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The ultimate goal of any business is— to boost revenue, improve profitability, and enhance customer satisfaction. In the past, companies were mainly focused on making customers happy with timely services or product fulfillment. Today, most companies realize that providing better products/services alone is no longer enough; managing the customer experience and providing clear line of sight to outcomes are also important. This paradigm shift drives an evolution in business strategy and acts as a key differentiator in an “outcome economy.”

In addition to addressing the end needs of the customer, Outcome Economy identifies and prepares the wish-lists that generate new business opportunities to enhance the profitability and revenues, delivering a remarkable ROI and achieving a considerable decrease in total cost of ownership (TCO). Numerous businesses in varied sectors have been leveraging AI tools and facilitating the progression of the outcome economy and have experienced varying levels of success in improving business outcomes.


The key challenges that most organizations face with respect to their supply chains include:

  • Assessment of data touch-points and customer interactions

  • Estimation of the future demand and fluctuations

  • Agile and critical actions from the real-time insights which can cater to evolving needs

  • Form alliances with partners to support speed-to-market

  • Compound processes and technology environment that cause longer lead times

  • Visibility and transparency all through the value chain


In order to address these challenges, organizations are adopting digital transformation all across the supply chain. Effective digital transformation depends not wholly on the utilization of advanced technologies, but in remodeling the business to take advantage of the emerging opportunities that the new technologies present.

Most digital transformation initiatives are focused on reinventing the customer experience (CX), operating models and business processes. The union of the physical supply chain / logistics management and the online world into a physical-cyber ecosystem will steer the transformation across supply chains of different industries—with Advanced Analytics, Big Data, Automation, Robotics, Internet of Things (IoT) and the artificial intelligence (AI) playing a major role in decision making and transaction automation. This is changing the dynamics of supply chain costs and businesses that ignore this will be outdone by their competition. It has become a decision of ‘embrace or perish'.

For example, manufacturing companies are using advanced analytics to forecast the current efficiency of their installed bases and decrease downtime using data collected from the IoT-based sensors. Robots are being used to perform shop floor assembly operations to enhance the efficiency and cut down on costs. Customer Packaged Goods (CPG) businesses are using sensor platforms that are driven by algorithms in order to forecast future demand and as a measure to control drop orders and optimize inventory. Customer service operations are highly implementing Cognitive AI applications to improve important customer interactions.


Traditionally, the economy was mainly designed for efficiency; however, in this ‘outcome economy’, responsiveness, scalability, agility, and transparency are necessary as well. In this regard, the digital supply chain transformation should be built primarily on four main pillars:

  •  Cognitive analytics

  •  Intelligent processes

  •  Connected ecosystem

  •  Autonomous fulfillment

By approaching the digital transformation in this manner, businesses can not only propel optimization of operations and processes but also unlock channels to new and advanced business models, which can bring:

Scalability – the ability to support speed to market from product initiation stage to commercialization.

Agility- reforming the operating model to make it flexible, modular and illimitable to acclimate to the changing market settings.

Transparency- allowing employees, clientele, and partners to communicate seamlessly, encompassing real-time transparency across the value chain.

Responsiveness- the capability to make fast and knowledgeable decisions to react to the market needs in the real time.

When implemented successfully, automation breaks down the traditional barriers, allowing the supply chain to turn into a unified ecosystem that is completely transparent to everyone involved— starting from material suppliers to transportation providers of those supplies to the finished goods, and lastly to the customers expecting fulfillment. The automated supply network will provide a new level of responsiveness and resiliency, allowing early entrants to outshine the competitors by offering the most transparent and effective service delivery to the customers.


Better Planning: Artificial Intelligence (AI) can speed up the forecasting and scheduling processes and improves accuracy. Virtually there are no limitations to data access. Hence, it can consider a wide range of changing trends. Also, with AI, human errors can be reduced significantly and decision-making becomes easier and faster.

Optimized Logistics: AI is proven to be highly beneficial in logistics optimization. Whether it is driverless trucks or automated batch release of manufactured products, AI optimizes the resources used and the effectiveness of transactions.

Streamlined Processes: Another important benefit of artificial intelligence is, it can adapt and learn. With deep learning, artificial intelligence is highly suitable for error-prone and tiresome processes. For instance, AI could help in identifying the stock levels and fulfilling orders. Besides, this technology can collect huge amounts of historical data and learns from mistakes. When a mistake occurs, it will learn and make sure that doesn’t occur in the future. Fundamentally, AI can make quick and accurate decisions. This potential of streamlining processes can be used across your supply chain for astonishing results.

The benefits of AI in the supply chain are not just limited to these three areas; there are many areas to be explored, for example, warehouse management, procurement, supplier selection and management and so on.


Intelligent automation with AI makes possible the development of a new system for complete automation to derive the value for the business. However, with so much hype on digitization and automation, organizations are likely to deploy technologies randomly that can result into point benefits but won't generate organization-wide value addition. Such experiences abound.

With the availability of numerous technologies, applications, and tools, finding the best solution that provides the most appropriate working system in the prevailing situations is vital.

Businesses should not just focus on automation technologies but should make them an integral part of their strategic methodology to the delivery of services.

If you are interested to learn more about how Artificial Intelligence and automation can bring the change in your business, please drop your email here