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Feb 22 2024
Measuring and Reporting on Supply Chain Sustainability the Right Way

In an era where sustainability is not just a buzzword but a strategic imperative, the supply chain plays a pivotal role in shaping an organization’s environmental and social footprint. Here are some ways to guide your business on the essential aspects of measuring and reporting sustainability within the supply chain, focusing on data management, goal and metric definitions, and adherence to reporting standards.

Data Management: Unraveling the Threads of Sustainability

In the intricate web of supply chain operations, data serves as the thread that weaves together the fabric of sustainability. Comprehensive data management is essential for measuring, monitoring, and optimizing sustainability initiatives within all aspects of your organization’s supply chain.

The first step in sustainable data management is collecting relevant information across the organization. Some examples of this data include energy consumption, water usage, waste generation, emissions, and social impact factors such as labor practices and community engagement. The challenge, however, is gathering data from diverse sources—including suppliers, manufacturers, logistics partners, and internal operations. Strategies for overcoming this include implementing data-sharing agreements with vendors, conducting regular audits, and leveraging emerging technologies like Internet of Things (IoT) sensors, blockchain, and the API integration capabilities of your data platform to track and trace environmental and social performance throughout the supply chain.

Once collected, sustainability data must be organized coherently and structured to facilitate fast analysis and decision-making. This means establishing a clear taxonomy and data schema that categorizes information according to relevant sustainability indicators, like carbon emissions or waste generation. This is where data visualization tools and dashboards come in handy because they will help present the information in a user-friendly format.

Defining Goals and Metrics: Charting a Course for Sustainable Success

Once the data is collected and integrated, the next step is to establish goals and metrics for meaningful action and measurable progress. By breaking down silos and integrating data from various departments, sources, and stakeholders, organizations can gain a comprehensive understanding of their environmental and social impact across the entire supply chain. This integrated approach allows you to identify and establish goals that address the most significant areas of opportunity and risk.

Implementing policies to act on the data requires a strategic and proactive approach that aligns with your defined goals and metrics. Best practices include setting ambitious, yet achievable, targets based on data-driven insights and industry benchmarks. These targets should provide clear direction and accountability for sustainability efforts. Additionally, your organization should develop policies and procedures to track progress toward these targets, leveraging technology and data analytics to monitor performance in real-time to course correct as needed.

Establishing a culture of continuous improvement and accountability is essential, with regular reviews and updates to policies and targets based on evolving data insights and stakeholder expectations.

Reporting Standards: Navigating the Landscape of Transparency

Established reporting frameworks such as the Global Reporting Initiative (GRI) and the Sustainability Accounting Standards Board (SASB) play a crucial role in guiding organizations toward transparent and consistent sustainability reporting. These frameworks provide comprehensive guidelines and standardized metrics for measuring and disclosing environmental, social, and governance (ESG) performance.

Adhering to recognized reporting standards helps organizations enhance credibility and comparability in the eyes of stakeholders—including investors, customers, employees, and regulators. Consistent reporting enables investors to make informed investment decisions, customers to make ethical purchasing choices, and regulators to enforce compliance with environmental and social regulations.

The emergence of integrated reporting represents a paradigm shift in how organizations disclose their performance and make holistic decisions, moving beyond traditional financial metrics to encompass broader value creation for all stakeholders. Integrated reporting seeks to present financial and sustainability performance cohesively, acknowledging the interconnectedness between financial success and environmental and social impact.

By integrating financial and non-financial data into a single, comprehensive report, organizations can provide stakeholders with a holistic view of their long-term value-creation strategy. Integrated reporting encourages a more balanced and sustainable approach to business decision-making, where financial considerations are complemented by environmental and social considerations. As organizations increasingly recognize the importance of holistic value creation, integrated reporting, and integrated data in general, is the key for communicating sustainability performance and demonstrating long-term resilience and viability.

Integration is Hard, but Actian Can Help

The Actian Data Platform offers invaluable capabilities to companies striving to enhance their ESG efforts and reporting accuracy. By providing a unified platform for data management, integration, and analytics, Actian empowers organizations to access, analyze, and leverage sustainability-related data from across the entire supply chain in real-time.

