Here is a helpful post on how Blockchain can unlock the true potential of ESG initiatives by one of our closest partners: Finboot. We have been working with Finboot over the past 3 years envisioning and solving real-world, customer needs with blockchain technologies.
It’s a great read, don’t miss out on it!
Read it, here!
Digital Supply Chain Institute conducts annual surveys of leading issues, identified by global supply chain leaders, impacting supply chains.
This report is part 1 of the 2019 annual survey and covers the following topics:
Survey reached from over 150+ supply chain executives from over 14 countries and survey data was collected between June 15 and July 15 from direct responses and social media. Survey reached across many industries, such as Manufacturing, Consumer Goods, Technology, and many more.
Please reach out to us at vghelani@thecge.net if you have any questions or would like to have a call to discuss survey results.
Download report here.
DSCI has recently completed a major survey of companies from around the world on the impact of the USA-China trade conflict and the immediate measures that should be taken by supply chain professionals.
Here are the key takeaways from the survey:
Please reach out to us at vghelani@thecge.net if you have any questions or would like to have a call to discuss survey results.
Download report here.
This report is based on survey research of top supply chain executives across the world. The Digital Supply Chain Institute is working on four topics that are of high interest to our Digital Supply Chain members and Community; Algorithm Council, Accelerated Change, Revenue Growth and Blockchain. We are doing fact-finding and on-site pilots in each area.
Download report here.
At the Digital Supply Chain Institute (DSCI) we’ve been working with senior executives from 72 companies around the world to develop the tools and insights to accelerate the transformation from a traditional supply chain toward a more powerful Digital Supply Chain.
There are many actions that companies can take to build a leading-edge Digital Supply Chain, but Artificial Intelligence and Machine Learning (AI/ML), is essential to capitalizing on the flood of data instead of drowning in it.
We made a list of the Top Ten Insights that we think will be essential for companies to utilize AI/ML to make rapid progress. Consider which of the Top Ten are priorities for your organization.
The Data 80/20 Rule – Getting it Right
What’s the optimum mix of collecting, cleaning and storing data versus analysis and execution? Companies should spend 80 percent of their effort on analyzing data and making decisions and 20 percent on collecting and cleaning the data. Unfortunately, too many companies are mired in the opposite equation. Hire the data analyst and data scientist talent who know how to collect, manage and analyze data. Educate line and staff people on the skills needed for data-driven decision-making. And stock up on AI/ML talent.
Real-Time Demand Shaping Beyond Forecast Accuracy
Forecast accuracy is important but Digital Supply Chains must do more; they must increase and manage demand. How? Invest in the technology to capture new data, develop new algorithms and use it to make decisions in real time. Incent people to collaborate to make things happen.
Battle of the Algorithms
Companies must collect more customer data and use AI/ML to develop algorithms that win in the marketplace. Algorithm-based approaches that can learn, improve, and eventually reveal hidden patterns in large volumes of data are within our grasp. By uncovering hidden patterns and unlocking predictive power in information, supply chains will have the best chance of competitively satisfying customers. Just look up the valuations of some such algorithm-driven companies as Amazon, Google and Netflix.
Visibility Reduces Risk
Visibility into suppliers and customers is an essential way to reduce the risk of supply chain disruption. Developments in tracking and analytics will enable a true, transparent, end-to-end supply chain. This new transparent and secure system will be enabled by Blockchain, allowing for trust and increased visibility.
New Talent Management for Supply Chain Talent
New people with data scientist skills and deep analytical skills must be found and current people must be trained in data-based decision making. Develop a new talent management plan with three components: First, hire people with the skills to develop algorithms that better predict and manage customer demand. Second, improve the overall level of data-driven decision-making skills across the workforce. Third, change job descriptions and develop new compensation plans to attract and retain people with the right experience.
New Business Models We Can’t Anticipate
Get the data and use AI/ML to discover new ways of adding value to customers. Define critical business problems and determine what new data sources should be identified and gathered to help address them. Once companies have identified, gathered, processed and aligned large “lakes” of data, they will start to discover that there are new ways to create value in the marketplace that were previously hidden.
New Product, New Wins
Digital Supply Chain knowledge should be added to the process of deciding what to make or do to drive growth. Winning companies will adopt a more integrated cross-functional view that includes their DSC to gather important customer insights and information. They add value by being in touch with the customer and learning from them through delivery and infield use. This insight will help develop algorithms that best predict the customer demand for the new product and analyze DSC availability to produce and deliver.
Dynamic Pricing
Rapidly adjusting pricing as market conditions change will alter the way that the supply chain is managed and drive profitability. Predictive analytics will be used to continually set and adjust pricing for more and more products and services. AI will guide companies on customer buying behavior, mega trends and history. New production and delivery methods will enable companies to seamlessly integrate the speed of getting the product to the customer into their dynamic pricing.
Own It or Clone It and the Tools to Know
Decide what DSC functions should be outsourced and which should be revenue producers using new tools. More companies will insource production as 3D manufacturing lowers labor costs and permits operation near the target end customer. The challenge will be to help make the right “in or out choice” and then make either choice work well. AI/ML will be used to gather and control production information either way.
