Forecasting Sucks!
Well, not really, but it is incredibly difficult to do well.
It takes a special level of capacity and love for details to be really good at it. Most professionals have to make a tradeoff between model fidelity and having it ready in a timely manner. Doing it well, fast, and with high fidelity takes a level of AI/ML and inferential statistics that is eye-watering. We take care of that. We eat the complexity of the most complicated inferential statistics parts of forecasting and make it easy. We want our finance professionals to be able to focus on the business instead of the math and statistics.
About Nate, our Founder:
Nate Kaemingk is founder and Chief Forecaster of Better Forecasting. In his words:
I’ve been doing forecasting and inferential statistics for my entire career. It started when I was a mechanical engineer and had to solve a chemistry problem for Diesel engine emissions. That multi-year project started me down the path of predictions and the basis of machine learning that I use today. The business math I learned in my MBA is much less complicated, thankfully, but the tools are even more powerful.
Since then, I’ve worked with multiple Fortune 500 companies on forecasting and predicting product line financials and strategies for those products. With titles like Global Product Planning Manager, and Director of Digital Engineering, I’ve had visibility to $20+ Billion in product pipeline. I’ve also run several of my own businesses, and I’ve been a Fractional CFO for several companies. So I’ve used this stuff every day in practical applications.
I broke Excel one too many times with my attempts to do inferential and probabilistic forecasting and modeling in Excel. Yes, it worked, because Excel is amazing and I love it. But, it was limited to about 20 inferential models that had to be manually updated, and it broke too often. I decided to build myself a tool that takes care of this part, and in the process, I ended up building the company you see today.
Core Values:
Learners first: We endeavor to never stop learning. Every business, market, and person have a unique perspective that can be uniquely valuable when listened to, harnessed, and applied.
Integrity and honesty: Be honest, even if it hurts. Some things aren’t for sale. It is uniquely important to quantify and state the limits of capability and the basis of assumptions in forecasting. Be exceptional at it.
Be exceptional at what is hard: This technology and space is not for the weak. It is exceptionally difficult and complex to master. We endeavor to become masters and be exceptional where things are difficult.
Eat the complexity: Just because our space is complex, doesn’t mean that the application of the technology needs to be complex. We take on the complex so that our customers can live in a simpler world.