With these real-time insights into key ESG metrics, your company can make informed decisions that drive sustainable practices and optimize resource usage. Actian’s advanced integration capabilities empower your organization to identify trends, patterns, and opportunities for improvement, facilitating proactive interventions to minimize environmental impact and maximize social responsibility. Moreover, by streamlining data collection and aggregation, Actian enhances confidence that sustainability reports are comprehensive, accurate, and timely, bolstering credibility and trust with stakeholders.

Measuring and reporting sustainability in the supply chain requires a strategic and holistic approach. By mastering data management, defining clear goals and metrics, and adhering to reporting standards, businesses can not only enhance their environmental and social impact but also build trust with stakeholders. By making data easy, the Actian Data Platform enables you to drive and monitor sustainability initiatives across your entire supply chain.

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Author: Actian Corporation

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Jun 15 2023
Data-Driven Analytics Use Cases Powered by the Avalanche Cloud Data Platform

Our new eBook “Data-Driven Analytics Use Cases Powered by the Avalanche Cloud Data Platform” is designed for users and application builders looking to address a wide range of data analytics, integration, and edge use cases. We have included the following examples from real-world customer experiences and deployments to serve as a guide to help you understand what is possible with the Actian (also known as Avalanche) platform.

Customer 360

With the Actian (also known as Avalanche) platform powering Customer 360, organizations can rapidly personalize the customer experience through micro-segmentation, next-best action, and market basket analysis while improving customer acquisition and retention through campaign optimization, and churn analysis to increase customer loyalty.

Healthcare Analytics

The Actian Data platform helps healthcare payer and provider organizations leverage analytics to protect their businesses against fraud, increase care delivery, provider efficiency, and accuracy, while accelerating the transformation to an outcome-centric model.

IoT-Powered Edge-to-Cloud Analytics

Edge applications and devices rely on complex data processing and analytics to improve automation and end-user decision support. The underlying cloud and edge data management solutions must leverage a variety of hardware architectures, operating systems, communications interfaces, and languages. The Actian Platform and its Zen Edge Data Management option provide broad, high-performant, and cost-effective capabilities for this demanding set of requirements. 

ITOps Health and Security Analytics

With the explosion of ITOps, DevOps, AIOps, and SecOps data streaming from multiple clouds, applications, and on-premises platforms, many vendors are working to provide data visibility in their domains. However, they fall short of creating a holistic view to predictively identify trouble spots, security risks, and bottlenecks. How can businesses gain real-time actionable insights with a holistic IT analytics approach? The Actian platform makes it easy to combine data from thousands of data sources into a unified hybrid-cloud data platform capable of real-time analysis of applications, infrastructure, and security posture.

Supply Chain Analytics

Manufacturing is a far more complex process, compared with just a few decades ago, with subcomponents required to assemble a single final product sourced from several places around the globe. Along with this complexity is a massive amount of data that needs to be analyzed to optimize supply chains, manage procurement, address distribution challenges, and predict needs. The Actian platform helps companies easily aggregate and analyze massive amounts of supply chain data to gain data-driven insights for optimizing supply chain efficiency, reducing disruptions, and increasing operating margins.

Machine Learning and Data Science

The Actian Data Platform enables data science teams to collaborate across the full data lifecycle with immediate access to data pipelines, scalable compute resources, and preferred tools. In addition, the Actian platform streamlines the process of getting analytic workloads into production and intelligently managing machine learning use cases from the edge to the cloud. With built-in data integration and data preparation for any streaming, edge, or enterprise data source, aggregation of model data has never been easier. Combined with direct support for model training systems and tools and the ability to execute models directly within the data platform alongside the data, companies can capitalize on dynamic cloud scaling of analytics, compute, and storage resources.

Why Actian?

Customers trust Actian because we provide more than just a platform. We help organizations make confident, data-driven decisions to reduce costs and enhance performance. Using our Actian Data Platform, companies can easily connect, manage, and analyze their data for a wide range of use cases. You can trust that your teams are making the best decisions that address today’s challenges and anticipate future needs.

Read the eBook to learn more.

