Band-Aids were invented in 1920 by Earle Dickson, a Johnson & Johnson employee, to help his wife Josephine, who often cut herself while cooking. Initially handmade and not very popular, they became widely successful after being mass-produced in 1924 and have since sold over 100 billion worldwide. Overtime, the term was genericized to represent a temporary fix for a problem.

Today, we have a problem. The traditional definition of supply chain planning lags business needs. I have largely given up on the large solution providers to close the gaps. The reasons are many — scalability, talent shortages, technology reliability, changes in management, and technology platform limitations–I could go on an on, but I will not bore you.

Existing solution providers do not see the problem. Tech sales teams are making great money, but most are out of touch with their clients. The demand for solution automation is high, but yet, they accelerate hype cycles by chasing false idols like the Gartner Magic Quadrant which is meaningless in today’s market.

When the planning solutions do not meet expectations, and there are holes in required functionality, companies struggle with what to do. The issues become acute. Dissatisfaction mounts.

In parallel, technologies for data scientists are evolving at a rapid pace. Palantir is now worth more than the total value of all supply chain planning applications combined. The approach is expensive, and Palantir does not understand supply chain. Short on domain expertise, when using Palantir technologies, business leaders need to craft a strategy for an interpreter to sit between the line of business team and the data scientist teams to attempt to craft a solution. Good data scientists are at a premium, and companies struggle to define business problems clearly to drive success. Palantir is not the answer.

The Beauty of A Band-aid

This problem is not going to be fixed over night. Nor is the answer hanging the term AI all over software marketing to promise non-existent innovation on old platforms. (What I see from most technology vendors today.) I firmly believe that we should not AI stupid.

Yesterday, I woke up at 2:00 AM to catch a flight to Chicago to attend Lyric’s Empower conference. I try to avoid vendor conferences, but I wanted to attend this one, because I am intrigued by the approach. The solution, built by the prior founders of Opex Analytics, with a brand promise of– Built for Builders. Backed to Scale— is new.

Prior to the conference, the company announced raising $43.5M in Series B funding led by Insight Partners with participation from Primary, Permanent Capital Ventures, VMG Partners, PSP Partners, and NewBuild VC—bringing total investment funding to $67M.

My take away? I think Lyric is a Band-aid to help companies close the gaps between promised and delivered capabilities of planning software and enable quick solution turn around by making it easier for business leaders to work with data science capabilities at scale.

Observations

I arrived at the conference at 8:00 AM, and it was like old-home week. Sales personnel from my network that had left Anaplan, Blue Yonder, Coupa, Kinaxis, o9, Optilogic, and SAP, flocked towards me. Each shared their excitement on their choice to join Lyric and the difficulties of selling traditional software in today’s market.

As I grabbed coffee before the conference started, nine business leaders voluntarily shared their stories on the difficulties of implementing Kinaxis, OMP, o9 Solutions, and SAP. Genpact and E&Y consultants volunteered their stories that validated the issue. The excitement was real, and the stories flowed. I struggled to get to my seat.

I took a seat at a back table, took out my white moleskin notebook and took notes. I always feel the most at ease with a yellow mechanical pencil between my fingers. (Yes, I am that nerdy-kind of gal.) I filled several pages as Ganesh Ramakrishna, Founder, spoke of his vision of A³ (autonomous, agentic learning, and learning through large language models). As he spoke, I smiled. I found the clear definition refreshing. At break, we spoke about the need to build ontological frameworks to drive supply chain semantics. The speed of the demo solution was impressive as was the knowledge of his team.

So, would I recommend companies replace old-fashioned supply chain planning platforms with Lyric? My answer is no. However, with the number of gaps of today’s solutions, if a company needs to write custom code for existing applications, they should contact Lyric. The excitement of a team that is steeped both in data science and supply chain is great to see. The platform is enterprise class, and the no BS approach is refreshing.

Conclusion

So, just as Earle Dickson’s wife needed a band-aid, so do supply chain leaders today. I encourage you to kick the Lyric tires and find out what they are about. Let me know what you find.