BlockChain Final

AI, Blockchain, Machine Learning: Is Your Data Ready?

And are you asking the right stupid questions to make sure it is?

How to prepare your supply chain data for artificial intelligence, blockchain, machine learning and emerging technology applications.

Data is the new oil – it is becoming more essential than ever before. Technological leaps like blockchain, artificial intelligence and machine learning run on data. They’re already beginning to transform supply chain operations across many sectors. Is your supply chain organization prepared to adopt these emerging technologies and generate the operational improvements to deliver the anticipated ROI? As we’re seeing, digital technology in supply chain enables end-to-end decision-making, visibility into supply-demand information across the network and supports the operational level response in plants, DCs and retail stores. Many organizations have challenges based on legacy processes and systems, possibly decades old, which could significantly hinder the implementation of new data-driven technologies. In fact, industry experts estimate that 35 to 40 percent of all data in supply chain systems is faulty. 1 Many organizations operate today with data that is stored in silos, incompatibly formatted, difficult to access and hard to analyze in a comprehensive fashion. To overcome these barriers, it can be productive to engage a third party to cut through the culture and technology to find out why things are the way they are, and what can be done about it. Sometimes it takes an outsider to ask the obvious questions about processes that employees no longer question – like why do you use 106-inch-high pallets? Why do you handle inbound products four times instead of two? Why do you do use so many manual inputs and bypass your technology? Why did you want to place your new assembly line far from your customer base just because that’s where you have space? The usual answer is, we’ve always done it that way.

Industry experts estimate that 35 to 40 percent of all data in supply chain systems is faulty.

1 Wollenhaupt, G. (2019, Feb. 26). Why humans are blockchain’s weakest link. Supply Chain Dive. Retrieved August 8, 2019, from https://www.supplychaindive.com/news/blokchain-technology-trust-data-integrity-supply-chain/549139/

What’s a stupid question?

Stupid questions aren’t actually stupid. They’re the kind of thing an outsider asks after taking a 30-minute tour of your facilities. They uncover the things that staff and vendors have become accustomed to, like a workaround for broken processes or out-of-date technology. It might be as simple as printing out a form, filling it out, and faxing it to another location. Why not make a fillable form or send the information in an email? The smartest question is, why? Why do we do it that way? Why can’t we change it? Why are we afraid to change it? It often takes asking “Why?” at least five times to get to the root of the problem.

DATA COLLECTION

One of the main benefits of sharing data with a third party is an objective perspective that can cut through the culture and the “We’ve always done it that way” syndrome. Data collection, validation, management and analysis are fundamental to advancing digital supply chain optimization strategies. Even for organizations with internal capabilities, an independent partner with broad industry expertise, technology-enabled tools and an unbiased lens provides actionable support. After a few decades of digital transformation, many organizations still struggle with fundamental data quality management challenges. Do you have the right information at the right time to make an informed decision? If not, why not? Sometimes it takes drilling down into the obvious questions to arrive at smart answers.

DATA COLLE

DATA COLLECTION

Why Share Your Data?

To determine data readiness, organizations hoping to tap the benefits of emerging technology face these difficult questions. Hurdles To Making The Best Use Of Your Data

Sharing data with third parties and vendors will be necessary for implementation of blockchain and artificial intelligence assisted decision-making. Most organizations won’t have the capabilities to support these activities internally. Shared data will flow to vendors for analysis and use in the applications. While due diligence is required, any organization that won’t share data is effectively opting out of the mainstream supply chain.

When Is The Right Time To Share Your Data?

Sharing data with third parties and vendors will be necessary for implementation of blockchain and artificial intelligence assisted decision-making. Most organizations won’t have the capabilities to support these activities internally. Shared data will flow to vendors for analysis and use in the applications. While due diligence is required, any organization that won’t share data is effectively opting out of the mainstream supply chain.

Are You Measuring The Right Things?

Can You Trust Who is Reading Your Your Data

Once your data is cleaned and processed, its value to your organization increases exponentially. The information will drive tactical and strategic decisions that will support predictive analytics and demand forecasting to drive operational efficiencies. You need a partner to trust to interpret your valuable data. An Enterprise Logistics Provider with deep analytical experience can help you identify and focus on the actionable information that you already capture on a regular basis.

While traditional KPIs are still important, it’s essential to understand which data is most valuable to drive decision-making. An experienced Enterprise Logistics Provider will help you home in on the key business drivers and identify those aspects that can be a lower priority.

Do You Know What Your Data Is Trying To Tell You?

For shippers, reports like a least-cost carrier report drive further analysis. There may be many valid reasons why the lowest-cost carrier wasn’t used. Perhaps you’re focused on meeting service level agreements. Or the lowest-cost carrier couldn’t meet specialized parameters of the load. Legacy strategies focused on cost reduction and resource optimization must give way to a culture focused on creativity, resilience and problem-solving. Asking the “why?” questions will move beyond surface-level analysis to uncover hidden opportunities to optimize your processes. Using optimization software and simulation tools can reveal options that drive structural changes to ensure the lowest landed cost to the customer.

Five Best Practices For Independent Support

To position your enterprise for the next generation of technological advancement, we identified some best practices to help you succeed.

