If you can’t tell, I have a keen interest in how software companies commercialize their products in the energy & industrial verticals.
I also feel that there is no central resource to track common contracts that serve the energy & industrial verticals. It is widely known what the costs are for traditional technology solutions: a CRM, an email management platform, a HR network. But what about the energy and industrial customers: AI model to optimize manufacturing production? Wind turbine or solar O&M contracts? Developer software like construction management or inventory management and logistics? We need to democratize access to many of these answers so that we can accelerate the energy and industrial technology transition
Every Sunday, I am going to be posting details on publicly known software contracts (specific or trends) that serve customers in the energy and industrial verticals. I will also aim to cover the reasons for the pricing structure, the value offered, and the likely sales cycle and channel. I will post this information in the (Natural) Resources section of the site. My aim is to showcase hundreds of contracts so that entrepreneurs looking to serve these customers (either initially or through expansion) have more data on how to best commercialize in this space, avoid common pitfalls, and understand value. Of course, the best outcome here is that more software contracts signed further
Contract 1: “Intelligence Industrial Operations” Software contract
The technology: Deep learning platform assigned to evaluate datasets from industrial processes and increase throughput and operational efficiency of the facility
Replacing / Enhancing: Replacing manual spreadsheets and the goal is to enable subject matter experts (SMEs) and institutionalize employee knowledge.
Target Customers: Smart factories that have complex production facilities
Business Model: Small implementation fee to train the SMEs; Upon implementation the product is priced on a “training cycles per month” revenue basis. This pricing structure aligns the software’s revenue to the complexity of the production site’s architecture. The more complex a production site, the more cycles the model will require to identify prospective recommendations.
Pricing: These contracts ultimately get value-based pricing, but the standard is around 1-2 cents per model run. And an industrial customer will likely run 5 to 10 million models on an industrial production site per year. This results in an ~$100k contract for a high value production facility.
Analysis: While the software vendors in this space have been lenient on pricing, one of the beauties of this model is that the pricing self-selects a customer. Firstly, a customer has to have a production facility that is digitized and ready to engage. Secondly, the SME needs to be aware of optimization potential AND the General Manager of the site needs to have a grasp on the potential value of the improvements. If a customer leans in, all three gateways have been passed. Usually, a great software contract can capture about 33% of the value it provides. Armed with this knowledge, a sales team should look to understand a site’s throughput and pick up any small hints about software-derived improvements to begin to ballpark the $/model. Of course, even if you are helping drive $10M in improvements, you are unlikely to capture the full upside…. competitors and general sticker shock will come up. A ballpark figure around $50-$250k per site is where I am seeing successful Industrial AI software contracts get done.