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Author: Teresa Wingfield

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May 23 2023
Unlocking Business Insights: How Supply Chain Analytics Measures Your Company’s Health

In today’s highly competitive business world, companies are constantly looking for ways to improve their supply chain operations. One of the most effective ways to do this is by measuring supply chain performance using real-time analytics. By understanding the performance of each aspect of the supply chain, companies can identify bottlenecks, reduce lead times, and improve customer satisfaction. By implementing real-time supply chain analytics, you can gain valuable insights into your company’s health and identify areas for improvement.

Key Performance Indicators in Supply Chain Analytics

Before diving into the benefits of supply chain analytics, it’s essential to understand the key performance indicators (KPIs) that are typically used to measure supply chain performance. These metrics are vast, but three that are common examples are:

Inventory Turnover: This KPI measures how quickly you are selling your inventory. A low inventory turnover rate can indicate that you are carrying too much inventory, while a high rate can suggest that you are not keeping enough stock on hand.

Order Cycle Time: This KPI measures the time it takes from when a customer places an order to when the order is fulfilled. A longer order cycle time can lead to dissatisfied customers, while a shorter cycle time can improve customer satisfaction.

Perfect Order Rate: This KPI measures the percentage of orders that are delivered on time, in full, and without any errors. A low perfect order rate can indicate that you have issues with your order fulfillment process, which can lead to lost sales and dissatisfied customers.

Using Data Analytics to Improve Supply Chain Performance

One of the most effective ways to improve supply chain performance is using data analytics. By collecting and analyzing data from various aspects of the supply chain, companies can identify patterns and trends that can be used to optimize operations. Data analytics can be used to identify areas where supply chain operations are inefficient or ineffective, such as high inventory levels or long lead times. It can also be used to identify opportunities for improvement, like reducing transportation costs or improving manufacturing efficiency. Some specific areas where supply chain analytics can improve performance include:

  1. Improved forecasting accuracy: By analyzing historical data and trends, you can improve your forecasting accuracy. This can help you better anticipate demand for your products and avoid overstocking or understocking.
  2. Better inventory management: By analyzing inventory turnover and other metrics, you can optimize your inventory levels to reduce carrying costs while still meeting customer demand.
  3. Increased supply chain visibility: By using analytics tools, you can gain more visibility into your supply chain operations. This can help you identify bottlenecks or inefficiencies and make data-driven decisions to improve your supply chain.
  4. Faster order fulfillment: By analyzing order cycle times and perfect order rates, you can identify areas where you can streamline your order fulfillment process. This can help you deliver products to customers faster and improve customer satisfaction.
  5. Reduced risk: By analyzing your supply chain, you can identify potential risks and take steps to mitigate them. For example, you may identify a supplier who is at risk of going out of business, and you can take steps to find a new supplier before a disruption occurs.

Best Practices for Implementing Supply Chain KPIs

Implementing KPIs in a supply chain can be a complex process, but there are several best practices that companies can follow to ensure success. These include:

  1. Defining Clear Objectives: Before implementing KPIs, it’s important to define clear objectives that align with overall business goals. This ensures that KPIs are relevant and meaningful.
  2. Choosing the Right KPIs: Not all KPIs are created equal, and it’s important to choose KPIs that are relevant to specific aspects of the supply chain. This ensures that KPIs provide meaningful insights.
  3. Collecting Accurate, Data: KPIs are only as good as the data that is used to measure them, so it’s important to collect accurate and reliable data. That means that the data must be consistent, complete, and correct, and that data must be available in a timeframe that allows your business to react to changes.
  4. Communicating Results: KPIs should be communicated to all stakeholders in a clear and concise manner. This ensures that everyone understands the importance of KPIs and how they contribute to overall business success.
  5. Continuously Improving: Supply chain operations are constantly evolving, so it’s important to continuously review and improve KPIs to ensure they remain relevant and effective.

By analyzing key performance indicators, businesses can identify inefficiencies, improve customer satisfaction, and reduce costs. Supply chain analytics can provide valuable insights into overall business health when they are built using KPI’s that are directly tied to overall business objectives. Use these resources to learn how the Avalanche Cloud Data Platform is helping to deliver real-time data for supply chain analytics:

The post Unlocking Business Insights: How Supply Chain Analytics Measures Your Company’s Health appeared first on Actian.


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Author: Traci Curran

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May 11 2023
What is Supply Chain Analytics?

