Supply Chain

Within a span of three months, we saw failure of global supply chains, a very short demand surge and a prolonged demand drop. All events happening in quick succession. Which begs the question “How do we build supply chains and networks that can withstand such changes?”

The new normal is here to stay and it demands two things from every supply chain – stay resilient and stay lean, apart from the changes in demand patterns. Thus learning to be adaptive and change with the new consumer demands will become the need of the hour.

supplychain
ourperspective-1

The trends shaping supply chain transformation are the ability of a company and its ecosystem to address the 3 Vs – Volatility, Visibility and Value and the 3 Rs – Responsiveness, Resilience and Responsibility.

Demand volatility has increased multifold with disruptive changes to customer purchase and consumption patterns due to a variety of purchase channels and other social media influence and options. More than a single company, end-to-end supply chain ecosystems need to be tailored to the market needs and be responsive to be able to address this volatility faster. With multiple partners across the value chain, product visibility and status is critical to manage both customer and value chain partner expectations and decisions. For the supply chain ecosystem to function smoothly value needs to be created and realized appropriately for alignment of goals and for smoother functioning of the supply chain.

Re-invention of supply chain strategy and transformation are sought by companies to align to the changing market demands and have taken multiple overlapping forms, a few of which are listed below:

  • Customer centric supply chain – addressing volatility
  • Transparent supply chain – addressing visibility and value transactions
  • Strategic supply and network management – managing value and cost
  • Digital supply chain with advanced digital technologies – Managing risk and resilience and quicker value generation and realization

Insights from advanced analytics on customer preferences and behaviors drive better demand sensing and planning capabilities supported by end-to-end supply chain alignment towards customer value is the focus in customer centric supply chains. Transparent supply chains support the ability to maintain enterprise and ecosystem wide visibility.

Strategic sourcing and supply management and an agile and optimized network enables value creation and realization within the supply chain ecosystem. Data integration and advanced analytics enable better preparedness for the supply chain to manage risk.

ourperspective-2

With digitization in supply chain through use of connected IoT devices, use of machine learning and AI to predict and automating several functions, reduce the response time and provide additional opportunity for value creation. Block chain technologies are enabling better visibility of value transactions across supply chain partners and ensures value chain integrity across the supply chain especially in regulated industries like food and pharma to ensure transparency and better control.

Advanced Data Management and Analytics have supported cost reduction and value creation to supply partners through intelligent sales and ops planning, inventory optimization, intelligent distribution and replenishment and logistics and transportation.

With the Covid-19 crisis and the impending global climate crisis, companies have started focusing on environmentally responsible supply chain and its supply chain sustainability.

Supply Chain systems in 2020

Supply chain systems have been constantly evolving over the years. Today’s supply chain systems have more collaboration and automation compared to systems from a decade ago. We are going to look at the state of supply chain systems in 2020 and what are some of the key capabilities that one should evaluate when rehauling their supply chain systems.

Traceability

Traceability of products through its fulfilment supply chain, followed by manufacturing and all the way back into the raw material supply chain is still a very important aspect of modern supply chain systems. Being able to provide the proverbial farm-to-fork or factory-to-shelf capability is important to the modern consumer and retail.

Traceability

Traceability

Traceability

Traceability of products through its fulfilment supply chain, followed by manufacturing and all the way back into the raw material supply chain is still a very important aspect of modern supply chain systems. Being able to provide the proverbial farm-to-fork or factory-to-shelf capability is important to the modern consumer and retail.

Agility

Agility

Ability to ramp up production during market demand and ability to scale it down when there is a slump are two key patterns that are fundamental to the supply chain systems. Measuring the total cost of such ramp up / ramp down through simulation using digital twins for various actors in the supply chain would be a great feature to battle test our planning processes to see if it holds up to actual situations.

Agility

Agility

Ability to ramp up production during market demand and ability to scale it down when there is a slump are two key patterns that are fundamental to the supply chain systems. Measuring the total cost of such ramp up / ramp down through simulation using digital twins for various actors in the supply chain would be a great feature to battle test our planning processes to see if it holds up to actual situations.

Anti-fragility

Anti-fragility is now a norm for supply chain systems. While it is not a directly measurable and verifiable attribute, we believe in a combination of collaboration and transparency across the network through open API on the cloud and open data platforms. Data and information exchange should be powered by analytics driven insights. So a robust analytics platform to look at data across the entire network is necessary.

