparency. Lag times can have a significant impact on an organization’s ability to detect and respond immediately to disruptions or new information.


MetaBeat 2022

MetaBeat will bring together thought leaders to provide guidance on how metaverse technology will transform the way all industries communicate and do business on October 4th in San Francisco, CA.

Register here

End-to-end connectivity across the supply chain

The disruptions in supply and demand in 2020 and 2021 clearly demonstrated the need for digital transformation and end-to-end visibility and orchestration. And the availability of new digital capabilities such as artificial intelligence (AI), machine learning (ML), data science and advanced analytics has been nothing short of a game-changer in connecting the world’s supply chains. To keep pace with manufacturers’ and retailers’ increases in demand, supply chains must evolve to become real-time adaptive ecosystems.

When an exception or disruptive event occurs anywhere in the ecosystem, it can be recognized and addressed autonomously in a synchronized and collaborative manner. Regardless of how geographically distributed the value network is and how many suppliers it includes, today even the most complex global supply chain can be connected digitally via intelligent solutions in near real time.

The advanced technology that enables near real-time monitoring and communication relies on data for success. Across the value chain, each supplier contributes digitally with information on costs, timing, stock levels, availability and other key figures – and provides the opportunity for key partners to receive and provide feedback in real time, thereby gaining important insight into the development of demand.

But that’s just the beginning. Today’s forecasting, business planning, and execution optimization engines also depend on vast amounts of third-party data—including news, weather, and even social media—that impact end-to-end supply chain performance. Enabled by new, advanced capabilities such as AI, ML and predictive analytics, these new cognitive engines are incredibly powerful and accurate at translating vast amounts of raw data into strategic, actionable recommendations, often autonomously, allowing supply chain teams to shift their focus from firefighting to strategic improvements.

Leverage partners to build a supply chain ecosystem

Digital platforms can bring together these disparate data sources and functions to enable faster decisions and greater collaboration. Unified data management makes companies more agile and flexible when it comes to responding to changes. Through a best-of-breed network of partners and internal developers, companies can share data and ideas across teams, enabling real-time response and cognitive planning across stakeholders. However, to deliver a synchronized response across the global supply network, traditional walls must be overcome with advanced technology that supports real-time end-to-end orchestration.

Breaking down these traditional walls requires a partner- and developer-friendly platform, fully integrated across the network, to help democratize data access, streamline data management, and encourage self-learning and continuous improvement. Through a digital command center, information can be shared across the supply chain to generate cognitive insights, identify disruptions and opportunities, and recommend strategic actions. These partnerships can transform data into a competitive advantage by unifying the entire supply chain around a holistic, truly integrated technology ecosystem.

And as data is aggregated and made available to all stakeholders, businesses can make intelligent, strategic decisions based on a single set of real-time insights. The supply chain is a robust ecosystem fed by data, and it requires scalability, security, data integrity, real-time response and exceptional processing speeds. Think of the huge amounts of data from customers, partners and suppliers that are consumed by businesses. Millions of bits of information flood every network touchpoint. Without collaboration, users will find themselves bogged down by their disparate data-driven workflows, making decisions based on slow, incomplete and disconnected data.

To truly leverage this vast amount of data, companies should look for solutions that support self-learning. Democratized supply chains are not created overnight. They require all partners and functions to have equal access to data and optimization engines that consider all outcomes and priorities – ingesting data and making decisions faster than ever before. Such ecosystems result in supply chains that are strategic, functional and built to withstand today’s fluctuations and obstacles.

Jim Beveridge is Senior Director of Product Marketing at Blue Yonder

Data Decision Makers

Welcome to the VentureBeat community!

DataDecisionMakers is where experts, including the technical people involved in data work, can share data-related insights and innovation.

If you want to read about cutting-edge ideas and up-to-date information, best practices and the future of data and data technology, join us at DataDecisionMakers.

You may even consider contributing an article of your own!

Read more from DataDecisionMakers

Leave a Reply

Your email address will not be published.