Supply Chain Control Tower (SCCT — Part 1 of 3)
What is a Supply Chain Control Tower (SCCT)?
A Supply Chain Control Tower (SCCT), as defined by Dhaneshwar, Singh, and Khan (2018) is…
a. A cross-functional team (it’s actually a group of people)
b. Their job is to
- analyze and
- take actions to improve the Supply Chain
c. Tailored to an organization’s specific needs.
SCCT is NOT…
a. It is NOT a product or software provided by a vendor
b. It is NOT here to replace Enterprise Resource Planning (ERP) (Wikipedia, 2019b) or Materials Requirement Planning (MRP) (Wikipedia, 2019c) systems
c. It is NOT a “one-size-fits-all” solution
d. It is NOT a pure “end-to-end” visibility tool.
Figure 1 shows the layers/components of a Supply Chain Control Tower.
There are three layers:
1. 1st Layer — Early 360 Degree Visibility
2. 2nd Layer — Cognitive Computing Engine
3. 3rd Layer — Collaborative Responsive Mechanism
1st Layer — Early 360 Degree Visibility
- To provide near-real-time visibility to relevant events
1a. Data Feeds
- First step is to gather data inputs.
- But what sort of data is required?
- Basically, any data that is helpful in achieving the organization’s Key Performance Indicators (KPIs) are collected.
1b. Data Processing
- After data is collected and inputted, the organization’s KPIs are distilled into Data Elements (DE) to reveal which Events should be tracked.
-  The process of separating the components or substances
-  Data Elements (DE) are any unit of data defined for processing; for example, ACCOUNT NUMBER, NAME, ADDRESS and CITY. (Magazine, 2019)
- DEs and Events are then mapped to Enterprise Systems (ES) to house the information.
1c. Data Presentation (Dashboard)
- Figure 3 shows a SCCT Dashboard.
- This dashboard presents the information that was collated at Step 1b.
- It helps the SCCT team to have an easy-to-understand visual of the Supply Chain.
1d. Data Alerts
- The SCCT Dashboard alerts the team when an important event is about to occur
- These alerts can be customized by the team, and they can manage exceptions through the Dashboard.
2nd Layer — Cognitive Computing Engine
- Deep analysis of information to assist decision-making
Outcome of Deep Analytics:
2a. What is happening now — Quantifying Impact
- The SCCT Dashboard will quantify the impact of events that has recently occurred.
- That is, KPIs such as Service Level, Fill Rates and Revenue will be shown on the screen.
2b. What is going to happen — Scenario Analysis
- The SCCT Dashboard will quantify the impact of events about to occur.
- Then, what-if Scenario Analysis will be conducted automatically by the Dashboard.
- Different solution options will be generated for the SCCT team to consider.
3rd Layer — Collaborative Responsive Mechanism
- To foster collaboration across multiple functional areas both within and outside the organization.
3a. Internal and External Collaboration
- To foster collaboration with external stakeholders, feedback and notifications could be sent out to everyone.
- For example, if a delivery is delayed then notifications could be sent out to all parties: buyers, logistics managers and transportation planners.
3b. Tracking and Monitoring
- To enhance tracking and monitoring, the notifications from the SCCT Dashboard can be integrated with the organization’s enterprise system to automate response mechanisms — but only if initiated by the SCCT team.
- Dhaneshwar, G., Singh, N., & Khan, A. A. (2018). How a Well Executed Supply Chain Control Tower Can Accelerate Digital’s Business Benefits: Cognizant.
- Magazine, P. (2019). Definition of Data Element. from https://www.pcmag.com/encyclopedia/term/40771/data-element
- Wikipedia. (2019a). Cognizant. from https://en.wikipedia.org/wiki/Cognizant
- Wikipedia. (2019b). Enterprise resource planning (ERP). from https://en.wikipedia.org/wiki/Enterprise_resource_planning
- Wikipedia. (2019c). Material Requirements Planning (MRP). from https://en.wikipedia.org/wiki/Material_requirements_planning
About Dr. Alvin Ang
Dr. Alvin Ang earned his Ph.D., Masters and Bachelor degrees from NTU, Singapore.
Previously he was a Principal Consultant (Data Science) as well as an Assistant Professor. He was also 8 years SUSS adjunct lecturer. His focus and interest is in the area of real world data science. Though an operational researcher by study, his passion for practical applications outweigh his academic background
He is a scientist, entrepreneur, as well as a personal/business advisor. More about him at www.AlvinAng.sg.