Why is Novi Labs Is Jumping Into the Data Game?
Since starting Novi Labs seven years ago, there has been a consistent strategy – build software that improves economic outcomes on energy investments. To execute on our strategy, we had to rely on utilizing public data aggregated by legacy energy industry data providers. The varying quality of this data required us to build all sorts of data quality checks into our software workflows to ensure high quality data that was being fed into our forecasting models. It’s a very simple principle – garbage in=garbage out.
After years building the industry leading cloud based machine learning driven forecasting software driving energy investments, the conclusion was reached that we had to take a more active role in ensuring data quality – making sure that data used in modeling pipelines was Accurate, Timely, and Complete. The thesis is simple – if the data was of higher quality, the results generated from our software would also be better.
We developed the view that the commercial frameworks under which data was licensed needed a fresh look. It started with some simple questions:
- Why are customers being asked to buy a bunch of data they don’t need just to get the data they want?
- Why is aggregated public data so expensive to license?
- Why is data not connected directly to decision making workflows?
- Why is there no method offered for customers to create their own configured datasets or data transformations, versus just being fed the same data that everyone else receives (e.g. – dynamic, or configured, vs. static data)?
- Why is it so hard to merge my proprietary data with the public data offerings?
- Why is it so time intensive to download data from traditional providers, prepare it for analytical purposes, and utilize it to support business decisions?
- Why has data quality pretty much stagnated for the past ten years, particularly in the onshore space?
So…is there a better way?
We decided the best way to address the questions above was to either build our own data aggregation framework, or acquire an industry leader that had built this solution the way we would have built it.
Right around the time we reached this conclusion, we met Enno Peters and the team from ShaleProfile. Many in the industry have been exposed to the ShaleProfile blog over the years (including us), and we had a high opinion of what we had read and heard from our customers. We engaged in a months-long due diligence process with the ShaleProfile team where we compared the accuracy, timeliness and completeness of the ShaleProfile data to a reference database of proprietary data.
The conclusions we reached after our diligence:
- ShaleProfile data was as good or better than any other data offered in the market.
- Combining the two companies would enable the full integration of the the ShaleProfile data aggregation pipeline with Novi’s best-in industry AI-driven modeling and forecasting software.
- We could build a stronger value proposition around a fully integrated workflow that started with our data, unlocking significant efficiencies for our customers by reducing chances of error and improving overall results.
- While the ShaleProfile data was already very good, many areas including lease-allocation can be improved by leveraging our database of tens of thousands of wells of proprietary data. This leap change improvement in the quality of the underlying public data would leverage Novi’s core competencies in statistics and machine learning.
- If the ShaleProfile data were integrated into a pre-built Novi model, customers could spend a lot more time analyzing and recommending and a lot less time fixing and preparing data.
- Commercially, we believe the bundling of data and modeling software together will radically improve the value proposition and reduce total cost of ownership.
- Time to value could be improved by packaging data, models, and software together, all delivered on the first day of a Novi contract.
Based on these compelling value propositions, we completed the acquisition of ShaleProfile on December 29, 2021. We are now integrating our companies and product roadmaps.
Introducing…the Novi Data → Decision Workflow
Our vision is to deliver a fully integrated, automated, and user configurable software workflow whereby customers can derive better investment decisions for oil & gas operators and energy investors. We have named this workflow “Data to Decision”. With this, customer may blend from any source internal or external with Novi’s data, create high quality analytical datasets, build machine learning driven models, and leverage those models to make high consequence business decisions. All in one platform with one contiguous workflow.
Our mission in the coming months:
- Disrupt the traditional commercial models under which data is licensed today.
- Offer customers flexible commercial packages that include only the data, software and models they need.
- Fully integrated data delivered through a seamless pipeline.
- Self-service software capabilities allowing customers to configure the data and tune analytical dataset creation algorithms.
- Offer a “day one” value proposition while still giving customers complete control of the workflow to build their own custom models with their own proprietary data.
- Affect economic outcomes of oil & gas investments in a positive way.
- Greatly improve workflow efficiency.
We have a burning ambition to deliver on our market vision, and we are actively working on integrating the ShaleProfile team and products. We will keep everyone informed on our progress. As we enter 2022, we zealously want to help our customers succeed in optimizing their economic outcomes , and help the broader energy industry deliver on commitments to stakeholders. Feel free to reach out directly if you have questions or comments at email@example.com.