By- Saurabh Jerath, Director – Engineering, GlobalLogic
In today’s time, digital innovation is accelerating digital transformation, which is paving the way for a new era of supply chain management to emerge. The increase in digitization of processes has enabled disruption across industries, that is redefining their engagement with the market and ensuring business continuity. Supply chains have become integrated, agile, and responsive, thanks to the expansion of digital channels, the power of mobile devices, and the proliferation of big data.
This new digital age is driving new customer relationships, opening new business avenues, speeding up time to market, and reducing costs across the supply chain. However, with increasing economic globalization, distributed global supply chains, market demand
volatilities, never-ending peer pricing pressures, and unpredictable situations such as COVID-19, it is becoming far more difficult for the enterprises in the global markets to maintain efficient business process supply chain operations. Delayed shipments, inefficient plants, poor quality, inconsistent suppliers, and handling huge volumes of order data to achieve integrated, efficient, and agile supply chains are some of the common challenges enterprises are facing today.
1. Constant rise of omnichannel needs: Customers are moving seamlessly between online and offline experiences. Therefore, the challenge is to ensure an omnichannel experience that allows consumers to interact wherever and, in any manner, they wish to, while incorporating feedback.
2. Digital Transformation: With ever-evolving customer behavior and needs, there’s a constant challenge to rapidly transform digitally to remain competitive.
3. Maintaining customer stickiness: Customers are spoilt for choices; therefore, brand loyalty has become relevant to a brand’s success.
4. Shrinking Margins: Factors like peer pricing pressures, global fluctuations, etc., forces companies to meet competitive global price points. This creates additional pressure, as manufacturers need to ensure the delivery of high-quality products while finding innovative ways to cut costs and have optimum inventory readiness.
5. Data Insights and Analytics: The trend of data-driven decision-making is yet to meet strong acceptance in the retail and consumer goods industry, especially with supply chains. Companies struggle with a lack of strong data granularity and analytics to properly respond to demand requests.
The dire need for Supply Chain Analytics to mitigate the risks
Considering the challenges, it’s imminent that there is an increasing need for Data Analytics in the Retail & Consumer goods industry, especially for supply chains to prepare for the next decade of industrial evolution. Supply Chain Analytics (SCA) enables organizations to derive insights from a large amount of data associated with the procurement, processing, and distribution of goods.
Therefore, arises the need for SCA in enhancing the firm’s supply chain by gathering insights around supplier performance, performing market intelligence, risk management, and mitigating disruptive events to ensure cost-saving adjustments to inventory and faster delivery. Most often, SCA is applied across the entire chain, but can also be applied on some of the key business process workflow components, such as warehouse management, inventory management, order management, demand planning, manufacturing, transportation management, etc.
Streamlining value chains with Supply Chain Analytics
SCA aims to improve operational efficiency and effectiveness by enabling data-driven decisions at strategic, operational, and tactical levels. Following are some of the potential levers through which SCA can be enabled to accelerate an organization’s journey to streamline its supply chains:
1. Extend analytics capability: These could be tailored around some of the leading Supply Chain Management (SCM) and business data processing platforms to build strong data pipelines which can be deployed on business intelligence (BI) platforms. Organizations can also build data analytics tools on the back of supply chain data to forecast accuracy, streamline operations, and maximize resource utilization.
2. Enhance AI/ML capabilities: AI helps solve challenges by using data sitting in silos. Using advanced machine learning algorithms, organizations can understand where and when to source, based on past purchases, commodity pricing, and industrial trends, thereby providing them intelligence in procurement.
3. Leverage Hyperautomation: Hyperautomation is an upcoming framework that suggests the application of advanced technologies such as RPA, Artificial Intelligence, and Machine Learning, to automate complex business processes is more impactful than traditional automation capabilities.
4. Expand footprint in IoT offerings: IoT in the supply chain provides real-time location tracking, and storage area monitoring and predicts the transportation and arrival cycle of the product. Whether data sources are from ERP systems, or any other medium, the supply chain now has access to these data sources that will grow further with time.
5. Enhance AR/VR capabilities: Immersive technologies such as virtual, augmented, and mixed reality have the potential to influence supply chain management. Expanding AR/VR offerings will provide benefits for various use cases like onboarding new workers through immersive on-the-job training in a safe, realistic virtual environment.
In the current environment of global complex supply chain networks, effective analytics need to be more customer-centric and responsive, while maintaining accuracy and data integrity. Organizations are looking for supply chain analytical solutions that can quickly analyze huge amounts of data from disparate data sources. Moreover, supply chain analytics is being used increasingly to predict a growing number of supply chain variables including external forces such as weather, war, workers, economy, and regulations. Therefore, companies along with accelerating their digital strategy execution should leverage analytics to understand consumers better and generate more insights to improve business effectiveness and conversion rates.
