Digital Supply Chain: Three Steps For Moving Forward Today

Hans Thalbauer

My previous blog looked at how a digital supply chain can help companies survive and thrive in a volatile world. But the question remains: How do you move forward? If your organization is looking for ways to transform its supply chain into a digital supply chain, consider the following.

A digital supply chain is a connected supply chain

Total supply chain visibility requires total supply chain connectedness. Critically, this connectedness needs to extend across not only supply chain partners but, as we design and manufacture smarter assets, “things” as well.

Regarding partners, it is important to be comprehensive. It is estimated that the typical organization is digitally connected to only 10% of its suppliers – the so-called key suppliers. This leaves 90% of suppliers in a “black box” where processes are manual and visibility is limited at best.

Suppliers, of course, are only part of the picture. A connected supply chain that achieves total visibility brings into focus all participants in the end-to-end supply chain – including logistics service providers, equipment manufacturers, design and research teams, and manufacturing partners.

More and more, to increase visibility and control, we need to connect to all of the assets operating within the network. But here again, the typical organization is, perhaps, only 5%–10% connected – which leaves on the table tremendous opportunity for improvement.

Connected assets can include equipment on the shop floor, trucks out on the road, robots in the warehouse, and much more. With embedded sensors that feed out data regarding KPIs such as asset health, location, and temperature, organizations can achieve critical visibility into operational data.

When combined with data from the full range of supply chain partners in the network, organizations can achieve total, real-time supply chain visibility. The result is the ability to more effectively minimize inventory levels, improve responsiveness, speed execution, and optimize supply chain spend even in the face of increased volatility and uncertainty.

A digital supply chain is predictive supply chain

Insights into this new data can be used to not only determine what happened in the past but also to predict what will happen in the future. Today, organizations are exploring patterns in their supply data – enabling better forecasts and the ability to predict outcomes.

This is a big step forward for supply chain managers because it means a move away from reactive, alert-driven processes where the supply chain is always attempting to catch up to real-time circumstances. Instead, organizations are using technologies such as predictive analytics and machine learning to see what’s coming – and to take steps to proactively drive outcomes that keep customers satisfied.

Just as Netflix – with its celebrated recommendation engine – can predict what customers will want to watch next, supply chain teams can predict what customers will want to buy next. This moves the organization from “forecasting” – traditionally a time-consuming, cumbersome, spreadsheet-based chore that takes place as the first part of a linear business planning process – to demand sensing. Now the planning process is much more dynamic. With signals constantly coming in from the analysis of trends, customer behavior, social media sentiment, and more, organizations can understand what customers want faster – and respond faster as well.

Predictive capabilities can be deployed to optimize a wide range of processes. Some of these include:

  • Predictive maintenance – where organizations monitor and analyze sensor data from equipment to predict machine failure and take proactive measures to ensure uptime and availability
  • Predictive quality management – where data on asset operations, warranty claims, quality tests, and even social media sentiment can be combined and analyzed to detect and head off potential quality issues
  • Predictive logistics – where data on promised delivery times and current weather and traffic conditions can be mixed with connected vehicle data and real-time track-and-trace insight to dynamically route products and materials and ensure on-time delivery
  • Predictive demand management – where data from point of sales systems, customer sentiment, and more can be mixed with third-party market trend analysis to see what customers will want next

A digital supply chain is an intelligent supply chain

Finally, a digital supply chain is also an intelligent supply chain. What does this intelligence mean? It means automation.

Automation can exist at many levels: manufacturing equipment on the shop floor, robots moving goods within the warehouse, drones flying overhead to do inventory counts (or door-to-door delivery).

One critical area ripe for automation is the ability to leverage real-time information to drive demand-driven material requirements planning (DDMRP) processes, which enable relevant material and information flow driven by actual demand. With DDMRP, organizations can identify strategic inventory positioning to determine where the strategic “decoupling points” are placed across the supply chain. You can then dampen the effect of demand and supply variation on the supply chain by calculating dynamic inventory buffers and assigning and managing those buffers at the decoupling points. Replenishment can then be driven based on actual demand.

A major goal of leveraging this type of intelligence is to create a “touchless” or “self-correcting” supply chain, where organizations have the technology, processes, and automation in place to be far more responsive, efficient, and effective. Then, supply chain experts have more time and energy to devote to the higher-level, more strategic issues and tasks that help deliver truly better customer experiences.

Integration from design to operation

All of this, of course, requires integration across critical phases including design, plan, manufacture, delivery, and operation. Fortunately, this integration doesn’t require wholesale organizational restructuring to break down silos. Rather, data flows should be designed to bridge these silos – something certainly achievable with today’s connectedness and intelligent technologies.

A new product can be designed with a better understanding of the true demand for the product – as well as an understanding of the associated manufacturing, delivery, and operational challenges required to execute. If circumstances change somewhere along the way – and surely they will – the self-correcting digital supply chain has the adaptiveness to accommodate these changes without sleepless nights for supply chain experts or delays for customers.

A digital supply chain, then, is one that is connected, predictive, and intelligent. Such a supply chain can go a long way toward helping organizations thrive in a digital economy of growing complexity where customers always demand more.

For more information on how to move forward with digital supply chain capabilities, download the IDC report “Leveraging Your Intelligent Digital Supply Chain to find out how an end-to-end digital supply chain – from design and planning to manufacture, logistics, and operations – can help your supply chain be more connected, predictive, and intelligent.


Hans Thalbauer

About Hans Thalbauer

Hans Thalbauer is globally responsible for solution management and the go-to-market functions for SAP digital supply chain solutions and the SAP Leonardo portfolio of Internet of Things solutions. In this role, he is engaged in creative dialogues with businesses and operations worldwide, addressing customer needs and introducing innovative business processes, including the vision of creating a live business environment for everyone working in operations. Hans has more than 17 years with SAP and is based out of Palo Alto, CA, USA. He has held positions in development, product and solution management, and the go-to-market organization. Hans holds a degree in Business Information Systems from the University Vienna, Austria.