AI in Supply Chain: Enhancing Data Quality with Rob Bailey, CEO of Backbone AI

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TL;DR

• The supply chain software market is fragmented, making it difficult to streamline processes and achieve seamless integration.
• Building a positive work culture is crucial, even in a remote setup, to ensure team cohesion and productivity.
• Staying updated with AI advancements through networking and continuous learning is essential for maintaining a competitive edge.
• Automating data processing with AI can significantly improve supply chain data quality and reduce dependency on manual methods like spreadsheets.
• The growing acceptance of AI in mainstream business processes highlights the importance of demonstrating value and ROI to overcome resistance from technologically inexperienced companies.

Catch the full episode here:

The Plight of Data QuWho is Rob Bailey?

In this week’s episode of Pioneers, we sat down with Rob Bailey, Founder & CEO of Backbone AI, to discuss the role of AI in supply chain operations. 

Rob’s interest in AI started in the 90s with the book Complexity, which influenced his thoughts on using technology to mimic artificial intelligence. He became deeply involved with AI-related companies over 10 years ago and continues to drive innovation and advancements in the field to this day.

“I’ve been working on AI companies for more than 10 years, and I have never seen such an exciting time to be doing AI.“  — Rob Bailey

Rob highlighted the value of global supply chains at $25 trillion and noted that annual software sales for managing these chains range from $25 million to $3 billion. He pointed out that many of these supply chain organizations still rely heavily on people exchanging spreadsheets via email. 

This situation presents a significant opportunity to leverage AI to create data bridges between various applications and enhance efficiency and connectivity.

"Our mission is to set out to build data bridges between different applications using AI…Predictive AI has enormous potential for supply chains“  — Rob Bailey

He further explained how AI offers a solution and paves the way for groundbreaking advancements in this domain.

Backbone AI's Approach

Rob’s company, Backbone AI, originated when he was involved with a blockchain fund and explored its potential in supply chain management. This led him to pivot from blockchain to using AI to process various data between suppliers and distributors in the industrial sector.

“I was very focused on how different companies could use blockchain technology to make supply chains more efficient. We came to the conclusion that there was actually a bigger opportunity, which was to use AI to actually process all kinds of data that were coursing between suppliers and distributors specifically in the industrial sector in the US.“ — Rob Bailey

Backbone AI's mission was to enhance supply chain solutions data quality by using AI to automate and transform data between different software applications. It aimed to replace the current dependency on Excel spreadsheets and manual data bridges.

The company has successfully secured lead customers, even benefiting from the COVID-19 pandemic, accelerating the shift to online sales and the need for better data quality in supply chains.

Backbone AI's journey offers a concrete example of the transformative role of artificial intelligence in supply chain management. By leveraging AI to process data flows between suppliers, manufacturers, and distributors, Backbone AI has enhanced the quality and accessibility of product data, driving efficiency and growth for its clients.

Backbone AI moved faster by enabling manufacturers and distributors to upload files in various formats (e.g., spreadsheets, CSVs, zip files) to their self-service platform. Once data is uploaded, Backbone AI’s platform ingests and assesses it. The data undergoes iterative transformations based on user requirements, with several rounds of redundant QA to ensure quality. 

Supply Chain Data Quality

“If you have better data, you're growing your online sales faster“ — Rob Bailey

Supply chain data encompasses different information, from product details and inventory levels to shipment tracking and supplier contracts. The involvement of various formats, sources, and systems in data collection and processing compounds the complexity. 

Data quality is a big challenge for supply chain companies. AI is becoming crucial in improving product data as organizations strive to meet the growing demands for efficient and timely deliveries. 

“We came to the conclusion that there was a bigger opportunity, which was to use AI to actually process all kinds of data that were coursing between suppliers and distributors." — Rob Bailey

Inconsistent, incomplete, or outdated data can lead to many issues, including inventory inaccuracies, delayed shipments, and misinformed decision-making.

Financially, it can lead to significant losses due to overstocking, stock-outs, and inefficient resource allocation. Perhaps most critically, it can erode customer trust and damage brand reputation.

Artificial Intelligence in Supply Chain

Approximately 40% of supply chain organizations are investing in generative AI, focusing on knowledge management applications.

Before we explain in more detail the benefits of AI in the supply chain, here is a brief reminder of Generative AI’s abilities:

1. It classifies and categorizes information based on visual, numerical, or textual data.
2. It quickly analyzes and modifies strategies, plans, and resource allocations based on real-time data.
3. It automatically generates content in various forms that enables faster response times.
4. It summarizes large volumes of data, extracting key insights and trends.
5. It assists in retrieving relevant information quickly and provides instant responses by voice or text.

Our solutions at Multimodal, for example, primarily utilize hybrid models that combine generative AI, which creates new data based on input, and predictive AI, which makes forecasts and predictions based on historical data. This combination enables more informed decision-making and automates workflows with ease.

A McKinsey survey showed that a few major CPG companies demonstrated that autonomous supply chain planning can boost revenue by up to 4%, reduce inventory by up to 20%, and lower supply chain operational costs by up to 10%. 

This is solid proof that investing in artificial intelligence in the supply chain can lead to significant revenue growth, inventory reduction, and cost savings.