Supply chain analytics uses data and advanced analytics to analyze and optimize various aspects of the supply chain, including procurement, manufacturing, and logistics. The main goals of supply chain analytics are to improve efficiency, lower costs, and increase revenue. Supply chain analytics can also provide real-time insights that help businesses adjust to changing conditions quickly and effectively.

Using supply chain analytics, you can ask the right questions, find the right answers, and realize the benefits of a well-optimized supply chain.

Frequently Asked Questions

There are four primary types of supply chain analytics: descriptive, diagnostic, predictive, and prescriptive. These advanced analytics techniques may sound complex, but you should find this simple business-level overview of what each type reveals with examples to be straightforward.

What events have happened?

Descriptive analytics mines historical data to identify trends and relationships. Examples include identifying excess inventory and late deliveries.

Why did these events happen?

Diagnostic analytics examines trends and correlations between variables to determine the root cause of a supply chain event. This type of analytics can diagnose events such as why there was too much stock and why deliveries were late.

What might happen in the future?

Predictive analytics uses supply chain data to predict future outcomes, such as forecasting demand or anticipating possible transportation bottlenecks.

What should we do?

Prescriptive analytics uses data to prescribe the best course of action, such as decreasing production or using alternative shippers.

Benefits of Supply Chain Analytics

Answering these types of questions provides a myriad of benefits. Below are just a few of them:

  • Improved efficiency and cost savings: Through using supply chain analytics to streamline processes, reduce waste and optimize operations. Examples include optimizing routes and schedules, reducing manufacturing downtime, using less fuel and better sourcing of materials, and many more opportunities.
  • Increased visibility and transparency: Allow organizations to identify potential problems early on and take proactive measures to address them.
  • Better risk management: By highlighting interdependencies and uncovering areas along the supply chain where disruption can lead to failure.
  • More accurate planning: Gain better insight into sourcing, manufacturing, and distribution to meet customer demand.
  • Better customer experience: Real-time insights into customer demand can improve how you manage inventory levels and ensure that products are in stock when customers want them.
  • Less environmental impact: Normalize analyzing energy consumption, waste, and other sustainability factors.

Getting Started

Supply chain analytics provides a data-driven way for businesses to optimize their operations, with its ability to provide real-time visibility, highlight risks, reduce costs and inefficiencies, better plan for customer demand, improve the customer experience, and reduce environmental impact.

To get started, you’ll need the right data platform to run your descriptive, diagnostic, predictive, and prescriptive supply chain analytics. The Avalanche Cloud Data Platform can help you transform your supply chain, by simplifying how you connect, manage, and analyze data. Using the Avalanche platform, you can easily aggregate and analyze massive amounts of supply chain data to gain data-driven insights in real-time, for optimizing supply chain operations.

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Author: Teresa Wingfield

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Apr 25 2023
Best Practices for Using Data to Optimize Your Supply Chain

When a company is data-driven, it makes strategic decisions based on data analysis and interpretation rather than mere intuition. A data-driven approach to supply chain management is the key to building a strong supply chain, one that’s efficient, resilient, and that can easily adapt to changing business conditions.  

How exactly you can best incorporate data and analytics to optimize your supply chain depends on several factors, but these best practices should help you get started:     

#1. Build a Data-Driven Culture 

Transitioning to a data-driven approach requires a cultural change where leadership views data as valuable, creates greater awareness of what it means to be data-driven, and develops and communicates a well-defined strategy that has buy-in from all levels of the organization.  

#2. Identify Priority Business Use Cases 

The good news is that there are a lot of opportunities to use supply chain analytics to optimize your supply chain across sourcing, processing, and distribution of goods. But you’ll have to start somewhere and should prioritize opportunities that will generate the greatest benefits for your business and that are solvable with the types of data and skills available in your organization.  

#3. Define Success Criteria 

After you’ve decided which use cases will add the most value, you’ll need to define what your business hopes to achieve and the key performance indicators (KPIs) you’ll use to continuously measure your progress. Your KPIs might track things such as manufacturing downtime, labor costs, and on-time delivery.  

#4. Invest in a Data Platform  

You’ll need a solution that includes integration, management, and analytics and that supports real-time insights into what’s happening across your supply chain. The platform will also need to be highly scalable to accommodate what can be massive amounts of supply chain data.  