Algorithm Council: The Secret Weapon
Form a cross-functional team to create algorithms that drive data collection, analysis, market focus, manufacturing, inventory and a host of other critical business decisions. We call this team the “Algorithm Council.” This team will include members from Sales and Marketing, Supply Chain, Information Systems, HR, Enterprise Risk Management and Finance. The primary purpose of the Algorithm Council is to build algorithms addressing the right issues that lead to market dominance and make decisions that increase sales while increasing margin and/or lowering cost.
Each company should set out a plan for addressing these insights. Not all insights can be handled at once so set priorities and support these actions with an investment plan and clear revenue and productivity goals.
Customers will love what they get and will soon insist that a company have a true Digital Supply Chain or they will move their business elsewhere.
Companies work hard to understand, predict and manage customer demand. They know the data they have, and collect from an array of sources, is valuable. They understand that the Internet of Things (IoT) is in full swing with everything from electric toothbrushes to automobiles to credit cards contributing data to it. They are aware of the tremendous power of social media and its profound influence on society and business.
Yet, most companies are frustrated that they are unable to harness this data, clean it, analyze it and apply it to drive demand and the needed supply chain decisions to capture this demand. They feel that their ability to understand, predict and swiftly respond to changes in customer demand is…inadequate.
One of the causes for this is data that is either incomplete, or too narrow in its scope. Another reason is organizational. Companies are typically organized into silos that prevent effective data gathering, data sharing, data analytics and data-based decision-making. For example, many supply chain organizations lack access to the customer data collected by their sales department. They simply rely on the sales forecasts produced in each region. Similarly, many sales teams have limited knowledge of customer preferences for logistics and service requirements.
When a product or service becomes a big hit, the supply chain has a hard time catching up with demand. When a product or service does not sell, then supply chains tend to be slow to reduce cost.
Artificial Intelligence and Machine Learning (AI/ML) is currently being used most often in supply chain manufacturing. Our research, conducted with senior executives from 72 companies around the world, highlighted that AI/ML should also be applied to developing demand for new products and services, and in the management of the flow of goods and services to the consumer. Sales force intuition has not proven to be an accurate indicator of high value and demand for products and services.
“Supply chains used to be about coordinating operations and managing transactions, and much of this was manual. Technology and the digital economy have changed this irreversibly,” said Robert Sinclair, President, Supply Chain Solutions, Li & Fung. “Today transactions are automated, and supply chain management is about aggregating and analyzing data end-to-end to drive operational efficiencies and create intelligence about markets and players.”
The good news is that the use of AI/ML, driven by specific algorithms, can unlock the potential for companies to anticipate and shape future demand and predict the likelihood of future risks.
The secret to unlocking this new fountain of demand and supply is to create an empowered cross-functional team to ask the right questions, collect the right data and build the right algorithms to make the right data-driven adjustments to stay ahead of customer needs and desires. Effective use of AI/ML will require people to define the right problems and perhaps, most important, use their judgement. Imagine a team that had deep customer insight and includes members from Sales and Marketing, Supply Chain, Information Systems, HR, Enterprise Risk Management and Finance.
The concept of the Algorithm Council represents a fundamental management shift away from making situational supply chain decisions based on slow moving batch information, and instead pivots toward a machine-driven approach that is informed by integrated subject matter expertise and insights.
The Algorithm Council’s charge is to develop and continuously improve algorithms that will enable companies to create opportunities to not only sense demand but to also more effectively manage and stimulate it closer to real time than their human equivalents. AI/ML is essential to capitalizing on the flood of data instead of drowning in it.
Where do you start? Begin with taking stock of the algorithms you are currently using within your company. How many are there? What are they being used for? Who else other than the owner of that algorithm knows its purpose? Then ask: “What do I want to know about market demand that I can’t presently assess?” And, “How can I get that data and apply it to give me competitive advantage given the assets we have presently?” Next, convene the relevant high-level stakeholders to create a new cross-functional team–the Algorithm Council—to execute a management process to better stimulate and meet demand through a dynamic handling of algorithms.
Some companies have started to experiment with Algorithm Council-like committees, but few have incorporated the right skills and the high-level authority to build and refresh market-winning algorithms that drive customer success. Creating a successful Algorithm Council will require leadership to drive organizational change that breaks down silos and fosters a new era of cross-functional collaboration where success is interdependent. Companies that do this will leap ahead their competition and be positioned to capture customer demand as it arrives.
Irving Wladawsky-Berger, CGE Fellow, describes how companies are looking beyond efficiency as the point of the Digital Supply Chain in his Wall Street Journal, CIO Journal article.
With the rapid advent of new technologies with far-reaching middle-market implications such as autonomous fleets, 3D printing, e-brokerage and Internet of Things platforms, it is now more important than ever for business logistics to be carefully and competitively orchestrated.
A digital supply chain (DSC) focused on customers can have a tremendous impact on an organization’s financial performance, helping to cut costs and boost revenue, according to a report last year from The Center for Global Enterprise (CGE).
Substantial investments in supply chain resilience have enabled companies to vastly improve their capacity for bouncing back after a disruption. But the digitization of supply chains is introducing new demands on company operations that require a different approach to building supply chain resilience.