Anti-fragility

Anti-fragility

Anti-fragility

Anti-fragility is now a norm for supply chain systems. While it is not a directly measurable and verifiable attribute, we believe in a combination of collaboration and transparency across the network through open API on the cloud and open data platforms. Data and information exchange should be powered by analytics driven insights. So a robust analytics platform to look at data across the entire network is necessary.

Robots-in-warehouses

Assisted by automation

Data and insights are great but the warehouses of yesterday where human labor ruled supreme should now be augmented by autonomous machine assisted labor force. Robots in warehouses working in an automated fashion assisting the human labor force in improving efficiencies, tracking warehouse inventory and providing real-time data from warehouse floor through computer vision algorithms are some of the key features of a modern supply chain system.

Assisted by automation

Robots-in-warehouses

Data and insights are great but the warehouses of yesterday where human labor ruled supreme should now be augmented by autonomous machine assisted labor force. Robots in warehouses working in an automated fashion assisting the human labor force in improving efficiencies, tracking warehouse inventory and providing real-time data from warehouse floor through computer vision algorithms are some of the key features of a modern supply chain system.

Intelligence

Data gathered from partners, suppliers, shop and factory floors that are aggregated into analytics and insights is great, but this still requires human intervention even for simple data based decisions. The advent of machine learning (ML) in the supply chain hopes to alleviate the need for human decision. ML algorithms to bring in high accuracy require high quality training data and large computation power to be effective. This has been the roadblock to better adoption in the supply chain. By bringing in high quality training data we can increase the applicability of ML in the supply chain.

The applicability of intelligence is not just within the organization. By extending this intelligence to be made available to partners, we can help partners take advantage and participate in a collaborative network planning. To enable partners to take advantage of the intelligence a simple chatbot style interface can be enabled so that partners can ask freeform questions that can be responded to by the ML engine via the chatbot interface.

Intelligence

Intelligence

Intelligence

Data gathered from partners, suppliers, shop and factory floors that are aggregated into analytics and insights is great, but this still requires human intervention even for simple data based decisions. The advent of machine learning (ML) in the supply chain hopes to alleviate the need for human decision. ML algorithms to bring in high accuracy require high quality training data and large computation power to be effective. This has been the roadblock to better adoption in the supply chain. By bringing in high quality training data we can increase the applicability of ML in the supply chain.

The applicability of intelligence is not just within the organization. By extending this intelligence to be made available to partners, we can help partners take advantage and participate in a collaborative network planning. To enable partners to take advantage of the intelligence a simple chatbot style interface can be enabled so that partners can ask freeform questions that can be responded to by the ML engine via the chatbot interface.

Sustainability

Sustainability

Companies that have adopted environmentally responsible supply chain strategies have incorporated fair labor practices and environmental responsibility throughout their supply networks. They have started developing and disseminating industry wide sustainability standards. Few have joined hands to start industry associations (for example Responsible Business Alliance (RBA), whose members include Intel, HP, IBM, Dell, Philips, and Apple) and have started offering sustainability training to Tier-1 and Tier-2 suppliers.

Sustainability

Sustainability

Companies that have adopted environmentally responsible supply chain strategies have incorporated fair labor practices and environmental responsibility throughout their supply networks. They have started developing and disseminating industry wide sustainability standards. Few have joined hands to start industry associations (for example Responsible Business Alliance (RBA), whose members include Intel, HP, IBM, Dell, Philips, and Apple) and have started offering sustainability training to Tier-1 and Tier-2 suppliers.

supplychain-What-Client-Needs
  • Build Supply chains of the future that are antifragile and resilient
  • Replan production to suit reduced (or increased) demand in the midst of supplier shortage and labour shortage
  • Harness data (supplier and internal) together with AI and ML for insights to build resilient networks
  • Cloud based supply chain and collaboration tools for visibility and transparency
  • Holistic data driven connected view of the supply chain

Supply Chain Transformation

whatwedeliver-Supply-Chain-Transformation

As supply chains pivot to become adaptive and change with customer demands, it will require a level of nimbleness in supply chain systems and processes.