#5. Use Advanced Analytics 

Artificial intelligence techniques such as machine learning power predictive analytics to identify patterns and trends in data. Insights help manufacturers optimize various aspects of the supply chain, including inventory levels, procurement, transportation routes, and many other activities. Artificial intelligence uncovers insights that can allow manufacturers to improve their bottom line and provide better customer service.  

#6. Collaborate with Suppliers and Partners 

Sharing data and insights can help develop strategies aimed at improving supply chain efficiency and developing innovative products and services.  

#7. Train and Educate Employees 

The more your teams know about advanced analytics techniques, especially artificial intelligence, and how to use and interpret data, the more value you can derive from your supply chain data. Plus, with demand for analytics skills far exceeding supply, manufacturers will need to make full use of the talent pool they already have.  

Learn More 

Hopefully, you’ve found these best practices for using data to optimize your supply chain useful and actionable. Here’s my recommended reading list if you’d like to learn more about data-driven business and technologies:   

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Author: Teresa Wingfield

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Mar 30 2023
Deciphering the Data Story Behind Supply Chain Analytics

When it comes to supply chain data, there’s an intriguing story to be told. If businesses have access to accurate data in real time about their supply chain operations, they have tremendous opportunities to increase efficiency, reduce costs, and grow revenue. Here’s a look at some of the types of supply chain data and the data story that supply chain analytics can reveal.

Procurement Data

This includes information about the type, quality, quantity, and cost of raw materials and components used in the production process. Analyzing spend can help businesses identify areas where they can reduce costs and make data driven decisions about how to best allocate their budget. For example, real-time comparisons of supplier pricing can help sourcing teams negotiate more favorable prices.

Supplier Data

This includes data about suppliers, such as their performance history, delivery times, and product quality. Supplier data is key to reducing order fulfillment issues and to identifying and proactively planning for supply chain disruption. Companies are increasingly leveraging supplier data in real-time to enhance their environmental, social and governance efforts.

Production Data

This includes data about manufacturing processes, including production schedules, output levels, and equipment utilization and performance. Faster insights into production data can help optimize material availability, workforce and processes needed to keep production lines running. Businesses can also more quickly spot quality control issues and equipment problems before they lead to costly downtime.

Inventory Data

This includes data about the quantity and location of inventory, inventory turnover and safety stock requirements. Demand forecasting using predictive analytics helps to determine the right level of inventory. Real-time visibility is essential to dynamically adjust production up or down as demand fluctuates and to offer promotions and sales for slow-moving inventory.

Transportation Data

This includes data about the movement of goods from one location to another such as shipment tracking, transit conditions and times, and transportation costs. Predictive analytics can estimate transit times to determine the best possible routes. What’s possible today was inconceivable a decade ago: using sensors to track things such as temperature and safe transportation at any point in time to protect goods and improve driving habits.

Customer Data

This includes customer data such as order history, purchase behavior, and preferences. Companies can meet customer expectations and increase sales when they understand and anticipate what their customers need – and when they are able to create personalized experiences and quickly adjust the supply change based on constantly changing customer behavior.

Sales Data

This includes sales data such as revenue, profit margins and customer satisfaction. Companies use demand forecasting based on past sales to help them adjust production, inventory levels, and improve sales and operations planning processes.

Create Your Data Story

What’s your supply chain data story going to be? It all depends on the data platform you choose to process your supply chain analytics. The platform will need to be highly scalable to accommodate what can be massive amounts of supply chain data and must support real-time insights into supply chain events as they happen so decision makers can form next-best actions in the moment.

The Avalanche Cloud Data Platform provides data integration, data management, and data analytics services in a single platform that offers customers the full scalability benefits of cloud- native technologies. The Avalanche platform provides REAL, real-time analytics by taking full advantage of the CPU, RAM, and disk to store, compress, and access data with unmatched performance.

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Author: Teresa Wingfield

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Mar 17 2023
How to Use Data to Get More Visibility into Your Supply Chain

Supply chains have undergone—and continue to experience—major changes and disruption. Worker shortages, rapidly changing customer demands, logistics problems, transportation bottlenecks, and other factors have all contributed to challenges. Even sales patterns that used to be easy to predict, such as those based on holidays and seasonal buying, have become much harder to understand, amplifying the need for visibility across the entire supply chain. 

