This interview analysis is sponsored by Arkestro and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.
Over the last decade, the supply chain management software and procurement market has expanded more than twice. Despite these advances, numerous challenges in the post-pandemic era persist, posing significant hurdles for logistics leaders.
A 2021 survey of supply chain leaders from the American Productivity & Quality Center reported that 40% of respondents reported that their biggest supply change challenges involved a “lack of support for collaboration across functions and externally.” Perhaps more tellingly, 42% percent reported their biggest challenge was “too much change.”
Emerj CEO and Head of Research Daniel Faggella recently sat down with Edmund Zargorin, Founder & Chief Strategy Officer of Arkestro, and Len DeCandia, former Chief Procurement Officer at Johnson & Johnson, for a wide-ranging conversation focused on adapting to the evolving supply chain landscape by prioritizing data quality and talent development, and the importance of audience-centric communication in storytelling.
In the following analysis of their conversation, we examine three key insights for procurement leaders in overcoming two main obstacles to AI adoption:
- Adapting to a dynamic supply chain landscape through data quality and talent focus: Organizations should rebalance investments, prioritizing data quality and talent development in the supplier base and procurement systems to adapt to the evolving supply chain landscape.
- Enhancing efficiency through user-centric design: Prioritizing a user-friendly design, especially integration with prevalent communication channels like email, can enhance procurement efficiency by simplifying processes and minimizing onboarding efforts.
- Telling compelling stories in audience-centric communication: Solid skills in data analytics are crucial, but equally important is the ability to tell compelling stories, requiring an understanding of the audience’s pressures and interests.
Guest: Edmund Zargorin, Founder & Chief Strategy Officer, Arkestro
Expertise: Entrepreneurship, Artificial Intelligence, Operations Management
Brief Recognition: Edmund Zagorin is the Founder & CEO of Arkestro Inc. Before founding Arkestro, he worked as a strategic sourcing advisor specializing in digital process transformation for large health systems and the Fortune 1000, with a focus on predictive pricing, process design, and data operations. He graduated from the University of Michigan with a degree in International Affairs and Public Policy.
Guest: Len DeCandia, Advisory Board Member/ Consultant, Leonardo DeCandia, P.E. LLC; former Chief Procurement Officer for the Johnson & Johnson Pharma Group and Estee Lauder Companies, respectively.
Expertise: Engineering, Manufacturing, Sourcing and Supply Chain Management
Brief Recognition: Len is an award-winning Supply Chain/Procurement Executive with 40+ years of experience. During Len’s most recent assignment as Global Chief Procurement Officer at Johnson & Johnson, he led a generational transformation to a center-led, enterprise-wide operating model. He is currently an advisor to companies seeking to transform their procurement and broader supply chain management processes for productivity, governance, and digitization, particularly in healthcare, pharmaceuticals, and adjacent industries.
Adapting to a Dynamic Supply Chain Landscape through Data Quality and Talent Focus
Edmund opens the conversation by discussing the primary challenges around data quality issues within procurement processes. He explores the need for a solid foundation in data to track spending across various parameters such as geographies and product lines. These data points are essential for cost reduction — a top priority for large enterprises — as well as proactive decision-making and risk management in the supply chain.
He also delves into a specific challenge in manufacturing procurement: the data quality issues between individual plant locations and corporate procurement. These issues include duplicate and missing records as well as other discrepancies that complicate the overall understanding of spending patterns.
“So the pressure in a lot of companies is how can we get our demand forecast to be more granular, more specific, and more targeted for individual locations because that’s how you unlock major cost reductions,” says Edmund. “And that’s where people are running into this data challenge between the plant and corporate item-level data quality.”
In line with Edmund’s points about challenges in procurement, Len emphasizes that the past decade has seen significant investments in customer relationship management, prioritizing the ability to get customized products efficiently. However, this has led to an imbalance, with insufficient investment in the supplier base and employee resources. Len suggests that it’s now crucial for organizations to rebalance these investments, particularly in the context of a changing supply chain landscape.
