There is a lot of confusion in the market about what a control tower actually means and offers to supply chain organizations. Rather than just looking at it from a technology perspective, supply chain technology leaders would be wise to consider its underlying capabilities.
Gartner defines a supply chain control tower as a concept that results in combining people, process, data, organization and technology. Control towers capture and use (close to) real-time operational data from across the business ecosystem to provide enhanced visibility and improve decision making.
“Supply chain control tower is not a stand-alone SCM application, but an integrated capability embedded in a broader SCM suite or tool. It could be an intelligent data platform providing use-case specific insights, predictions and suggestions”, says Christian Titze, VP Analyst at Gartner.
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How can supply chain technology leaders realize a control tower?
Establish a central hub as an integrated part of a broader SCM platform using these building blocks: people, process, data, organization and technology. The idea is to capture and use data to provide enhanced real-time visibility and in-depth analysis. This can enable better short- and midterm decision making aligned with strategic organizational objectives.
6 key technology capabilities for a supply chain control tower:
- Continuous intelligence: Capture data continuously and in real time (event stream processing or business activity monitoring).
- Advanced analytics: Leverage predictive and prescriptive analytics to move from being reactive to proactive.
- Impact analysis: Understand the impact of signals from the digital ecosystem to the company’s supply chain.
- Scenario modeling: Simulate different scenarios for providing a suitable smart response.
- Collaborative response: Connect and collaborate in the ecosystem (aka collaboration room).
- Artificial intelligence: Drive a higher degree of automation by artificial intelligence/machine learning.
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How to deploy a supply chain control tower
There are two major deployment options to consider:
- Buy. Going this route means embedding control tower capabilities as part of a broader SCM platform. It is mainly about domain-specific towers allowing visibility and control. These control towers support the framework of “see > understand > act > learn” and represent that horizontal layer well-integrated in the tool on top of other core SCM application functions.
- Build. This is about creating a data lake and applying business intelligence on top. Such towers predominantly serve visualization needs, with all being about “conversation with the data.” Lately, new vendor entrants are offering more sophisticated capabilities around data science to support analytics and provide some degree of data correlation, impact analysis and recommended next actions.
Learn more: Supply Chain Planning — Your Strategic Guide to What, Why and How
Possible challenges when establishing a supply chain control tower
Supply chain technology leaders primarily see control towers as extensively visual dashboards and, at times, fail to leverage them as analytics-driven, decision-support tools.
Many companies lack end-to-end visibility, process orchestration and aligned decision making.
Visibility is a necessary foundation and first step, but you will also need advanced deep analytics (predicting), providing scenario-based options for the next best action (prescriptive) and decision support to optimize the outcome.
Read more: Your Ultimate Guide to Data and Analytics
These are both business- and technology-related challenges when starting a control tower initiative:
- Lack of clarity on the span of control. Overcomplicating the span/scope of supply chain operations managed by a control tower can lead to unrealistic expectations about benefits.
- Resistance when breaking down functional silos for end-to-end visibility and control. Supply chain control towers are still functionally siloed in their setup and do not provide the anticipated end-to-end visibility, control and decision-making support. Data lakes are only a partial answer.
- Questions on actual data ownership. With many business partners providing data into the control tower, who owns the data? Who is allowed to see what data? Who evaluates the data? Who gets benefits out of insights? Who benchmarks the data?
- Required talent. Lack of clarity and/or required skills to work in a control tower environment.
- Ambivalence on build-versus-buy decision. Without a well-rounded understanding of what is required to design, implement, deploy and maintain a control tower, it is difficult to evaluate whether the control tower should be in-house (and there the options platform versus data lake), hybrid or outsourced.
- Inability to identify the right technology requirements. Investing a significant amount of time in reviewing and evaluating different technology platforms with multiple capabilities and functionality can result in analysis paralysis and the inability to make an investment decision.