Supply Chain Shaman

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Mourning the Death of the Data-Driven Supply Chain Guy

Joe died Wednesday.
As a great supply chain leader and my client for ten years, his energetic spirit always lifted my soul. In 2018, after a severe operation for kidney cancer, Joe declared to me in a positive voice that he was going to beat his diagnosis of stage 4 liver, brain, and lung cancer. I put the phone on mute as he spoke and sighed. Joe invited me to dance with him at the post-COVID-19 celebration party that he was planning. The event was to celebrate his journey of beating cancer. Sadly, this is one event that I will not be able to attend.
I was never as upbeat as Joe on his journey of cancer and asked how I could help. He quickly replied and asked that I call him each week and talk supply chain. He said, “Please don’t treat me as a sick man and feel sorry for me. Help me to invigorate my brain.” So, for two years, I called Joe each week to talk supply chain. I will miss our time together.
I remember one call vividly. Joe and I had an intense discussion on big data analytics and what he was learning by tracking his illness with his oncology team. We applied his insights to supply chain management.
Joe was always a numbers guy. His oncology team, composed of three physicians, was diverse. The older physician was a stabilizing force, while the younger doctor on the team was always sparking new ideas for treatment. His primary care doctor provided continuity.
The team worked in three different cities and healthcare providers but used digital imaging and testing to coordinate the treatment plan. Joe facilitated many of the discussions and attributed his treatment plan’s success to diverse thinking, collaborative technology, and big data discovery.  We abstracted what this meant to his business:
Insights from Images. Joe’s key insight from the treatment was the advancement of medicine through the digital interpretation of images. Joe, a leader in the agricultural industry, spoke of images to solve supply chain problems. We brainstormed on using images for port unloading lead times, crop yield projections, manufacturing quality, and corporate sustainability issues. He lamented that the large technology providers were not doing enough to use digital images as an input into supply chain decision making.
Diverse Teams. He loved the physicians’ dialogue and the differences in points of view, and his ability to use his data analysis skills to be actively involved in his treatment. Often bringing his own patient data to the meeting, he sparked friction. Joe often commented that the disagreements between the physician team brought better results. His experience with data scientists was mixed, and he struggled with why. We discussed the data from the recent talent study and his insights on helping data scientists to be more successful on teams. He strongly felt that it was not enough to hire data scientists but to create a learning environment for teams to learn from each other.
Figure 1. Top Openings in Supply Chain
Clear Outcomes. Companies’ toughest problem is not using big data analytics, but getting clear on the questions to ask. Joe would comment that it is easier to guide patient care because of clearer definitions of success than to lead a supply chain team when the definitions of supply chain excellence are muddy.
Data Wrangling. We had long discussions on supply chain master data and the industry’s naivety on the techniques for R, Python, and the use of unstructured data. We spoke of the lack of current leadership in the technology space to make this easier for supply chain leaders.
Rest in peace Joe. I smiled when your wife told me that she had decided to do an autopsy because your sudden death surprised your oncology team.  She told me that a data guy would want the team to know the definitive outcome. I agreed. I will miss you so.

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