Gartner’s recent research report entitled Don’t Believe the Control Tower Hype — Buyer Beware (August 2018) questions vendor messages that are “loaded with marketing hype”. It describes a disconnect between promise and reality, limitations not addressed by vendors, and their opinion on how the control tower concept needs to evolve in the future.
For starters, Gartner’s says that current control tower offerings are misguided. Capabilities such as identifying near-term exceptions that need attention (like capacity shortage, inventory shortage, late shipments) don’t really belong in control towers, they say, but instead are foundational to modern supply chain management (SCM) solutions. “The idea of a visualization layer on a set of data, with some simple rules that are based on BI, no longer provides the anticipated values required.” They believe this capability should be “an inherent part of the overall SCM technology landscape” rather than “bolt on technology.”
So how does Gartner see control towers evolving into a meaningful addition to the supply chain landscape? They see something quite different that “is not a control tower solution in the current markets’ understanding of control towers.” Instead Gartner sees “solution towers” that not only visualize data, but control the process as well. An automated process is monitored by a cockpit (control room – see image above) that provides exceptions to the planner based on probability of occurrences – as typically found in Statistical Process Control (SPC).
They see a digital supply chain platform that should include “the consumption of extended digital signals (e.g., Internet of Things [IoT]) as well as the leveraging of planning capabilities at various levels of granularity and time horizons to continuously learn, generate insights and recommendations. Ideally, this would enable leveraging ‘cognitive intelligence’ to sense demand and adjust supply in real time.”
Beyond just visibility, Gartner sees an “information hub” at the heart of an end-to end (E2E) visibility network. The central hub “gathers, integrates, normalizes and cleanses data from a variety of sources. It then stores and distributes it in a consistent format and meaning for further utilization. The information hub then feeds into a supply chain model to simulate the impacts of these changes and measures them across the entire chain through appropriate logic and analytics” by employing application knowledge and value-added software capabilities such as automated demand modeling, probabilistic forecasting, and multi-echelon inventory optimization (MEIO).
This approach would enable E2E decision making of various levels of granularity and time horizons combined with intelligence and supported by capabilities such as:
- Root cause diagnosis of symptoms through a unified model of the supply chain
- Predictive analytics for predicting the impact of an event on the supply chain)
- Simulation through a unified model of the supply chain
- Collaboration across relevant stakeholders, within an organization and even across multiple enterprises
- Decision automation and learning via artificial intelligence and/or machine learning
These capabilities would ideally preserve the inherent supply chain uncertainty, providing ranges of requirements that allow the optimization of bottlenecks.
Gartner offers the following example of a truck carrying components that has an accident or is impacted by a natural disaster, causing a two-day delay. “A predefined rule can spot late arrival, recalculate the new, estimated time of arrival (ETA) and alert a planner to expedite another shipment to meet the promise date. But the question would be if that expedite and additional cost were really required? A stand-alone control tower would not know because it lacks application context. If those components are to replace safety stock and there is plenty on hand, then there would be no need to expedite, as it would impact margins negatively and provide no benefit. On the other hand, if those parts were critical and production would stop because of the delay, they should be expedited immediately.”
Ultimately Gartner also sees the opportunity for a “digital twin”, a model of the physical supply chain that is updated in near real time. “The digital supply chain twin then enables supply chain planning (SCP) and supply chain execution (SCE) functionalities to support decision making and process orchestration, with the degree of E2E scope increasing with maturity. The digital supply chain twin also drives collaboration with a single (and accurate) source of truth shared by all business partners in the ecosystem.”
Gartner recommends “challenging vendor messaging” and “looking beyond the marketing hype” to choose a supply chain “platform that can grow with you as your needs mature through the upper stages of supply chain maturity.”