Opex Analytics History (Part 3)- What We Did
What did our clients pay us to do? To give you a flavor, we did the following:
We helped Fortune-500 type of companies create an AI Center of Excellence where they could build and deploy different AI solutions throughout their organizations.
Ganesh Ramakrishna wrote an article describing how we helped e-commerce retailers with solutions around network design, helping with seasonal capacity planning in fulfillment centers, determining root cause of delivery failures, and cleaning out unproductive inventory with machine learning. Here is an example from Nordstrom.
In the transportation industry, we helped Landstar put AI solutions into the hands of drivers, worked with C.H. Robinson to create a routing engine, and won a supplier award from Nissan.
We created pricing solutions that combined predicting the outcomes of various price points and then determining what price to pick based on the overall business objectives.
We created risk management solutions mitigate supplier chain risks and to better collaborate with suppliers. In one case, our solution allowed a large CPG company to better collaborate with a major retailer and avoid $10M in delivery penalties.
And, there were many more interesting projects.
So, how did we deliver all this work?
This is where it gets tricky. We didn’t fit into a neat category. We were a mix of a consulting firm and a software firm.
We did projects that would look like traditional consulting projects. We did consulting projects where we built and maintained software products. And, we had a software product.
We definitely started by presenting ourselves as a consulting company. However, one of our earlier hires was the head of the software team in India. So, we always knew that we wanted to build and deliver software. You can say that in the early years, we were almost purely brining in revenue from consulting. But, in the background, we were building our software chops. We were building a lot of software solutions by the time we were acquired in 2019. If we had kept going as an independent company, the software side would likely have become much larger.
While it was fun to have this combination, it did create some confusion. We had to figure out how to best present ourselves to customers. We had to make trade-offs in the types of skills we needed in the company. And, people outside of the company had a hard time understanding it.
At the time, when the field of Practical AI was just getting started, we felt like this was the type of firm that the market needed.
For other articles on the history of Opex Analytics, see Part 1- the Timeline and Part 2- the People.