Tag Archives: sourcing

5 Ways Analytics Are Disrupting Supply Chain Management

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5 Ways Analytics Are Disrupting Supply Chain Management

5 Ways Analytics Are Disrupting Supply Chain Management

Harmonizing supply chain management analytics will put organizations on a path to automating their operations.

The evolution of infotech increased customer expectations, economic behavior, and other competitive priorities have caused firms to modify themselves in the current business landscape. Supply chains globally are becoming more complex, thanks to globalization and the consistently changing dynamics of demand and supply. As per a forecast by Gartner, the global supply chain management market was valued at USD 15.85 billion in 2020 and is expected to reach almost USD 31 billion by 2026.

Businesses are channeling the power of big data analytics to disrupt transformations at all levels of supply chain management. Data started as a fundamental component of digital transformation and is now a revolutionary concept. It is the key to achieving breakthroughs in supply chain management systems, and more organizations are integrating data analytics to mine data for proactive insights and accelerate intelligent decision-making.

Big data implementation in supply chain management addresses several issues, from strategic to operational to tactical. It includes everything from building efficient communication between suppliers and manufacturers to boosting delivery times. Decision-makers can utilize analytics reports to increase operational efficiency and boost productivity by closely monitoring the system’s performance at each level.

What is Big Supply Chain Analytics, and How Does it Work?

Integrating big data analytics with the supply chain makes big supply chain analytics enable business executives to compute better growth decisions for all possible maneuvers by combining data and quantitative methodologies. Notably, it adds two features.

First, it broadens the dataset for analysis beyond internal data stored in existing SCM and ERP systems. Second, it uses advanced statistical techniques to analyze the new and existing data. This generates new insights that help make better decisions for improving front-line operations and strategic decisions like implementing the best supply chain models.

Here are five ways big data and analytics are disrupting supply chain management:

1) Improved demand forecasting

Demand forecasting is one of the crucial steps in building a successful supply chain strategy. With data science and analytics in play, businesses experience automated demand forecasting. This assists them in quickly responding to fluctuations in the market and streamlining the optimal stock levels every time.

2) Enhanced production efficiency

Data science and analytics play a significant role in gauging organizational performance. Accurate application of big data analytics can help organizations track, analyze, and share employee performance metrics in real time. You can identify excellent employees who are struggling to maintain a consistent performance. This could be quickly done with IoT-enabled work badges, which exchange information with sensors installed in production line units.

3) Better sourcing and supplier management

Supply chain management systems have empowered organizations to collate data on multiple suppliers. Using data science solutions, you can leverage this data to gain insights into the historical record of any supplier. With this, you can gauge based on crucial metrics such as compliance, location, reviews, feedback, services, etc.

4) Better warehouse management

Warehouses are acquiring modern technology and have started installing sensors to collect data on the inventory flow. This helps you build an extensive database containing information based on the weight and dimensions of the packages. With sensors installed in your warehouse, you can identify bottlenecks that obstruct the flow and can be easily resolved at the earliest with the big data-fueled systems.

5) Improved distribution and logistics

Order fulfillment and traceability are essential for business productivity and customer satisfaction. Logistics have traditionally been cost-focused and effectively look for ways that provide them competitive advantages. Data science solutions enable logistic providers to leverage data analytics to improve their operations. For instance, they use fuel consumption analytics to improve driving efficiency. With GPS technology, they can track real-time routing of deliveries and reduce long waiting times by allocating nearby warehouses.

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5 Critical Supply Risk Mitigation Principles for Your Sourcing Process

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Supply chain risk management (SCRM) is becoming a top priority in procurement, as organizations lose millions because of cost volatility, supply disruption, non-compliance fines and incidents that cause damage to the organizational brand and reputation.
Bribes to shady government officials, salmonella in the spinach and forced labor in the supply chain can all result in brand-damaging headlines that can cost an organization tens of millions in sales and hundred of millions in brand damage. And while reputation may only be important for name brands, cost volatility and supply disruption affect all manufacturers.

