I have been writing recently about the risks associated with buying enterprise software, advances in cloud computing, and the benefits of software-as-a-service. I have tried to keep those articles fairly vendor agnostic. This article is going to be more self-serving. I am basically going to describe why we at cQuant.io decided to build a new type of energy analytics company.
What is wrong with the current choices? How can the energy industry benefit from something new?
As many of you know, energy companies are driving their business with analytic decision making. The best energy companies spend $millions on analytic solutions and are constantly looking for ways to improve. Smaller organizations often outsource analytic decisions to outside firms because they cannot afford to spend much on analytic solutions and analytic staff.
Why is this happening? Is there another way?
Let us first examine the current options for adding or improving your analytics. There are basically three choices that you have as a customer:
- Build it yourself – this requires the customer to go into the software business. The company must hire staff to build the quantitative models, the UI, the database, the system integrations, etc. Then maintain and improve it over time.
- Hire a consultancy – this is outsourcing the software development. Now you must pay consulting fees for the life of the project, which is often quoted in months but requires years to complete (funny how that works).
- Buy a vendor solution – analytic software vendors normally have solutions that are both enterprise ready and highly configurable. Unfortunately, they also require large upfront fees, deployment projects, and annual maintenance contracts.
These options require the buyer to shoulder large upfront risk. Push your money in the middle of the pot and hope that it all works out. To address this risk, many energy companies employ bureaucratic procurement processes.
It can take years to get the solution in place.
We decided that the energy industry needed another choice. Our goal was to eliminate 100% of the risk, 100% of the waiting and over 80% of the cost associated with the existing choices. So, we began working with top quantitative experts to build sophisticated energy models and we deploy those models in a modern cloud computing platform.
Now energy analysts have a place to go to find and use analytic models – on demand! Our models can be used for a day, a week, a month, or a year. We are adding new models every few months.
In truth, we are just at the beginning of our journey. Our team has tremendous plans to revolutionize the energy analytic landscape. You deserve more and better choices. We hope to be a part of this revolution.
This is just the beginning and I hope that you will join us!
This article was written by David Leevan. David is the Managing Director of cQuant.io, a SaaS platform for energy analytics.