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Evolution of the logistics control tower

Shriharsha Parampalli
3 Aug 2022

Implementing a best-in-class logistics control tower requires the design and deployment of a strong core operating model core and the right technology to drives real transformational benefits.

While the term “logistics control tower” has been in vogue for quite some time, the concept itself is often understood differently.

For some executives, it means a comprehensive set of dashboards displaying logistics metrics with data refreshes in real-time, enabling them to take data-driven decisions and prioritize actions. For others, it means a central team of employees crunching numbers, figuring out the bottle-necks in the supply chain, and taking coordinated and concerted action, while addressing priority customer requirements.

While none of these definitions are necessarily wrong, a comprehensive logistics control tower in its fullest sense has a wider scope encompassing people, processes, and a governance framework glued together by a technology layer.

Logistics control tower challenges

To get a comprehensive understanding of how the logistics control tower has a powerful value accretive effect, it’s worthwhile examining the pressing logistics imperatives that organizations need to address:

  • Elastic logistics – the ability to rapidly scale-up or shrink logistics capabilities and shift resources in the face of quickly changing demand and global factors will to a large extent determine the agility of the supply chain
  • Hyper-visibility – the need for extreme transparency in the fulfilment process right from order to delivery is percolating to the most mundane of product categories. This will no more be a differentiator as customers are starting to expect this as a given. Added to this is the need for traceability to be maintained for certain categories of products either as a customer value-add or as a regulatory requirement
  • Micro-services and hybrid cloud – the days of expensive standalone logistics software implementations on-prem are to put it mildly numbered. Micro-services architecture offering modularity and scalability riding on the back of dedicated or multi-tenancy cloud models with unprecedented data security is quickly becoming the norm. For the end customer, there’s a plethora of customized technology offerings that are cost-effective and tailored to the needs of the organization
  • Sustainability challenges – a good to have customer message today that caters to environmentally conscious communities is rapidly influencing the regulatory framework under which businesses operate. It’s not just about adhering to regulations but sustainability aspects, such as carbon footprint, reverse logistics and disposal make sound business sense and have a direct impact on brand reputation in communities they operate in.

Leveraging an adaptive control tower model

With this in mind, how do we meet these challenges head on? At Capgemini, we leverage an adaptive control tower model based on years of experience and numerous implementations for our clients across industry sectors.

Input flows into the much overlooked aspect of control tower operating model design through our Digital Global Enterprise Model (D-GEM) transformation platform and ESOAR framework (Eliminate, Standardize, Optimize, Automate, Robotize) depending on the repeatability, criticality, and business logic complexity of the process.

Once the building blocks of the basic control tower operating model design and governance has been set up, the chosen technology elements are operationalized to address critical needs such as extracting data at the optimal frequency, fusing together the information, and surfacing the actionable intelligence at the right time to create the desired business impact. This is where the sheer computing power and cost-effectiveness of cutting-edge technology elements such as micro-services and hybrid-cloud really come into their own.

A strong core operating model drives enhanced business outcomes

What differentiates a truly adaptive control tower from a well-managed one is the seeding of machine learning algorithms in tandem with cognitive automation to provide predictive and prescriptive analytics that pre-empt supply chain events and dramatically reduce risk. Our clients have seen tangible impact across the 3 “Es” – efficiency, effectiveness, and experience, including:

For a leading Aircraft company

  • 2–3% reduction in transport costs
  • Productivity improvements through consolidation and standardization of activities
  • Improved shipment visibility and tracking
  • Pro-active customer notifications and improvement in overall service levels.

For a world-leading CPG company

  • Seamless, integrated operations with multi-disciplinary teams housed under a supply chain Center of Excellence
  • 10–11% reduction of freight rate/tonne
  • Developed and deployed in-house small-tech tools for visibility, analytics, and optimization

For multiple global clients in the freight forwarding and 3PL space:

  • Unified system to handle varied customer requests
  • Data consolidation of master data, offer data and operational data leading to unprecedented transparency
  • Significant cost reduction and service level improvement through consolidation of orders and utilization of capacity

To summarize, the control tower is not an off-the shelf software that acts as a magic bullet for today’s logistics challenges. There’s as much to the core control tower design and operating framework as there is to the choice of technology. To enable real transformational benefits to flow into the modern day logistics processes, there’s no shortcut to building a strong core operating model.

About author

Shriharsha Parampalli, Director, Capgemini’s Business Services

Shriharsha Parampalli

Director, Capgemini’s Business Services
Shriharsha is a supply chain leader with over 18 years of delivery, consulting, and practice building experience working with marquee clients across Manufacturing, Healthcare, Retail/CPG, Hi-Tech and E-commerce spaces.

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