Automotive

Asterisk’s automotive platform has unique and proprietary features to manage the characteristic complexities of the industry. Several leading organizations have been operating their supply chains on the Asterisk platform, enabling seamless collaboration across internal and external stakeholder.

Features

Know your vendors better

The visibility of Tier 1 to Tier N in terms of capacities, allocation to Original Equipment Manufacturers (OEMs), domestic value-added content, and commodity dependencies and related hedging.

 

 

Be future ready

The planning of constraints across internal shops and Tier-N suppliers' lines, readiness for multiple demand/supply/sunset scenarios - including existing and new platforms (New Product Introductions or NPIs), quantification of risks in the form of Capital Expenditure (Capex) requirements and subsequent Capex planning, as well as early warning signals based on lead times.

Reliable short-term planning

The scheduling process, based on Collaborative Heijunka, involves obtaining supplier sign offs. Proactive alerts to Production Planning and Control (PPC) and vendors are triggered based on risks, such as misses or delays in Advanced Shipping Notices (ASN). Recovery planning is also carried out using existing resources to address any potential disruptions.

Miss nothing in operations

A unified view of production and part risks is developed to ensure comprehensive visibility. Timely scheduling of long lead time parts, such as steels and chips, is prioritized to avoid potential delays. AI-based triggers are used to identify and rectify errors in master data, ensuring data accuracy and reliability in the production process.

Transforming customer experience

Customers are provided with an e-commerce-like delivery experience, where reliability of service is ensured through a seamlessly connected planning process. This involves integrating different stages of planning to create a streamlined and efficient system that delivers products in a timely and reliable manner.

AI/ML based demand sensing and collaboration

Data scientists utilize short-term, mid-term, and long-term forecasting techniques, including feature modeling, to improve forecasting accuracy. Ready pipelines are developed to incorporate relevant external drivers into the forecasting process. Additionally, forecasting efforts are extended to cover new product introductions (NPIs) to better anticipate demand for new products. Consensus-based planning is also implemented to align sales targets, along with exception-based tracking, to identify and address any deviations from the plan.

Agility of response

The Theory of Constraints (TOC) approach is powered by AI/ML technologies to optimize inventory management. A proprietary Multi-Echelon Inventory Optimization (MEIO) methodology is used to strike a balance between minimizing loss of sales and ensuring optimal customer service levels. The inventory norms are self-correcting and dynamic, with built-in outlier correction and truck load optimization capabilities. The entire ecosystem is seamlessly synced on the platform to achieve execution excellence and enhance operational efficiency.

Predictive and prescriptive decision making

Real-time calculation of business impact metrics based on roles, including both current and predictive metrics, is implemented. Root Cause Analysis (RCA) decision trees are utilized to assign accountability for identified issues. Priority reports are generated to facilitate timely actioning on identified areas of improvement, allowing for effective management of business operations and performance optimization.

EXIM

End-to-end visibility is provided to both internal and external stakeholders, with a focus on creating a B2B customer experience similar to e-commerce. By leveraging technology, enhanced transparency, efficiency, and customer satisfaction in the end-to-end business processes are provided to stakeholders with real-time visibility and a seamless experience.

Sustainable supply chains

A comprehensive carbon footprint assessment is conducted across the extended supply chain to evaluate the environmental impact of operations. An Environmental, Social, and Governance (ESG) scoring system is also implemented enabling the organizations to monitor, manage, and report on its ESG performance effectively, aligning with sustainability goals and stakeholders' expectations.