Business and consumer needs change faster than ever, which has a ripple effect across supply chains that are trying to keep up. On top of this, global supply chains have become increasingly complex, making them more susceptible to delays caused by everything from inclement weather to shipping problems to raw materials shortages.  

Keeping the supply chain moving without interruption places new demands for data and analytics to provide visibility and insights. A supply chain that’s driven by a modern approach to data and analytics enables new benefits, such as improved operations, enhanced demand forecasting, increased efficiencies, reduced costs, and better customer experiences.   

Supply Chain Analytics Keep Modern Supply Chains Running 

Data that can provide visibility into supply chains is coming from traditional, new, and emerging sources. This includes enterprise resource planning and point of sale systems, a growing number of internet of things (IoT) devices, inventory and procurement solutions, and more.  

Customer-centric supply chains integrate additional data to better understand the products and services consumers want. This entails data across social media, purchasing histories, and customer journeys to have insights into customer behaviors and sentiment.  

Supply chain analytics and enterprise data management capabilities are needed for organizations to know where their products and materials are at any moment and identify ways to optimize processes. These capabilities, for example, allow companies to track and trace products—from parts to sub-assemblies to final builds—as they move from one location to another through the supply chain until they arrive at their final destination. That destination could be a retail store or a customer’s front doorstep.  

Supply chain visibility helps organizations minimize risk while identifying opportunities, such as improving planning to avoid higher cost next-day shipping to meet tight timeframes. Better planning allows companies to use less expensive shipping options without causing unexpected downtimes in factories.  

Visibility is also essential for building resilience and agility into the supply chain, allowing the business to pivot quickly as customer needs change or new trends emerge. The enabler of visibility, and for insights delivered at every point across the end-to-end supply chain, is data. When all relevant data is brought together on a single platform and readily available to all stakeholders, businesses not only know where their parts, components, and products are, but they can proactively identify and address potential challenges before they cause delays or other problems.   

A Growing Need for Supply Chain Resilience  

Although companies need a resilient supply chain, most are not achieving it. According to “Gartner Predicts 2023: Supply Chain Technology,” by 2026, 95% of companies will have failed to enable end-to-end resiliency in their supply chains. “Due to the last few years of major and minor supply chain disruptions, many companies are looking to drive more resiliency into their supply chains,” according to Gartner. “They see this as a key means to help them buffer against the impacts of these ongoing disruptions more effectively.” 

Improving resiliency requires the business to move from analysis on basic forecasting data to connecting and analyzing all data for real-time insights that produce more accurate and robust forecasts, uncover opportunities to improve sustainability, and meet other supply chain goals. The insights help organizations identify macro- and micro-level issues that could impact the supply chain—and predict issues with enough time for the business to proactively respond.  

Manual processes and outdated legacy systems that won’t scale to handle the data volumes needed for end-to-end insights will not give organizations the resiliency or visibility they need. By contrast, a modern cloud data platform breaks down silos to integrate all data and can quickly scale to solve data challenges.  

This type of platform can deliver the supply chain analytics and enterprise data management needed to reach supply chain priorities faster. For example, manufacturers can know where raw materials are in the supply chain, when they’re due to arrive at a facility, and how a change in transportation methods or routes can impact both operations and profitability. Retailers can know when items will be available in warehouses to meet customer demand, fill orders, and nurture customer journeys.  

Easily Connect, Manage, and Analyze Supply Chain Data 

Organizations that have the ability to bring together data from all sources along the supply chain and perform analytics at scale can gain the visibility needed to inform decision making and automate processes. With the right approach and technology, organizations can turn their supply chain into a competitive advantage. 

The Avalanche Cloud Data Platform makes data easy. It simplifies how people connect, manage, and analyze their data to modernize and transform their supply chain. With Avalanche’s built-in data integration, businesses can quickly build pipelines to ingest data from any source. Anyone in the organization who needs the data can easily access it to make informed decisions, gain insights, expand automation, and optimize it for other supply chain needs.  

Related resources you may find useful: 

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Author: Brett Martin

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