Regular data management activity with broad awareness of marketplace competitiveness. Data management is not a “set it and forget it” activity. A culture of continuous learning will be the key. Your enterprise must continually evaluate the integrity of your data collection and management programs not only against your internal requirements but also in light of external developments. Are there gaps or inconsistencies in your data? Will it be available in the formats necessary to support adoption of relevant technology? For example, inventory optimization relies on a body of robust, accurate data. Without it, the results will be skewed and potentially damaging to your supply chain. Why is your enterprise not able to ensure your data is accurate and up to date? Collecting and validating data from disparate systems and reflecting a variety of metrics. Complete and validated data will be the lifeblood of any new technology. Artificial intelligence will only be as smart as the underlying data. Fundamental systems such as the Item Master, Customer Master and Vendor Master must be comprehensively reviewed and corrected. In many cases, you’ll find generic zip codes or item dimensions, or item weights that don’t include pallets. When many actions are still performed manually, these discrepancies can be managed. But when there are thousands of automated transactions each day, the data must be correct to have any hope of realizing the intended benefits of artificial intelligence. Cross-checking among different data sources is vital. Shipment data in the ERP must match the data in the TMS and then be reflected in the actual freight bill. Data from all touchpoints should align. Capturing all the data elements that are available is vital as well. Even though you might not need it immediately, artificial intelligence will be able to get smarter faster with historic data to crunch. Once the data is lost, there’s no going back to recreate it.

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Leveraging capital-intensive technology tools for data visualization, data analysis and mapping. Rather than investing in technology tools directly, a trusted Enterprise Logistics Provider with deep technological expertise can support data management and analysis capabilities as a value-add in the partnership. As a solutions provider, the Enterprise Logistics Provider can stay up to date on the latest developments and evolution, reducing the need for ongoing investments in IT infrastructure. For consumer businesses, customer insights from social media and voice ordering systems through smart home devices have the potential to influence demand forecasting through a new flood of data. B2B enterprises can take advantage of sensor-enabled equipment driving replenishment orders and self-provisioning with a data flow that allows for a very high level of personalization. You must have the ability to manage, analyze and present these new data sources for actionable business intelligence. Look for an Enterprise Logistics Provider partner with the capabilities to support your adoption of the emerging technology.

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Data Managment

Data Elements

Technology Tools

Mapping

Data Analysis

Visibility from summary-level to item-level to manage consumer expectations.

Customers have come to expect near-real-time visibility into the location and estimated delivery times for both B2B and B2C shipments. Also you must have visibility down to SKU level data to inform your decision-making and manage customer expectations. It is vital to understand interrelationships down to the SKU level. If you rationalize one SKU you need to understand the implications for other SKUs. For example, if you drop a slow-selling consumer item, then any accessories or spare parts should be identified for rationalization as well. If you change the sourcing for stores or particular products, you must understand the implications for the new configuration. Otherwise, you could incur higher costs or longer lead times. Even if your supply chain has data flows across multiple tiers to produce a statistical forecast, that is only the beginning of the demand forecasting process today. Market intelligence and economic data can shape the demand curves even further. Tools are becoming available to utilize unstructured, qualitative data, such as what is available from social media to redefine de- mand expectations. Consider your supply chain strategic planning. If your customer data or item data is not accurate, your enterprise could place a distribution center in the wrong location or acquire a facility that is not the right size. With many companies remapping their footprints to move distribution locations closer to the customer, it is a very real concern. Why don’t you have inventory and shipment visibility down to the item level?

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Consider your supply chain strategic planning. If your

customer data or item data is not accurate, your enterprise could place a distribution center in the wrong location or acquire a facility that is not the right size.

Best Practices

Independent, unbiased analysis of data.

It’s important for senior leadership to have an objective view of the data landscape, both internal and external to the organization. A trusted third party will provide that perspective. During World War II, British Prime Minister Winston Churchill created the Special Operations Executive, an independent intelligence organization to provide him with unbiased input and recommendations. Churchill feared any recommendations from the Royal Navy or British Army would naturally be skewed toward their specialties. The same thing is true for many enterprises. The IT Department will typically make technology-based recommendations, while the Operations group will focus on their specialties. Talent is another key component - the IT team must transition to trusted advisors focused on business solutions rather than operate with a technology help-desk mentality. A trusted Enterprise Logistics Provider with deep technology and operational experience can provide that objective view of the data and make recommendations without regard to internal silos. With a holistic, department-agnostic view, senior leaders can have confidence in the foundations of their decisions. There are many factors to consider in ensuring your data is ready to support the next level of technology. Creating a comprehensive plan to clean and structure existing data and capture as much data as possible going forward will deliver benefits across the enterprise. As the digitization of the supply chain continues, those who aren’t able to ask the right questions could be left behind. 2 SCM World. (2017). Future of Supply Chain Report [PDF File]. Retrieved from http://www.neeley.tcu.edu/Centers/Center_for_ Supply_Chain_Innovation/PDFs/Future_of_Supply_Chain.aspx 3 Stafford, David. (2011, Winter,) Churchill and Intelligence – Adventures in Shadowland, 1909, 1953. Finest Hour #149. Retrieved Sept. 18, 2019, from https://winstonchurchill.org/publications/finest-hour/finest-hour-149/churchill-and-intelligence-adven- tures-in-shadowland-1909-1953/

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Is Your Data Ready?

Get on Board!

Emerging technologies are rapidly transforming the future of supply chain. The end of business as usual is very close. But we can’t get there without genuinely reexamining how we collect, manage and analyze information that we collect from our operations, customers and suppliers. Leaders who understand what they need to change within their organizations to optimize these new technologies will emerge as survivors and leaders.

For more information on how a trusted partner can help you prepare your data for the next generation of technology visit TransportationInsight.com.

877.226.9950 www.transportationinsight.com Info@transportationinsight.com

310 Main Avenue Way SE • Hickory, North Carolina 28602

BlockChain R1 12/2019

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