Len’s emphasis on the importance of data aligns with Edmund’s focus on data quality issues in procurement. Len argues that data is not just a choice but a necessity that requires investment in people and relationships.
He mentions that organizations must invest significantly in talent and procurement systems as supply chains diversify and move toward more localized production (“make it where you sell it”). These investments are crucial for effectively managing relationships within the supply chain, as highlighted by Edmund’s discussion of the challenges and transformations in procurement.
Enhancing Efficiency Through User-Centric Design
Len describes a shift in the last decade towards outsourced cloud-based technology, forcing congruent changes in the role of CIO.
While in the era of ERP systems, Len insists, CIOs were elevated to executive suites and managed large internal teams. Now, the advent of cloud-based technology has decentralized this process. Procurement organizations, in particular, play a more significant role in this new landscape because many competencies and skills previously invested in internally are now outsourced:
“A lot of the technology investments that companies are making are cloud-based, managed with a third party, and the relationship now is between the functions and those technology providers. It’s not being funneled through an IT organization. Therefore, these organizations really need to think about how they’re going to use technology, and how they’re going to translate that technology, their own practices within their own organization. It’s a big, big leap from the old days.”
-Len DeCandia, Advisory Board Member/ Consultant, Leonardo DeCandia, P.E. LLC
Edmund discusses the new paradigm around AI and how machine learning models are transforming the procurement landscape. With the increased ubiquity of AI and improvements in machine learning models, there’s a shift in perspective. Edmund notes that these models are helpful for live processes and effective in cleansing and structuring foundational data.
He mentions an emerging trend termed “procurement orchestration,” where data is integrated into live procurement processes, such as sending a table to a supplier for review or managing a set of documents. Machine learning models then power these processes, orchestrating various actions.
Edmund then discusses the design and user experience considerations in developing procurement tools. He mentions that a significant portion of procurement work is done through email. In response, his team deliberately created a user interface (UI) integrated into email systems.
Inspired by the success of DocuSign, which simplified complex processes like document review and approvals, the goal is to streamline procurement similarly. Edmund emphasizes the simplicity of the UI, eliminating the need for a separate login or extensive onboarding process.
Edmund then introduces the “best next step” or “best next action” concept in AI. It uses predictive models to provide intelligent recommendations to users throughout the procurement process. Integrating these predictive models with the email-based UI aims to make change management more effortless.
These functions are especially crucial in industries that are becoming more accustomed to extensively using digital apps or systems. “That’s really the future of AI in this space,” Edmund emphasizes. “Because you’ll have business leaders who say, ‘Look, I don’t need to understand it. I don’t want to understand it. I just want to see is this going to impact my P&L?'”
Telling Compelling Stories in Audience-Centric Communication
Len emphasizes that while having foundational skills in data analytics is essential, the ability to tell stories is equally crucial. He notes that internal and external business partners are vital to understanding the audience. Such understanding involves empathy and awareness of the pressures and interests that audience faces everyday and is essential for making stories about data and information more accessible to wider audiences.
He advocates for identifying and elevating individuals interested in digital transformation, even if they are not in traditional leadership roles. Changing the definition of a successful contributor and providing opportunities for those interested in the journey is crucial. In the context of AI, Len echoes the sentiment that the technical aspects cannot be the only focus at the expense of knowing how to translate technical knowledge into value.
In turn, Edmund highlights the unprecedented opportunity to make quick technological strides in digital transformations, encouraging a focus on “responsible speed.“ He insists there may be more effective approaches in a rapidly changing technological landscape than committing to long-term projects with a two-year roadmap.
Instead, Edmund advocates for achieving tangible and reportable results in weeks (typically two to six weeks). A more rapid results-driven approach will improve how teams measure success and ensure that technology solutions align with the current pace of change.
Lastly, Edmund addresses the shift from what some call “the era of learned helplessness“ to an era where organizations acknowledge that having insufficient data is a choice. He emphasizes that organizations can make choices to improve their data quality and decision-making processes. While he acknowledges that building these entertainment capabilities requires serious investment, perseverance, and cultural change, he believes organizations can drive transformative change with the right culture and courage.