In fact, in the latest 2015 study by the Business Continuity Institute, supply chain disruption doubled in priority relative to other enterprise disruptions (48% of firms are concerned or extremely concerned). Roughly three-quarters of respondents said they had at least one disruption, and the same amount lack full visibility of their supply chains.

In the same study, 14% had losses from supply chain disruptions (e.g., natural hazards, labor strikes, fires, etc.) that cost over €1 million, and these disruptions can easily go up to nine figures. For example, Toyota estimates the costs for the recent Kumamoto earthquakes to be nearly $300 million. Imagine being out of stock on a product line that does $12 million in annual sales for two months. That’s $2 million in immediate lost sales and longer-term brand damage.

Risk management, and what is necessary for ongoing risk management, never gets operationalized, and as new suppliers get added, supply shifts and supply chains change, new risk enters the picture — risks that go undetected unless risk management is embedded in all key procurement activities, including sourcing. It is important to remember that:

1. When You are Sourcing, You are Really Changing Your Supply Chain Network

2. Supplier Risk is Only One Aspect of Supply Chain Risk

3. Your Sourcing Criteria Must Be ‘Protected’ and Risk Must Be Factored In

4. You Need to Cost the Risk” and Also Get It in the Contract

5. You Must Design a Monitoring System That is Part of Onboarding

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5 Data-Driven Supply Chain Challenges to Overcome in 2016

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Supply chain, sourcing and procurement executives are feeling immense pressure to cope with the expansion into global markets, waves of disruptive innovation, rising customer expectations and complex regulatory requirements. These are catalysts that require supply chain management strategies to become bimodal and to make a shift from tactical to strategic.

In addition to the sourcing of goods and services, cost management and internal stakeholder compliance, executives’ responsibilities will include the ability to promote and support the top line. They have to be a trusted advisor to internal business partners and will have a tremendous impact on the success of an organization engaging with suppliers, managing relationships with strategic vendors and solving business problems.

For 2016, I see leading supply chain organizations making these top-five data-driven supply chain management challenges a priority.

1. Meet Rising Customer Expectations on Supply Chain Management

2. Increase Costs Efficiency in Supply Chain Management

3. Monitor and Manage Supply Chain Compliance & Risk

4. Make Supply Chain Traceability and Sustainability a Priority

5. Remain Agile and Flexible in Volatile Times and Markets

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New Solutions for Supply Chain Risk Management: A Case Study

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We are entering an era where it is becoming possible to detect supply chain risks much more quickly. A case in point is offered by AGCO. AGCO AGCO +1.96% is a global leader in the design, manufacture and distribution of a wide range of agricultural equipment. In a discussion with AGCO’s Jan Theissen, Director of Strategy and Methods, and Jake Stone, Manager of Supply Chain Risk and Contract Management, I learned about this public, Atlanta headquartered corporation’s journey to improve their sourcing and supply base risk management capabilities.

AGCO’s products are marketed under a number of well-known brands, including Challenger, Fendt, GSI, Massey Ferguson and Valtra. The manufacture and assembly of their products occurs at 34 locations worldwide and historically each of these brands was managed as a separate supply chain. Further, because the company had grown by acquisition, these different supply chains used more than 10 different enterprise resource planning (ERP) solutions for direct sourcing.

Beginning in 2012, Mr. Theissen, a newly appointed procurement leader, led a transformation of the sourcing organization. AGCO moved from a fragmented and decentralized procurement to a centralized commodity management structure in order to better leverage buying synergies and increase the overall maturity level of this organization. Implementation of standardized roles and responsibilities, and global policies and procedures, were supported by an extensive change management program. The company formed a School of Purchasing to further develop the capabilities of the organization.

The risks associated with sourcing became part of each category manager’s job; these managers became responsible for supplier risk management, not just savings. Mr. Stone was brought into establish new, systems, processes and capabilities to manage procurement risk. One thing Mr. Stone put in place was a clear communication and escalation process to deal with risks once detected.

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