The Supply chain control tower is defined as:

A supply chain control tower is traditionally defined as a connected, personalized dashboard of data, key business metrics, and events across the supply chain.

A supply chain control tower enables organizations to more fully understand, prioritize and resolve critical issues in real-time.
Supply chain executives are under enormous pressure to provide customers with what they need — when and where they need it — while also optimizing supply operations and achieving cost-saving goals. This is especially challenging in times of unpredictable yet inevitable vulnerabilities and disruptions.

A smarter control tower should provide end-to-end visibility across the supply chain — particularly into unforeseen external events. It should leverage advanced technologies, such as AI with machine learning, to help you break down data silos, reduce or eliminate manual processes, and get real-time actionable insights.

A smarter control tower will enable collaboration across teams and trading associates and preserve organizational knowledge to improve and accelerate decision-making and outcomes. Ultimately, this helps you better predict disruptions, improve resiliency, manage exceptions and respond to unplanned events.

Key capabilities and benefits of supply chain control towers

Real-time, end-to-end visibility
Establish end-to-end visibility across your supply chain with a control tower that correlates data across siloed systems with external event information to provide actionable insights into potential disruptions — all in personalized dashboards — so you can manage the exceptions.

Predictive and prescription decision support
Better predict disruptions and improve resiliency with smart alerts and real-time actionable insights to help you understand the upstream and downstream impact of events on customers and prioritize your response.

Collaborative information sharing
Better collaborate on and manage exceptions across the entire supply chain with AI-powered resolutions rooms and digital playbooks, combined with supply chain applications, that help you quickly respond to unplanned events and hone execution to drive KPI performance.

Supply chain control towers for industries

Healthcare
Hospitals lose as much as 10% of inventory value due to lost or misplaced items. Protect inventory investments, increase efficiencies and improve quality of care by ensuring you have the critical lifesaving equipment and supplies you need at the right place and time.

Grocery
Manage overwhelming demand and ensure the availability of goods by monitoring and mitigating an ever-increasing range of potential disruptions. Keep shelves stocked with expanded inventory visibility to see beyond warehouses, including in-store locations and supplies in transit.

Industrial
Meet service contract SLAs while minimizing the amount of inventory you hold. Get visibility into service parts by SKU and stocking locations across ERP and other systems to help ensure critical parts are in stock to meet customer expectations.

Considerations when deploying a supply chain control tower

Data Quality
An effective supply chain control tower depends on quality data, which directly influences the level of visibility that can be achieved, as well as the output of insights.

Practical and actionable outputs
For data to be useful, it must first be usable. Practical and actionable outputs ensure data is understandable and applicable to common activities and problems.

Mindset change management
Deploying a control tower typically requires much planning and significant changes in operation, and a concerted effort to get away from existing mindsets.

https://www.ibm.com/topics/control-towers

01 Process Discovery and Mining

Get to know the invisible process in a fast and simple way

• Organizations are primarily interested in an improved “to be/ new” process, so often they have little interest in exploring “as is,” or how the process is currently performed.
• Understanding the current process is critical to know whether it is worth investing in improvements, where performance problems exist, and how much variation there is in the process across the organization.
• Process mining can help in understanding the current situation in a fast and affordable manner.

02 RPA Robotic “Processes Automation”

What is RPA?

RPA stands for Robotic Process Automation and refers to software robots that transact in any application or website. typically, in the same way, a human would automate complex rule-based work.

RPA Tool Features 

Web Automation: This Feature allows you to automate web interactions by identifying web elements and accurately manipulating them.

GUI Automation: This is the process of simulating mouse and keyboard actions on windows and controls.

Screen Scraping: This is the process of extracting text from website and win32 apps. 

Microsoft Automation: Automating Microsoft Office applications may be the most used feature of any RPA tool.

CITRIX Automation: Surface/CITRIX Automation is used because you can not access the elements that make up virtual machines

RPA Global Market Size

RPA Benefits

1. Cost Savings
   • RPA can create cost savings of approximately 35-65% when the bot replaces a business process performed by an FTE.
2. Rapid Return on Investment
   • The average RPA implementation time is typical of 3 months, and the time for ROI is between 6 to 9 months.
3. Free up Staff
   • Automotive repetitive and time-consuming processes free up your staff to make a more value-add contribution
4. Improved Customer Service Experience
   • RPA can improve quality by reaching an accuracy rate of 100%.
5. Reduce Paper/Waste
   • RPA forces digitalization as it requires that companies have the data and files being manipulated by software robots in a digital form.
     
     

RPA Software Vendors

Robotic Processes Assessment

03 Real-Time Dashboards "From Descriptive to Prescriptive"

04 Data Mining and Machine Learning

1. Credit ratings/targeted marketing: Given a database of 100,000 names, which persons are the least likely to default on their credit cards?
   • Identify likely responders to sales promotions
2. Fraud detection
   • which types of transactions are likely to be fraudulent, given the demographics and transactional history of a particular customer?
3. Customer relationship management:
   • Which of my customers are likely to be the most loyal, and which are most likely to leave for a competitor?

Data Mining helps extract such information