Benefits of AI Technology in Supply Chain

AI and machine learning algorithms are adept at processing large volumes of data, identifying patterns, and making predictions. Here are several examples of how that translates to supply chain management:

• Enhanced data accuracy: AI algorithms can cleanse, validate, and enrich data, ensuring its accuracy and completeness. This involves correcting errors, filling in missing information, and standardizing data formats.
• Real-time data processing: AI enables the real-time analysis of data, providing up-to-date insights into inventory levels, demand forecasts, and supply chain disruptions.
• Predictive analytics: AI-driven predictive analytics can forecast future trends, demand patterns, and potential bottlenecks, enabling proactive decision-making.
• Automation of repetitive tasks: AI can automate routine data entry and processing tasks, freeing human resources for more strategic activities.
• Personalized customer experience: AI-driven analytics and 24/7 customer service chatbots allow organizations to gain deeper insights into customer preferences, behaviors, and purchasing patterns. This improves customer satisfaction, fosters loyalty, and drives sales growth.

Mainstream Acceptance of AI

Bailey acknowledged initial skepticism around using AI to transform data but noted that the tide is shifting. Companies like OpenAI and their ChatGPT have helped mainstream the acceptance of AI for transforming business processes. 

This growing acceptance is evident as more companies recognize AI’s value in enhancing data quality and operational efficiency. By harnessing the power of AI, as visible in the above potential applications, supply chain companies can transform their approach to data management, improving efficiency, accuracy, and decision-making. 

Selling AI to Non-Tech Savvy Businesses

Introducing AI solutions to an unfamiliar audience requires a strategic approach. The key lies in emphasizing AI’s practical value and ROI rather than its technical intricacies.

Focusing on Value and ROI

Bailey pointed out the importance of delivering value and ROI to customers rather than focusing solely on technology. He said the better data quality of top industrial distributors correlates with faster online sales growth.

“I've been scaling AI companies for 10 years, and there's always been a really key recurring theme: you focus on value, not technology.“ — Rob Bailey

When presenting AI solutions to decision-makers, the emphasis should be on how AI can solve specific problems, improve operations, and contribute to the bottom line. This involves:

1. Demonstrating improved efficiency: Illustrate how AI can streamline operations, reduce manual errors, and speed up processes.
2. Quantifying financial benefits: Provide concrete examples of cost savings, revenue growth, and ROI achieved through AI implementation.
3. Highlighting competitive advantages: Show how AI can give them an edge over competitors, whether through improved customer service, faster delivery times, or better inventory management.

Security and Data Privacy

Bailey stressed that data security and privacy are critical for AI companies. He stated that AI companies must be thoughtful about these issues to succeed, as Fortune 500 enterprises are very savvy about data security, copyright, and provenance. 

"I firmly believe that AI companies must address privacy and data security issues, or they will fail."  — Rob Bailey

He believes market forces will drive the adoption of robust privacy measures, resulting in greater respect and protection for data in B2B compared to B2C scenarios.

Overcoming Resistance

A common issue among technologically inexperienced companies is their reluctance to adopt artificial intelligence. This resistance to new technologies often stems from a lack of understanding or fear of the unknown. 

Overcoming this barrier involves education, clear communication, and demonstrating success stories or case studies that resonate with the company’s needs and concerns.

The Future of AI in Supply Chain Management

When asked how Rob sees AI further transforming the supply chain management of complex industries in the next 5 to 10 years, he said it is vast and still largely untapped. He noted that the future promises advancements in several key areas:

• AI-powered inventory optimization: AI algorithms can analyze historical sales data, market trends, and other factors to optimize inventory levels, reducing waste and ensuring product availability.
• Fleet management and logistics: AI can optimize shipping routes, predict maintenance needs, and improve overall fleet efficiency.
• Robotics and automation: Integrating of AI with robotics can revolutionize warehouse operations, from automated picking and packing to intelligent inventory management.

By automating high-volume, repetitive tasks, AI allows humans to focus on higher-value activities such as QA flows and data optimization. This shift enables workers to engage in more meaningful and impactful work, improving overall job satisfaction and productivity.

Staying on Top of AI Developments

We asked Rob where AI specifically comes in and how they build defensibility in their AI and machine learning models amidst newer models and capabilities. He highlighted their approach of constantly evaluating and benchmarking new technologies. 

To stay competitive for supply chain leaders and operations managers, Rob suggests:

• Engaging with online communities: Platforms like Twitter and LinkedIn offer valuable insights and opportunities for networking with industry experts.
• Attending conferences and events: Participating in AI-focused conferences, both virtual and in-person, provides exposure to new ideas, technologies, and potential partnerships.
• Continuous learning: Stay informed about the latest research and advancements in AI through webinars, online courses, and industry publications.

Integrating AI in supply chain management is not just a trend but a necessity in today's fast-paced, data-driven world. By transforming and improving data quality, AI paves the way for more efficient, accurate, and responsive supply chains. As the industry continues to evolve, embracing AI will be key to staying competitive and meeting the ever-growing demands of the global market.

Want your business to win the AI game? Check out this episode on how industry data gives you a competitive advantage with Cory Janssen, Co-CEO at AltaML and Former Co-Founder of Investopedia.