Our transformation approach integrates demand management, planning, and scheduling functions with Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES) to bring nimbleness and resilience in an organization’s supply chain processes.

We use digital transformation of traditional supply chain technologies by leveraging data on the cloud to make real time adjustments to the planning and execution process through data driven decision making and provide a holistic data driven connected view of the supply chain.

Our approach involves creating accurate demand forecasts; optimize forecast-to-stock, order-to-cash, procure-to-pay, accounting, analytics, prepare effective production schedules; and optimize inventory levels to help lower operating costs. Benefits of our approach

Key benefits of our approach

  • A nimble supply chain since ERP and MES feed real time analytics data to create a closed loop system.
  • A leaner supply chain since real time plan adjustments help reduce cost of inventory carry.
  • Better customer fulfillment time since supply chain is operated at a now inventory just in time process reducing

Digital Supply Chain Enablement

Organizations aim to be agile and intelligent, and underpinning both is the power of data. Making supply chains agile requires enabling accurate real-time data to flow from ERP and MES systems back into the planning process. It also requires warehouses to move from a people centric approach to an autonomous robot centric approach. Their built in sensors collect real-time data such as inventory levels of raw materials, warehouse space planning and so on.

On the other hand making supply chains intelligent requires better predicting capabilities. This requires pattern recognition and learning in the form of ML and AI in supply chains. The data requirements is met by IoT devices in the warehouse and across the supply chain constantly measuring various operational parameters and sharing them in a real-time stream. This stream creates the contextual information required by an AI engine to make predicting supply chain needs.

The IoT layers provide contextual data streams, the AI algorithms trained on various business scenarios help interpret this data in real-time and help AI powered supply chains provide decision insights in real time.

We build this entire IoT implementation leveraging our expertise in building embedded system for automobile and ancillary industries, best-of-breed AI algorithms (Google and Microsoft) and build applications that integrate with existing supply chain processes.

whatwedeliver-Agile-Supply-chains

Digital Supply Chain Enablement

Organizations aim to be agile and intelligent, and underpinning both is the power of data. Making supply chains agile requires enabling accurate real-time data to flow from ERP and MES systems back into the planning process. It also requires warehouses to move from a people centric approach to an autonomous robot centric approach. Their built in sensors collect real-time data such as inventory levels of raw materials, warehouse space planning and so on.

On the other hand making supply chains intelligent requires better predicting capabilities. This requires pattern recognition and learning in the form of ML and AI in supply chains. The data requirements is met by IoT devices in the warehouse and across the supply chain constantly measuring various operational parameters and sharing them in a real-time stream. This stream creates the contextual information required by an AI engine to make predicting supply chain needs.

The IoT layers provide contextual data streams, the AI algorithms trained on various business scenarios help interpret this data in real-time and help AI powered supply chains provide decision insights in real time.

We build this entire IoT implementation leveraging our expertise in building embedded system for automobile and ancillary industries, best-of-breed AI algorithms (Google and Microsoft) and build applications that integrate with existing supply chain processes.

whyus
  1. Expertise in engaging right supply chain levers to enable supply chain value creation.
  2. Ability to integrate bolt-on solutions to establish ERP based processes
  3. Leverage our deep expertise in ground up device development for custom board design for your IoT integration needs
  4. Bring in best-in-class AI algorithms from open source instead of closed arcane technology stacks giving better control over the AI technology stacks
  5. Focus on AI enabled supply chain solutions rather than AI algorithms
  6. Work with enhancing your existing supply chain platforms
success-Supply-Chain

Smart IoT based monitors offer oil distributors remote view of stock levels

For a leading oil distributor we developed a remote monitoring solution with the ability to install monitors without alterations to oil tanks and remotely monitor oil levels up to 4m high. Ensured reliable performance under severe weather conditions.

The New Normal is here. Is your Supply Chain Ready?

Making them antifragile and resilient.

Build a supply chain that is resilient, lean, adaptive and keeps pace with customer demands.

Supply Chain Transformation

Integrate systems and applications to bring in nimbleness and resilience.

Digital Supply Chain Enablement

Holistic approach spanning real-time data flow, autonomous robots, sensors and prediction capabilities.

IoT Implementation

Embedded systems know-how, best-of-breed AI algorithms and application development and integration.