When Coe Distributing was looking for the ideal location for their next office ferning distribution center, the company relied on data. CEO James D. Ewing Jr. tapped a team of data analytics students at Katz Graduate School at the University of Pittsburgh.
“They took multiple pieces of information into consideration, including distribution space, cost of distribution space, customer concentration, logistics costs,” explains Ewing. After three months of review, they chose their Houston location up to the block. The company leased a building that spans 150,000 square feet.
AI is a game changer. Currently, only 3.9% of companies report using AI, according to the US Census Bureau. However, 6.5% report that they plan to use AI in the next six months.
$10,000 per semester
After his successful experiment, Ewing then used AI to students to predict which products would be the most successful and utilized predictive analytics. This positions his company as one of the more advanced applications in AI applications, especially for the Pittsburgh-based office furniture company.
Ewing, on his side, funded classes for $10,000 per semester. With the consultant far less than cost, he was able to launch impactful projects and apply data analytics talent to these students to real-world business challenges. This approach allows businesses to test AI solutions at an affordable price.
Data Analysis Division
Considering the challenge of finding a reliable AI consultant, why not take advantage of your student classes? While it is unlikely to find an “AI division” at a local university, university data analytics classes can provide companies with affordable entry points for AI.
Taking the page from Coe Distributing, my company is scaling up and focusing on Harvard's Engineering Sciences 139: Innovation in Science and Engineering Class. Students will create ventures around our proposed product ecosystem of executive coaching tools. They build demonstrations, carry out research and culminate in the final showcase. Shuya Gong, who helps lead the class, is always looking for additional projects.
Your local university or university may have professors looking for similar projects for their students. I reach out to them.
Ready-made solution: eliminate “Administivia”. Companies can start small from student-driven data analytics projects, expand to specific solutions, and ultimately build in-house AI capabilities. For example, when Ewing discovered that AI was helping his company run more efficiently, he brought in an AI solution called Olivia. It was created in collaboration with Forethought, but was then brought in-house for additional development. During the pandemic, his staff spent countless hours tracking answers about product availability. Olivia has become a smart AI bot that can efficiently handle inquiries about inventory availability and order updates. “This is still quite new to us, but we met an amazing reception,” says Jennifer Jubin, Vice President of Customer Experience at COE.
We hire a few students to build AI capabilities within the company. After some projects, Ewing went a step further, hiring several students to create internal data analysis and AI capabilities. He currently uses AI tools in various parts of his business, particularly on his design team. AI can be used to predict trends such as which wood color and design will become popular. AI generates photos, designs furniture, avoid the need for physical mockups and photography, and speeds up the process significantly.
Please do not postpone it. We all feel our way with AI. The university is a great place to start exploring, and all companies, especially scale-ups, should consider the type of partnership distribution with the University of Pittsburgh.
